JP7266250B2 - Interactive Health Promotion System, Interactive Learning Promotion System, Interactive Purchase Promotion System - Google Patents

Description

The present invention relates to a system that promotes health, learning, and purchasing of system users through dialogue that makes them feel as if they are in contact with a person who cares about them.

2. Description of the Related Art There is known a system for managing health by inputting data and information about an individual's health condition into a dedicated application, analyzing the input data and information, and providing advice on diet and exercise. In recent years, a system using AI is also used as a system for analyzing input data and information.

Alternatively, there is known a learning system that analyzes an individual's learning pace and academic ability using AI or the like and provides a learning program tailored to the individual.

Alternatively, by analyzing an individual's purchase history and browsing history using AI, etc., we can market products and brands that the individual likes and is interested in, and when that individual uses the Internet on another occasion. A system is known that automatically displays an advertisement about a product or brand that an individual likes or is interested in.

Patent application 2015-535931

However, as in the technology shown in Prior Art Document 1, currently used health promotion applications collect health promotion information and perform health promotion only by mechanical interaction with the system within the dedicated application. I was just giving advice for Therefore, the user could not feel the warmth of talking to a human through interaction with the system. If the user cannot feel the warmth of talking to a human being, he or she is encouraged, watched over, or supported by someone, does not want to be seen in a pathetic place, or is praised. It has been difficult for humans to sustainably hold emotions such as happiness, feeling sorry for not being able to do well, and sadness, which are indispensable for humans to continue their efforts repeatedly. As a result, the desire to improve health diminishes as time passes from the start of use, making it difficult for users to continue using the system for a long period of time. For example, after some time has passed since the start of use of the system, people may no longer follow health promotion advice from the system, or use information and data that the system deems optimal to avoid troublesome health promotion advice from the system. It was supposed to be entered into the system. Therefore, in order for the system user to sustain the emotions that are essential for humans to continue their efforts through interaction with the system, it is possible to have a warm dialogue as if they were talking to a human being. There was a need to provide an interactive system.

Another problem with learning systems is that no matter how many individualized learning programs are provided, if the individual is not motivated to start learning in the first place, no effect will be obtained. rice field. People's motivation is encouraged by someone, being watched over, being supported, not wanting to be seen as pathetic, happy to be praised, sad because they can't do well, and so on. It is possible to inspire and continue by continuously holding the emotions that are indispensable for repeating and continuing. Therefore, in order for the system user to sustain the emotions that are essential for humans to continue their efforts through interaction with the system, it is possible to have a warm dialogue as if they were talking to a human being. There was a need to provide an interactive system.

Alternatively, the system for advertising only provides information unilaterally and cannot accurately provide the information requested by the user at that time. There were few cases that lead to such opportunities, and there was a problem that the effect of improving the actual willingness to buy was weak. People's willingness to buy is to be able to promote what they think is good to others, to gain empathy from people about what they think is good, and to repeatedly have dialogue with people other than themselves. It is possible to inspire and continue by Therefore, there is a need to provide an interactive system for approaching products while giving the feeling of talking to a person.

Therefore, it is an object of the present invention to provide an interactive system that allows the user of the system to have an illusion as if he or she were talking with a human being, and that allows a warm dialogue. Make it an issue.

In order to solve the above problems, the present invention provides the following interactive health promotion system and the like. That is, as a first invention, a user identification information holding unit that holds user identification information that identifies a user who uses an SNS, and user-related information that includes user remarks of the SNS that the user uses in association with the user identification information. An SNS user-related information acquisition unit that acquires certain SNS user-related information as external information, and an analysis that is a rule for acquiring health condition information by analyzing the external information in association with user identification information from the viewpoint of grasping the health condition. An analysis rule holding section that holds rules, and a health status information analysis and acquisition section that acquires health status information based on the acquired external information associated with user identification information and the analysis rule associated with the same user identification information. a dialogue information accumulation unit that accumulates dialogue information to be transmitted according to the health condition information acquired in association with the user identification information; and user identification information that selects the accumulated dialogue information based on the acquired health condition information. for each user based on a holding unit for holding user-specific dialogue information selection rules, which are rules associated with the and a dialog for outputting the selected dialog information to the user identified by the user identification information via the SNS. and an information output unit.

Next, as a second invention, the apparatus further includes a browser search history user-related information acquisition unit that acquires, as external information, browser search history user-related information, which is search history information of a browser searched by a user in association with user identification information. An interactive health promotion system according to one invention is provided.

Next, as a third invention, the interactive health promotion system according to the first invention or the second invention further comprising a news user-related information acquisition unit that acquires news information as external information in association with user identification information. offer.

Next, as a fourth aspect of the invention, the first device further includes a lifelog user-related information acquisition unit that acquires, as external information, lifelog user-related information, which is a lifelog recorded in the user's terminal in association with the user identification information. An interactive health promotion system according to any one of the inventions (1) to (3) is provided.

Next, as a fifth invention, the interactive health promotion system according to any one of the first invention to the fourth invention, further comprising a response dialogue information acquisition unit for acquiring response dialogue information to the output dialogue information. I will provide a.

Next, as a sixth aspect of the invention, an effectiveness judgment rule holding unit that holds an effectiveness judgment rule that is a rule for judging whether or not response dialogue information acquired with respect to output dialogue information is effective; A fifth invention according to the fifth aspect, further comprising a dialog information validity determination section for determining validity of the dialog information based on the dialog information, the response dialog information acquired for the dialog information, and the validity determination rule. provides an interactive health promotion system.

Next, as a seventh aspect of the invention, the dialogue information effectiveness determination unit is a rule for statistically processing the effectiveness of dialogue information of a plurality of users for each user attribute that is partly common to the population. validity statistical processing rule holding means for holding statistical processing rules;
Based on the interaction information of multiple users and the held effectiveness statistical processing rule, the statistical effectiveness of the interaction information is statistically determined for each user attribute that is partly common to at least the population statistical dialogue information effectiveness information acquiring means for acquiring dialogue information effectiveness information;
To provide an interactive health promotion system according to the sixth invention having

Next, as an eighth aspect of the present invention, there is further provided a user-specific dialogue information selection rule updating unit for updating the user-specific dialogue information selection rule held in the user-specific dialogue information selection rule holding unit based on the validity determination result. An interactive health promotion system according to the sixth invention or the seventh invention is provided.

Next, as a ninth aspect of the present invention, there is provided statistical dialogue information selection for each user, in which a selection rule for each user dialogue information held in a holding section for selection rule for each user dialogue information is updated based on the acquired statistical dialogue information effectiveness information. There is provided an interactive health promotion system according to the seventh invention, which further has a rule update section, or the eighth invention, which is dependent on the seventh invention.

Next, as a tenth invention, a user identification information holding unit that holds user identification information that identifies a user who uses the SNS and analyzes external information in association with the user identification information from the viewpoint of grasping the health status An analysis rule storage unit that stores analysis rules that are rules for acquiring status information; a dialogue information storage unit that stores dialogue information to be transmitted according to health status information acquired in association with user identification information; a user-specific dialogue information selection rule holding unit that holds a user-specific dialogue information selection rule, which is a rule associated with user identification information for selecting accumulated dialogue information based on the health status information obtained An SNS user-related information acquisition step of acquiring, as external information, SNS user-related information, which is user-related information including user's remarks of an SNS used by the user in association with user identification information, in a method of operating a promotion system; a health status information analysis obtaining step of obtaining health status information based on the obtained external information associated with the identification information and an analysis rule associated with the same user identification information; a dialogue information selection step of selecting, from a dialogue information storage unit, dialogue information in a dialogue form suited to the characteristics of each user based on a user-specific dialogue information selection rule; and identifying the selected dialogue information with user identification information. and a dialog information output step for outputting to the user via the SNS.

Next, as an eleventh invention, a user identification information holding unit that holds user identification information that identifies a user who uses the SNS, and analyzes external information in association with the user identification information from the viewpoint of grasping the health status. an analysis rule storage unit that stores analysis rules that are rules for acquiring health status information; a dialogue information storage unit that stores dialogue information to be transmitted according to the health status information acquired in association with user identification information; a user-by-user dialogue information selection rule holding unit that holds a user-by-user dialogue information selection rule that is a rule associated with user identification information for selecting accumulated dialogue information based on acquired health status information An SNS user-related information acquisition step for acquiring, as external information, SNS user-related information, which is user-related information including user-reported SNS users use in association with user identification information, in an operation method program for a health promotion system; a health status information analysis acquisition step of acquiring health status information based on the acquired external information associated with the user identification information and the analysis rule associated with the same user identification information; a dialogue information selection step of selecting, from a dialogue information storage unit, dialogue information in a dialogue form suited to the characteristics of each user based on a user-by-user dialogue information selection rule; and an interactive information output step for outputting to the identified user via the SNS.

Next, as a twelfth invention, a first learning user identification information holding unit that holds user identification information that identifies a user who uses the SNS and the learning system, and a user of the SNS that the user uses in association with the user identification information A first learning SNS user-related information acquisition unit that acquires, as external information, SNS user-related information, which is user-related information including the remarks, and a learning system that is used by the user in association with the user identification information. A first learning history information acquisition unit that acquires learning history information, which is information indicating a history of learning, and information indicating the effect of learning performed in the learning system from the learning system used by the user in association with the user identification information. A first learning effect information acquiring unit for acquiring certain learning effect information, and learning status information by analyzing external information, learning history information, and learning effect information in association with user identification information from the viewpoint of grasping the learning situation. A first learning analysis rule holding unit that holds a learning analysis rule that is a rule for acquiring the acquired external information associated with the user identification information, the learning history information, the learning effect information, and the same user identification a learning situation information analysis and acquisition unit that acquires learning situation information based on analysis rules associated with the information; Learning dialogue information accumulation unit; First learning user-specific dialogue information holding a user-specific dialogue information selection rule, which is a rule associated with user identification information for selecting accumulated dialogue information based on the acquired learning situation information Based on the selection rule storage unit, the acquired learning situation information, and the stored user-by-user dialogue information selection rule, dialogue information in a dialogue format that conforms to the characteristics of each user is selected from the first learning dialogue information storage unit. and a first learning dialogue information output unit for outputting the selected dialogue information to the user identified by the user identification information via the SNS. provide the system.

Next, as a thirteenth invention, a second learning user identification information holding unit that holds user identification information that identifies a user who uses the SNS and the learning system, and a user of the SNS that the user uses in association with the user identification information A second learning SNS user-related information acquisition unit that acquires, as external information, SNS user-related information, which is user-related information including the remarks, and a learning system used by the user in association with the user identification information. A second learning history information acquisition unit that acquires learning history information, which is information indicating a history of learning, and information that indicates the effect of learning performed in the learning system from the learning system used by the user in association with the user identification information. A second learning effect information acquisition unit that acquires certain learning effect information, a second learning curriculum information acquisition unit that acquires curriculum information from a learning system used by the user in association with user identification information, and a user Retains learning analysis rules that are rules for acquiring learning status information by analyzing external information, learning history information, learning effect information, and curriculum information in association with identification information from the perspective of grasping learning status a second learning analysis rule holding unit, acquired external information associated with user identification information, learning history information, learning effect information, curriculum information, and analysis rules associated with the same user identification information a second learning situation information analysis acquisition unit that acquires learning situation information based on; a second learning user-specific dialogue information selection rule holding unit that holds a user-specific dialogue information selection rule that is a rule associated with user identification information for selecting accumulated dialogue information based on the acquired learning situation information; second learning dialogue information selection for selecting dialogue information in a dialogue format suited to the characteristics of each user from the second learning dialogue information storage unit based on the learned situation information and the stored user-by-user dialogue information selection rule and a second learning dialogue information output unit for outputting selected dialogue information to a user identified by user identification information via the SNS.

Next, as a fourteenth invention, a third learning user identification information holding unit that holds user identification information that identifies a user who uses the SNS and the learning system, and a user of the SNS that the user uses in association with the user identification information a third learning SNS user-related information acquisition unit for acquiring, as external information, SNS user-related information, which is user-related information including statements of learning system officials (including statements generated by a computer), and user identification information a third learning history information acquisition unit that acquires learning history information, which is information indicating the history of learning performed in the learning system from the learning system used by the user in association with the A third learning effect information acquisition unit that acquires from a learning system learning effect information that is information indicating the effect of learning performed in the learning system, external information associated with user identification information, learning history information, and learning effect A third learning analysis rule holding unit that holds a learning analysis rule that is a rule for acquiring learning situation information by analyzing the information from the viewpoint of grasping the learning situation; a third learning learning situation information analysis acquisition unit that acquires learning situation information based on external information, learning history information, learning effect information, and analysis rules associated with the same user identification information; A third learning dialogue information accumulation unit that accumulates dialogue information to be transmitted according to learning situation information acquired in association with a user identification information that selects accumulated dialogue information based on the acquired learning situation information. for each user based on a third learning user-specific dialogue information selection rule holding unit that holds a user-specific dialogue information selection rule that is a rule that has been acquired, and the acquired learning situation information and the held user-specific dialogue information selection rule a third learning dialogue information selection unit that selects dialogue information in a dialogue format that conforms to the characteristics of from the third learning dialogue information storage unit; and a third learning dialogue information output unit for outputting an interactive learning promotion system.

Next, as a fifteenth aspect of the present invention, there is a learning effectiveness judgment that holds a learning effectiveness judgment rule that is a rule for judging whether dialogue information is effective based on learning effect information acquired with respect to output dialogue information. a rule holding unit; a learning dialogue information effectiveness judging unit for judging effectiveness of the dialogue information based on output dialogue information, learning effect information acquired for this dialogue information, and a learning effectiveness judgment rule; The interactive learning promotion system according to any one of the twelfth invention to the fourteenth invention, further comprising:

Next, as a sixteenth aspect of the invention, there is provided a learning history validity determination rule for determining whether or not dialogue information is effective based on learning history information acquired for output dialogue information. learning history dialogue information valid for judging effectiveness of dialogue information based on a gender judgment rule holding unit, output dialogue information, learning history information acquired for this dialogue information, and a learning history effectiveness judgment rule and a sex determination unit.

Next, as a seventeenth invention, the learning dialogue information effectiveness judgment unit and/or the learning history dialogue information effectiveness judgment unit evaluates the effectiveness of dialogue information of a plurality of users with respect to a population. Learning effectiveness statistical processing rule holding means for holding learning effectiveness statistical processing rules that are rules for performing statistical processing for each common user attribute, interaction information of a plurality of users, and the held learning effectiveness statistical processing rules Obtaining learning statistical dialogue information effectiveness information obtained by statistically determining the effectiveness of dialogue information for at least a population, partly for each common user attribute, based on learning statistical dialogue information effectiveness information acquisition The interactive learning promotion system according to the fifteenth invention or the sixteenth invention having means.

Next, as an eighteenth invention, based on the determination results of the learning dialogue information effectiveness judgment unit and/or the learning history dialogue information effectiveness judgment unit (any of the first to third) The dialogue according to any one of the fifteenth to seventeenth inventions, further comprising an individual user dialogue information selection rule updating unit for updating the individual user dialogue information selection rule held in the dialogue information selection rule holding unit. A formula learning promotion system is provided.

Next, as a nineteenth invention, based on the acquired learning statistical dialogue information effectiveness information (any one of the first to third), the user-by-user held in the learning user-by-user dialogue information selection rule holding unit The interactive learning promotion system according to the seventeenth invention or the eighteenth invention dependent on the seventeenth invention, further comprising a learning statistical user-by-user dialogue information selection rule updating unit for updating the dialogue information selection rule.

Next, as a twentieth invention, a learning user identification information holding unit that holds user identification information that identifies a user who uses the SNS and the learning system, external information associated with the user identification information, and learning history information, a learning analysis rule holding unit that holds a learning analysis rule that is a rule for acquiring learning status information by analyzing the learning effect information from the viewpoint of grasping the learning status;
A learning dialogue information accumulation unit that accumulates dialogue information to be transmitted according to learning situation information acquired in association with user identification information, and user identification information that selects accumulated dialogue information based on the acquired learning situation information. and a learning user-specific dialogue information selection rule holding unit that holds an associated user-specific dialogue information selection rule, which is used by a user in association with user identification information. A learning SNS user-related information acquiring step of acquiring, as external information, SNS user-related information, which is user-related information that includes user's remarks on the SNS; a learning history information acquisition step of acquiring learning history information, which is information indicating the history of learning performed by the learning history information; A learning effect information acquisition step of acquiring learning effect information, acquired external information associated with user identification information, learning history information, learning effect information, and an analysis rule associated with the same user identification information. interactive information in accordance with characteristics of each user based on a learning situation information analysis acquisition step of acquiring learning situation information based on the acquired learning situation information and the stored user-specific interaction information selection rule from the learning dialogue information accumulation unit; and a learning dialogue information output step of outputting the selected dialogue information to the user identified by the user identification information via the SNS. A method of operating an interactive learning facilitation system is provided.

Next, as a twenty-first invention, a learning user identification information holding unit that holds user identification information that identifies a user who uses the SNS and the learning system, external information associated with the user identification information, and learning history information , learning effect information, and a learning analysis rule holding unit that holds a learning analysis rule that is a rule for acquiring learning status information by analyzing learning effect information from the viewpoint of grasping the learning situation, and learning acquired in association with user identification information A learning dialogue information accumulation unit that accumulates dialogue information to be transmitted according to situation information, and a user-specific dialogue that is a rule associated with user identification information that selects the accumulated dialogue information based on the acquired learning situation information. An operation program of an interactive health promotion system having a learner-specific dialogue information selection rule holding unit that holds an information selection rule, the user related including user's remarks of the SNS used by the user in association with the user identification information A learning SNS user-related information acquisition step of acquiring SNS user-related information, which is information, as external information, and a learning system used by the user in association with the user identification information. learning history information acquiring step of acquiring learning history information; and learning effect information acquiring learning effect information indicating the effect of learning performed in the learning system from the learning system used by the user in association with the user identification information. Learning to acquire learning status information based on the acquisition step, the acquired external information associated with the user identification information, the learning history information, the learning effect information, and the analysis rule associated with the same user identification information Based on the situation information analysis acquisition step, the acquired learning situation information, and the stored user-specific interaction information selection rule, dialog information in a dialog form that matches the characteristics of each user is selected from the learning dialog information storage unit. An operation program for an interactive learning promotion system, comprising: a learning dialogue information selection step; and a learning dialogue information output step for outputting the selected dialogue information to a user identified by user identification information via the SNS. offer.

Next, as a twenty-second invention, a first purchasing user identification information holding unit that uses SNS and holds user identification information that identifies a user who has a purchase history of a specific product; a first purchase SNS user-related information acquisition unit that acquires, as external information, SNS user-related information, which is user-related information that is user-related information including remarks of a user of the SNS used by the; and a first purchase history information acquisition unit that acquires purchase history information that is information indicating a; and the external information in association with the user identification information, the purchase history information, and the advertisement transmission history information are analyzed from the viewpoint of grasping the purchase status of the specific product. a first purchase analysis rule holding unit that holds a first purchase analysis rule that is a rule for acquiring purchase status information by using A first purchase purchase status information analysis acquisition unit for acquiring purchase status information based on advertisement transmission history information and a first purchase analysis rule associated with the same user identification information, and a purchase acquired in association with the user identification information A first purchase dialogue information accumulation unit that accumulates dialogue information to be transmitted according to situation information, and a user that is a rule associated with user identification information for selecting accumulated dialogue information based on the acquired purchase situation information. According to the characteristics of each user, based on a dialog information selection rule storage unit for each first purchasing user that stores another dialog information selection rule, and the acquired purchase status information and the retained dialog information selection rule for each user a first purchase dialogue information selection unit for selecting dialogue information in dialogue form from the first purchase dialogue information storage unit; and a first purchase dialogue information output unit.

Next, as a twenty-third invention, a second purchase user identification information holding unit that holds user identification information that identifies a user who has a purchase history of a specific product using SNS, and a user a second purchase SNS user-related information acquisition unit that acquires, as external information, SNS user-related information, which is user-related information including remarks of a user of the SNS used by the, and a purchase history of the specific product of the user in association with the user identification information and a second purchase history information acquisition unit that acquires purchase history information that is information indicating a; and a second purchase behavior/life log information that obtains behavior/life log information, which is information indicating the behavior and/or life log of the user in association with the user identification information. The acquisition unit analyzes the external information associated with the user identification information, the purchase history information, the advertising transmission history information, and the behavior/life log information from the viewpoint of grasping the purchase status of the specific product, and analyzes the purchase status. A second purchase analysis rule holding unit that holds a second purchase analysis rule that is a rule for acquiring information, acquired external information associated with user identification information, purchase history information, and advertising transmission history information a second purchase purchase status information analysis acquisition unit for acquiring purchase status information based on the behavior/life log information and a second purchase analysis rule associated with the same user identification information; A second purchase dialogue information accumulation unit that accumulates dialogue information to be transmitted according to the acquired purchase status information, and a rule associated with user identification information that selects the accumulated dialogue information based on the acquired purchase status information. characteristics of each user based on a second purchasing user-specific dialogue information selection rule holding unit that holds the user-specific dialogue information selection rule, and the acquired purchase status information and the held user-specific dialogue information selection rule a second purchase dialogue information selection unit that selects dialogue information in a dialogue format conforming to the above from the second purchase dialogue information storage unit; and outputs the selected dialogue information to the user identified by the user identification information via the SNS. and a second purchase dialogue information output unit for purchasing an interactive purchase promotion system.

Next, as a twenty-fourth aspect of the present invention, there is a purchase validity determination rule that determines whether dialogue information is effective based on purchase status information acquired for output dialogue information. a determination rule holding unit; a purchase dialogue information validity determination unit that determines validity of dialogue information based on output dialogue information, purchase status information acquired for this dialogue information, and purchase validity determination rules; and the interactive purchase promotion system according to the twenty-second invention or the twenty-third invention, further comprising:

Next, as a twenty-fifth aspect of the invention, the purchase dialogue information effectiveness determination unit is a rule for statistically processing the effectiveness of dialogue information of a plurality of users for each user attribute that is partly common to the population. A purchase validity statistical processing rule holding means for holding a certain purchase effectiveness statistical processing rule, a plurality of users' interaction information, and statistically effective interaction information based on the held purchase effectiveness statistical processing rule. Statistical purchase dialogue information effectiveness information acquisition means for acquiring statistical purchase dialogue information effectiveness information determined for each user attribute that is partly common to at least a population provides an interactive purchase promotion system as described in .

Next, as a twenty-sixth invention, based on the judgment result of the purchase dialogue information effectiveness judgment unit There is provided an interactive purchase promotion system according to the twenty-fourth invention or the twenty-fifth invention, further comprising a user-by-user dialogue information selection rule update unit for updating dialogue information selection rules.

Next, as a twenty-seventh invention, based on the acquired statistical dialogue information validity information (which may be the first or second), the user-specific dialogue held in the user-specific dialogue information selection rule holding unit The interactive purchase promotion system according to claim 25 or the twenty-sixth invention dependent on claim 25, further comprising a purchase statistical user-by-user interactive information selection rule updating unit for updating the information selection rule.

Next, as a twenty-eighth invention, a purchasing user identification information holding unit that holds user identification information that identifies a user who has a purchase history of a specific product using an SNS, and a purchase SNS user-related information acquisition unit that acquires, as external information, SNS user-related information that is user-related information including remarks of a user of an SNS that uses the SNS, external information associated with user identification information, purchase history information, and advertising transmission a purchase analysis rule holding unit that holds a purchase analysis rule that is a rule for analyzing history information and acquisition status information of the specific product from the viewpoint of understanding the purchase status of the specific product; A purchase dialogue information accumulation unit that accumulates dialogue information to be transmitted according to the purchase situation information acquired, and a purchase rule that is associated with user identification information that selects accumulated dialogue information based on the acquired purchase situation information. and a purchasing user-specific dialogue information selection rule holding unit that holds user-specific dialogue information selection rules, the operation method of an interactive purchase promotion system indicating the purchase history of a user's specific product in association with user identification information. a purchase history information acquisition step of acquiring purchase history information as information; Based on the step of acquiring the information on the transmission history of the advertisement, the acquired external information associated with the user identification information, the purchase history information, the transmission history information of the advertisement, and the purchase analysis rule associated with the same user identification information a purchase status information analysis acquisition step for acquiring purchase status information through the purchase status information analysis acquisition step; a purchase dialogue information selection step of selecting information from a purchase dialogue information storage unit; and a purchase dialogue information output step of outputting the selected dialogue information to a user identified by user identification information via the SNS; To provide an interactive purchase promotion system operating method.

Next, as a twenty-ninth aspect of the invention, a purchasing user identification information holding unit that holds user identification information that identifies a user who has a purchase history of a specific product using an SNS; a purchase SNS user-related information acquisition unit that acquires, as external information, SNS user-related information that is user-related information including remarks of a user of an SNS that uses the SNS, external information associated with user identification information, purchase history information, and advertising transmission a purchase analysis rule holding unit that holds a purchase analysis rule that is a rule for analyzing history information and acquisition status information of the specific product from the viewpoint of understanding the purchase status of the specific product; A purchase dialogue information accumulation unit that accumulates dialogue information to be transmitted according to the purchase situation information acquired, and a purchase rule that is associated with user identification information that selects accumulated dialogue information based on the acquired purchase situation information. An operation program for an interactive purchase promotion system, comprising: a purchase user-specific dialogue information selection rule holding unit that holds user-specific dialogue information selection rules, wherein the purchase history of the user for the specific product is shown in association with user identification information. a purchase history information acquisition step of acquiring purchase history information as information; Based on the step of acquiring the information on the transmission history of the advertisement, the acquired external information associated with the user identification information, the purchase history information, the transmission history information of the advertisement, and the purchase analysis rule associated with the same user identification information a purchase status information analysis acquisition step for acquiring purchase status information through the purchase status information analysis acquisition step; a purchase dialogue information selection step of selecting information from the purchase dialogue information storage unit; a purchase dialogue information output step of outputting the selected dialogue information to the user identified by the user identification information via the SNS;
To provide an interactive purchase promotion system operating program consisting of:

Next, as a thirtieth aspect of the invention, the interactive purchase promotion according to claim 22 to claim 27, wherein a user having a history of sending out advertisements for a specific product is used instead of the user having a purchase history for the specific product. provide the system.

Next, as a thirty-first invention, a learning response dialogue information acquisition unit for acquiring response dialogue information for the output dialogue information, and determining whether the response dialogue information acquired for the output dialogue information is valid. a learned response validity determination rule holding unit that stores a learned response validity determination rule that is a rule for determining the validity of a learned response, output dialogue information, response dialogue information acquired for this dialogue information, and a learned response effectiveness determination rule; The interactive learning promotion system according to the 12th invention to the 16th invention, further comprising a learning response dialogue information effectiveness judgment unit for judging the effectiveness of the dialogue information based on.

Next, as a thirty-second invention, a learning response dialogue information acquisition unit for acquiring response dialogue information for the output dialogue information, and determining whether the response dialogue information acquired for the output dialogue information is effective a learned response validity determination rule holding unit that stores a learned response validity determination rule that is a rule for determining the validity of a learned response, output dialogue information, response dialogue information acquired for this dialogue information, and a learned response effectiveness determination rule; and a learning response dialogue information effectiveness judgment unit that judges the effectiveness of the dialogue information based on
The learned response dialogue information effectiveness determination unit holds a learned response effectiveness statistical processing rule that is a rule for statistically processing the effectiveness of dialogue information of a plurality of users for each user attribute that is partly common to a population. Based on learning response effectiveness statistical processing rule holding means, dialogue information of a plurality of users, and the held learning response effectiveness statistical processing rule, the effectiveness of dialogue information is statistically evaluated for at least a population 12th to 16th inventions, further comprising learning response statistical dialogue information effectiveness information acquisition means for acquiring learning response statistical dialogue information effectiveness information partially determined for each common user attribute An interactive learning facilitation system according to the invention is provided.

Next, as a thirty-third invention, based on the determination result of the learned response dialogue information effectiveness determination unit (any of the first to third), the The interactive learning promotion system according to the 31st invention or 32nd invention, further comprising a learning response user-specific dialogue information selection rule update unit for updating the user-specific dialogue information selection rule.

Next, as a thirty-fourth invention, based on the acquired learning response statistical dialogue information effectiveness information (any one of the first to third) is held in the learning user-by-learning user dialogue information selection rule holding unit The dialogue according to the 32nd invention or the 33rd invention dependent on the 32nd invention, further comprising a learned response statistical user dialogue information selection rule updating unit for updating the individual user dialogue information selection rule Expression learning promotion system.

Next, as a thirty-fifth invention, a purchase response dialogue information acquisition unit for acquiring response dialogue information to the output dialogue information, and determining whether the response dialogue information acquired for the output dialogue information was effective a purchase response validity determination rule holding unit that stores a purchase response validity determination rule that is a rule for determining the validity of a purchase response; output dialogue information, response dialogue information acquired for this dialogue information; The interactive purchase promotion system according to the 22nd to 24th inventions, further comprising a purchase response dialogue information effectiveness judgment unit for judging the effectiveness of the dialogue information based on.

Next, as a thirty-sixth aspect of the invention, there is provided a purchase response dialogue information obtaining unit for obtaining response dialogue information to the output dialogue information, and determining whether the response dialogue information obtained for the output dialogue information is valid. a purchase response validity determination rule holding unit that stores a purchase response validity determination rule that is a rule for determining the validity of a purchase response; output dialogue information, response dialogue information acquired for this dialogue information; and a purchase response dialogue information effectiveness judging unit for judging the effectiveness of the dialogue information based on a purchase response effectiveness statistical processing rule holding means for holding purchase response effectiveness statistical processing rules, some of which are rules for performing statistical processing for each common user attribute;
Based on multiple users' interaction information and stored purchase response effectiveness statistical processing rules, the effectiveness of the interaction information was statistically determined for each user attribute that is partly common to at least the population. The interactive purchase promotion system according to any of the twenty-second to twenty-fourth inventions, further comprising purchase response statistical dialogue information validity information acquisition means for acquiring purchase response statistical dialogue information validity information. offer.

Next, as a thirty-seventh invention, based on the judgment result of the purchase response dialogue information validity judgment part (it may be the first or second), the user held in the dialogue information selection rule holding part for each purchasing user There is provided an interactive purchase promotion system according to the thirty-fifth invention or the third tree-6 invention, further comprising an updating unit for the purchase response user-specific dialogue information selection rule for updating the separate dialogue information selection rule.

Next, as a thirty-eighth invention, based on the acquired purchase response statistical dialogue information effectiveness information (first or second), the user-by-user held in the purchasing user-by-user dialogue information selection rule holding unit The interactive purchase according to the thirty-sixth invention or the thirty-seventh invention dependent on the thirty-sixth invention, further comprising a purchasing response statistical user-by-user dialogue information selection rule updating section for updating the dialogue information selection rule. Provide a promotion system.

Next, as a thirty-ninth invention, instead of a user who has a purchase history of a specific product, a user who has a history of transmitting advertisements for a specific product is described in the thirty-fifth invention to the thirty-eighth invention. provides an interactive purchase promotion system.

According to the present invention, a warm dialogue as if talking to a human being is provided in order to make the user of the system continuously feel the emotions that are essential for humans to continue their efforts repeatedly through interaction with the system. An interactive system can be provided that allows

Conceptual diagram showing how this interactive health promotion system is used Simplified conceptual diagram of how dialogue information is output from this interactive health promotion system An example diagram showing the configuration of the interactive health promotion system of Embodiment 1 Hardware configuration example diagram of the interactive health promotion system of the first embodiment An example diagram showing the flow of processing of the interactive health promotion system of the first embodiment Example diagram showing the configuration of the interactive health promotion system of the second embodiment Hardware configuration example diagram of the interactive health promotion system of the second embodiment An example diagram showing the flow of processing of the interactive health promotion system of Embodiment 2 Example diagram showing the configuration of the interactive health promotion system of Embodiment 3 Hardware configuration example diagram of interactive health promotion system of embodiment 3 Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 3 Example diagram showing the configuration of the interactive health promotion system of Embodiment 4 Hardware configuration example diagram of the interactive health promotion system of Embodiment 4 Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 4 An example diagram showing individuality of the interactive health promotion system of Embodiment 5 Hardware configuration example diagram of interactive health promotion system of embodiment 5 Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 5 Example diagram showing the configuration of the interactive health promotion system of Embodiment 6 Hardware configuration example diagram of the interactive health promotion system of Embodiment 6 Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 6 Example diagram showing the configuration of the interactive health promotion system of Embodiment 7 Example diagram of statistical dialogue information validity information of Embodiment 7 Hardware configuration example diagram of interactive health promotion system of Embodiment 7 Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 7 Simplified conceptual diagram of user-based information selection rule update Example diagram showing the configuration of the interactive health promotion system of Embodiment 8 Simplified conceptual diagram of the function of AI in the interactive health promotion system of Embodiment 8 Hardware configuration example diagram of the interactive health promotion system of the eighth embodiment Example diagram showing the flow of processing of the interactive health promotion system of Embodiment 8 Example diagram showing the configuration of the interactive health promotion system of Embodiment 9 Hardware configuration example of the interactive health promotion system of the ninth embodiment Example diagram showing the flow of processing of the interactive health promotion system of the ninth embodiment Example diagrams of configurations of Embodiments 10 and 11 Conceptual diagram showing how this interactive learning promotion system is used Simplified conceptual diagram of how this interactive learning promotion system outputs dialogue information Example diagram showing the configuration of the interactive learning promotion system of the twelfth embodiment Hardware configuration example of the interactive learning promotion system of the twelfth embodiment Example diagram showing the flow of processing of the interactive learning promotion system of the twelfth embodiment Example diagram showing the configuration of the interactive learning promotion system of the thirteenth embodiment Hardware configuration example diagram of interactive health promotion system of embodiment 13 Example diagram showing the flow of processing of the interactive learning promotion system of the thirteenth embodiment Example diagram showing the configuration of the interactive learning promotion system of the fourteenth embodiment Hardware configuration example of the interactive learning promotion system of the fourteenth embodiment Example diagram showing the flow of processing of the interactive learning promotion system of the fourteenth embodiment Example diagram showing the configuration of the interactive learning promotion system of the fifteenth embodiment Hardware configuration example of the interactive learning promotion system of the fifteenth embodiment Example diagram showing the flow of processing of the interactive learning promotion system of the fifteenth embodiment Example diagram showing the configuration of the interactive learning promotion system of Embodiment 17 Hardware configuration example diagram of interactive learning promotion system of embodiment 17 Example diagram showing the flow of processing of the interactive learning promotion system of Embodiment 17 Example diagram showing the configuration of the interactive learning promotion system of Embodiment 18 Simplified conceptual diagram of the AI function of the interactive health promotion system of Embodiment 18 Hardware configuration example diagram of interactive learning promotion system of embodiment 18 Example diagram showing the flow of processing of the interactive learning promotion system of Embodiment 18 Example diagram showing the configuration of the interactive learning promotion system of Embodiment 19 Hardware configuration example of interactive learning promotion system of embodiment 19 Example diagram showing the flow of processing of the interactive learning promotion system of the nineteenth embodiment Conceptual diagram showing how this interactive purchase promotion system is used Simplified conceptual diagram of how interactive information is output from this interactive purchase promotion system Example diagram showing the configuration of the interactive purchase promotion system of the twenty-second embodiment Hardware Configuration Example of Interactive Purchase Promotion System of Embodiment 22 Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-second embodiment Example diagram showing the configuration of the interactive purchase promotion system of implementation body 23 Hardware Configuration Example of Interactive Purchase Promotion System of Embodiment 23 Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-third embodiment Example diagram showing the configuration of the interactive purchase promotion system of the twenty-fourth embodiment Hardware Configuration Example of Interactive Purchase Promotion System of Embodiment 24 Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-fourth embodiment Example diagram showing the configuration of the interactive purchase promotion system of the twenty-fifth embodiment Hardware Configuration Example of Interactive Purchase Promotion System of Embodiment 25 Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-fifth embodiment Example diagram showing the configuration of the interactive purchase promotion system of the twenty-sixth embodiment Simple conceptual diagram of the AI function of the interactive health promotion system of Embodiment 26 An example diagram of the hardware configuration of the interactive purchase promotion system of the twenty-sixth embodiment Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-seventh embodiment Example diagram showing the configuration of the interactive purchase promotion system of the twenty-seventh embodiment Hardware Configuration Example of Interactive Purchase Promotion System of Embodiment 27 Example diagram showing the flow of processing of the interactive purchase promotion system of the twenty-seventh embodiment A diagram showing an example of the configuration of the twentieth embodiment and the twenty-first embodiment A diagram showing an example of the configuration of the twenty-eighth embodiment and the twenty-ninth embodiment

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Embodiment N corresponds to claim N. However, N is 1 to 39. It should be noted that the present invention should not be limited to these embodiments in any way, and can be implemented in various forms without departing from the gist of the present invention.

<Embodiment 1>
<Outline of Embodiment 1 Invention>
The interactive health promotion system according to the present embodiment obtains user's remark information and browsing information on SNS as external information, and analyzes the information to analyze the user's health condition (physical health and mental health). and give advice that matches the user's current health condition.
FIG. 1 is an image conceptual diagram showing the relationship between an interactive health promotion system, various SNS services, and users. A (0102a), B (0102b), C (0102c), D (0102d), and E (0102e) using SNS use SNS systems such as SNS1 (0103), SNS2 (0104), and SNS3 (0105). use and interact. At this time, for example, when A uses the interactive health promotion system (0101), A interacts with the interactive health promotion system via SNS1 that A uses on a daily basis. For example, when B uses the interactive health promotion system, B selects SNS2 or SNS3 that B usually uses to interact with the interactive health promotion system. FIG. 2 is an image conceptual diagram when health promotion advice is given to a certain user by the interactive health promotion system. The interactive health promotion system (0201) is a user (0202) who has registered with the interactive health promotion system. "I've been eating out a lot lately.""Today's plan is to go outside Σ(~Ro~lll).""It's pretty cool today!" ”, etc.) and information on the transmissions of third parties being viewed (“Like” responses to SNS remarks related to baby pandas, set to receive SNS transmissions related to the exhibition schedule of the museum) automatically acquires (0204) user-specific SNS-related information (0203) such as The user's current health status (0206) is obtained by analyzing (0205) the acquired SNS-related information from both physical and mental health aspects. The interactive health promotion system determines a background goal from the acquired user's current health status, and determines appropriate interactive information to achieve the goal. For example, if you decide to have the user do aerobic exercise as a background goal, the appropriate interactive information for achieving the goal might be, "Good morning. I'm feeling a little tired. Today's recommendation is Ueno Park." Do you want to go for a walk? Today's recommendation is Ueno Park! You can see museums and super cute baby pandas (^_-)-☆". (0207) is output to a mobile terminal (0208) that receives interactions with the user's own interactive health promotion system.

The first characteristic of the interactive health promotion system is that it uses external information such as user's comments on SNS. Next, as a second feature, the acquired external information is analyzed as data, and the user's "feelings" are analyzed from the information, instead of simply acquiring numerical physical health status information. In addition to physical health status information, mental health status information is also acquired, and the “current health status” is analyzed and acquired considering both physical health and mental health. Furthermore, as a third feature, the optimal advice content is selected from the analyzed "current health condition", and the advice content selected using the optimal tone of voice in accordance with the user's usual tone of voice. to output

<Embodiment 1 Configuration of the Invention>
FIG. 3 is a diagram showing an example of the configuration of the interactive health promotion system of Embodiment 1. As shown in FIG. As shown in FIG. 3, the interactive health promotion system of Embodiment 1 includes a user identification information storage unit (0301), an SNS user-related information acquisition unit (0302), an analysis rule storage unit (0303), and a health status information analysis acquisition unit. It consists of a section (0304), a dialogue information accumulation section (0305), a user-by-user dialogue information selection rule holding section (0306), a dialogue information selection section (0307), and a dialogue information output section (0308). It should be noted that the present system does not need to house all the functional parts in one housing, and is not limited to one composed of only one computer or server. The system may be configured to function as a whole by being housed in a plurality of housings, or may be configured to function in cooperation with a plurality of computers and servers. Furthermore, if this system is composed of multiple chassis, multiple computers, and servers, it does not prevent it from being installed across national borders. This is common not only to this system, but also to those that use an idea equivalent to this system as an operation method or an operation program. This concept of the system applies throughout this specification (all of Embodiments 1 through 39).

<Description of Embodiment 1 Configuration>
<Embodiment 1 User identification information holding unit>
The 'user identification information holding unit' holds user identification information for identifying a user who uses the SNS. The user identification information held by the user identification information holding unit is the user identification information in the interactive health promotion system of the user who uses the interactive health promotion system. User identification information is information that can uniquely identify a user in this system. , vein authentication information, an individual identification code of a mobile terminal with which the user is using SNS and capable of communicating, and a MAC address of a mobile terminal with which the user is using SNS and which can communicate are the user identification information as they are. Alternatively, it is conceivable that these are associated with identification information composed of symbols, codes, numerals, alphabets, and the like. Information stored in association with user identification information is information registered by the user as user information at the time of use (for example, telephone number, email address, ID specially set by the user, name, date of birth , address, occupation, age, gender, height, weight, average body temperature, normal pulse rate, normal respiratory rate, normal heart rate, average amount of exercise (time, quality, mode, etc.), commuting time, commuting distance, commuting method , alcohol intake, gym attendance, family structure, etc.), information for specifying the SNS service used by the user, and the ID used by the user for the SNS service. Furthermore, as a life log that shows the user's physical condition, heart rate, pulse rate, respiration rate, body temperature, degree of muscle contraction/relaxation, electroencephalogram, blood flow velocity, blood oxygen concentration, blood alcohol content, allergies It may be configured to include one or more of the degree of reaction, the degree of accumulation of fatigue substances, and the like. These are obtained from a wearable terminal that is worn on the body and capable of measuring the state of the body, a body data measuring device that is not worn on the body but has a communication function, or the like. Alternatively, physical data stored in a portable memory that is not in communication can be transferred to a portable memory (e.g., USB memory, IC card (including prepaid card with RFID function, etc.), portable disk drive, optical recording medium, magnetic memory, etc.). ) can also be obtained from In the case of a prepaid card, it is possible to obtain data indicating the physical condition by receiving information on the physical condition at the time of medical examination or payment of fees for medical treatment by a doctor. The user attribute information held in association with the user identification information is configured to be registered by the user himself when starting to use the interactive health promotion system. With this registration, this interactive health promotion system can be configured to be available. Furthermore, the user attribute information can be transferred or copied from another system already used by the user. For example, it is possible to use data owned by facilities such as hospitals with usage history, electronic medical record systems used by users, training gyms used by users, and training apps used by users.

<Embodiment 1 SNS user-related information acquisition unit>
The 'SNS user-related information acquisition unit' acquires, as external information, SNS user-related information, which is user-related information including user remarks of the SNS used by the user in association with user identification information. Here, the 'SNS user-related information' is one of the 'external information', and in addition to this, the external information may include various information to be described later. The SNS user-related information includes, for example, user's utterance information on the SNS, user reaction information to other utterances on the SNS, information on others set to check utterances on the SNS, Information about others designated as friends or other special relationships, information about remarks of others viewed by the user on SNS, remarks made by other users who are friends on SNS, at that time via SNS So-called check-in information that transmits the whereabouts of the user, information such as photos and videos uploaded by the user to SNS, recorded information (voice memo) saved on SNS, information on the content of calls made via SNS, user within SNS , location information acquired from SNS, game-related information used in SNS (game usage frequency, game win/loss information, game progress information, game-related friend information, etc.), user activity on SNS behavior of the user when the user is active on the SNS (e.g., often at home, often at work, often during meal times, often during travel, with someone) information not selected by the user on the SNS, information ignored by the user on the SNS, and the like. The SNS user-related information includes not only information displayed as text via a network, but also data input and output as voice, image, moving image, and the like. Therefore, conversations, silence, laughter, absence, yelling, shouting, screaming, tone of voice, etc. exchanged by phone (including smartphones, mobile phones, landline phones, tablet terminals, portable computers, desktop computers, etc.) are also external information. (It is the same throughout this specification that these apply as external information).
Here, “SNS” broadly refers to a service or website that enables the construction of a social network (connection between people). Therefore, blogs with communication functions such as comments and trackbacks, electronic bulletin boards, and telephones (fixed-line phones, smartphones, mobile phones, tablet terminals, portable computers: (including those with Internet calling functions).
On the other hand, in a narrow sense, social networking services are "community-type registration-based services" that promote and support connections between people. used for In some cases, there is a system that emphasizes close human connections and cannot participate without an invitation from an existing participant. Examples of SNS include “Facebook (registered trademark)”, “LINE (registered trademark)”, “Twitter (registered trademark)”, “Youtube (registered trademark)”, and “Instagram (registered trademark)”. can.

<Embodiment 1 Analysis Rule Holding Unit>
The 'analysis rule storage unit' stores analysis rules that are rules for acquiring health status information by analyzing external information in association with user identification information from the viewpoint of grasping the health status. Since the analysis rule is associated with the user identification information, the analysis rule matches the characteristics of the user. For example, if A makes many statements claiming that he is tired when it is hot and many statements that he is active when it is cool, A's statement of "cool" will indicate that he is comfortable, active, and active. Therefore, the rule "cool = healthy" becomes an analysis rule that matches the characteristics of A. On the other hand, B makes many statements indicating that he is active when it is hot, but when it is cool, he goes to bed early, refrains from doing activities, and when he tends to make more negative statements, he says that he is cool. From B's remarks, it can be inferred that he is in a state of poor physical condition, fatigue, or feeling depressed. Alternatively, C regularly makes remarks that claim to be in good physical condition whether it is hot or cool, and is actively engaged in activities such as going out. If C's utterance of "cool" increases, it can be inferred that she is in a state of wanting to go somewhere far away and wanting to be more active. The rule "cool = energetic enough to want to be active" is a rule that matches the characteristics of C. In addition, it is assumed that the user sets access permission in advance so that the interactive health promotion system can access information on the user's SNS.

As shown in the example of C, the analysis rule does not have to be a rule for acquiring only the states of "healthy", "poor physical condition", and "cold" as health status information. "I am in good health", "I am relatively healthy", "I am very unwell", "I am a little unwell", "I have a fever", "I have a severe sore throat", etc. The rule may be such that health condition information including information indicating the degree and symptoms can be obtained.

Mental health status information can be acquired by moods that can be acquired from conversations, etc. Examples of the moods include happy, pleasant, happy, pleasant, refreshed, satisfied, exhilarated, impressed, impressed, soothed, healed, and calm. , excited, excited, proud, nostalgic, like, love, in love, admiration, respect, etc. can be judged.
Conversely, pitiful, lonely, sad, loneliness, troubled, confused, painful, withered, heartbroken, melancholy, tired, painful, heartrending, crying, disgusted, unpleasant, irritated, worried, forlorn, anxious, frightened, eerie, Hesitation, wry smile, suffocating, annoyed, atrophy, impatient, miserable, embarrassed, humiliated, tired, miserable, depressed, disappointment, disappointment, despair, disappointment, regret, frustration, indebtedness, guilt, resentment, regret, dislike, look down on , Hate, Jealousy, Want, Want, Excitement, Concern, Dullness, Moyamoya, Pity, Sympathy, etc. can.

In addition, the mental state is not only good or bad, but also relief, anxiety, gratitude, astonishment, excitement, curiosity, sexual curiosity, calmness, impatience, wonder (confusion), good luck, relaxation, tension, and honor. , responsibility, respect, affinity (familiarity), admiration (admiration), desire (motivation), fear, courage, pleasure, regret, satisfaction, dissatisfaction, chagrin, disgust, shame, contempt, jealousy, guilt, murderous intent, expectation, An analysis rule may be configured to grasp mental conditions such as superiority, inferiority, resentment, suffering, sadness, sadness, emotion, anger, resignation, despair, hatred, emptiness, etc. as health condition information. If it is possible to understand individual health conditions, such as not only good health, but also good health, feeling at ease, good health, and feeling grateful, it is possible to select dialogue information that is more suitable for life improvement. It becomes possible. For example, when you are feeling relieved, you can say something like, "You did well. Let's do this again next time." It can be thought of as a compliment. This is because the more dialogue information that is suitable for the situation can be selected, the more it will appeal to the user.

In addition, by analyzing photos and videos on SNS, it is possible to determine whether the person is shrugging, blank, impatient, frowning, embarrassed, flinching, irritated, sullen, or pouting. playing, frowning, fidgeting, determined, confused, flinching, fearful, bitter, staring being upset, irritable, upset, depressed, joking, disgusted, distracted, sad, upset, stunned, discouraged, cheerful, timid, guilty, defiant, troubled, quizzical, dismayed, warped , hesitant, overwhelmed, laid back, shy, envious, mocking, frustrated, naive, uneasy, looking sorry, sneering, pitying, relaxed, reserved, pissed off, unfocused, unimpressed, ecstatic present, relentless, open-minded, exultant, relaxed and at ease, delighted, lonely, disappointed, compromising, ruthless, timid, admiring, despising, meek, bold, sensitive, attuned, calm, resentful, single-minded, A rule may be set to acquire the feeling of "," and to further acquire mental health status information from this. In addition, since these are often common actions for many people in general, even if the analysis rules are associated with user identification information, they may be used by the majority of other users using this system. It may be configured to utilize information for analysis. This will be more accurate if artificial intelligence or the like is used.

In order to sublimate external information such as conversations into health status information, if the conversation is not directly linked to health status information, the words that came out in the conversation, the subject of the topic, or what to imagine from these is described through SNS, and by analyzing the verbal expression, it is possible to estimate the user's thought process, mental state, and physical state. Information that can be directly grasped as health status information included in the life log and the results of health checkups obtained as external information are used as reference points for estimation. Words that appear in conversations with the same person obtained around this reference point in time (I slept well this morning, etc.), topics of discussion (year-end big sale, etc.), or what we can imagine from these It is used as information for estimating situation information. Alternatively, the present system may be configured to provide target words or topics and actively ask the user what he or she will associate or think about. A similar technique is the Rorschach test. The Rorschach test uses for analysis what you imagine from what you see through your eyes. Includes all comprehensible subjects. For example, it may be words such as "park bench" and "crosswalk". Basically, this method is used using AI and the like, and the correlation estimation accuracy between conversations of many users and estimated health status information is improved while learning. In addition, when the SNS conversation includes both the target of the topic and the imagination about it, this system can estimate the thinking process, mental state, and physical state without asking what to imagine. can do. This is also a method close to the free association method used by psychologists Freud and Jung. In Freud's time, the effectiveness of this method depended on the experience of psychologists, but in this system, we were able to improve the accuracy by using statistical processing and artificial intelligence.

The analysis rule is preferably a rule for acquiring not only physical health information but also health information combining both physical health information and mental health information. Physical health status information includes physical fatigue, drowsiness, nausea, fatigue, fever, headache, abdominal pain, sore throat, back pain, muscle pain, hangover, dizziness, high blood pressure, high pulse, shallow breathing, and blood sugar. This is health status information determined from the presence or absence of dialogues and images complaining of pathological symptoms, such as high values, obesity, and illness under treatment. According to the physical health condition information, if there are no dialogues and images appealing to pathological symptoms, it is judged to be healthy, and if there are dialogues and images appealing to pathological symptoms, it is judged to be unhealthy. In addition, "health condition information" includes exercise amount, breathing amount, walking amount, calorie intake amount, intake food component, intake food component amount, alcohol consumption, water intake, weight, height, body temperature, blood pressure, BMI value, waist circumference, Visceral fat, body fat percentage, visual acuity, intraocular pressure, pulmonary function, urine test value, stool test value, blood biochemical test value, and the like may be used. Generally speaking, "physical health status information", as defined by WHO, refers to health status as "a complete dynamic state of physical, mental, spiritual and social well-being." physical health is defined as "a state of complete physical, dynamic (capable of normal activity), not merely the absence of disease or infirmity." The physical health state is therefore defined as a state of complete physical, dynamic (normal activity), not merely the absence of disease or infirmity. It refers to something that indicates a situation. Therefore, whether the person is healthy or unhealthy, the information indicates the situation.

Mental health status information refers to positive mental states such as feeling good, feeling uplifted, motivated, wanting to take on challenges, having fun, being happy, and being happy. and negative mental states such as depressed, troubled, sad, angry, disgusted, impatience, and hunger. be. According to the mental health status information, a positive mental state is judged to be healthy, and a negative mental state is judged to be unhealthy. Generally speaking, mental health status information is mental health, "a state of complete mental, spiritual and social well-being dynamic (normally active), not just mental health." is not the absence of any serious disease or mental infirmity.” indicates the absence or presence of physical illness or mental infirmity.

From the above, health status information includes "information on pain," "information on stress," "information on habituation," "information on labor productivity," and "so-called population information." intelligence, conversational computer, artificial intelligence speakers, and other robot-like objects such as "mental information about mental distance" and the like. Acquiring health status information by combining both physical health status information and mental health status information means, for example, that even if there is no physical disease symptom and is healthy in general, it is mentally negative. If the person is in a mental state of , he or she cannot spend the day actively and often feels unwell in terms of their perceived health. will be obtained. Alternatively, if the person is physically sick but mentally in a positive mental state, it is important to make the person aware of the physical condition and allow them to recuperate, so it is judged to be unhealthy.

Physical and mental ill health are closely related, and physical ill health often causes mental ill health. In that case, removing physical ill health often improves mental ill health. However, mental ill-health often causes physical ill-health, and in such cases, removing physical ill-health does not improve mental ill-health. Therefore, it is extremely effective to pay attention to mental unhealthy and give advice to promote mental health. Counseling therapy has been established for mental symptoms (depression, manic depression, irritability, etc.), but in this interactive health promotion system, not only counseling but also mental symptoms from various angles such as exercise and diet It is characterized by the fact that it promotes healthy health. In order to give advice for promoting mental health, it is necessary to analyze the mental state of the user. Therefore, it is necessary to analyze various data not only for physical health status but also for mental health status as equivalent health status information. In addition, the purpose of this system is to improve and maintain a good state of health. It is intended to achieve the goal by improving the daily life of people. Therefore, it is not intended to achieve the goal in terms of merits and demerits, but the improvement and maintenance of lifestyle habits is required of the user in order to achieve the goal by this system. From this point of view, the analysis rules shall include rules for analysis from the perspective of whether the health status has been improved from a medium- to long-term perspective, or whether a good health status has been maintained. is preferred. Therefore, it is necessary to analyze the daily variation in health status, but it is also necessary to judge whether the health status is improving, stagnating, or deteriorating in the medium term despite the variation. We need rules. For this purpose, not only analysis based on short-term external information such as the day before and the day before, but also statistical statistics such as one week before and today, the day before, one month before and today, or daily changes from one month ago It is preferable that the rules are such that they are processed systematically and analyzed for medium-term changes in the situation.

<Embodiment 1 Health condition information analysis acquisition unit>
The 'health condition information analysis/acquisition unit' acquires health condition information based on the acquired external information associated with the user identification information and the analysis rule associated with the same user identification information. Among the many statements of the user in the SNS user-related information, it is common for a plurality of statements to be mixed, ranging from statements judged to be healthy by analysis rules to statements judged to be unhealthy. The health condition information analysis/acquisition unit acquires the user's health condition information by comprehensively analyzing a plurality of pieces of health condition information on health and unhealthy acquired by the analysis rule. For example, a method of comparing the number of pieces of health condition information and unhealthy condition information acquired by an analysis rule and adopting the larger number of pieces of health condition information can be considered. Alternatively, a method can be considered in which a point is set for each degree of health condition and a judgment is made based on the point. If the points are simply summed up, the accuracy of the health condition information analysis will differ depending on whether the person has a large number of remarks or a person with a small number of comments.

The user's comments on SNS, etc., which are external information used for analyzing the health status, and the analysis rules used for analyzing the health status are associated with the same user identification information. The analysis is based on the individuality of each individual. Therefore, even if the conversation log is the same, if the user is different, the health condition information obtained by analyzing the health condition information may be different. By accumulating external information such as user's conversations on SNS, the accuracy of analysis increases, and since it is possible that users' feelings change with age, similar external information of the same user is also included. Different results may be obtained even if the health status information is analyzed and obtained at the same time.

<Embodiment 1 Dialogue Information Storage Unit>
The 'dialogue information accumulation unit' accumulates dialogue information to be transmitted according to the health condition information acquired in association with the user identification information. The dialogue information is a database of all kinds of conversations that may be said in general society. In the present interactive health promotion system, example sentences of conversation that serve as a base for giving advice to the user on health promotion or establishment of health habits are particularly heavily stored. In addition to general conversational information dictionaries, it would be desirable to have some kind of health specific dictionary. The language may be stored in a language understood by the user, or the dialogue information may be stored in a standard language such as Japanese, English, Chinese, etc., and configured to be translated and selected according to the language used by the user. You can also Therefore, based on a language dictionary database, a conversation dictionary database, etc., the foundation is built, and furthermore, SNS, information sites, corporate advertisement sites, bulletin board sites, telephone call contents, etc., are viewed and viewed by this interactive learning promotion system. It is preferable to accumulate interaction information collected from all available sources. These may include, for example, dialects, gyarugo, pictograms, emoticons, jargon, coined words, new words, abbreviations, idioms, etc., which are collected by artificial intelligence and gradually improve conversation accuracy (intentions are accurate). It is preferably configured so that the Furthermore, it is conceivable that dialogue information that constitutes health promotion advice or the like may be provided using specialized medical terms, specific food names, specific store names, or coined words. Technical terms, specific store names, and coined words cannot always be obtained from the Internet, so a special language group can be entered by directly entering them into the storage unit. is preferred.

This interactive health promotion system reflects the individuality of each user and selects and outputs dialogue information so that it becomes a natural conversation for the user. It is characterized by making you feel as if you are in contact with a real human being. Therefore, depending on the user's daily conversation, whether to use polite language, casual language with a colloquial tone, dialects such as Osaka dialect or Hakata dialect, and words mixed with English in the document It is preferable that the dialogue information is stored so that not only the contents of the conversation such as whether it will be used as an errand, but also the form of the conversation can be selected. The dialogue information accumulation unit may accumulate dialogue information as different dialogues even if they have the same meaning for each difference in formation of the dialogue. That is, expressions such as "Thank you." back. Alternatively, the dialogue information storage unit stores only the most basic dialogue information for each meaning, and the dialogue information output unit described later selects the basic dialogue information from the dialogue information storage unit according to the user's personality. I can think of a way to convert it to an existing interactive format. In this case, a rule for converting the basic dialogue information into a dialogue format suited to the characteristics of each user is included in the user-specific dialogue information selection rule. In this case, in the dialog information storage unit, "Thank you." "Thank you." "Thank you." "Thank you." Only "thank you" will be saved.

The dialogue information accumulated in the dialogue information accumulation unit may be configured so as to be displayable on the interface monitor. The dialog information storage unit has dialog information storage unit management means so that it is possible to manually perform management actions such as addition, change, and deletion of the dialog information on the interface screen on which the stored dialog information is displayed. Alternatively, it is conceivable to configure such that the dialog information storage section management section is provided as a new configuration. It is assumed that the person who manages and provides this interactive health promotion system performs the management action of the dialogue information accumulation unit.

<Embodiment 1 User-specific dialogue information selection rule holding unit>
The 'storage unit for individual user interaction information selection rule' stores individual user interaction information selection rules, which are rules associated with user identification information for selecting accumulated interaction information based on acquired health condition information. The user-by-user dialogue information selection rule reflects the individuality of each user in order to make the user feel as if he/she is in contact with a real person who cares about him or her. It is a rule for selecting dialogue information so as to have a natural conversation. From external information, such as user-generated information on SNS (character remarks, voice remarks, browsing records, information on other registered SNS users, etc.), the form of conversation that conforms to the user's dialogue form It is a rule that allows selection of conversation information based on health status information obtained by analysis of health status information, and selection of dialogue information that reflects the individuality of the user by combining both selections.

The user-by-user dialogue information selection rule is configured to be selected according to health status information based on external information that may include user response dialogue information, but the ultimate goal is to become healthy and maintain good health. , the goals to be achieved are accumulated in a hierarchical structure, and appropriate utterances (dialogue information) are made according to where in this hierarchical structure the health status that is judged and estimated based on the health status information is located. may be configured to be selected. In other words, when a health goal to be achieved is determined, the dialogue information may be selected in association with the health condition in the hierarchical structure so that the dialogue information is selected accordingly. For example, for a user suffering from mild diabetes, it is possible to determine and estimate the intake of sugar, which is the cause of diabetes, based on health status information, and reduce sugar intake by about 5% from the current level. The dialog information is selected as follows. On the other hand, for a user suffering from severe diabetes, the dialogue information is selected so as to reduce sugar intake by about 20%, and the dialogue information is selected so that insulin intake becomes a habit. Configure. In other words, even for users with diabetes, it is possible to configure so that the dialogue information selected according to the hierarchical position seen from the ultimate goal of good health is appropriate.

Dialogue formats include polite language, colloquial language, gyaru language, Osaka dialect, Kyoto dialect, Hakata dialect, Nagoya dialect, Hokkaido dialect, Okinawa dialect, and other regional dialects. A method of selecting from the information selection rules to make the user-specific dialogue information selection rule, and a method of assembling all originals from the user's conversation information are conceivable. The reason why the user can recognize this interactive health promotion system as if it were a more familiar and real existence is the method of assembling an original interactive form that can more strongly reflect the individuality of the user. However, at the stage when the user starts using this interactive health promotion system, the amount of accumulated external information for analyzing the user's individuality is small. Therefore, it automatically selects the default format when there is not enough information to obtain the rules for selecting the original format according to the user's personality. For example, it is conceivable to allow the user to select and register an interactive format so that the interactive format of the user's preference is started. Also, it may be configured to automatically select an appropriate interactive format according to the attributes of the user. User attributes include age, gender, hometown, current address, nationality, language used, conversation (dialogue) style on SNS, conversation (dialogue) style of friends on SNS, preferred clothing type, and preferred movie type. , favorite book type, favorite celebrity type (talent, actor, politician, writer, singer, comedian, historical figure, announcer, character), and the like. When the user's external information sufficient for acquisition of the dialogue information selection rule is accumulated, a specific user-specific dialogue information selection rule is constructed so as to select from the dialogue information accumulation unit a format corresponding to the individuality of the user.

When analyzing the form of dialogue information from the user's SNS conversation information, rather than simply focusing on the user's utterance form, analyze the conversation form of friends and family with whom the user frequently communicates. It is conceivable to construct separate dialogue information selection rules. By analyzing and reflecting the manner of speaking of the conversation partner with whom the user actually has a daily conversation, it is possible to give the user a sense of security as if talking with a friend or family member. Therefore, it is possible to make the user feel as if he or she is interacting with a real person who is worried about the user, and the user can feel that he or she is being encouraged by someone or watching over the user. Being supported, being supported, not wanting to be seen as miserable, being happy to be praised, feeling sorry for not being able to do well, being sad, etc., which are indispensable for human beings to continue their efforts continuously. It becomes possible to hold. In addition, if the advice comes from a person who is similar to the person who usually consults about troubles and gives advice, it becomes easier for the user to follow the advice obediently, and the user promotes health according to the dialogue information output from the interactive health promotion system. It can also be expected that it will be easier to take action. From this point of view, a wide variety of dialogue information is accumulated, such as dialogue information that conveys affection, dialogue information that conveys favorability, dialogue information that praises the other party, and dialogue information that encourages the other party. preferably.

In addition, the user's personality, such as always responding with negative remarks, but being unable to refuse when asked many times, disliking it exaggeratedly even though it is not really disliked, or disliking it for the time being, can be analyzed using personality diagnosis and attributes. If it is acquired by information, etc., it cannot be said that the output dialogue information is not effective only with a few negative responses from the user, and it takes until the user accepts the output of the same dialogue information on average. If it is recommended to repeat until a specific number of times is greater than the required number of times as a response that should be taken as a result of analysis of personality as an attribute, that response may be a rule selected by the dialogue information selection unit. Conceivable. That is, such a never-give-up rule (sub-step, sub-rule) or a never-give-up process can be included in the user-specific dialogue information selection rule, or a process configured by this can be included.

<Embodiment 1 Dialogue information selection unit>
The 'dialogue information selection unit' selects, from the dialogue information storage unit, dialogue information in a dialogue format that matches the characteristics of each user based on the obtained health condition information and the stored user-by-user dialogue information selection rule. . When dialogue information is accumulated in the dialogue information storage unit for each difference in dialogue format, dialogue information matching the dialogue format and dialogue content selected by the user-specific dialogue information selection rule is selected. If dialogue information is not accumulated for each difference in dialogue format in the dialogue information accumulation unit, and dialogue information is accumulated for each meaning of dialogue content regardless of the dialogue format, the user-by-user information selection rule basic dialogue information is selected from the dialogue information storage unit according to the dialogue contents specified by . In this case, the basic dialogue information may refer to a set of words instead of the words themselves. In this case, identification information is given to dialogue information that expresses gratitude, and this is selected, followed by ``thank you'', ``thank you'', ``thank you'', ``thank you'', and ``thank you''. Configure to select one of the expressions such as "Thank you". In other words, basic dialogue information is selected from the dialogue information storage unit according to the dialogue content specified by the user-specific information selection rule, and the selected dialogue information is used as the dialogue format specified by the user-specific dialogue information selection rule. is converted to an interactive format that matches The above operation becomes the selection of dialogue information. This selection is constructed so that it can be made instantaneously by a computer. Specifically, it is the speed at which, when an input from a user is received via an SNS, a reply is displayed on the screen without allowing the user to close the SNS screen. As an example, it is about 1 second or less on average.

<Embodiment 1 Dialogue Information Output Unit>
The 'dialogue information output unit' outputs the selected dialogue information to the user identified by the user identification information via the SNS. As described above, the speed at which the dialogue information output unit outputs the dialogue information is the speed at which the user's input can be immediately responded to if necessary. This is because if the user closes the SNS screen, there is a high risk that the call from the system side will be left unread without being marked as read. It should be noted that it is not always necessary to respond immediately, and there may be some type of transmission that is output after some time. This is the case, for example, in a conversation to hear the result of advice. The output is the user's portable terminal. The SNS to be output may be an application dedicated to this interactive health promotion system, or an SNS service managed and provided by another system that is not dedicated to the interactive health promotion system that the user uses on a daily basis. good too. The format of the output is not limited as long as it is a method capable of transmitting information to the user, such as characters, illustrations, sounds, images, and moving images. In order to make it feel as if you are talking to a real person, it is better to use the SNS service that is used for daily communication with real people than to use a dedicated application. It is effective because the interactive information output from the interactive health promotion system is naturally displayed among them. "Effective" means that the advice from the Interactive Learning Acceleration System can be seen naturally on a daily basis, so it is effective in that it does not make people strongly conscious of interacting with the system (inorganic computer or server). This is the reason why The output from the Interactive Learning Acceleration System uses the SNS service of the output destination. With such a configuration, the above effect can be ensured, so that it is more effective. Conversely, chat heads and the like are immediately noticeable on smartphones, etc., and are preferable because they reduce the sense of distance from the present system.
The dialogue information to be output is not limited in content and format, such as information including question format, information including advice, greetings, onomatopoeia, and the like.

In addition, the output format is not always the same, but characters, illustrations, sounds, images, videos, vibrations (including those via SNS, e-mail, and AV equipment), robot movements and sounds・Facial expressions, animated characters in the display (it may be a simulated human being close to the real thing, and the human being may be a user's teacher, lecturer, friend, relative, or an entertainer or celebrity employed in an advertisement or campaign. Combining multiple output methods such as the movement, voice, and facial expressions of characters in the projection image, room temperature, lighting, etc., can approximate the interaction with a live human being. It becomes more effective (this example of the output format is applied throughout this specification (Embodiment 1 to Embodiment 39)). Therefore, in addition to outputting dialogue information as characters to the output interface and outputting recorded voice data as dialogue information, real-time dialogue information output (automatic voice utterance) and response dialogue using the voice call function Information acquisition may be performed. In addition, if a person accesses a telephone consultation service (mainly mental health service, suicide prevention service, etc., but also includes physical health consultation service) using voice call, that person is received by a communication device that uses this interactive health promotion system, even if there is no user registration for this interactive purchase promotion system on the output side, the user identification information is immediately displayed using a telephone number, etc. By generating and holding the person and having the interactive health promotion system that receives the voice call recognize that person as a guest user, it is possible to output interactive information to the guest user by voice via this voice interactive health promotion system. It is also possible to configure such that In this case, the guest user is simply registering with the remote interactive health promotion system through a voice call. The user terminal itself is defined as a guest user in order to distinguish from the case where this interactive health promotion system is activated. By giving an identification number in association with user attributes such as number, etc., in subsequent voice calls, guest user attribute information (preferences, speaking style, spacing, hobbies, etc.) accumulated by past voice calls It is possible to output dialogue information reflecting thoughts, etc.). In this case, the output of the dialogue information is generated by an SNS-enabled terminal that is not possessed by the user receiving the voice call, and the voice output is delivered to the guest user via the phone. It can be said that this is an output of dialogue information via SNS.

The dialogue information output as health promotion advice may be dialogue information that encourages exercise based on health therapy, dialogue information that encourages exercise to become a habit, or dialogue information that encourages regular intake of supplements or medicine. Information such as a notification that it is time to take the medicine, dialogue information that encourages consumption, and dialogue information that encourages the purchase of sports goods, supplements, medicines, etc. to promote the user's health more efficiently. This includes all health-promoting advice.

The output of the dialogue information via the SNS is the output as comments of the user's friends, etc. participating in the SNS. Therefore, since it is preferable to have a conversation as a friend or the like that looks unique to the user as much as possible, it is preferable to use as many names as possible so that the same name does not overlap among users as much as possible. Alternatively, the name may be freely set at the time of initial user registration. Also, the attributes that determine the elements used for conversation selection may be freely set at the time of user registration. For example, it is the gender, age, character, avatar, clothing, life rhythm, hobby, etc. of the system friends. Furthermore, the system does not necessarily have to have only one friend, and may be designed so that a plurality of friends can talk to one user. The conversation to be selected may include not only a conversation between the user and the system friend or the like, but also a conversation between the system friend or the like. In this case, the user can obtain motivation for health maintenance and promotion from conversations exchanged among friends and the like. In addition, in cooperation with a location information system of the user terminal, etc., it may be configured to switch utterances of friends, etc., who are the system, according to the location information.

For example, when a user goes to Osaka, a friend who speaks Osaka dialect appears, and when a user goes to Kyushu, a friend who speaks Kyushu dialect appears. In this case, the friend in Osaka may be configured to select a conversation on the premise that they have met for the first time in a long time since the last time they went to Osaka (meeting timing situation). For example, a conversation such as "You've gained a lot of weight since we last met." Also, it may be effective to set a common system, such as friends, for a plurality of users. For example, comparative conversations such as "I heard that Mr. Tanaka lost 3 kilos after exercising together last time, how about you?" This is because such a solicitation conversation becomes possible. Note that the avatars of friends and the like do not necessarily have to be human avatars, and may be set as mammals, fish, insects, objects, and the like. The avatar may also be configured to send photos, videos, pictures, etc. to the user depending on the settings. For example, food photos, landscape photos, ideal body photos, videos explaining how to exercise, etc. In addition, you may send us information on equipment, supplements, etc. to promote use. In addition, friends, etc., who are the system, may use avatar schedules that set events according to the passage of time, such as having an accident or climbing the stairs of life, to create a sense of realism, warmth, and humanity. For example, catching a cold, entering school, graduating from school, getting a lover, being dumped, getting married, getting divorced, losing weight, getting fat, thin, having surgery, being late, etc. I took the wrong ride, overslept, drank too much, ate too much, had a child, got a promotion, changed jobs, reached retirement age, had a grandchild, and so on.

<Embodiment 1 Hardware Configuration>
FIG. 4 is a diagram showing the hardware configuration of the first embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, as a program constituting the hardware of the first embodiment, a "user identification information holding program" holds user identification information. The "SNS user-related information acquisition program" acquires SNS user-related information. This is done through an interface program with SNS. The "analysis rule holding program" holds analysis rules. The "health condition information analysis acquisition program" acquires health condition information based on analysis based on analysis rules. The "dialogue information accumulation program" accumulates dialogue information. The "program for holding dialogue information selection rules for each user" holds dialogue information selection rules for each user. The 'dialogue information selection program' selects appropriate dialogue information from the accumulated dialogue information based on the obtained health condition information and the held user-by-user dialogue information selection rule. The "interactive information output program" outputs the selected interactive information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Various setting information such as dialogue information and communication (not shown) are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.
In this computer, a nonvolatile memory, a main memory, a CPU, and an interface are connected to a bus line so that they can communicate with each other. In addition, in some cases, smartphones, mobile phones, tablet terminals, personal computers, televisions, radios, robots, wristwatches, wearable terminals (glasses, collars, rings, wristbands, hats, etc.), game terminals, and installations on the streets used by users, etc. information terminals, terminals in means of transportation (television terminals on trains, car navigation systems), cameras, displays, monitors, projectors, image generation devices, speakers (including AI speakers), earphones, headphones, vibrators, lighting, Air conditioners, WIFI devices, Internet connection devices, various household appliances, etc., and interfaces for communicating with these may be included. This point applies to the entire specification (embodiments 1 to 39 (excluding methods and programs)).

<Embodiment 1: Flow of processing>
FIG. 5 is a diagram showing the processing flow of the most basic configuration of the first embodiment. As shown in this figure, a user identification information holding step (0501) for holding identification information of one or more SNSs used by the user, SNS user-related information for acquiring user's SNS-related information as external information An acquisition step (0502), an analysis rule holding step (0503) for holding an analysis rule that is a rule for analyzing the user's health status from external information, for acquiring the user's health status information from the external information and the analysis rule health condition information analysis acquisition step (0504), conversation information accumulation step (0505) for accumulating information on innumerable languages and conversations used on the Internet etc., reflection of user's individuality acquired from external information Then, a user-specific dialogue information selection rule holding step (0506) for holding user-specific dialogue information selection rules for selecting health promotion advice in accordance with the user's health condition information, A dialog information selection step (0507) for selecting dialog information suitable for the user's health condition and individuality from the dialog information and the user-specific dialog information selection rule held by the user-specific dialog information selection rule holding unit (0507), dialog information selection and a dialog information output step (0508) for outputting the dialog information selected by the unit to the user's form terminal or the like.

<Embodiment 2>
<Overview of Embodiment 2>
In addition to the configuration of the first embodiment, the interactive health promotion system in this embodiment can acquire information about the user's browser search history as external information.

<Embodiment 2 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 2 is, as shown in FIG. 0603), analysis rule storage unit (0604), health condition information analysis acquisition unit (0605), dialogue information storage unit (0606), user-by-user dialogue information selection rule storage unit (0607), dialogue information selection unit (0608), dialogue and an information output unit (0609). Below, the description of the common configuration with the first embodiment is omitted, and the characteristic configuration of the present embodiment will be described.

<Description of Embodiment 2 Configuration>
<Embodiment 2 Browser Search History User Related Information Acquisition Unit>
The "browser search history user-related information acquisition unit" associates with user identification information, and uses a communication terminal such as a mobile phone, smartphone, tablet terminal, personal computer, etc. that the user uses this interactive health promotion system, Acquire the browser search history performed by the user as external information. "Browser search history user-related information" includes information on products purchased via the Internet by the user, information on products viewed even if not purchased, site information searched, search words searched, The information includes all kinds of activity contents performed by the user using the communication terminal, such as information on the searched place and event.

By acquiring the browser search history user-related information and analyzing it as health condition information, for example, if the user's shopping volume is increasing, it is possible to acquire health condition information indicating that the user tends to be stressed. can. For example, according to the user's browser search history, if he or she frequently searches for information on food at seasonal fairs, the calorie intake tends to be excessive, so the health status of the user is likely to be obese. Information can be obtained. For example, if information is acquired that the user is searching for an information site about countermeasures against low back pain and stiff shoulders, it means that the user is in a state of pain in the waist or shoulders, or has a feeling of discomfort in the waist or shoulders. It is possible to obtain health status information that the person is in a state of being From the browser search history user-related information, we can see what the user is worried about at that time, what they are worried about, what they are interested in, what they are planning to do on that day, etc. It is possible to obtain external information that indicates the user's behavior and status in Furthermore, browser search activities are carried out in a closed space in which no one other than the user is involved. It is possible to acquire information about the state of mind and body of the user that cannot be obtained. Acquisition of browser search history user-related information by the present interactive health promotion system makes it possible to output more effective interactive information that appeals to the deep psychology of the user.

If there is a history of using a restaurant search site, restaurants visited on that search site (e.g., restaurants associated with the tag "I went" instead of "I want to go", reservations made online) (restaurants) and use it to predict food intake. Ingested food components are used for prediction by, for example, analyzing food photos and menus posted on the search site. Therefore, a means such as image analysis is used for this analysis.
If there is a history of using a travel search site, the actual application is detected, the travel route for which the application was made is analyzed, the calories consumed, the calorie intake, and the ingredients of the food intake are analyzed, and health status information is acquired. Useful for For example, if the route of the trip involves going up and down the approach, map information is used to predict the energy consumed due to the difference in height. If there is a meal menu set for the trip, the calorie intake and food ingredients are predicted from the menu.
In addition, when using search sites for public transportation (trains, buses, airplanes, travel plans on foot from the departure point to the destination) for travel, consumption for travel on the determined search route Predict the amount of calories consumed, etc., and use it to obtain health status information. Furthermore, it is conceivable to make a prediction based on product information purchased on the Internet. For example, it is possible to obtain calorie intake information and ingested food component information from information on foods that are likely to be consumed in a predetermined period from the purchase history of an Internet supermarket. It is also conceivable to predict the average daily energy consumption based on information on exercise-related equipment purchased on the Internet (equipment for training abdominal muscles, equipment for building muscle, equipment used for dieting, etc.). In addition, although it is not the browser search history, it is also conceivable to acquire the amount of typing on the keyboard and predict the calorie consumption.

<Embodiment 2 Hardware Configuration>
FIG. 7 is a diagram showing the hardware configuration of the second embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the second embodiment shown in this figure, the programs having functions common to those of the first embodiment have already been explained, so the explanation will be omitted. The "browser search history user-related information acquisition program" newly added in this embodiment acquires the browser search history as user-related information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information and browser search history user-related information), analysis rules, health status information, dialogue information, user Various setting information such as separate dialogue information selection rules, selected dialogue information, and communication (not shown) are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Embodiment 2: Flow of processing>
FIG. 8 is a diagram showing the processing flow of the most basic configuration of the second embodiment. As shown in this figure, a user identification information holding step (0801), an SNS user related information acquisition step (0802), and a browser search history user related information acquisition step (0803) for acquiring the user's browser search history as external information. , analysis rule storage step (0804), health condition information analysis acquisition step (0805), dialog information storage step (0806), user-by-user dialog information selection rule storage step (0807), dialog information selection step (0808), dialog information output and a step (0809).

<Embodiment 3>
<Overview of Embodiment 3>
In addition to the configuration of Embodiment 1 or Embodiment 2, the invention in this embodiment acquires news information related to the user.

<Embodiment 3 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 3 is, as shown in FIG. , analysis rule storage unit (0904), health condition information analysis acquisition unit (0905), dialogue information storage unit (0906), user-by-user dialogue information selection rule storage unit (0907), dialogue information selection unit (0908), dialogue information output Part (0909). Hereinafter, the description of the common configuration with the first or second embodiment will be omitted, and the characteristic configuration of this embodiment will be described.

<Description of Embodiment 3 Configuration>
<Embodiment 3 News user-related information acquisition unit>
The "news user-related information acquisition unit" acquires news information as external information in association with user identification information. The news user-related information includes news related to events that the user is interested in acquired from the SNS user-related information, news related to events near the user's residence, near the company, etc., which is the base of activity, The news may be news from an information providing site registered by the user, weather news (including weather forecast) for the area where the user is located, and the like. The news user-related information is information that plays an important role in multidimensional analysis of the user's health condition, although it is not directly related to the form of dialogue or health condition information. For example, if there is news that "the epidemic of influenza has begun," examples of health status information obtained based on the analysis rules are "There is a risk of being infected with influenza." Therefore, the risk of contracting influenza is high.” If there is news that "the amount of pollen scattered is the highest ever", the health status information obtained based on the analysis rules will be "There is a risk that the symptoms of hay fever will worsen than usual", "New hay fever There is a risk of developing symptoms.” When there is news that "there is an occurrence of PM2.5", an example of the health condition information obtained based on the analysis rule is "there is a risk of developing asthma". Health status information obtained based on the analysis rules when there is news that "O-157 has occurred." There is a high risk of infection with O-157 when eating at affiliated stores.” If there is news that "Yellow sand will reach Japan," examples of health status information that can be obtained based on the analysis rules are "There is a risk of developing asthma." There is a risk of deterioration.” If there is news that a fire ant has been found, an example of health status information obtained based on the analysis rule is, "If you wear sandals that expose your bare feet, there is a risk of being bitten by a fire ant." There is.”

Although the news user-related information is not directly related to the health condition information, it is effective to reflect it in the contents of health promotion advice. If the health promotion advice is associated with an event related to the field in which the user is interested or related events, the user is more likely to follow the advice and take a health promotion action. Also, if there is an event near the user's residence, such as a festival, a flea market, or a fireworks display, the usual running route may have traffic restrictions or be crowded. Since there is a possibility that the user may not be able to run like this, it is conceivable to suggest running on a different route, or to advise the user not to run on that day and to perform stretching and muscle training indoors. Alternatively, if information such as a new product is posted on an information providing site such as a shop or magazine registered by the user, the user should take a detour and take a walk on the way to see the new product. or advice to have lunch at a nearby health food store. Merely advising the user of exercise or recommended meals would not be interesting in the interaction, making it difficult for the user to feel humanness from the interactive health promotion system, or making it impossible to continue using the health promotion system for the same interaction every time. There is a risk of However, if it is possible to connect it to familiar events and things that the user is interested in, model proposals for how to spend holidays, and health promotion advice related to recommended places to go out, etc. It becomes possible for the user to enjoy taking health-promoting actions, and it becomes easier for the user to perceive that the interaction is human-like rather than mechanical interaction.

Also, for example, when obtaining weather information in the area where the user is located as news user-related information, information such as the temperature, fine weather, rain, and strong wind of the day is used to analyze the health condition information. For example, if the weather information is ``Today is sunny, the maximum temperature is 35 degrees Celsius, and the humidity is high'', an example of the health status information obtained based on the analysis rule is ``If you go out during the day, you will get heat stroke.'' There is a risk.", "There is a risk of dehydration in the body when going out in the daytime." In the case of "today is cloudy, the maximum temperature is 5 degrees Celsius, and the humidity is low", the health status information obtained based on the analysis rules is "risk of hypothermia", "I have a slight cold, There is a risk of further deterioration.”, “There is a risk of damaging the throat.” In the case of "today's weather is a typhoon with strong winds and heavy rain." Although not directly related to health status information, it is also effective to reflect it in the content of health promotion advice. Even if you go for a walk or go out and exercise on a rainy day or a strong wind day, it will be advice that cannot be carried out. On rainy or windy days, we recommend doing yoga indoors, doing muscle training indoors, relaxing in a hot bath, and burning aromatherapy. It is desirable to advise what actions can be taken, such as recommending that the patient relax by spending time. By obtaining weather information, it is possible to give health promotion advice according to the weather at the place where the user is present at that time. Furthermore, it becomes possible to analyze the user's physical health and mental health, which fluctuate according to the weather. For example, if you have information about a user's specific weather and conditioned health conditions, such as migraine headaches on rainy days, weight gain, or frequent dehydration on hot days, It is possible to give preventative advice when rain forecasts or midsummer days are forecast. Although not directly related to the form of interaction or health status information, weather information is information that plays an important role in multidimensional analysis of the user's health status.

<Embodiment 3 Hardware Configuration>
FIG. 10 is a diagram showing the hardware configuration of the third embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs that constitute the hardware of the third embodiment shown in this figure, the programs that perform the same function as those of the first or second embodiment have already been explained, so the explanation will be omitted. The "news user-related information acquisition program" newly added in this embodiment acquires news information as user-related information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information and news user-related information), analysis rules, health status information, dialogue information, and user-specific dialogue. Various setting information such as information selection rules, selected dialogue information, and communication (not shown) are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Embodiment 3 Flow of processing>
FIG. 11 is a diagram showing the processing flow of the most basic configuration of the third embodiment. As shown in this figure, user identification information holding step (1101), SNS user related information acquisition step (1102), news user related information acquisition step (1103) for acquiring news information related to the user as external information, Analysis rule holding step (1104), health condition information analysis acquisition step (1105), dialogue information accumulation step (1106), user dialogue information selection rule holding step (1107), dialogue information selection step (1108), dialogue information output step (1109).

<Embodiment 4>
<Overview of Embodiment 4>
In addition to the configuration of any one of Embodiments 1 to 3, the invention of this embodiment can acquire a user's lifelog.

<Embodiment 4 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 4 includes, as shown in FIG. ), analysis rule storage unit (1204), health condition information analysis acquisition unit (1205), dialogue information storage unit (1206), user-by-user dialogue information selection rule storage unit (1207), dialogue information selection unit (1208), dialogue information and an output unit (1209). In the following, the description of the configuration common to any one of Embodiments 1 to 3 will be omitted, and the characteristic configuration of this embodiment will be described.

<Description of Embodiment 4 Configuration>
<Embodiment 4 Lifelog User Related Information Acquisition Unit>
The 'lifelog user-related information acquisition unit' acquires, as external information, lifelog user-related information, which is a lifelog recorded in the user's terminal in association with the user identification information.
Lifelog is information that can be obtained from a mobile terminal or other external device, such as the number of steps taken that day, distance traveled, blood pressure, pulse, heart rate, blood sugar level, water content, body fat percentage, and body weight. , height, muscle mass balance, bone density, respiratory rate, vital capacity, blood test results, MRS test results, urine test, blood alcohol concentration, body temperature, degree of muscle contraction/relaxation, electroencephalogram, blood flow velocity, blood They are medium oxygen concentration, degree of allergic reaction, degree of accumulation of fatigue substances, and so on. These can be obtained from a wearable terminal that is worn on the body and capable of measuring the state of the body, or a physical data measuring device that is not worn on the body but has a communication function, or the like. Alternatively, physical data stored in a portable memory that is not in communication can be transferred to a portable memory (e.g., USB memory, IC card (including prepaid card with RFID function, etc.), portable disk drive, optical recording medium, magnetic memory, etc.). ) can also be obtained from In the case of a prepaid card, it is possible to obtain data indicating the physical condition by receiving information on the physical condition at the time of medical examination or payment of fees for medical treatment by a doctor. The user attribute information held in association with the user identification information can be configured to be registered by the user himself/herself when using the interactive health promotion system. With this registration, this interactive health promotion system can be configured to be available. Furthermore, the user attribute information can be transferred or copied from another system already used by the user. For example, it is possible to use data owned by facilities such as hospitals with usage history, electronic medical record systems used by users, training gyms used by users, and training apps used by users.

Conventional technology promotes health status by numerically analyzing numerical information obtained from life logs. Therefore, the process of obtaining numerical information and the peculiarity of the content of numerical information to be obtained have been problematic. On the other hand, the present interactive health promotion system does not numerically analyze the information acquired from the life log, but analyzes the "feeling" health of the user in such behavior or state. As noted above, the interactive health promotion system obtains health status information from physical health and mental health. This physical health corresponds to numerical health, and mental health corresponds to "emotional" health. For example, when a person is mentally unstable, his/her pulse becomes faster, arrhythmia occurs, breathing becomes shallower and breathing rate increases, heart rate becomes faster, and body temperature rises sharply. Instead of using numerical fluctuations such as changes in pulse rate, breathing rate, heart rate, and body temperature to analyze abnormalities in physical health, instead of using " It is used to analyze the user's feelings such as restlessness, anxiety, and impatience. For example, when the mind is very clear and calm, the pulse rate becomes a constant speed of about 60 times per minute, the breathing rate becomes a constant speed of about 12 times per minute, and the heart rate becomes constant at about 60 times per minute, and the body temperature is around 36°C and does not fluctuate suddenly. This number is not used to analyze that there is no abnormality in the physical health status simply because it is an average number, but to analyze the feeling of "feeling calm" and "feeling radiant." use.

<Embodiment 4 Hardware Configuration>
FIG. 13 is a diagram showing the hardware configuration of the fourth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the fourth embodiment shown in this figure, the programs that work in common with any one of the first to third embodiments have already been explained, so the explanation will be omitted. A "lifelog user-related information acquisition program" newly added in this embodiment acquires a user's lifelog as user-related information. Acquisition of a life log is not limited to acquisition from a terminal using SNS. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information and life log user-related information), analysis rules, health status information, dialogue information, user-specific Dialogue information selection rules, selected dialogue information, various setting information such as communication (not shown), etc. are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Embodiment 4: Flow of processing>
FIG. 14 is a diagram showing the processing flow of the basic configuration of the fourth embodiment. As shown in this figure, the hardware configuration of Embodiment 4 also includes a user identification information holding step (1401), an SNS user related information acquisition step (1402), and life log information related to the user as external information. life log user-related information acquisition step (1403), analysis rule retention step (1404), health condition information analysis acquisition step (1405), dialogue information accumulation step (1406), user-by-user dialogue information selection rule retention step (1407) ), a dialog information selection step (1408), and a dialog information output step (1409).

<Embodiment 5>
<Overview of Embodiment 5>
In addition to the configurations described in Embodiments 1 to 4, the invention in this embodiment can acquire a response from the user.

<Embodiment 5 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 5 is, as shown in FIG. Situation information analysis and acquisition unit (1504), dialogue information storage unit (1505), user dialogue information selection rule storage unit (1506), dialogue information selection unit (1507), dialogue information output unit (1508), response dialogue information acquisition unit (1509). In the following, the description of the configuration common to Embodiments 1 to 4 will be omitted, and the characteristic configuration of this embodiment will be described.

<Description of Embodiment 5 Configuration>
<Embodiment 5 Response Dialogue Information Acquisition Unit>
The 'response dialogue information acquisition unit' further includes a response dialogue information acquisition unit that acquires response dialogue information for the output dialogue information. Response dialogue information refers to a user's response to health promotion advice output from the interactive health promotion system. A life log of actions taken by the user after giving advice corresponds to the response dialogue. Therefore, the response dialogue information is not limited to language information, and includes behavior information, numerical information such as blood pressure and blood sugar level, and the like.

<Embodiment 5 Hardware Configuration>
FIG. 16 is a diagram showing the hardware configuration of the fifth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the fifth embodiment shown in this figure, the programs that work in common with any one of the first to fourth embodiments have already been explained, so the explanation will be omitted. A "response dialogue information acquisition program" newly added in the present embodiment acquires response dialogue information corresponding to output dialogue information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Various setting information such as dialogue information, response dialogue information, and communication (not shown) are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Embodiment 5: Flow of processing>
FIG. 17 is a diagram showing the processing flow of the most basic configuration of the fifth embodiment. As shown in this figure, user identification information storage step (1701), SNS user related information acquisition step (1702), analysis rule storage step (1703), health status information analysis acquisition step (1704), dialogue information storage step (1705). ), a user-by-user dialogue information selection rule holding step (1706), a dialogue information selection step (1707), a dialogue information output step (1708), and a response dialogue information acquisition step for acquiring the user's response dialogue information to the output dialogue information. (1709).

<Embodiment 6>
<Overview of Embodiment 6>
In addition to the configuration described in Embodiment 5, the invention in this embodiment determines whether the interactive information provided by the interactive health promotion system is effective for the user from the user's response to the interactive information. It has the function of making judgments.

<Embodiment 6 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 6 is, as shown in FIG. Situation information analysis and acquisition unit (1804), dialogue information storage unit (1805), user dialogue information selection rule storage unit (1806), dialogue information selection unit (1807), dialogue information output unit (1808), response dialogue information acquisition unit (1809), validity judgment rule storage unit (1810), dialogue information validity judgment unit (1811). Below, the description of the common configuration with the fifth embodiment is omitted, and the characteristic configuration of the present embodiment will be described.

<Description of Embodiment 6 Configuration>
<Embodiment 6 Validity Judgment Rule Holding Unit>
The 'storage unit for validity judgment rules' holds validity judgment rules for judging whether or not response dialogue information obtained for output dialogue information is effective. The validity determination rule determines that the output dialogue information is effective only when the user is performing a health promotion action that matches the contents specified and proposed by the output dialogue information, and the other health promotion is judged to be effective. behavior, or failure to take health-promoting behavior, we would conclude that the output was not valid.

The effectiveness judgment rule has a background purpose of how to improve or maintain the health condition based on the health condition information. It is a rule to judge from the point of view. Therefore, words, pictures, videos, phrases, and lifelogs (including differences) that should be judged to have a positive effect, no effect, or an adverse effect depending on the background purpose are accumulated. The contents of the response dialogue information (dialogues, photographs, videos, lifelogs) are searched for stored words and the like to determine the effectiveness. It can also be configured to not only include a word, but also perform contextual analysis to determine whether it is positive or negative for its background purpose. Here, "background purpose" is defined by the person who uses or designs this system based on its philosophy, but generally refers to information that defines the state of "human health." This definition may be the value or range of values of various physiological information, the words that a healthy person would say or the frequency of words that a healthy person would say, or the definition that a healthy person would do. It may be a gesture or the frequency of occurrence of the gesture.

As a specific example for background purposes, in the value of physiological information, the upper blood pressure is set to 140 or less as a "target blood pressure value". Lower blood pressure to 90 or less, "BMI value" to 25 or less, "abdominal circumference" to 85 cm or less for men, 90 cm or less for women, visceral fat of 100 square centimeters "Percentage of body fat" should be 20% or less for men, 28% or less for women, "Visual acuity" should be between 0.7 and 2.0, "Intraocular pressure" should be 10 Change from milliHg to 20 milliHg, "lung function" % vital capacity of 80% or more and 1 second rate of 70% or more, "urinalysis value" urine protein (+-) ketone body (-) urine Sugar (-) occult blood reaction (+-) urobilinogen (+-) urine specific gravity between 1.0101 and 1.025, pH between 4.8 and 7.5, urine pH between (-) The urinary albumin quantitative test value should be less than 30 mg/g. Fecal worm egg test (-), "blood chemistry value" between 0.2 mg/dl and 1.2 mg/dl total bilirubin, ZTT (Kunkel test) between 2.0 units and 12 between 0 units, TTT (thymol turbidity reaction) between 0 and 4 units, ALP (alkaline phosphatase) between 110 lU/l and 354 lU/l, CK (CKP) (creatine kinase) between 38 lU/l and 196 lU/l for men, between 30 lU/l and 172 lU/l for women, LAP (leucine aminopeptidase) between 30 lU/l and 70 lU/l, LDH (lactate dehydrogenation Enzymes) between 121 lU/l and 245 lU/l, γ-GT below 80 lU/l, cholinesterase between 213 lU/l and 501 lU/l, AST (GOT) below 35 lU/l, ALT (GPT ) to 40 lU/l or less, total cholesterol between 140 mg/dL and 219 mg/dL, triglycerides between 30 mg/dL and 149 mg/dL, HDL cholesterol at 40 mg/dL deciliter to 119 milligrams/deciliter, LDL cholesterol from 60 milligrams/deciliter to 139 milligrams/deciliter, serum amylase from 38 lU/l to 136 lU/l, uric acid from 2.1 milligrams/deciliter to 7.0 Between milligrams/deciliter, urea nitrogen between 8 milligrams/deciliter and 22 milligrams/deciliter, total protein between 6.5 grams/deciliter and 9.0 grams/deciliter, serum albumin between 4.0 grams / deciliter or more, protein A/G ratio, protein fraction, A/G ratio from 1.5 to 2.5, Alb from 60.2% to 71.4%, α-1 from 1.9% to 3 .3%, α-2 between 5.7% and 9.7%, β between 6.9% and 10.7%, γ between 10.5% and 20.3%, and creatinine between 1 in men. ≤ 0 mg/dL, ≤ 0.7 mg/dL for women, eGFR > 60 mL/min/1.73 m2, TSH (thyroid stimulating hormone) 0.54 μU/ml to 4.54 μU/ml between 58 and 188 micrograms/deciliter of serum iron, BNP (human brain natriuretic peptide) below 18.4 pg/ml, Na (sodium) between 135 mEq/l and 150 mEq/ml l, K (potassium) between 3.5 mEq/l and 5.3 mEq/l, Ca (calcium) between 8.4 milligrams/deciliter and 10.2 milligrams/deciliter, Cl ( chloride) between 98 mEq/l and 110 mEq/l, P (inorganic phosphorus) between 2.5 mg/dL and 4.5 mg/dL, total homocysteine between 3.7 nmol/ml and 13.5 nmol /ml, and so on.

In addition, the background purpose of mental health is to create a situation in which words and gestures that utter words and gestures that suggest that they are in a state of "peace of mind,""mentalstability," and "relaxation" are acquired as external information. , to maintain the status quo.
In addition, mental health status is not only good or bad, but also relief, anxiety, gratitude, surprise, excitement, curiosity, sexual curiosity, calmness, impatience, wonder (confusion), good luck, relaxation, tension, Honor, Responsibility, Respect, Affinity, Admiration, Desire, Fear, Courage, Pleasure, Regret, Satisfaction, Dissatisfaction, Regret, Disgust, Shame, Contempt, Jealousy, Guilt, Murderous Intent, Expectation , superiority, inferiority, resentment, suffering, sadness, sorrow, emotion, anger, resignation, despair, hatred, emptiness, etc., are graded, scored, and stored. For example, if the mental health status information is D, the second worst rank for anxiety, the background objective is to have the anxiety rank of the mental health status information B rank or higher, which is one rank higher than the middle one. is.

In addition, by analyzing photos and videos on SNS, it is possible to determine whether the person is shrugging, blank, impatient, frowning, embarrassed, flinching, irritated, sullen, or pouting. playing, frowning, fidgeting, determined, confused, flinching, fearful, bitter, staring being upset, irritable, upset, depressed, joking, disgusted, distracted, sad, upset, stunned, discouraged, cheerful, timid, guilty, defiant, troubled, quizzical, dismayed, warped , hesitant, overwhelmed, laid back, shy, envious, mocking, frustrated, naive, uneasy, looking sorry, sneering, pitying, relaxed, reserved, pissed off, unfocused, unimpressed, ecstatic present, relentless, open-minded, exultant, relaxed and at ease, delighted, lonely, disappointed, compromising, ruthless, timid, admiring, despising, meek, bold, sensitive, attuned, calm, resentful, single-minded, It is also possible to set a rule so that mental health status information can be obtained by ranking or quantifying it.

It should be noted that these superordinate concepts are the superordinate concept objectives of making the body healthy by improving habits of daily life and maintaining it. External information obtained in relation to the user is transformed into information that can be evaluated in view of the above background purposes. This background objective and the stored response interaction information analysis content are configured to be associated in a many-to-many relationship. For example, "I slept well" is judged to be positive if it is a normal sleeping time zone, and is judged to be negative if it is an action during working hours. A photo analysis program and a video analysis program are used to analyze photos and videos. A large number of photographs and images are stored in association with semantic information, and the distance in the N-dimensional space between each photograph or image and the photograph or image included in the response dialogue information is measured. The N dimension is the number of types of features of the photograph or video, and the larger the number of dimensions, the more accurate estimation is possible. Therefore, the meaning of the photograph or video can be obtained more accurately, and the subsequent determination of the validity determination rule will also be more accurate. In this way, effectiveness judgment is carried out through the procedure of obtaining meaning and evaluating the effectiveness of the obtained meaning in relation to the background purpose.

Alternatively, it is conceivable to evaluate the effectiveness of certain dialogue information based on proximity, ie, how closely each user has taken actions or formed intentions to the advice contained in the dialogue information. Specifically, when the user takes exactly the same actions or thoughts as the advice, or when the user takes additional actions or thoughts that are not inconsistent with the advice in addition to the actions or thoughts that are completely the same as the advice, it is considered to be the behavior of the user. Since the approximate value of the content of the advice is 100%, the highest evaluation is 5 on a scale of 5. If the user follows the advice but takes a partly different action or takes an action that contradicts the advice that is not in the advice, the approximate value of the user's action and the content of the advice will not be 100%, so 90% to 80%, and in the 5-point evaluation, it is 4, which is highly evaluated but not the highest. Although the user follows the purport of the advice, if the purport is realized by actions and thoughts different from the advice, and if the results are acceptable, the approximate value of the user's actions/thoughts and the content of the advice is 50. % to 70%, and in the 5-point evaluation, the effect is 3, which cannot be evaluated as particularly good for those who have a certain degree of effect. If the user does not follow the advice, but does not act or think inconsistent with the advice (i.e., does not react to the advice or ignores the advice), the user's behavior and the content of the advice The approximate value is 20% to 40%, and the 5-point evaluation is 2, which indicates that the expression has no value for the user. If the user actively takes actions that contradict the advice, the approximate value of the user's actions and the content of the advice will be from 0% to 10%, and the 5-point evaluation will provoke the user's opposition. It becomes 1 as a harmful expression. A method of performing such an evaluation is conceivable.

Also, a single piece of dialogue information may contain a plurality of elements such as advice, questions, and guidance dialogues described below. In this case, it is possible to determine the effectiveness for each element, or it is possible to determine the effectiveness based on the sum of the elements. Synergistic effects and inhibitory effects of combinations may occur by combining elements in a complex manner and outputting dialogue information. Therefore, a configuration is conceivable in which a rule for calculating the degree value of synergistic effect and the degree value of inhibitory effect is also included as the content of the validity determination rule.

<Determining the effectiveness of guidance dialogue information>
Furthermore, the effectiveness of dialogue information can be determined not only for the advice itself, but also for the guiding dialogue, which is the dialogue used to increase the effectiveness of the advice. There are several types of guiding dialogues. Examples of types include, first, a kind of guiding dialogue that draws attention to the speaker system, a kind of guiding dialogue that makes the system favorable, a kind of guiding dialogue that makes the system interesting, The kind of guided dialogue that evokes some sort of association based on the dialogue from the system, the kind of guided dialogue that gives some desire to the dialogue from the system, and the desire to make some kind of comparison with the dialogue from the system. the kind of guided dialogue that makes the system feel certain, the kind of guided dialogue that makes the dialogue from the system provoke some kind of decision, etc. can be mentioned. It is not necessary for the system to assign all of these types of guiding dialogue attributes, but assigning one or more of these types enables effective statistical processing. Note that these types (guidance dialogue attributes) may be stored in the dialogue information storage unit in association with the dialogue identification information. Further, a configuration is also conceivable in which the validity of the output timing of dialogue information and the timing between dialogues is also determined.

It is conceivable that the method of determining the effectiveness of guidance dialogue information is also based on numerical evaluation, similar to dialogue information including advice. The numerical value of the numerical evaluation cannot be determined based on the proximity between the user's behavior and the contents of the advice, because the behavior corresponding to the dialogue is not fixed like the dialogue information including advice. The factors that can be used for evaluation also become more complex. Since there is a user's action including advice at the end of a chain of dialogue information that does not include advice, when the user followed the advice as a result, the flow of dialogue leading to it was effective for the user. that can be evaluated. In this case, the combination of chained dialogue information, the number of dialogues repeated before advice, the grounds for deciding to switch to dialogue information including advice, the details of the arrangement according to the user attributes of the selected dialogue information, and the user to the advice response time, proportion of expressions other than letters given by the user in response to advice, frequency (pictograms, emoticons, stamps, photos, etc.), whether users actively ask questions, etc. in response to advice , etc., which can be obtained from the SNS user-related information that a person would unconsciously judge in an interpersonal conversation, can be a judgment factor for the effectiveness of the guidance dialogue information.

It should be noted that determination of the proximity between advice and user behavior in dialog information including advice can also be obtained from SNS user-related information that people unconsciously judge in interpersonal conversations, as described above. Any and all elements can be effective elements for judging proximity.

<Evaluation of user's negative reaction>
Since this system is a system that learns the combination of dialogue information, the flow of dialogue leading up to advice (guidance dialogue), and the selection, it also learns the user's non-response and negative attitude. , it is possible to determine the effectiveness of the selected dialogue information and continue to select and output dialogue information that is effective for the user. For example, if the user has read the dialogue information output to the dialogue output from the system but has not responded, or if the output dialogue information has not been read for a long time, If there is no response at all, it is considered that the output was at an undesirable timing for the user, an undesirable tone of voice, an undesirable output from an avatar, etc. If the effectiveness of the process is high, it is possible to evaluate whether the flow of dialogue was unfavorable to the user, or that the selection of a dialogue format was unfavorable to the user. . Based on the effectiveness obtained from such negative reaction information of each user, it is possible to obtain the statistical effectiveness of dialogues with respect to negative reactions.

The effectiveness of the dialogue for negative reactions is different from the general effectiveness. attributes), user's personality, environmental factors, etc., when the dialogue information is output in an environment different from the general dialogue environment, it becomes effectiveness information for the uncommon environment of the user. In other words, it often doesn't react when it's time to eat, it often doesn't react when the boss scolds it, it often doesn't react when it's a fight with a friend, it often doesn't react when it's time to wake up. etc. can be obtained as effectiveness. In order to determine the validity of the negative dialogue information, it is conceivable to configure the response dialogue information acquisition section to have negative dialogue information acquisition means. Further, it is conceivable that the dialog information validity determination unit has negative dialog information validity determination means. Further, as described above, when judging the effectiveness of dialogue information, it is possible to judge the effectiveness for each environmental factor. Therefore, the effectiveness of dialogue information is also obtained for each environmental factor.

In addition, the character of the user is diagnosed according to various questions to the user and response information from the user, or utterances not including questions to the user and response information from the user, and the character is used as a user attribute. It is possible to keep it. It is conceivable that this personality diagnosis is configured such that personality diagnosis rules are stored in this system, and personality is diagnosed according to dialogue information and response information from the user. It is also possible to use a commonly used personality test for this purpose. Personality diagnostic tests include the questionnaire method, the projective method, and the task test method. The questionnaire method is a test method for diagnosing a person's personality by answering questions and scoring the answers. This test includes the main five-factor personality test, the main five-factor personality test for children and students, the YG personality test (Yatabe-Guilford personality test), the MMPI (Minnesota Multifaceted Personality Inventory), the MPI (Moseley personality test), and the egogram. and so on. Projection methods include test methods in which subjects are asked to accomplish some task using relatively vague stimuli. In addition, there are Rorschach test, TAT (Thematic Apperception Test), Baum Test (Tree Test), SCT (Sentence Completion Test), P-F Study (Painting Frustration Test), CPT (Color Pyramid Test), etc. The work test method is a test method in which a subject is made to perform a certain work and personality is diagnosed from the result. For example, there are the Uchida-Kraepelin psychiatric examination and the Bourdon obliteration examination. In this system, one or more of these can be used in combination.

<Type of Personality>
There are various ways of classifying personality types. For example, in temperament typology, "Cyclical temperament: Alternates between sociable and quiet times, Divisive temperament: Unsociable, both oblivious and noticing, Sticky temperament: Methodical, active Introverted temperament: Introverted temperament: Interested in things in the external world. Interested in the subjective factors of the world.Thoughtful.Tends to be unaffected by the opinions of those around him.Thinking temperament:Strong ability to perceive things consistently through intelligence.Emotions:Strong tendency to perceive things based on likes and dislikes. , Intuitive temperament: The ability to perceive the possibilities behind things is strong, Sensory temperament: The ability to perceive physiological stimuli is strong", and Dilthey's classification is classified as "heroic type, sensual type, contemplative type". Or, as Spranger's classification, "theoretical person, economic person, esthetician, power person, religious person, social person", and Erich Fromm's classification as "receptive, exploitative, accumulative Karen Horney's classification as 'Dependent, Aggressive, and Separating', and the Enneagram classification as 'Critic, Helper, Performer, Artistic House, Observer, Loyalty, Enthusiast, Challenger, Mediator", and Haruya Noguchi's classification of body habits is as follows: "Upper-bottom type: Brain type sensitive to praise and praise, Left-right type: Sensitive to likes and dislikes" Sensitive digestive type, anteroposterior type: Respiratory type sensitive to gains and losses, Torsion type: Sensitive to winning and losing, Opening and closing type: Genital type (pelvic type) sensitive to love and hate, Slow type: Body hypersensitive or insensitive Various classifications such as "type" can be used, and these classifications can be mixed and used. By holding these personality classifications as user attributes, statistically analyzing dialogue information and response information for each personality classification, what kind of response information exists for what kind of dialogue information (including introductory dialogue), By analyzing whether the effectiveness of dialogue information is judged, it is possible to determine how effective the introductory dialogue (dialogue selection) should be, even if there is a negative reaction to each attribute. can. By judging the effectiveness of the guidance dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule or the never-give-up process. It is possible to improve the system of dialogue methods such as being attacked by various means. By selecting dialogue information based on the validity judgment rule according to the user's personality, it is possible to change the selection, output mode, and output format of the dialogue information to be selected until the user elicits a positive response. It is also possible to tenaciously output dialogue information to the responding user and induce a positive response. As a result, it becomes possible to make the positive response continue, and it becomes possible for the user to make a habit of giving the positive response naturally.

User attribute information is configured to be stored in a user attribute information storage unit or the like in association with user identification information. The user attribute information held in the attribute information holding unit may be updated. Further, it may be configured such that a personality diagnosis test, which will be described later, is performed regularly or irregularly (using personality diagnosis dialogue information or the like) to update this retained user attribute information. Furthermore, regarding the user's personality that constitutes the initial user attribute information, a median value is assigned after each personality type is scored and held, or a questionnaire is conducted for users and the questionnaire results are held. It is conceivable to configure it so that Further, the personality may be configured such that the conversation information of the SNS is analyzed by the conversation information analysis unit based on the conversation information analysis rule and the personality is determined. Since a huge amount of conversations with friends or the like is stored in SNS, it can be used effectively. Further, it may be configured such that reading tendency, movie preference tendency, music preference, hobby, favorite entertainer or celebrity, etc. introduced in the SNS are analyzed to determine personality. Furthermore, it is possible to diagnose the personality by analyzing the place where the user checked in, the photograph in which the user himself/herself is included or not, and the like. Places where you can check in include commercial facilities (department stores, supermarkets, convenience stores, home appliance mass retailers, fast fashion, esthetic salons, beauty salons), entertainment facilities, stadiums, restaurants, museums, parks, stations, ports, airports, national parks, Personality can be analyzed in public parks. For example, are you active, do you like shopping, are you quiet, and so on. Personality analysis can be performed based on whether there are many group photos, whether there are many photos of one person, whether there are many landscape photos, and whether there are many photos of food. Note that the personality analysis rule can be designed according to the design policy. In addition, it is also possible to analyze a user's character according to the character of a friend connected via SNS.

<Embodiment 6 Dialogue Information Validity Determining Unit>
The 'dialogue information validity determination unit' determines the validity of the dialogue information based on the output dialogue information, the response dialogue information obtained for this dialogue information, and the validity determination rule. The effectiveness is highest when the user's response dialogue information matches the output dialogue information, and the effectiveness decreases as the approximation increases. When multiple elements are included, such as when multiple advice contents are combined, questions and advice are mixed, it is possible to judge the effectiveness of each element, or make a composite judgment. It is also possible to Moreover, since it is conceivable that a synergistic effect or an inhibitory effect may occur due to the combination, it is conceivable to configure such that the degree of synergistic effect and the degree of inhibition can also be determined. The degree of synergistic effect and the degree of inhibition are the differences and ratios when comparing the numerical value of effectiveness when simply summing the effectiveness of each element in combination with the numerical value of effectiveness of the combined state. can be obtained as

<Sixth Embodiment Hardware Configuration>
FIG. 19 is a diagram showing the hardware configuration of the sixth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the sixth embodiment shown in this figure, the programs that operate in common with the fifth embodiment have already been explained, so the explanation will be omitted. The "validity judgment rule holding program" newly added in this embodiment holds validity judgment rules. The 'dialogue information validity determination program' determines the validity of the output dialogue information based on the validity determination rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Various setting information such as dialogue information, response dialogue information, effectiveness judgment rules, effectiveness judgment results, communication (not shown), etc. be done.

<Embodiment 6: Flow of processing>
FIG. 20 is a diagram showing the processing flow of the most basic configuration of the sixth embodiment. As shown in this figure, user identification information storage step (2001), SNS user related information acquisition step (2002), analysis rule storage step (2003), health status information analysis acquisition step (2004), dialogue information storage step (2005). ), user-by-user dialogue information selection rule holding step (2006), dialogue information selection step (2007), dialogue information output step (2008), response dialogue information acquisition step (2009), effectiveness judgment rule for holding effectiveness judgment rule It consists of a holding step (2010) and a dialog information validity judging step (2011) for judging the validity of the dialog information from the response dialog information.

<Embodiment 7>
<Summary of Embodiment 7 Invention>
In addition to the feature of claim 6, the invention in this embodiment has a rule for statistically processing the effectiveness of dialogue information of a plurality of users in the dialogue information validity determination unit.

<Embodiment 7 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 7 includes, as shown in FIG. Situation information analysis and acquisition unit (2104), dialogue information storage unit (2105), user dialogue information selection rule storage unit (2106), dialogue information selection unit (2107), dialogue information output unit (2108), response dialogue information acquisition unit (2109), validity judgment rule storage unit (2110), dialog information validity judgment unit (2111), validity statistical processing rule storage means (2112), statistical dialogue information validity information acquisition means (2113) Become. Hereinafter, the description of the common configuration with the sixth embodiment will be omitted, and the characteristic configuration of the present embodiment will be described.

<Description of Embodiment 7 Configuration>
<Embodiment 7 Effectiveness Statistical Processing Rule Holding Means>
The "effectiveness statistical processing rule holding means" holds an effectiveness statistical processing rule, which is a rule for statistically processing the effectiveness of interactive information of a plurality of users at least for a population for each common attribute. As the processing in the dialog information validity determination unit described above, generally speaking, the validity of the dialog information for a specific user is determined from the response dialog information returned in response to the dialog information output to the specific user. It is conceivable to judge on an individual basis. However, although the effectiveness of dialogue information can be judged based on the relationship with individual individuals, it is also possible to judge the statistical effectiveness of a group. For example, just as the characteristics of ethnic groups and people differ slightly from country to country and region to country, it is only natural that certain trends emerge within a country, depending on the population. For example, if the population is the Japanese population, it is possible to narrow down the dialogue information that has a certain degree of effect on the entire Japanese population, and the population is determined according to other attributes to narrow down the effective dialogue information. can also

A method for acquiring user attributes has been described in the first, fourth, and sixth embodiments. In this system, it is assumed that some attribute information of the user is held in association with the user identification information. Health status information can also be included in this. By constructing a population with such attributes and narrowing down effective dialogue information for each population with common attributes, we have improved the accuracy of dialogue even more than the effectiveness of dialogue found from response information to individual dialogue information. Effective dialogue information can be narrowed down (selected). Effectiveness information statistically processed for dialogue information is obtained for each user attribute. Therefore, by updating the user-by-user dialogue information selection rule of the user identified by the user identification information having the user attribute, the system is updated as needed so that the dialogue information corresponding to the user attribute can be selected. . In addition, if there is a contradiction between the effectiveness judgment result found from the dialogue information for an individual user and its response information and the effectiveness judgment result statistically processed, the effectiveness judgment result for each user give priority to Also, if the two do not contradict each other, weighting can be used to determine the order of effectiveness. It is considered that the most effective weighting is to weight the judgment result of each individual. may be weighted to about 7:3 and 6:4 and incorporated into the user-by-user dialogue information selection rule.

<Regarding effectiveness statistical processing rules>
"Effectiveness statistical processing rule" means a rule for acquiring the statistical effectiveness of certain dialogue information and a rule for determining the identity of dialogue information that differs for each user and is arranged according to user attributes. , is composed of two. In this system, the format of the output dialogue information is changed according to the characteristics of the user, so the same message "Please run" is changed to "Let's run" or "Would you like to run?" Or it may be converted to ``Please return to your home (1 km away) in 5 minutes''. Unless it is determined that the output to each user with different expression methods is the same as "Please run", aggregate the data group that will be the population for statistical processing from each user's reaction I can't. The conceptual or expressive breadth of this aggregation can be set based on the operational policy of the system. The width may also be configured to be hierarchically selectable. As a hierarchical structure, for example, the highest level is the "intention" for the user of the system, and the lower level is the "behavior" that the user wants to evoke. There is ``speech (dialogue)'', and below that there are various modest expressions, polite expressions, honorific expressions, equivalent words, and imperative expressions in standard Japanese, and further below that, there are various expressions by dialect, and further below that. It can be constructed so that various indirect expressions (euphemisms, metaphors, etc.) are included in In other words, for example, if the ``intention'' is to supply a large amount of oxygen to the blood, the actions to be induced include ``aerobic exercise'', ``deep breathing'', and ``use of an oxygen capsule''. If the desired action is "aerobic exercise", the "remarks (dialogues)" when expressed directly in the lower standard language are "Let's do aerobic exercise", "Exercise to take in oxygen". For example, if the utterance (dialogue) is "Let's do aerobic exercise", then "I would appreciate it if you could do aerobic exercise" or "I would appreciate it if you could do aerobic exercise" Would you like to exercise?”, “Do some aerobic exercise, please!”, and “Do some aerobic exercise!” If you use the dialect to express "do aerobic exercise", you can say, "do aerobic exercise (Okinawa dialect),""do aerobic exercise (Hakata dialect)," )”, and these are statistically processed as having the same dialogues belonging to the same hierarchy.

After obtaining the effectiveness of each user, how much effectiveness (including both positive and negative sides) of the dialogue information can generally be judged from the distribution of effectiveness of each user It is conceivable to judge statistical validity by judging. Furthermore, the statistical dialogue information validity determination information can be configured to be able to determine the statistical validity of the guidance dialogue and the user's negative reaction. By judging the effectiveness of the guiding dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule or the never-give-up process. It is possible to improve the system of dialogue methods such as being attacked by various means.

<Embodiment 7 Statistical Dialogue Information Effectiveness Information Acquisition Means>
The 'statistical dialogue information effectiveness information obtaining means' statistically obtains the effectiveness of the dialogue information for at least the population based on the dialogue information of a plurality of users and the held effectiveness statistical processing rule. Some obtain statistical interaction information effectiveness information determined for each common user attribute. The reason for "partially for each common user attribute" is that it is rare to be able to form a common population with respect to all user attributes. However, depending on the system configuration, statistical processing may be performed on a population common to all user attributes. This is because the effectiveness of dialogue information tends to be determined according to user attributes, particularly the user's character (nature), gender, age, and in some cases, the region of residence and nationality. Therefore, the user is classified into each kind type indicated by the already explained "personality type", and the effectiveness of the dialogue information is statistically processed, or the degree of matching with each type of personality indicated by the "personality type" is quantified. can statistically process the effectiveness of dialogue information. By performing such statistical processing, it becomes clear what kind of dialogue information is effective for users belonging to each personality. Similar processing can be performed for "gender", "age", "residence area", and "nationality". Furthermore, it is conceivable to grasp the trend of effectiveness of dialogue information by performing statistical processing on arbitrary combinations of "personality", "sex", "age", "residence" and "nationality". In addition, by adding attributes of dialogue information (forcing intensity, intensity of tone, clarity of intention, timing of utterance with the strongest intention, etc.) to the dialogue information and performing statistical processing, not only the effectiveness of the dialogue information but also the It is also possible to determine what attributes of dialogue information are effective based on the attributes attached to the dialogue information. It should be noted that the meaning of "for each user attribute that is partially common to the population" is the 30 and embodiment 39.) As described above, in this system, it is assumed that some attribute information of the user is held in association with the user identification information, and such attribute By constructing a population and collecting the effectiveness information of dialogue information for each population with common attributes, statistical dialogue information effectiveness information is acquired for each user attribute that is at least partially common to the population can do.

"Statistical dialogue information effectiveness information" means the effectiveness of dialogue (from low effectiveness to high effectiveness) according to user attributes, etc. as a result of statistical processing, and various dialogue information with each effectiveness It is information expressed as a function of the number of types of , and is generally normally distributed. In other words, the number of dialogue information with "medium" effectiveness is the largest (the types of dialogue information with average effectiveness are the largest), and the number of dialogue information with "high" and "low" effectiveness is a group of data distributed so that By using this data, it is possible to know what kind of conversational information exhibits how effective it is, and it can be used as a computer. The statistical dialogue information effectiveness information is preferably stored separately for each theme and purpose of using the dialogue information, and a plurality of pieces of information exist for each theme and purpose of using the dialogue information. FIG. 22 is one example of statistical interaction information validity information. On the horizontal axis, the more to the right of the origin, the more positive the effectiveness is, and the more to the left of the origin, the more negative the effectiveness becomes. The vertical axis indicates the number of types of dialogue information, and the higher the position from the origin, the greater the number of types of dialogue information. As shown in the figure, the number of expressions (the number of types) of dialogue information that can be tentatively recognized as effective is the largest among the population having a certain theme or purpose and a certain user attribute, and the number of graphs rises. be the apex. On the other hand, there is not so much dialogue information that is very effective, hardly effective, or harmful, and becomes the left and right foot of the graph mountain. Expressions with some validity exist between the peaks of the graph and the right foot. For example, when the effectiveness of the dialogue information positioned at validity 3 decreases slightly, the dialogue information positioned at validity 3 moves slightly to the left as shown in the figure. The height of the mountain 3 is lowered by the amount that the dialog information is no longer included in the validity 3, and the portion that is slightly shifted to the left from the validity 3 is raised by the amount that the dialog information is included. A slight increase in effectiveness produces a similar change toward the right as shown in the figure. Statistical dialog information validity information is transmitted, and update is repeated each time statistical dialog information validity information is acquired.

<Embodiment 7 Hardware Configuration>
FIG. 23 is a diagram showing the hardware configuration of the seventh embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the seventh embodiment shown in this figure, the programs that operate in common with the sixth embodiment have already been explained, so the explanation will be omitted. The "effectiveness statistical processing rule holding program" newly added in this embodiment holds the effectiveness statistical processing rules. The 'statistical dialogue information effectiveness information acquisition program' acquires statistical dialogue information effectiveness information based on effectiveness statistics processing rules. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Various setting information such as dialogue information, response dialogue information, effectiveness judgment rules, effectiveness judgment results, effectiveness statistical processing rules, statistical dialogue information effectiveness information, communication (not shown), etc. It is loaded into memory and referenced and used when executing a series of programs.

<Embodiment 7: Flow of processing>
FIG. 24 is a diagram showing the processing flow of the most basic configuration of the seventh embodiment. As shown in this figure, user identification information storage step (2401), SNS user related information acquisition step (2402), analysis rule storage step (2403), health status information analysis acquisition step (2404), dialogue information accumulation step (2405). ), user-by-user dialogue information selection rule retention step (2406), dialogue information selection step (2407), dialogue information output step (2408), response dialogue information acquisition step (2409), validity determination rule retention step (2410), dialogue an information effectiveness judgment step (2411), an effectiveness statistical processing rule holding substep (2412) for holding rules for statistically processing the effectiveness of dialogue information of a plurality of users in the dialogue information effectiveness judgment unit, a plurality of users a statistical dialogue information effectiveness information obtaining substep for obtaining statistical dialogue information effectiveness information in which the effectiveness of the dialogue information is statistically determined based on the dialogue information and the held effectiveness statistical processing rule (2413).

<Embodiment 8>
<Overview of Embodiment 8>
In addition to the configuration of the sixth embodiment, the invention in this embodiment has a function of using AI to update rules for selecting health promotion advice based on the effectiveness of output health promotion advice. FIG. 25 is a conceptual diagram showing an outline of the function of AI in this embodiment. This interactive health promotion system holds user-by-user dialogue information selection rules that reflect individual characteristics. The individual characteristics of each user reflected here are reflected both in the form of dialogue information, i.e., the language used during conversation, and in the content of dialogue information, which is health promotion advice content corresponding to health status information. Become.

FIG. 25 is a diagram conceptually showing the process of selecting one piece of dialogue information from a plurality of pieces of dialogue information and changing the selection rule according to the user's response to the selection. As shown in the figure, the horizontal axis (2501) represents the dialogue information group, and the vertical axis (2502) represents the effectiveness of the dialogue information. The degree of effectiveness of dialogue information with the highest degree of effectiveness is the highest vertex (2504) of a plurality of crests of waves. The dialog information around the peak of the mountain is synonymous with the dialog information, and the degree of effectiveness gradually decreases as the distance from the peak increases. In the dialogue information selection rule, first, which dialogue information group area (2505) is to be selected as rough dialogue information is determined, and the most effective one among the selected dialogue information group areas is selected. select. After selecting and outputting the dialogue information, the validity of the selected dialogue information can be obtained by obtaining the user's response dialogue information. An option whose validity is confirmed from the response dialogue information has a higher probability of selection effectiveness than other dialogue information stored in the dialogue information storage unit. Therefore, the selection rule is updated so that the apex of the mountain is at a higher position (2506). As compared with the other dialogue information stored in the dialogue information storage unit, the validity of the selection of the option confirmed as invalid from the response dialogue information is low. Therefore, the selection rule is updated so that the apex of the mountain is at a lower position (2507) than before selection. Alternatively, for example, when health condition information for which rules have not yet been obtained for user X is obtained, interaction information is selected by combining already obtained rules with similar health condition information (pseudo form a stack of interaction information and validity piles in the , and select the interaction information for the vertex). A new rule corresponding to the response result to the output dialogue information is obtained (the pseudo dialogue information group and the pile of effectiveness are modified and reconfigured according to the actual response dialogue information). The effectiveness may be configured to be held according to the effectiveness determined based on the health status information, the effectiveness determined based on other response dialogue information, and the information based thereon. Furthermore, the effectiveness may be expressed as the frequency with which dialogue information should be selected, or the number of times dialogue information should be selected during guidance dialogue. Further, the effectiveness may be configured to be associated with the speaker's avatar or the speech style.

<Configuration of Embodiment 8 Invention>
An example of the configuration of the interactive health promotion system of Embodiment 8 includes, as shown in FIG. Situation information analysis and acquisition unit (2604), dialogue information storage unit (2605), user dialogue information selection rule storage unit (2606), dialogue information selection unit (2607), dialogue information output unit (2608), response dialogue information acquisition unit (2609), validity judgment rule storage unit (2610), dialogue information effectiveness judgment unit (2611), user dialogue information selection rule update unit (2612). Below, the description of the common configuration with the sixth or seventh embodiment will be omitted, and the characteristic configuration of this embodiment will be described.

<Description of Embodiment 8 Configuration>
<Embodiment 8 User-specific dialog information selection rule update unit>
The 'updating unit for individual user interaction information selection rule' updates the individual user interaction information selection rule held in the individual user interaction information selection rule holding unit based on the validity determination result. FIG. 27 is a conceptual diagram showing an overview of the function of AI (artificial intelligence) that updates selection rules in the eighth embodiment. This interactive learning promotion system holds user-by-user dialogue information selection rules that reflect individual characteristics. The individual characteristics of each user reflected here are the form of dialogue information, i.e., the language used during conversation, the content of dialogue information corresponding to health status information, the timing of output of dialogue information, the output interval of dialogue information, and guidance. It will be reflected in the way dialogues are arranged, the process of not giving up (repeating dialogue information with the same intention), and the selection of avatars that output dialogue information. As shown in the figure, for user X (2701), when health condition information A (2702) is selected, rule 1 (2703) for selecting dialogue information "Don't overeat today's lunch." In the case of information B (2704), rule 2 (2705) selects dialogue information "Let's walk to the next station for a change of pace."Let's have a good meal and get some rest early." rule 3 (2707) for selecting dialogue information is held as a user-by-user dialogue information selection rule.

The health status information D (2708) that has not been acquired so far differs from the specific contents of the health status information B by 1 in physical health, 1 in mental health, and 2 in sleep time. However, the rest matches. On the other hand, the specific contents of the health status information A are consistent with physical health, but different from the rest. The specific contents of the health condition information C are the same as the sleep time, the numerical value of the mental health is close, and the rest is different. Based on the above information, we can cite rule 1, rule 2, and rule 3 as related rules. Let's go." (2709) is selected and output. When the response dialog information acquisition unit acquires the response dialog information (2710) that says, "On the way home, I found a nice bar and had a drink" in response to the output dialog information, I feel refreshed, but 2 points (2711) are obtained as the dialogue information effectiveness judgment result because the effectiveness is low in relation to the promotion of calorie consumption. In response to this dialog information validity determination result, a new rule is to select dialog information such as "Let's walk to the next station for a change of pace and go home. Don't detour!" when health condition information D is acquired. (2712) is obtained, the updated user-specific dialogue information selection rule is obtained, and the user-specific dialogue information selection rule held in the user-specific dialogue information selection rule holding unit is updated.

<Embodiment 8 Hardware Configuration>
FIG. 28 is a diagram showing the hardware configuration of the eighth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the eighth embodiment shown in this figure, the programs that operate in common with the sixth or seventh embodiment have already been explained, so the explanation will be omitted. A “program for updating user-specific dialogue information selection rules” newly added in this embodiment updates the user-specific dialogue information selection rules based on the validity determination result. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Various setting information such as dialogue information, response dialogue information, validity judgment rules, effectiveness judgment results, updated user dialogue information selection rules, communication (not shown), etc. are held in non-volatile memory, loaded into main memory, are referenced and used during program execution.

<Embodiment 8: Flow of Processing>
FIG. 29 is a diagram showing a processing flow of the most basic configuration of the eighth embodiment. As shown in this figure, user identification information storage step (2901), SNS user related information acquisition step (2902), analysis rule storage step (2903), health condition information analysis acquisition step (2904), dialogue information accumulation step (2905). ), user-by-user dialogue information selection rule retention step (2906), dialogue information selection step (2907), dialogue information output step (2908), response dialogue information acquisition step (2909), validity judgment rule retention step (2910), dialogue It consists of an information validity judgment step (2911) and an individual user dialogue information selection rule update program (2912) for updating the individual user dialogue information selection rule based on the acquired dialogue information validity judgment result.

<Embodiment 9>
<Embodiment 9 Outline of the Invention>
In addition to the features described in Embodiment 7, the invention in this embodiment updates the user-by-user dialogue information selection rule based on the acquired statistical dialogue information effectiveness information, thereby enabling dialogues according to the individuality of the user. Information can be selected.

<Embodiment 9 Configuration of the Invention>
An example of the configuration of the interactive health promotion system of Embodiment 9 is, as shown in FIG. Situation information analysis and acquisition unit (3004), dialogue information storage unit (3005), user dialogue information selection rule storage unit (3006), dialogue information selection unit (3007), dialogue information output unit (3008), response dialogue information acquisition unit (3009), validity determination rule storage unit (3010), dialog information validity determination unit (3011), validity statistical processing rule storage means (3012), statistical dialog information validity information acquisition means (3013), statistical User-by-user dialogue information selection rule update unit (3014). In the following, the description of the common configuration with Embodiment 7 or Embodiment 8 is omitted, and the characteristic configuration of this embodiment will be described.

<Description of Embodiment 9 Configuration>
<Embodiment 9 Statistical user-by-user dialogue information selection rule update unit>
The “statistical user-by-user dialogue information selection rule update unit” updates the user-by-user dialogue information selection rule stored in the user-by-user dialogue information selection rule storage unit based on the acquired statistical dialogue information effectiveness information. The statistical dialogue information effectiveness information is used to select dialogue information to be output to the user. Therefore, the statistical dialogue information validity information is information that should be reflected when updating the user-by-user dialogue information selection rule. The user-by-user dialogue information selection rule is updated by statistical dialogue information effectiveness information and/or effectiveness determination results.
It should be noted that how the effectiveness of dialogue information obtained independently for each user and the effectiveness of dialogue information obtained by statistical processing are reflected in the dialogue information selection rule depends on the design concept of the system. When effectiveness is acquired based on individual user's learning effect information, learning history information, and response dialogue information, the reliability of the effectiveness, such as the P value, the significance level (statistical term) is compared to compare the reliability It is conceivable to design so as to give a weight that reflects according to the size of . It should be noted that when updating the user-by-user dialogue information selection rule statistically, the same design can be applied throughout this specification.

<Embodiment 9 Hardware Configuration>
FIG. 31 is a diagram showing the hardware configuration of the ninth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. Of the programs constituting the hardware of the ninth embodiment shown in this figure, the programs that operate in common with the seventh or eighth embodiment have already been explained, so the explanation will be omitted. The "statistical user-by-user dialogue information selection rule update program" newly added in this embodiment updates the user-by-user dialogue information selection rule based on the statistical dialogue information validity information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), analysis rules, health status information, dialogue information, user-by-user dialogue information selection rules, selection Dialogue information, response dialogue information, effectiveness judgment rules, effectiveness judgment results, effectiveness statistical processing rules, statistical dialogue information effectiveness information, updated user-specific dialogue information selection rules, various setting information such as communication (not shown), etc. It is held in non-volatile memory, loaded into main memory, and referenced and used when executing a series of programs.

<Ninth Embodiment Processing Flow>
FIG. 32 is a diagram showing the processing flow of the most basic configuration of the ninth embodiment. As shown in this figure, user identification information storage step (3201), SNS user related information acquisition step (3202), analysis rule storage step (3203), health status information analysis acquisition step (3204), dialogue information storage step (3205). ), user-by-user dialogue information selection rule retention step (3206), dialogue information selection step (3207), dialogue information output step (3208), response dialogue information acquisition step (3209), validity determination rule retention step (3210), dialogue information effectiveness determination step (3211), effectiveness statistical processing rule retention sub-step (3212), statistical dialogue information effectiveness information acquisition sub-step (3213), user-specific dialogue based on the acquired statistical dialogue information effectiveness information and a statistical user interaction information selection rule update step (3214) for updating the information selection rule.

<Embodiment 10>
<Overview of Embodiment 10>
The invention in this embodiment is an invention describing the method of the first embodiment, and basically expresses the category of the invention of the first embodiment as a method of operating a computer.

<Embodiment 10 Configuration of the Invention>
FIG. 33 is a diagram showing the most basic configuration of the operating method of the interactive health promotion system of the tenth embodiment. As shown in the figure, an SNS user-related information acquisition step (3301) for acquiring SNS user-related information as external information, a health status information analysis acquisition step (3302) for acquiring health status information based on the analysis of the analysis rule, It consists of a dialogue information selection step (3303) for selecting dialogue information based on the obtained health status information and the user-specific dialogue information selection rule, and a dialogue information output step (3304) for outputting the selected dialogue information.

<Embodiment 11>
<Overview of Embodiment 11>
The invention in this embodiment is an invention that describes the method of Embodiment 1, and basically expresses the category of the invention of Embodiment 1 as a computer operating program.

<Embodiment 11 Configuration of the Invention>
The most basic configuration of the operation program of the interactive health promotion system of the eleventh embodiment is, as shown in FIG. 3302), a dialog information selection step (3303), and a dialog information output step (3304). Since the configuration is common to the embodiment, the description is omitted below.

<Embodiment 12>
<Outline of Embodiment 12 Invention>
The present embodiment to the 21st embodiment describe an interactive learning promotion system. The interactive learning promotion system in the present embodiment is related to learning such as user's learning history, learning effect, etc. acquired by the learning system in addition to external information such as user's statement information and browsing information on SNS By acquiring information and using it for analysis, we acquire the user's learning situation (including the user's introverted elements such as learning motivation, learning attitude, spontaneity, and continuity without simply focusing on grades). , promotes the user's learning by selecting dialogue information suitable for the user's current learning situation. FIG. 34 is an image conceptual diagram showing the relationship between the interactive learning promotion system, various SNSs, and the learning system. When a user (3401) who communicates using SNS1 (3402a) and SNS2 (3402b) on a daily basis specifies SNS2 as the SNS for using this interactive learning promotion system (3403), This interactive learning promotion system outputs interactive information through SNS2 (3404). This interactive learning promotion system is installed outside this interactive learning promotion system in addition to the SNS user related information (3405a) that can be acquired through SNS1 and/or the SNS user related information (3405b) that can be acquired through SNS2. Learning history information, learning effect information, etc. (3408) are acquired from a learning system (3407) or the like used by a certain user.

<Learning system>
There can be multiple types of learning systems. In type 1, the learning history information, etc. is separated from the learning materials and held in the learning system server, and is output to the interactive learning promotion system. The learning materials are stored in the system server, and the learning materials themselves are provided to the user via the Internet, etc., the answers are returned to the learning system server via the Internet, etc., and the results graded by the rater are input to the learning system server, and sent via the Internet. This is a type in which learning history information is output to this interactive learning promotion system. Type 3 is basically the same as type 2, but the learning system server itself grades the returned answers. . Type 2 is mostly applied to essay-type questions, and type 3 is mostly applied to multiple-choice questions. Type 3 can also be applied to English pronunciation problems and listening problems, and also includes a type in which the learner is asked to make an argument by selecting an option, or to answer a calculation formula on the way. Type 3 includes foreign languages, arithmetic, science (science: chemistry, physics, biology, geology, astronomy), history, geography, ethics, society, politics, economics, arts, music, home economics, health and physical education, etc. can also include

<Learning system type 1>
The learning system server is provided with an input/output interface, through which learning history information and learning effect information are input by the questioner and/or the grader. This input may be performed in association with user identification information, and grader identification information may be input and output in association with learning history information and learning effect information. It is mainly used for the type of learning where practical skills are essential for learning.

<Learning system type 2>
The type 2 learning system server has common functions with the type 1 learning system server. In other words, in addition to holding learning history information and learning effect information, learning materials and answers, which are the learning results of users, are also held. The learning history information is automatically or semi-automatically generated based on the transmission history of learning materials to the user and the reception history of answers from the user.

<Learning system type 3>
The type 3 learning system server has common functions with the type 1 and 2 learning system servers. In other words, learning history information, learning effect information, learning materials, answers that are the user's learning results, and the like are also held. It also has a scoring function for the received answers. Scoring can be automatically performed for multiple-choice questions, and for essay questions, the grading result of the grader may be obtained, or grading may be performed by artificial intelligence.

FIG. 35 is an image conceptual diagram when the interactive learning promotion system gives learning promotion advice to a certain user. The interactive learning promotion system (3501) uses conversational information ("I'm still sleepy today", "Good morning", etc.) that users (3502) who have registered with the interactive learning promotion system routinely send using SNS, etc. "I've been staying up late lately." "I have a midterm test soon." "I hate mathematics. I hate my country." "I want to see that drama today." Automatically acquire (3504) user-specific SNS user-related information (3503) such as (browsing open campus information, etc.). Furthermore, at least learning history information and learning effect information are acquired from the learning system (3505). Learning status information (3507) is acquired by comprehensively analyzing (3506) the acquired SNS user-related information, learning history information, and learning effect information. This interactive learning promotion system uses the acquired learning situation information to determine the background purpose (e.g., ``I like mathematics that I dislike'', ``Improving motivation to study'', ``Studying part of the time spent playing games'', etc.). ) to select appropriate interaction information to achieve the objective. For example, if you want the user to study for a test, you can use dialogue information that is appropriate for achieving your goal: "Good morning! If you don't hurry up, you'll be late (;∀;) Lack of sleep?I fell asleep in class, (u_u)..oO It's almost halfway through, and karaoke would be nice, but why don't we have a study session at a cafe? Receive interactive information (3508) in a tone suitable for the user using SNS, such as "use is planned (* '艸 `)", and interaction with the interactive learning promotion system owned by the user The form to be performed is output to the terminal (3509).

The first feature of the interactive learning promotion system is that in addition to the information related to the user's learning held by the learning system (learning history information, learning effect information, etc.), external information such as remarks on SNS there is Next, as a second feature, we analyze the obtained information related to learning and external information as data, and rather than simply obtaining numerical information on academic ability, are analyzed as the case may be, and "current learning status information" that considers the motivation to learn is analyzed and acquired. Furthermore, as a third feature, the optimal advice content is selected from the "current learning situation information" obtained by analysis, and the optimal tone is matched to the tone that the user is usually familiar with and easy to persuade. output the advice content selected using

<Embodiment 12 Configuration of the Invention>
FIG. 36 is a diagram showing an example of the configuration of an interactive learning promotion system according to the twelfth embodiment. As shown in the figure, the interactive learning promotion system of the twelfth embodiment includes a first learning user identification information holding unit (3601), a first learning SNS user related information acquisition unit (3602), a first learning history information acquisition unit ( 3603), first learning effect information acquisition unit (3604), first learning analysis rule storage unit (3605), first learning situation information analysis acquisition unit (3606), first learning dialogue information storage unit (3607), first It consists of a learning user-specific dialogue information selection rule holding unit (3608), a first learning dialogue information selection unit (3609), and a first learning dialogue information output unit (3610).

<Description of Embodiment 12 Configuration>
<Embodiment 12 First learning user identification information holding unit>
The 'first learning user identification information holding unit' holds user identification information for identifying users who use the SNS and the learning system. The stored user identification information is the user identification information in this interactive learning promotion system of the user using this interactive learning promotion system. Name, address, telephone number, e-mail address, ID specially set by the user, date of birth, occupation, age, gender, etc. are generally stored in association with user identification information, and further related to health. physical information of the user (for example, height, weight, average body temperature, average pulse rate, average respiratory rate, average heart rate, average amount of exercise (time, quality, mode, etc.), whether or not the user goes to the gym) information such as In this interactive learning promotion system, in addition to or in place of the user's physical information, information related to the user's learning (graduation school information, school attendance information, specialized information, belonging laboratory information, Constructed to include one or more of areas of expertise, examination results, native language, second foreign language, family educational background, travel history, study abroad history, purchase reference book history, average sleep time, average self-study time, cram school history, etc.) can do. Further, it is configured to include information for identifying the learning system used by the user, an ID used by the user in the learning system, and the like. Furthermore, as a life log that shows the user's physical condition, heart rate, pulse rate, respiration rate, body temperature, degree of muscle contraction/relaxation, electroencephalogram, blood flow velocity, blood oxygen concentration, blood alcohol content, allergies It may be configured to include one or more of the degree of reaction, the degree of accumulation of fatigue substances, and the like. These are obtained from a wearable terminal that is worn on the body and capable of measuring the state of the body, or a physical data measuring device that is not worn on the body but has a communication function, or the like. Alternatively, physical data stored in a portable memory that is not in communication can be transferred to a portable memory (e.g., USB memory, IC card (including prepaid card with RFID function, etc.), portable disk drive, optical recording medium, magnetic memory, etc.). ) can also be obtained from In the case of a prepaid card, it is possible to obtain data indicating the physical condition by receiving information on the physical condition at the time of medical examination or payment of fees for medical treatment by a doctor. The user attribute information held in association with the user identification information is configured to be registered by the user himself/herself when starting to use the interactive learning promotion system. With this registration, the interactive learning facilitation system can be configured to be available. Furthermore, the user attribute information can be transferred or copied from another system already used by the user. For example, cram schools, schools, classrooms, correspondence courses, other learning systems, academic ability test databases, and learning chart systems used by users User evaluations related to learning are recorded as a history (for example, in units of learning) that can be used by the user), and the learning application used by the user, the academic achievement measurement application used by the user, etc. You can use data such as

<Embodiment 12 First learning SNS user-related information acquisition unit>
The 'first learning SNS user-related information acquisition unit' acquires, as external information, SNS user-related information, which is user-related information including comments on the SNS used by the user in association with the user identification information. Here, the definitions of "SNS user-related information" and "SNS" have already been explained in Embodiment 1 regarding the interactive health promotion system. "Acquisition" may be obtained by filtering. For example, the department may have keyword holding means for holding keywords related to learning, and may be configured to acquire only conversations containing those keywords. In addition, the scope of acquisition is not limited to utterances directly made by the user, and utterances made among related parties of the user may also be acquired. In particular, when the user is a student, it is considered that many of the related parties are friends from the same school or the same cram school. be. Information that can be gleaned from such statements among stakeholders is, "This math test was difficult...", "How are you preparing for next week's year-end exam?" It seems that 12 students passed the medical school this year...", which can be used to estimate the learning level and test level of the study group to which the user belongs. Furthermore, when the user is using a learning community within the SNS, if the user is configured to sufficiently (completely) acquire statements within this community, a learning environment for acquiring learning status information, which will be described later, will be established. Improves estimation accuracy.

<Embodiment 12 First Learning History Information Acquisition Unit>
The ``first learning history information acquisition unit'' is a learning history that is information indicating the history of learning performed in the learning system from the learning system used by the user in association with the user identification information and/or independently of the learning system. Get information. Here, “learning” generally refers to the occurrence of sustained changes in behavior through experience, or changes in behavior, thinking, knowledge, and behavioral abilities, resulting in an increase in the number of problems that can be solved, or the time required to solve them. It refers to actions that shorten the time, increase the ease of acquiring knowledge, and make it possible to take new actions. Learning using various learning systems linked to schools, cram schools, and interactive learning promotion systems is supported by teachers, various learning systems, and interactive learning promotion systems based on widely specified educational objectives and goals. It is a thing, and the learner takes the lead. The side that provides learning may include not only various systems that cooperate with the interactive learning promotion system, but also those by actual teachers (including seminar instructors who conduct classroom lectures, cram school instructors, home tutors, etc.). . Learning includes athletic ability (various sports), performance ability, creative ability (clothing, cooking, flower arrangement, tea ceremony, architecture, sculpture, painting, calligraphy, etc.), competitive ability (go, shogi, chess, mahjong, video games, Card games, Hanafuda games, Hyakunin Isshu, Othello, board games), and learning to acquire and maintain communication skills (presentations, discussions, etc.).

In this specification, learning may mainly refer to knowledge acquisition and sustained knowledge maintenance. Learning consists mainly of reading, listening to, and possibly using logical formulas consisting of sentences, diagrams, photographs, videos, mathematical formulas, chemical formulas, equations, and logical symbols to impart knowledge, thereby acquiring and maintaining that knowledge. It means to This includes the challenge of solving problems, understanding the errors in the challenged problems, and understanding the correct answers to the challenged problems.

“Learning history information” is a history of learning activities. The history of learning activities includes, for example, the types of teaching materials read or viewed (textbooks, reference books, examples, videos, photographs, audio, reference URLs on the network, etc.), the distribution date and time of the teaching materials, and the scope of instruction for learning the teaching materials. and the presence or absence of the course in the learning instruction range, the course period, the course time, the course activity (page turning activity, screen scrolling activity, video viewing activity, printout activity of teaching materials, drill practice activity, break activity during course time, e.g. SNS Analyzes of SNS user-related information acquired by the interactive learning promotion system, such as video and audio acquired by the camera and microphone connected to the terminal used by the user It may be information acquired by doing.), impressions of the user's learning results, questions, etc. More specifically, for example, "August 20, 17:43, mathematics, trigonometric functions, 1 hour, 1 question", "August 21, all subjects not studied", "August 22, 21:00・English (idioms) ・28 minutes ・50 questions” “August 22, 22:00 English: Pronunciation practice 30 minutes” “August 23, 19:00 History (Ancient Egypt) Video viewing” . When using a learning system, it is conceivable to acquire the time used, the selected subjects, and the learning units within the subjects as a learning history. On the other hand, if the learner does not use any of the various learning systems linked with this interactive learning promotion system and does not learn at all, it is conceivable to acquire the fact that the learner does not use it as a learning history. At least the information to be acquired as the learning history is information indicating the time (for example, start date and time and end date and time) of learning. This is because the interactive learning promotion system that has acquired the learning history information from the learning system needs to determine the validity of the dialogue information it has output, as will be described later. This is because it is necessary to at least analyze how much time has elapsed since learning was performed.

The learning system may acquire this learning history information by having users (students) enter it manually, or send teaching materials and information such as viewing, questioning, and answering of the teaching materials on the user's terminal through the network. You may acquire from an external learning system via and generate learning history information. Browsing by the user terminal can also be obtained by acquiring page views of teaching materials, using page turning information, or acquiring video playback information. In order to increase the accuracy of these information, for example, in the case of page turning, the average page turning information of the average learner at the time of actual learning of the material is held, and at the same time, the page turning information of each user is held. By comparing the page turning information (using the average value and standard deviation), for example, if it is outside the range of a predetermined variation, it is recorded that normal learning was not performed. If the learner is a normal learner, it is configured to record that normal learning was not performed when the question is not asked, or the user's utterance is not recorded in learning the pronunciation of a foreign language such as English. In some cases, it is configured to record that the learning was not performed normally, or it is detected that the answer to the question was searched by the Internet search on the user's terminal, and it is recorded that the learning for the question was not performed normally. It is conceivable to configure it so that

<Embodiment 12 First Learning Effect Information Acquisition Unit>
The 'first learning effect information acquisition unit' acquires learning effect information, which is information indicating the effect of learning performed in the learning system, from the learning system used by the user in association with the user identification information. “Learning effect information” is information about the results of learning performed by the user through an external learning system. Specifically, the learning effect information is acquired in association with the learning history (at least the learning unit, possibly the learning unit and date/time, or the learning unit, date/time and learning time length) specified by the learning history information. A “learning unit” is a unit of content to be learned. For example, when learning materials are communicated between a server and a user's terminal, a set of learning contents continuously transmitted from the server may be used. It means that a learning curriculum (learning plan) is organized within a block of time (this time may be divided into multiple blocks of time discontinuously). For example, in mathematics related to trigonometric functions in high school, basic trigonometric ratio values, triangle side lengths and mountain heights, trigonometric ratio interrelationship (1), trigonometric ratio interrelationship (2), trigonometric ratios Interrelation of ratios (3), obtuse trigonometric ratios (90° to 180°), trigonometric equations, trigonometric inequalities, sine theorem, cosine theorem, sinθ+cosθ→sinθcosθ(8), trigonometric equations (quadratic), trigonometric inequalities (Secondary), positive angle/negative angle, general angle represented by radius, definition of trigonometric functions (2nd quadrant), (3rd quadrant), (4th quadrant), unit of radian method: radian, triangle Function values (frequently used angles), sin(π+θ), graphs of trigonometric functions (translation of sinθ)/(translation of cosθ), graphs of sin(θ−α), addition theorem, double-angle formula, 3 Each double-width formula, half-width formula, etc. is a learning unit. Therefore, the learning history information is information indicating the history of learning for each learning unit. Exercise 3, August 21, 87 points out of 100". In this case, the test is different from the study day, but the test may be conducted during the study time.

In other words, “learning effect” is information that indicates the degree of understanding, mastery, improvement, etc. of the learning unit shown in the learning history, and includes test scores, population (same grade, same class, same gender, same school of choice, etc.). , Same school, Same prefecture/municipalities, Same SNS group, By science/humanities, Applicants wishing to go on to medical school, By returnees, Same body shape range, Same grade (dan, grade, etc.), Same school, Same region, Same personal attribute, Same family composition, same continuous years of study, same position (share in sports, title in company, etc.), etc. The same shall apply hereinafter). Score deviation value, correctness of each test question (may be the element unit that makes up the learning unit) (may be compared in the population), number of questions answered (also in the case of comparison in the population) number of blank questions left unanswered (may be a population comparison), ratio of the number of questions answered to the number of questions asked (may be a population comparison) ), types of questions answered (may be population comparisons), types of questions not answered (may be population comparisons), time taken to answer the questions (e.g. evaluation by where it falls relative to the normal distribution of problem answering times associated with the question) (may be population comparisons), included in the answer, and/or intermediate steps leading up to the answer (Intermediate development formula, intermediate chemical formula, intermediate logical development, number of thoughts, rewriting, etc.), questions asked, impressions of learning, accuracy of memorization (may be compared in the population), content of incorrect answers (population where the error occurred (may be a population comparison), how often the same question was repeated incorrectly (may be a population comparison) ), change in time taken to answer the same question (may be population comparisons), number of hints used if hints are available for the question (may be population comparisons), hints Usage frequency (may be compared within the population), hint usage rate (may be compared within the population), notes left when answering questions, study time, number of correct answers, number of incorrect answers, repetition Any one or more of the number of correct answers, the number of repeated incorrect answers, the ranking within the population, the deviation value within the population, the evaluation of the lecturer, etc., the accuracy of the creation, etc. may be included. The learning effect measurement is acquired in association with the learning history information. In other words, the questions and tests for measuring the learning effect are configured to be set in association with the learning history (including learning units).

Furthermore, the learning effect (information) includes, for example, the above-mentioned various factors (question answering time, learning time, test score of learning unit, number of thoughts, number of incorrect answers, number of repeated correct answers, repeated incorrect answers Elements to be considered for learning units in coordinates in N-dimensional space, with each dimension as one dimension (number, sound order within the population, deviation value within the population, evaluation of instructors, etc., accuracy of creations, etc.) The distance from the origin of each coordinate of the compared learning effect is compared. A process of determining that the Alternatively, one of the coordinates of the learning effect to be compared can be used as a starting point to compare the magnitude of the numerical values indicated by the coordinates, or the volume of the space formed by the coordinates of the learning effect to be compared from the origin and each dimension (Area in the case of two dimensions) can be considered as a rule. In any case, the shorter the question-answering time and study time, the better. (obtained from answers in questions, etc.) is preferable as it decreases, but if it is less than a certain number of times, it is not preferable because the thought cannot be explained completely, and it is preferable to reduce the number of incorrect answers. It is designed so that cases (for example, calculating positively in each dimension) and unfavorable cases (for example, calculating negatively in each dimension) are unified in each dimension. Therefore, the effectiveness of an element is configured such that the values of each dimension are obtained by substituting the measured values into a unique function so that the obtained measured values can be distributed appropriately within the N-dimensional space.

<Embodiment 12 First Learning Analysis Rule Holding Unit>
The ``first learning analysis rule storage unit'' is for acquiring learning status information by analyzing external information, learning history information, and learning effect information in association with user identification information from the viewpoint of grasping the learning status. Holds learning analysis rules that are rules. Since the learned analysis rule is associated with the user identification information, the learned analysis rule is adapted to the characteristics of the user. The ultimate purpose of this interactive learning promotion system is to realize voluntary continuation of learning. In order to achieve voluntary continuation of learning, it is necessary to acquire study habits, improve the motivation to learn to acquire these habits, and improve the quality of life to maintain the acquired habits. It is necessary to acquire the patience to create a rhythm and maintain the desire to learn. This interactive learning promotion system is a dialogue system for improving and maintaining motivation for learning, which is necessary for habit formation and habit maintenance. Therefore, the learning analysis rule is a rule for each user for analyzing and acquiring learning status information for each user, which is necessary for selecting dialogue information for improving and maintaining motivation to learn.

"Learning status information" is associated with user identification information, and includes the user's (1) degree of habituation of voluntary learning, (2) quality of voluntary learning, (3) voluntary learning (4) How do you judge the progress of your own learning? (6) degree of willingness to learn, which evaluates the user's learning situation quantitatively or qualitatively from one or more perspectives, and what kind of numerical weighting each element It depends on the design intention of the system whether it distributes to or what kind of result is produced qualitatively. It may be quantitative or qualitative, or may include both. As a design policy, if it is quantitative, it can be designed so that the larger the numerical value, the more positive the learning, and conversely, the smaller the numerical value, the negative the learning. The learning status information may be obtained in units of learning (for example, in units determined by the curriculum prepared by the learning system, or in units determined by the Course of Study published by the Ministry of Education, Culture, Sports, Science and Technology), It may be obtained for a group of a plurality of learning units, or for a learning subject, or for a group higher than that. Therefore, the learning status information can be configured to be acquired in association with learning unit identification information, learning subject identification information, or the like that identifies the learning unit. Further, the learning status information may be configured to be acquired in association with dialogue information related to reaching such learning status information. Therefore, the learning situation information may be acquired in association with dialogue information identification information or the like that identifies dialogue information. Furthermore, if the dialogue information that influenced the learning situation information cannot be clearly separated from a large amount of dialogue information, the degree of influence may be given to the dialogue information identification information based on the temporal distance.

“(1) Evaluation of degree of habituation of spontaneous learning” can be obtained mainly from the learning history. Habituation includes the rhythm of learning (specifically, the date and time of learning), the duration of learning, and external information (user's remarks on SNS, remarks on SNS of the interactive learning promotion system, other Remarks of users concerned, various information that can be obtained from SNS (for example, information on classes at school, tests, mock tests outside of school, etc., information on the population of mock tests: various prep schools, various cram schools, etc. on SNS can be evaluated by periodically evaluating the information transmitted to )) and how the variation fluctuates. Human life has a certain periodic rhythm. For example, it is already known to have a biorhythm. Therefore, it is possible to evaluate learning habits based on the cycle of biorhythm, to evaluate each semester as a unit of cycle in the case of a student, or to evaluate a student who studies according to a weekly timetable (curriculum). can be evaluated as a cycle of weeks. In addition, since there is a large variation among people, the evaluation period may be different for each user. Furthermore, instead of using the given period, the evaluation period may be calculated from the learning history of the user and used. The learning rhythm may also be measured for each category of learning content. For example, in the case of general junior high school students and high school students, there are subjects that are studied frequently at school and subjects that are not, so it is common that the rhythm of learning differs for each subject. Therefore, for example, there is a high frequency of learning (classes) in an external learning system that is linked to an interactive learning promotion system, or a non-linked system (such as a school, cram school, practice field, classroom, etc.), or For subjects that have a lot of curricula, it is judged whether or not they have acquired the habit of studying on the premise that the frequency of study is relatively high. It is also possible to make an evaluation in relation to how often the interactive learning system encourages the learner to learn or guides the learner to do so. In other words, it is also possible to measure the habituation of learning by the ratio of the number of utterances for encouraging or guiding learning to the number of times that actual learning is performed.

“(2) Voluntary learning quality evaluation” can be acquired mainly using learning history information and learning effect information. Learning effect information can generally be measured by improvement in ability relative to the amount of learning. The former is calculated using learning history information, and the latter is calculated using learning effect information. A quality assessment can be made. The quality of evaluation of voluntary learning compares the past ratio value and the current ratio value on a user-by-user basis, and judges that the quality of voluntary learning has improved when the value is large. be able to. Furthermore, the current specific user ratio value within a specific population may be calculated as a deviation value instead of per user to evaluate the quality of spontaneous learning within the population.

"(3) Evaluation of how much the learning content was acquired by voluntary learning" is evaluated by the degree of attainment of the target to be achieved as ability. For example, in the case of memorizing the multiplication table, if the multiplication table can be memorized repeatedly to some extent, the achievement can be evaluated as 100%. Alternatively, if there is a list of 100 English words to be memorized in a certain period of time, and the 100 words can be memorized without error with a certain amount of repetition, the achievement can be evaluated as 100%, and in the case of half, the achievement can be evaluated as 50. %.

“(4) Evaluation of how the user self-judges the progress of his/her own learning” can be determined by mainly analyzing the user's remarks on the SNS. This user's utterance may be a spontaneous utterance, or may be an answer utterance corresponding to an utterance selected and uttered by the interactive learning promotion system. Since the learning situation information depends on the user's brain and the skill acquired by the user, it is difficult to make a highly accurate evaluation only from the external information. Therefore, the learning situation information is calculated in consideration of the user's awareness of the situation. Analysis of user utterances is performed by a database that covers utterances related to learning. The utterances are aggregated into multiple (many) categorized intentions, and each intention is given an evaluation value in terms of how far the learning progresses. and may be negative.) is used to calculate the learning status information. For example, "Oh, I forgot to study math!", "I forgot to do math!", "Arithmetic is bad!" It is summarized in the intention of "crisis awareness", and although it is negative in terms of learning history information, it is judged positive (positive value) based on the evaluation that "study habits are being acquired" from the viewpoint of self-awareness. be able to. Conversely, statements such as "I don't know math!" Lack of motivation to learn" is the intention, and from the viewpoint of self-awareness, it can be judged negatively (negative value) based on the evaluation that "study habits have not yet been acquired".

“(5) Evaluation of how the people around the user evaluate the progress of their own learning” can be determined by mainly analyzing the statements of people related to the user on the SNS. . The utterances of the related parties of the user may be voluntary utterances, or may be utterances of the related parties in response to utterances selected and uttered by the interactive learning promotion system (relationship user's affiliates' responses to statements made by the interactive learning facilitation system within the SNS group that includes the user's affiliates). It is difficult to evaluate the learning situation information with high accuracy only from the information on the external shape. Therefore, the learning status information of the user is calculated in consideration of the evaluation status of the persons related to the user. Analysis of the user's related people's statements is performed by a database that also covers learning-related statements. The utterances are aggregated into multiple (many) categorized intentions, and each intention is given an evaluation value in terms of how far the learning progresses. and may be negative.) is used to calculate the learning status information. However, it may be configured such that weighting is performed according to the relationship between the user and the person concerned. For example, the user's parents' remarks are weighted less (assuming that there are remarks lacking objectivity in the case of parents), and the user's friend's remarks (assuming that the friend speaks objectively and empathetically) are the same remarks. However, it is conceivable to increase the weighting.

"(6) Evaluation of degree of willingness to learn" Since learning becomes a habit when the willingness to learn increases, it is useful to evaluate the degree of willingness to learn in order to calculate learning status information. Evaluation can be performed mainly by analyzing user comments on SNS, learning history information, and learning effect information. Analysis of the user's utterances is performed by a database that covers utterances related to learning. The utterances are aggregated into multiple (many) categorized intentions related to motivation to learn, and each intention is given an evaluation value in terms of the degree of motivation to learn. (It can be positive or negative.) can be used to calculate the evaluation value of the degree of willingness to learn. Accurate understanding of the user's motivation for learning at that time may be configured to be analyzed relative to others. Furthermore, it is also effective to analyze the current degree of motivation for learning of the user by relative comparison between past and present.

For example, although A is systematically studying for a certain amount of time every day through the learning system, his grades have been sluggish lately, and B is absorbed in club activities, especially on club days and on other days. It is assumed that C hardly learns through the learning system, and that C is studying to obtain a qualification while working, and that he also learns through the learning system for a short time late at night. Suppose that it is confirmed that all of A, B, and C made statements to the effect that they were "tired" through SNS around 22:00. Generally speaking, the statement "I'm tired" is meant to request rest, so it refers to the case where the degree of motivation for learning is low. However, by inferring from external information and learning history information/learning effect information whether the user feels the need to study even when he/she is tired, the level of willingness to learn at the time of a given statement can be estimated based on the user's own individuality. Can build learning analysis rules. In the case of A, it is presumed that he feels tired from his daily studies, and the rule that "I am tired = my motivation to learn is on the decline" is a learning analysis rule that matches his characteristics. In the case of B, it is presumed that the body is tired from club activities and wants to go to bed early, and the rule "tired = no desire to learn" becomes a learning analysis rule that matches the characteristics. In the case of C, it is presumed that the body and brain feel daily fatigue due to work, and the rule that "tired = motivated to learn, but not top priority" becomes a learning analysis rule that matches the characteristics.

<Embodiment 12 First Learning Situation Information Analysis Acquisition Unit>
The ``first learning situation information analysis acquisition unit'' analyzes the acquired external information associated with the user identification information, the learning history information, the learning effect information, and the learning analysis rule associated with the same user identification information. Acquire learning status information based on The acquired learning situation information may be temporally associated with the user identification information and the output dialogue information, including past information, and stored in the first learning situation information analysis and acquisition unit. It may be stored as part of the user attribute information stored as associated information. (1) the extent to which self-directed learning became a habit; (2) the quality of self-directed learning; (5) How the people around you evaluate your own learning progress (6) Degree of motivation to learn It can be configured to be acquired by comprehensively analyzing each of the above evaluations. Since each of the elements (1) to (6) includes the viewpoint of comparative evaluation, a negative evaluation value may be obtained. The learning status information may be acquired for each learning unit that the user is studying, or may be acquired for each learning subject. related subjects, art-related subjects, etc.) may be used as credits. You may acquire the whole without specifying the learning unit.

Moreover, it is also possible to configure so as to output qualitative learning status information as a result. As representative information, the user may specify each learning unit (including the learning unit itself, the learning environment related to the learning unit, the learning system related to the learning unit, etc.; the same applies to Embodiments 12 to 19 below), It includes psychological information about the superordinate concept, subordinate concept, and combination. For example, ``I am having difficulty learning mathematics,'' ``I am obsessed with memorizing multiplication tables,'' ``I feel that learning quadratic equations is interesting,'' and ``I am not interested in ancient times in studying history. "Situation where pole vaulting is scary", "Situation where learning shogi is interesting", "Situation where I feel that I don't want to learn ikebana anymore", "I've never done it, but I'm spinning tops." It can be configured to output various kinds of qualitative learning status information of the user, such as the situation in which the user wants to study, and the situation in which the user thinks that he/she must study the personal computer. The qualitative information is prepared in categorized ways, and a degree value is given for each category. The typification indicates one or more user's inner states such as "interest", "enjoyment", "difficulty", "necessity", "satisfaction", "malaise", "sense of danger", and "motivation" for each learning unit. It is configured such that a value from minus 5 to plus 5, for example, is given to the inner face index, which is an index, to indicate the degree of the user. The internal index is selected based on the design concept of the interactive learning promotion system. For example, if the type item "interest" of a user is "minus 2" for "multiplication tables", it indicates that the user has little interest in multiplication tables.

As already explained for qualitative evaluation, (1) the extent to which self-directed learning was habituated, (2) the quality of self-directed learning, and (3) the extent to which the learning content was mastered through self-directed learning. (4) How do you judge the progress of your own learning? (5) How do the people around you evaluate the progress of your learning? (6) It can be calculated and output from one or more viewpoints such as the degree of willingness to learn. Furthermore, as emotional indicators for learning units, relief, anxiety, gratitude, astonishment, excitement, curiosity, calmness, impatience (impatience), wonder (confusion), luck, relaxation, tension, honor, responsibility, respect, familiarity (familiarity) ), longing, desire, fear, courage, pleasure, regret, satisfaction, dissatisfaction, chagrin, disgust, shame, guilt, expectation, superiority, inferiority, suffering, sadness, sadness, emotion, Mental conditions such as anger, resignation, despair, hatred, emptiness, etc. may be obtained from SNS user-related information, rated or scored, and used to calculate the internal index, or the emotional index may be separated from the internal index. It is conceivable to store and use them to calculate the learning situation information, or to directly include these emotion indicators in the learning situation information.

As described above, the learning status information may be either one or both of numerical evaluation from the viewpoint of habituation of learning and evaluation from the viewpoint of the user's internal attitude toward qualitative learning. The learning status information is evaluated quantitatively or qualitatively, and it depends on the design intention of the system how the numerical weight is distributed to each element and what kind of qualitative result is produced. As a method for comprehensively analyzing the learning situation information, a configuration is conceivable in which an analysis value is obtained by totaling the evaluation values of each element. Alternatively, a configuration is conceivable in which an analysis value is obtained by giving different weights to each element. Alternatively, it is possible to obtain an analysis value by multiplying the evaluation value of each element (percentage of 100 perfection) to 100 when the perfect habit is acquired. In this case, the evaluation value of each element is When the evaluation value of each element is obtained as a percentage of the degree of completion of 100, the evaluation value of each element does not indicate a negative value.

It should be noted that the learning status information is external (whether or not the same operator, computer, server, or housing as this interactive learning promotion system is the same. The same applies to Embodiments 12 to 19.) It is also possible to configure the learning system to be fed back for creating and changing the curriculum of the system (regardless of whether it is singular or plural; the same applies to Embodiments 12 to 19). be. In general, the learning curriculum is changed according to test results or user requests, but it is believed that the user's learning efficiency can be improved if it is based on the learning situation information. This is because the learning status information consists of qualitative information such as learning habits and the user's psychological aspects, and is deeper than general information regarding the user's learning. Curriculum changes include replacement of learning units, new establishments, time allocation of learning units, time intervals, new learning subjects, deletion of learning subjects, changes in learning methods (for example, from text-based to tables, figures, pictures, (from focusing on mathematical formulas to focusing on tables, diagrams, pictures, and videos, from classroom learning to studying at home, from focusing on books to focusing on Internet information). Feedback can be automatically received by an external learning system, and the curriculum can be automatically changed according to the learning status information. etc., and the curriculum etc. may be changed by an external learning system administrator.

<Embodiment 12 First Learning Dialogue Information Storage Unit>
The 'first learning dialogue information accumulation unit' accumulates dialogue information to be transmitted according to the learning situation information acquired in association with the user identification information. The dialogue information is a database of all kinds of conversations that may be said in general society. In this interactive learning promotion system, example sentences of conversation that serve as a basis for giving advice to the user to promote learning or to establish learning habits are particularly heavily stored. Besides a dictionary of general conversational information, it is preferable to have something like a specialized dictionary for learning. The language may be stored in a language understood by the user, or the dialogue information may be stored in a standard language such as Japanese, English, Chinese, etc., and configured to be translated and selected according to the language used by the user. You can also Therefore, based on a language dictionary database, a conversation dictionary database, etc., the foundation is built, and furthermore, SNS, information sites, corporate advertisement sites, bulletin board sites, telephone call contents, etc., are viewed and viewed by this interactive learning promotion system. It is preferable to accumulate interaction information collected from all available sources. These may include, for example, dialects, gyarugo, pictograms, emoticons, jargon, coined words, new words, abbreviations, idioms, etc., which are collected by artificial intelligence and gradually improve conversation accuracy (intentions are accurate). It is preferably configured so that the Furthermore, the dialogue information that constitutes learning promotion advice, etc. is the terminology used in each specialized learning unit (field), the name of a specific learning field, the name of a specific learning field, a specific school, cram school, classroom, correspondence education, school , parliamentary groups, job titles, and other coined words. Since technical terms, specific proper nouns, and coined words cannot be reliably obtained from the Internet, it is recommended to be configured so that special language groups can be input by directly entering them into the storage unit. preferable. Furthermore, the dialogue information may include questions, problems, and the like for the system to know the degree of understanding of the learning unit (including its superordinate concept and subordinate concept). This makes it possible to improve the accuracy of the user's learning status information.

This interactive learning promotion system reflects the individuality of each user and selects and outputs dialogue information so that it becomes a natural conversation for the user. It is characterized by making you feel as if you are in contact with a real human being. Therefore, depending on the user's daily conversation, whether to use polite language, casual language with a colloquial tone, dialects such as Osaka dialect or Hakata dialect, and words mixed with English in the document It is preferable that dialogue information is accumulated so that not only the content of the conversation such as whether to use it as an errand, but also the form of the conversation can be selected. The dialogue information accumulation unit may accumulate dialogue information as different dialogues even if they have the same meaning for each difference in formation of the dialogue. That is, expressions such as "thank you", "thank you", "thank you", "thank you", "thank you", etc. are all stored as different dialogue information as dialogue information expressing gratitude. Alternatively, the dialogue information storage unit stores only the most basic dialogue information for each meaning, and the dialogue information output unit described later selects the basic dialogue information from the dialogue information storage unit according to the user's personality. I can think of a way to convert it to an existing interactive format. In this case, a rule for converting the basic dialogue information into a dialogue format suited to the characteristics of each user is included in the user-specific dialogue information selection rule. In this case, in the dialog information storage unit, "Thank you." "Thank you." "Thank you." "Thank you." Only "thank you" will be saved.

The dialogue information accumulated in the first learned dialogue information accumulation unit may be configured so as to be displayable on the interface monitor. The dialogue information storage unit management means is the first learning dialogue information storage unit so that management actions such as addition, change, and deletion of dialogue information can be manually performed from the interface screen on which the accumulated dialogue information is displayed. , or a configuration in which the dialogue information storage unit management unit is provided as a new configuration. It is assumed that the person who manages and provides this interactive learning promotion system performs the act of managing the first learning dialogue information storage unit. Further, the dialogue information storage unit can be configured to store dialogue information that should not be used as dialogue information so that such dialogue information is not selected or is not stored in a selectable manner. Dialogue information that should not be used includes discriminatory terms and dialogue information that is difficult to handle because it relates to social incidents. It can also be configured so as to be determined according to the attributes of the user.

<Embodiment 12 First learner-specific dialogue information selection rule holding unit>
The 'holding unit for selection rules for dialogue information by first learning user' holds dialogue information selection rules for each user, which are rules associated with user identification information for selecting accumulated dialogue information based on acquired learning situation information. do. The user-by-user dialogue information selection rule reflects the individuality of each user in order to make the user feel as if he/she is in contact with a real person who cares about him or her. It is a rule for selecting dialogue information so as to have a natural conversation. From external information, such as user-generated information on SNS (information on written statements, spoken statements, browsing records, other registered SNS users, etc.), a conversation format that conforms to the user's dialogue format This is a rule that enables selection of dialogue information that reflects the individuality of the user by combining both selection and selection of conversation content based on the acquired learning situation information.

Dialogue formats include polite language, colloquial language, gyaru language, Osaka dialect, Kyoto dialect, Hakata dialect, Nagoya dialect, Hokkaido dialect, Okinawa dialect, and other regional dialects. A method of selecting from the information selection rules to make the user-specific dialogue information selection rule, and a method of assembling all originals from the user's conversation information are conceivable. The reason why the user can recognize this interactive learning promotion system as if it were a real and familiar existence is the method of assembling an original interactive form that can more strongly reflect the individuality of the user. However, at the stage when the user begins to use this interactive learning promotion system, the amount of accumulated external information for analyzing the user's individuality is small. Therefore, it automatically selects the default format when there is not enough information to obtain the rules for selecting the original format according to the user's personality. For example, it is conceivable to allow the user to select and register an interactive format so that the interactive format of the user's preference is started. Also, it may be configured to automatically select appropriate interactive information in accordance with the attributes of the user. User attributes include age, gender, hometown, current address, nationality, language used, conversation (dialogue) style on SNS, conversation (dialogue) style of friends on SNS, preferred clothing type, and preferred movie type. , favorite book type, favorite celebrity type (talent, actor, politician, writer, singer, comedian, historical figure, announcer, character), hobbies, preferences, and the like. When sufficient user external information, learning history information, and learning effect information are accumulated to acquire dialogue information selection rules, there is a unique mechanism that selects dialogue information in a format that corresponds to the user's individuality from the first learning dialogue information storage unit. configure user-specific dialogue information selection rules. This should be updated by artificial intelligence so that appropriate dialogue information is selected on a daily basis based on external information.

When analyzing the form of dialogue information from the conversation information of the user's SNS, rather than simply focusing on the user's utterance form, analyze the conversation form of friends and family with whom the user frequently communicates. It is conceivable to construct separate dialogue information selection rules. By analyzing and reflecting the speaking style of the conversation partner with whom the user actually has a daily conversation, it is possible to give the user a sense of security as if he or she is talking with a friend or family member. Therefore, it is possible to make the user feel as if he/she is interacting with a real person who is worried about the user, and the user can feel that someone is encouraging him/her to watch over him/her. Being supported, being supported, not wanting to be seen as miserable, being happy to be praised, feeling sorry for not being able to do well, being sad, etc., which are indispensable for human beings to continue their efforts continuously. It becomes possible to hold. In addition, if the advice comes from a person who is similar to the person who usually consults about troubles and gives advice, it becomes easier for the user to follow the advice obediently, and the user takes learning promotion actions according to the advice from the interactive learning promotion system. Hopefully it will get easier. From this point of view, a wide variety of dialogue information is accumulated, such as dialogue information that conveys affection, dialogue information that conveys favorability, dialogue information that praises the other party, and dialogue information that encourages the other party. preferably.

In addition, the user's personality, such as always responding with negative remarks, but being unable to refuse when asked many times, disliking it exaggeratedly even though it is not really disliked, or disliking it for the time being, can be analyzed using personality diagnosis and attributes. If it is acquired by information, etc., it cannot be said that the output dialogue information is not effective only with a few negative responses from the user, and it takes until the user accepts the output of the same dialogue information on average. If it is recommended to repeat until a specific number of times is greater than the required number of times as a response that should be taken as a result of analysis of personality as an attribute, that response may be a rule selected by the dialogue information selection unit. Conceivable. That is, such a never-give-up rule (sub-step, sub-rule) or a never-give-up process can be included in the user-specific dialogue information selection rule, or a process configured by this can be included.

<Embodiment 12 First Learning Dialogue Information Selection Unit>
The ``first learned dialogue information selection unit'' selects dialogue information in a dialogue format that matches the characteristics of each user from the dialogue information storage unit based on the learning situation information and the stored user-specific dialogue information selection rule. do. ' and 'first learning dialogue information selection unit' select dialogue information from the first learning dialogue information storage unit based on the acquired learning situation information and the stored user-by-user dialogue information selection rule. When dialogue information is stored in the first learned dialogue information storage unit for each difference in dialogue format, dialogue information that matches the dialogue format and dialogue content selected by the user-specific dialogue information selection rule is selected. Become. If dialogue information is not stored for each difference in dialogue format in the first learning dialogue information storage unit, and dialogue information is stored for each meaning of dialogue content regardless of the dialogue format, then Basic dialogue information is selected from the first learned dialogue information storage unit according to the dialogue content specified by the information selection rule, and the selected dialogue information is transformed into a dialogue format that matches the dialogue format specified by the user-specific dialogue information selection rule. Convert. In this case, the basic dialogue information may refer to a set of words instead of the words themselves. In this case, identification information is given to dialogue information that expresses gratitude, and this is selected, followed by ``thank you'', ``thank you'', ``thank you'', ``thank you'', and ``thank you''. Configure to select one of the expressions such as "Thank you". In other words, basic dialogue information is selected from the dialogue information storage unit according to the dialogue content specified by the user-specific information selection rule, and the selected dialogue information is used as the dialogue format specified by the user-specific dialogue information selection rule. A process of converting to an interactive format that matches is performed. The above operation becomes the selection of dialogue information. This selection is constructed so that it can be made instantaneously by a computer. Specifically, the speed is such that when an input from a user is received via an SNS, a reply is displayed on the screen without allowing the user to close the SNS screen. As an example, it is about 1 to 3 seconds on average. However, in the case of a flow of dialogue information that an ordinary person would need to worry about, the dialogue information may be output after a longer period of time.

<Embodiment 12 First Learning Dialogue Information Output Unit>
The 'first learned dialogue information output unit' outputs the selected dialogue information to the user identified by the user identification information via the SNS. As described above, the speed at which the dialogue information output unit outputs dialogue information is the speed at which the user's input can be immediately responded to if necessary. This is because if the user closes the SNS screen, there is a high risk that the call from the system will be left unread without being marked as read. It should be noted that it is not always necessary to respond immediately, and there may be some type of transmission that is output after some time. This is the case, for example, in a conversation to hear the result of advice. It is the user's portable terminal, a fixed terminal such as a desktop personal computer, or the like that outputs the data. The SNS to be output may be an application dedicated to the interactive learning facilitation system, or an SNS service managed and provided by another system not dedicated to the interactive learning facilitation system that the user uses on a daily basis. good too.

The format of the output is not limited as long as it is a method capable of transmitting information to the user, such as characters, illustrations, sounds, images, and moving images. In order to make it feel as if you are talking to a real person, it is better to use the SNS service that is used for daily communication with real people than to use a dedicated application. Advice for promoting learning and advice for establishing study habits from the interactive learning promotion system are naturally displayed among the contents, which is effective. "Effective" means that the advice from the Interactive Learning Acceleration System can be seen naturally on a daily basis, so it is effective in that it does not make people strongly conscious of interacting with the system (inorganic computer or server). This is the reason why The output from the Interactive Learning Acceleration System uses the SNS service of the output destination. With such a configuration, the above effect can be ensured, so that it is more effective. Conversely, chat heads and the like are immediately noticeable on smartphones, etc., and are preferable because they reduce the sense of distance from the present system. The dialogue information to be output is not limited in content and format, such as information including question format, information including advice, greetings, onomatopoeia, and the like.

Furthermore, instead of always using the same output format, combining multiple output methods such as characters, illustrations, voices, images, videos, etc., and avatars generated by computer graphics can be similar to interacting with real people. , will be more effective. Therefore, in addition to outputting dialogue information as characters or outputting recorded voice data as dialogue information to the output interface, output (utterance) of dialogue information and response dialogue information in real time using the automatic voice call function Acquisition may take place. Furthermore, when a person accesses a cram school, etc. using a voice call, when that person's voice call is received by a communication device that uses this interactive learning promotion system, this interactive learning Even if there is no user registration for the promotion system, immediately generate and hold user identification information using a telephone number, etc., and recognize that person as a guest user by the interactive purchase promotion system that receives voice calls. It is also possible to configure the system so that dialogue information can be output by voice through the spoken interactive learning promotion system. In this case, the guest user simply registers with the remote interactive learning facilitation system through a voice call. The user terminal itself is defined as a guest user in order to distinguish from the case where this interactive learning promotion system is activated. By giving an identification number in association with user attributes such as number, etc., in subsequent voice calls, guest user attribute information (preferences, speaking style, spacing, hobbies, etc.) accumulated by past voice calls It is possible to output dialogue information reflecting thoughts, etc.). In this case, the output of the dialogue information is generated by an SNS-enabled terminal that is not possessed by the user receiving the voice call, and the voice output is delivered to the guest user via the phone. It can be said that this is an output of dialogue information via SNS.

The output of the dialogue information via the SNS is the output as comments of the user's friends, etc. participating in the SNS. Therefore, since it is preferable to have a conversation as a friend or the like that looks unique to the user as much as possible, it is preferable to use as many names as possible so that the same name does not overlap among users as much as possible. Alternatively, the name may be freely set at the time of initial user registration. Also, the attributes that determine the elements used for conversation selection may be freely set at the time of user registration. For example, it is the gender, age, character, avatar, clothing, life rhythm, hobby, etc. of the system friends.

Further, the dialogue information may be output not only by one character that the interactive learning promotion system pretends to be, but also by a plurality of characters. For example, one character can be used as a scolding and another can be used as a comforter. Character settings can also be configured to be selected based on acquired external information, learning history information, learning effect information, and the like. A suitable character can be selected according to the content (attribute) of dialogue information to be output. Therefore, attributes are added to the dialogue information and stored in the first learned dialogue information storage unit, and the first learned dialogue information output unit selects a character corresponding to the attribute information to compose a statement on the SNS. Good. The selected dialogue information may include not only dialogue between the user and friends, who are a plurality of system characters, but also dialogue between friends, etc. (characters) who are the system. In this case, the user can obtain motivation for promoting learning and establishing study habits, etc. from information exchanged with friends and the like. In addition, in cooperation with a location information system of the user terminal, etc., it may be configured to switch utterances of friends, etc., who are the system, according to the location information. For example, when a user goes to Osaka, a friend who speaks Osaka dialect appears, and when a user goes to Kyushu, a friend who speaks Kyushu dialect appears. In this case, the friend in Osaka may be configured to select a conversation on the premise that they have met for the first time in a long time since the last time they went to Osaka (meeting timing situation). For example, when you go out to a distant place and a friend on the system who is set as a friend who lives there appears in a SNS conversation, in a situation where you met for the first time in a long time since you went out last time, Middle school? Also, when setting up friends, etc., which is a common system for multiple users, you can say, "Mari-chan, you said you were left behind in the classic test (;∀;) You can think of comparative conversations such as "It might be dangerous soon ω", or solicitation conversations such as "It seems that Mr. Oda and Mr. Tokugawa are having a study session at Mr. Toyotomi's house. Why don't you join them?"

The avatars (characters) of friends and the like do not necessarily have to be people, and may be set as mammals, fish, insects, objects, and the like. Furthermore, it is not limited to a still image, and may be displayed as a moving image. Furthermore, it is not limited to what is displayed on the display, and a robot, an AI speaker, a projection, or the like may play the role of a friend. The avatar may also be configured to send photos, videos, pictures, etc. to the user depending on the settings. For example, food photos, landscape photos, ideal body photos, videos explaining how to exercise, etc. In addition, you may send us information on equipment, supplements, etc. to promote use. In addition, friends, etc., who are the system, can create a sense of realism, warmth, and humanity by using the above-mentioned avatar schedule that sets events according to the passage of time, such as being hit by an accident and climbing the stairs of life. good.

<Embodiment 12 Hardware Configuration>
FIG. 37 is a diagram showing the hardware configuration of the twelfth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, as a program constituting the hardware of the twelfth embodiment, a "first learning user identification information holding program" holds user identification information. The "first learning SNS user-related information acquisition program" acquires SNS user-related information. This is done through an interface program with SNS. The "first learning history information acquisition program" acquires user's learning history information from an external learning system used by the user. The "first learning effect information acquisition program" acquires user's learning effect information from an external learning system used by the user. The "first learning analysis rule holding program" holds learning analysis rules. The 'first learning situation information analysis acquisition program' acquires learning situation information from external information, learning history information, and learning effect information based on analysis based on learning analysis rules. The "first learning dialogue information accumulation program" accumulates dialogue information. The 'holding program for first learned user-specific dialogue information selection rules' holds dialogue information selection rules for each user. The 'first learning dialogue information selection program' selects appropriate dialogue information from the accumulated dialogue information based on the acquired learning situation information and the held user-by-user dialogue information selection rule. The 'first learned dialogue information output program' outputs the selected dialogue information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, communication (not shown), and other setting information are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Embodiment 12: Flow of Processing>
FIG. 38 is a diagram illustrating an example of the flow of processing according to the twelfth embodiment. As shown in this figure, first learning user identification information holding step (3801) for holding user identification information, first learning SNS user-related information acquisition step (3802) for acquiring user's SNS-related information, First learning history information acquisition step (3803) for acquiring user's learning history information from an external learning system, first learning effect information acquisition step (3804) for acquiring user's learning effect information from an external learning system used by the user ), a first learning analysis rule holding step (3805) for holding learning analysis rules, a first learning situation information analysis acquiring step (3806) for acquiring learning situation information by analysis based on the learning analysis rules, and accumulating dialogue information. First learned dialogue information storage step (3807); first learned user dialogue information selection rule holding step (3808) for holding user-specific dialogue information selection rules; It consists of a first learned dialogue information selection step (3809) for selecting dialogue information to be output based on dialogue information selection rules, and a first learned dialogue information output step (3810) for outputting the selected dialogue information. It should be noted that the above "holding step" and "accumulating step" are excluded from the processing procedure if they are held and accumulated in advance (same throughout the entire specification (claims 1 to 39)). .

<Embodiment 13>
<Outline of Embodiment 13 Invention>
The interactive learning promotion system in the present embodiment is related to the user's learning history, learning effect, and curriculum learning acquired by the learning system in addition to external information such as user's statement information and browsing information on SNS. By acquiring information and using it for analysis, the user's learning status information (including the user's introverted elements such as learning motivation, learning attitude, spontaneity, and continuity without simply focusing on grades) is acquired. Then, the user's learning is promoted by giving advice (selection of dialogue information) suitable for the user's current learning situation.

<Embodiment 13 Configuration of the Invention>
FIG. 39 is a diagram showing an example of the configuration of an interactive learning promotion system according to the thirteenth embodiment. As shown in FIG. 39, the interactive learning promotion system of the thirteenth embodiment includes a second learning user identification information storage unit (3901), a second learning SNS user related information acquisition unit (3902), a second learning history information acquisition unit (3903), second learning effect information acquisition unit (3904), second learning curriculum information acquisition unit (3905), second learning analysis rule storage unit (3906), second learning situation information analysis acquisition unit (3907), Consists of a second learning dialogue information storage unit (3908), a second learning user dialogue information selection rule storage unit (3909), a second learning dialogue information selection unit (3910), and a second learning dialogue information output unit (3911). .

<Description of Embodiment 13 Configuration>
<Thirteenth Embodiment Description of the Configuration of the Thirteenth Embodiment Working in Common with the Thirteenth Embodiment>
The "second learning user identification information holding unit" is the first learning user identification information shown in Embodiment 12, and the "second learning SNS user related information acquisition unit" is the first learning SNS user related information shown in Embodiment 12. The information acquisition unit and the "second learning history information acquisition unit" are the first learning history information acquisition unit shown in Embodiment 12, and the "second learning effect information acquisition unit" is the first learning effect shown in Embodiment 12. The information acquisition unit and the "second learning analysis rule holding unit" are the first learning analysis rule holding unit shown in Embodiment 12, and the "second learning situation information analysis acquisition unit" is the first learning shown in Embodiment 12. The situation information analysis acquisition unit and the "second learning dialogue information storage unit" are the first learning dialogue information storage unit shown in the twelfth embodiment, and the "second learning user-by-user dialogue information selection rule holding unit" are the same as those in the twelfth embodiment. The first learning user-by-user dialogue information selection rule holding unit shown and the "second learning dialogue information selection unit" are the first learning dialogue information selection unit shown in the twelfth embodiment, and the "second learning dialogue information output unit" are The function is the same as that of the first learning dialogue information output unit shown in the twelfth embodiment, and has already been described.

<Embodiment 13 Second Learning Curriculum Information Acquisition Unit>
The 'second learning curriculum information acquisition unit' acquires curriculum information performed in the learning system from the learning system used by the user in association with the user identification information. “Curriculum” refers to a plan of study instruction. As curriculum information, in addition to the curriculum provided by the administrator of the learning system that provides the learning system, it is possible to include curriculum information of the school the user attends, curriculum information of the cram school the user attends, etc. I can. By acquiring the curriculum information by this interactive learning promotion system, the dialogue selected based on the curriculum information will be reflected in the contents of the learning promotion advice included in the dialogue information output by this interactive learning promotion system. Become. In other words, it becomes possible to clarify the scholastic goals and ability goals that the user should have reached or to reach in the future, and to select interactive information useful for promoting more specific learning. Furthermore, by comparing the curriculum information with the learning effect information and the learning history information, the accuracy of the learning effect information and the learning status information can be further improved. Curriculum information is preferably configured so that it can be acquired in the form of a set of learning units. This is because the acquisition of learning effect information and learning history information in units of learning enables comparative analysis in a 1:1 relationship.

<Thirteenth Embodiment Hardware Configuration>
FIG. 40 is a diagram showing the hardware configuration of the thirteenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the thirteenth embodiment, the description of the programs that operate in common with the programs of the twelfth embodiment will be omitted. The "second learning curriculum information acquisition program" newly added in this embodiment acquires curriculum information from an external learning system or the like used by the user. The "second learning situation information analysis acquisition program" acquires learning situation information from external information, learning history information, learning effect information, and curriculum information based on analysis based on learning analysis rules. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, curriculum information, learning analysis rules, and learning status information. , dialogue information, user-specific dialogue information selection rules, selected dialogue information, various setting information such as communication (not shown), etc. are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs. .

<Thirteenth Embodiment Processing Flow>
FIG. 41 is a diagram illustrating an example of the flow of processing according to the thirteenth embodiment. As shown in this figure, a second learning user identification information holding step (4101), a second learning SNS user related information acquiring step (4102), a second learning history information acquiring step (4103), and a second learning effect information acquiring step (4104), second curriculum information acquisition step (4105) for acquiring curriculum information from the learning system, second learning analysis rule holding step (4106), second learning situation information analysis acquisition step (4107), second learning dialogue information It consists of an accumulation step (4108), a second learned user-specific dialogue information selection rule holding step (4109), a second learned dialogue information selection step (4110), and a second learned dialogue information output step (4111). It should be noted that descriptions of steps having functions common to those of the twelfth embodiment have been omitted, and only characteristic steps of this embodiment have been described.

<Embodiment 14>
<Overview of Embodiment 14 Invention>
The interactive learning facilitation system of Embodiment 14, which is a separate claim, is characterized in that, in addition to the features of Embodiment 13, the external information is utterances (including computer-generated utterances) of external learning system participants. ).

<Embodiment 14 Configuration of the Invention>
FIG. 42 is a diagram showing an example of the configuration of an interactive learning promotion system according to the fourteenth embodiment. As shown in FIG. 42, the interactive learning promotion system of Embodiment 14 includes a third learning user identification information holding unit (4201), a third learning SNS user related information acquisition unit (4202), a third learning history information acquisition unit (4203), third learning effect information acquisition unit (4204), third learning curriculum information acquisition unit (4205), third learning analysis rule storage unit (4206), third learning situation information analysis acquisition unit (4207), Consists of a three-learning dialogue information storage unit (4208), a third learning user-specific dialogue information selection rule holding unit (4209), a third learning dialogue information selection unit (4210), and a third learning dialogue information output unit (4211). .

<Description of Embodiment 14 Configuration>
<Embodiment 14 Concerning the configuration of Embodiment 14 that performs the same function as Embodiment 12 or Embodiment 13>
The "third learning user identification information holding unit" is the first learning user identification information shown in Embodiment 12, the "third learning history information acquisition unit" is the first learning history information acquisition unit shown in Embodiment 12, The "third learning effect information acquisition unit" is the first learning effect information acquisition unit shown in Embodiment 12, the "third learning curriculum information acquisition unit" is the second learning curriculum information acquisition unit shown in Embodiment 13, The "third learning analysis rule holding unit" is the first learning analysis rule holding unit shown in the twelfth embodiment, and the "third learning situation information analysis acquisition unit" is the first learning situation information analysis acquisition unit shown in the twelfth embodiment. , the ``third learning dialogue information storage unit'' is the first learning dialogue information storage part shown in the twelfth embodiment, and the third learning user-specific dialogue information selection rule storage part" is the first learning user shown in the twelfth embodiment. The separate dialogue information selection rule holding unit, the “third learning dialogue information selection unit” as shown in the twelfth embodiment, and the “third learning dialogue information output unit” as shown in the twelfth embodiment. Its function is the same as that of the first learning dialogue information output unit, and has already been explained. Note that the "third learning curriculum information acquisition unit" is not necessarily required.

<Embodiment 14 Third Learning SNS User Related Information Acquisition Unit>
The ``third learning SNS user-related information acquisition unit'' provides user-related information including user's remarks of the SNS used by the user in association with the user identification information, and remarks of the learning system officials (including computer-generated remarks) SNS user-related information is acquired as external information. The function of the third learning SNS user-related information acquisition unit is basically the same as that of the first learning SNS user-related information acquisition unit shown in the twelfth embodiment, and has already been described. As a function specific to the fourteenth embodiment, utterances (including computer-generated utterances) of persons involved in the learning system are acquired as SNS user-related information.

"Remarks by people involved in the learning system" means advice given to users by instructors, advisors, graders, correctors, etc. through external learning systems, SNS, etc., or a system (computer) acting as an instructor or It's about utterances. These advices and remarks may be given on the Internet within an external learning system, by telephone or face-to-face speech, or by paper. (obtained by OCR). Although it is not limited to any form, it is necessary that the data processed is stored in the learning system so that it can be incorporated into this interactive learning promotion system. The external learning system participant's utterances may be utterances returned in response to utterances from the interactive learning facilitation system. In this case, the instructor or the like may be a member of an SNS group that includes the user, or be provided with an interface that allows interaction between the external learning system and the system of the present embodiment. preferable.

<Embodiment 14 Hardware Configuration>
FIG. 43 is a diagram showing the hardware configuration of the fourteenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the thirteenth embodiment, the description of the programs that operate in common with the programs of the twelfth or thirteenth embodiment will be omitted. A “third learning SNS user-related information acquisition program” newly added in the present embodiment acquires, as SNS user-related information, utterances of SNS users as well as utterances of persons involved in the learning system. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information (including remarks by persons involved in the learning system)), learning history information, learning effect information, Curriculum information, learning analysis rules, learning status information, dialogue information, dialogue information selection rules for each user, selected dialogue information, various setting information such as communication (not shown), etc. are held in non-volatile memory, loaded into main memory, are referenced and used during program execution. Note that the third curriculum information acquisition program is not essential.

<Fourteenth Embodiment Processing Flow>
FIG. 44 is a diagram illustrating an example of the flow of processing according to the fourteenth embodiment. As shown in this figure, a third learning user identification information holding step (4401), statements of users of SNSs used by users in association with user identification information, statements of persons involved in the learning system (including statements generated by a computer) A third learning SNS user-related information acquisition step (4402), a third learning history information acquisition step (4403), and a third learning effect information acquisition step ( 4404), third curriculum information acquisition step (4405), third learning analysis rule holding step (4406), third learning situation information analysis acquisition step (4407), third learning dialogue information accumulation step (4408), third learning It consists of a user-by-user dialogue information selection rule holding step (4409), a third learned dialogue information selection step (4410), and a third learned dialogue information output step (4411). It should be noted that the description of the steps that work in common with the twelfth or thirteenth embodiment is omitted, and only the characteristic steps of this embodiment are described. Note that the third curriculum information acquisition step is not essential.

<Embodiment 15>
<Outline of Embodiment 15 Invention>
The interactive learning promotion system of Embodiment 15, in addition to the features described in any one of Embodiments 12 to 14, is characterized by judging the effectiveness of output dialogue information based on learning effect information. do.

<Embodiment 15 Invention Configuration>
FIG. 45 is a diagram showing an example of the configuration of the interactive learning promotion system of the fifteenth embodiment. As shown in FIG. 45, the interactive learning promotion system of Embodiment 15 includes a first learning user identification information storage unit (4501), a first learning SNS user related information acquisition unit (4502), a first learning history information acquisition unit (4503), first learning effect information acquisition unit (4504), first learning analysis rule storage unit (4505), first learning situation information analysis acquisition unit (4506), first learning dialogue information storage unit (4507), Learning user-by-study dialogue information selection rule storage unit (4508), first learning dialogue information selection unit (4509), first learning dialogue information output unit (4510), learning effectiveness judgment rule storage unit (4511), learning dialogue information and a validity determination unit (4512). In this embodiment, the description of the configuration common to any one of the twelfth to fourteenth embodiments will be omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 15 Configuration>
<Embodiment 15 Learning Effectiveness Judgment Rule Holding Unit>
The 'learning validity determination rule storage unit' stores a learning validity determination rule, which is a rule for determining whether dialogue information is effective based on learning effect information acquired with respect to output dialogue information. The effectiveness of the interactive information is determined by the interactive information and related learning effect information. If it can be judged that the learning effect has increased under the influence of the dialogue information, it can be judged that the dialogue information was effective, and if it can be judged that the learning effect has decreased, it can be judged that the dialogue information has had the opposite effect. Of course, there may be a judgment that it was neutral and had no influence. Assuming that the output date of the dialogue information is day A, the validity of the dialogue information may be determined on each of days A+N and A+2N. The number of times the validity is determined is not limited to two, and the validity may be determined any number of times. This is because the number of days until the dialogue information exerts a positive influence on the user to improve the learning effect cannot be uniquely determined, and may change depending on attributes such as the user's personality. Also, since generally a plurality of pieces of dialogue information are output for one learning unit, it is not necessary to divide the determination of validity among the plurality of pieces of dialogue information. In that case, we will evaluate the effectiveness of collective dialogue information chunks. On the other hand, when judging the effectiveness of common dialogue information issued to a plurality of users, as will be described later, the degree of influence of each piece of dialogue information constituting the plurality of pieces of dialogue information is divided to determine the effectiveness. can be done.

<Embodiment 15 Learning Dialogue Information Effectiveness Determining Unit>
The 'learning dialogue information effectiveness judging unit' judges the effectiveness of the dialogue information based on the output dialogue information, the learning effect information obtained for this dialogue information, and the learning effectiveness judgment rule. Comparing the learning effect of the same learning unit at an old point in time and another new point in time, if it is recognized that the learning effect at the new point in time has improved, the output is from the old point in time to the new point in time. It is judged that the dialogue information obtained was effective. If the learning effect at the new time point has declined, it is determined that the dialogue information output from the old time point to the new time point was not effective. It is also possible to judge whether the dialogue information was effective by using the learning effect information alone. This is the case of judging whether or not a completely new knowledge that has not been learned so far has been acquired, or the case of evaluating the deviation value within the population. Furthermore, it is also possible to determine which interactive information was effective in comparison with other users instead of the history of the user. Dialogue information and learning effect information do not necessarily have a 1:1 relationship. This is because one dialogue may work effectively for multiple learning units. On the other hand, a plurality of dialogues may work effectively for one learning unit, and after all dialogue information and learning effect information can have a many-to-many relationship. In the learned dialogue information validity determination unit, it is clear based on the user-by-user dialogue information selection rule that the dialogue information output from the dialogue information output unit is intended to induce the user to act. It is clear which dialogue information is compared with which learning unit. In other words, since the dialogue information is selected based on the acquired learning situation information and the held user-by-user dialogue information selection rule, which learning unit is specifically targeted by the acquired learning situation? will be shown.

Similarly to the effectiveness judgment rule of the interactive health promotion system, the learning effectiveness judgment rule is also capable of judging the effectiveness of the guidance dialogue and evaluating the user's negative reaction. It is conceivable to configure What about the effectiveness of the guided dialogue, the evaluation of the user's negative reaction, and the personality type? It has already been explained in the sixth embodiment. By judging the effectiveness of the guiding dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule and/or the never-give-up process. It is possible to improve the system of the dialogue method that is carried out and captures by various means.

<Fifteenth Embodiment Hardware Configuration>
FIG. 46 is a diagram showing the hardware configuration of the fifteenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the fifteenth embodiment, the description of the programs that operate in common with any one of the twelfth to fourteenth embodiments will be omitted. A "learning history effectiveness judgment rule holding program" newly added in this embodiment holds learning effectiveness judgment rules. The "learned dialogue information effectiveness judgment program" judges the effectiveness of the outputted dialogue information based on the learned effectiveness judgment rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, learning effectiveness judgment rules, learning effectiveness judgment results, various setting information such as communication (not shown), etc. Referenced and used during program execution.

<Fifteenth Embodiment Processing Flow>
FIG. 47 is a diagram illustrating an example of the flow of processing according to the fifteenth embodiment. As shown in this figure, first learning user identification information holding step (4701), first learning SNS user related information acquiring step (4702), first learning history information acquiring step (4703), first learning effect information acquiring step (4704), first learning analysis rule retention step (4705), first learning situation information analysis acquisition step (4706), first learning dialogue information accumulation step (4707), first learning user-by-user dialogue information selection rule retention step ( 4708), first learning dialogue information selection step (4709), first learning dialogue information output step (4710), learning effectiveness judgment rule holding step (4711) for holding effectiveness judgment rules, based on learning effectiveness judgment rules and a learned dialogue information validity judgment step (4712) for judging the validity of the dialogue information.

<Embodiment 16>
<Summary of Embodiment 16 Invention>
The interactive learning promotion system of Embodiment 16 is characterized in that, in addition to the features described in any one of Embodiments 12 to 15, the validity of interactive information is determined using learning history information.

<Embodiment 16 Configuration of the Invention>
An example of the configuration of the interactive facilitation system of the sixteenth embodiment is based on the configuration of the twelfth embodiment shown in FIG. is. A description of the configuration common to any one of the twelfth to fifteenth embodiments will be omitted, and only the configuration unique to this embodiment will be described.

<Sixteenth Embodiment Learning History Validity Judgment Rule Storage Unit>
The 'learning history validity determination rule storage unit' stores a learning history validity determination rule for determining whether dialogue information is effective based on learning history information acquired for output dialogue information. The “learning history validity determination rule” is a rule for determining the effectiveness of output dialogue information by judging from the learning history whether the user followed the dialogue information or took the action intended by the dialogue information. It is determined that the output dialogue information is valid when the user is taking actions that match or are close to the content specified, proposed, or intended by the output dialogue information. Which dialogue information is aimed at which learning unit or the like is acquired as described above. Also, it is possible to configure such that the action is taken only within a predetermined period of time from the output of the dialogue information. The length of time to be set depends on the system design concept, but an appropriate length of time can be determined in relation to user attributes. It is generally within a few hours to within a week.

The learning history validity determination rule is a rule for determining the validity of dialogue information based on learning history information. In this interactive learning promotion system, emphasis is placed on stimulating and improving or maintaining the willingness to learn in order to acquire learning behavior habitually. Therefore, although the judgment is somewhat external, it becomes possible to make a judgment closer to reality by deepening the information content of the learning history information and making a rule that uses the deep information. For example, if the user does not start learning a simple study after half a day has passed since the interactive information was output, it cannot be said that the user's desire to learn was immediately stimulated by the interactive information and that the user's desire to learn was increased. In some cases, it may be judged that the effectiveness of the dialogue information is low. Even if the user immediately responds to the dialogue information, during the same time that the learning continuation time is determined from the learning history information, the user may not have a conversation with a friend on the SNS or post an image of the problem being considered to the SNS. In the case of asking for a hint, even if the information that the learning effect is highly effective is acquired, it cannot be said that the user has acquired correct learning habits, and the output dialogue information is not effective. can be determined to be low. In this way, the learning history information may be configured to be modified by external information.

The learning history effectiveness judgment rule, like the effectiveness judgment rule of the interactive health promotion system, is also capable of judging the effectiveness of the guidance dialogue and evaluating the user's negative reaction. It is conceivable to configure as follows. What about the effectiveness of the guided dialogue, the evaluation of the user's negative reaction, and the personality type? It has already been explained in the sixth embodiment. By judging the effectiveness of the guiding dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule and/or the never-give-up process. It is possible to improve the system of the dialogue method that is carried out and captures by various means.

<Embodiment 16 Learning History Dialogue Information Validity Judging Unit>
The ``learning history dialogue information effectiveness judgment unit'' judges the effectiveness of the dialogue information based on the output dialogue information, the learning history information acquired for this dialogue information, and the learning history effectiveness judgment rule. . It is possible to design so that the evaluation is the highest when the user's learning history matches the intention of the output dialogue information, and the lower the proximity, the lower the evaluation. Evaluation of proximity is based on (1) length of time from the output of dialogue information to the start of intended learning, (2) deviation value within the population of said length of time, (3) length of time and intended learning The difference from the standard time specified in the unit and the deviation value within the population of the difference, (4) the difference between the intended start time of learning and the actual start time, (5) within the population of the difference (6) the difference from the standard time difference set for the learning unit of the difference and the deviation value within the population of the difference, (7) the duration of learning, (8) within the duration of learning (measured by time, number of times, etc.), (9) length of blank time between studies, (10) operation information for learning input devices such as keyboards, (11) installed near learning terminals (12) an evaluation by a person involved in learning of the user, or the like. The learning history dialogue information effectiveness judgment unit may be configured to judge the effectiveness of the dialogue information while the user is taking a learning action, or batch processing after the fact (e.g. Efficacy can be judged from the past learning history during times when the user does not normally interact with the system (sleep hours) or when interaction with the user is interrupted for a long time (time periods during classes or exams: can be identified from curriculum information, etc.) It is also possible to configure

<Sixteenth Embodiment Hardware Configuration>
The hardware configuration of the sixteenth embodiment is based on the hardware configuration of the twelfth embodiment shown in FIG. A description of a program that operates in common with any one of the twelfth to fifteenth embodiments will be omitted. A "learning history validity determination rule holding program" newly added in the present embodiment holds learning history validity judgment rules. The 'learning history dialogue information effectiveness judging program' judges the effectiveness of the output dialogue information based on the learning history effectiveness judging rule. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, learning history validity determination rules, learning history validity determination results, various setting information such as communication (not shown), etc. are held in a non-volatile memory and loaded into the main memory, It is referenced and used when executing a series of programs.

<Sixteenth Embodiment Processing Flow>
An example of the processing flow of the interactive learning promotion system of Embodiment 16 is based on the processing flow of Embodiment 12 shown in FIG. It has a learning history validity judgment rule holding step for holding judgment rules and a learning history dialogue information validity judgment step for judging the validity of dialogue information output based on the learning history validity judgment rules. A description of steps for performing information processing common to any one of the twelfth to fifteenth embodiments is omitted.

<Summary of Embodiment 17 Invention>
The interactive learning promotion system of Embodiment 17 is characterized by, in addition to the features described in Embodiment 15 or Embodiment 16, performing statistical interaction information validity determination by statistical processing of big data.

<Embodiment 17 Invention Configuration>
FIG. 48 is a diagram showing an example of the configuration of an interactive learning promotion system according to the seventeenth embodiment. As shown in FIG. 48, the interactive learning promotion system of Embodiment 17 includes a first learning user identification information storage unit (4801), a first learning SNS user related information acquisition unit (4802), a first learning history information acquisition unit (4803), first learning effect information acquisition unit (4804), first learning analysis rule storage unit (4805), first learning situation information analysis acquisition unit (4806), first learning dialogue information storage unit (4807), Learning user-by-study dialogue information selection rule storage unit (4808), first learning dialogue information selection unit (4809), first learning dialogue information output unit (4810), learning effectiveness judgment rule storage unit (4811), learning dialogue information It consists of an effectiveness judgment unit (4812), learning effectiveness statistical processing rule holding means (4813), and learning statistical dialogue information effectiveness information acquisition means (4814). In this embodiment, the description of the configuration common to the fifteenth or sixteenth embodiment is omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 17 Configuration>
<Embodiment 17 Learning Effectiveness Statistical Processing Rule Holding Means>
The "learning effectiveness statistical processing rule holding means" holds learning effectiveness statistical processing rules, which are rules for statistically processing the effectiveness of interactive information of a plurality of users for each user attribute, which is partly common to the population. and/or the learning history dialogue information effectiveness judgment unit. As the processing in the dialog information validity determination unit described above, generally, learning effect information corresponding to the dialog information output to a specific user and learning history information are used to evaluate the validity of the dialog information for the specific user. can be considered individually. “For each user attribute that is partly common to the population” is because the effectiveness of the dialogue information cannot be compared unless the user has a common user attribute with regard to learning. Specifically, it is possible to determine the effectiveness of the dialogue information with a population of users having user attributes that share learning units and their higher concepts (learning subjects, learning categories, etc.). The effectiveness of dialogue information can be judged in relation to individual individuals, but statistical effectiveness can also be judged for groups. In this system, it is assumed that some attribute information of the user is held in association with the user identification information. It is preferable that the learning status information is also held as attribute information for each user.

By constructing the population on the condition that they have such common attributes and narrowing down the effective dialogue information, the effectiveness of the dialogue that is more accurate than the effectiveness of the dialogue found from the response information to the individual dialogue information It becomes possible to narrow down (select) the relevant dialogue information. Statistically processed effectiveness information of interaction information is obtained for each common user attribute. Therefore, by updating the user-by-user dialogue information selection rule of the user identified by the user identification information having the user attribute, the system is updated as needed so that the dialogue information corresponding to the user attribute can be selected. . If there is a contradiction between the effectiveness judgment result found from the dialogue information for an individual user, its learning effect information and learning history information, and the statistically processed effectiveness judgment result, judgment is made for each user. Prioritize efficacy results. Also, if the two do not contradict each other, weighting can be used to determine the order of effectiveness. It is considered that the most effective weighting is to weight the judgment result of each individual. may be weighted to about 7:3 and 6:4 and incorporated into the user-specific dialogue information selection rule.

<Regarding learning effectiveness statistical processing rules>
"Learning effectiveness statistical processing rules" are rules for acquiring the statistical effectiveness of certain dialogue information, and for determining the identity of intentions of dialogue information that differs for each user arranged according to user attributes. It consists of two rules: As described above, the dialogue information is attached with dialogue information attribute information, and processing may be performed so as to determine the identity of intention based on this. For example, it is conceivable that the result of statistical effectiveness of certain dialogue information is obtained by numerical evaluation such as 5-level evaluation. Numerical evaluation values may be evaluated by each user based on learning effect information and learning history information for advice included in dialogue information. Statistical processing can also be performed using learning effect information and/or learning history information associated with dialogue information accumulated in the past. Furthermore, the acquisition of validity may be configured to be acquired according to the change in the learning situation information before and after the dialogue information is output. This is the same whether statistical processing is used or not. In addition, it is conceivable that the learning effectiveness statistical processing rule is configured so that the statistical effectiveness can be determined also for the introductory dialogue and the user's negative reaction evaluation. The introductory dialogue information, evaluation of negative reactions, and description of personality types have been described in Embodiment 6 of the interactive health promotion system. By judging the effectiveness of the guidance dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule or the never-give-up process. It is possible to improve the system of dialogue methods such as being attacked by various means.

User attribute information is configured to be stored in a user attribute information storage unit or the like in association with user identification information. The user attribute information held in the attribute information holding unit may be updated. Furthermore, it may be configured such that a character diagnosis test, which will be described later, is performed regularly or irregularly (using character diagnosis dialogue information, etc.) to update this retained user attribute information. Furthermore, with respect to the user's personality that constitutes the initial user attribute information, a median value is assigned after each personality type is scored and held, or a questionnaire is given to the users and the questionnaire results are held. It is conceivable to configure it so that Further, the personality may be configured such that the conversation information of the SNS is analyzed by the conversation information analysis unit based on the conversation information analysis rule and the personality is determined. Since a huge amount of conversations with friends or the like is stored in SNS, it can be used effectively. Further, it may be configured such that reading tendency, movie preference tendency, music preference, hobby, favorite entertainer or celebrity, etc. introduced in the SNS are analyzed to determine the character. Learning-related information of user attribute information includes nationality, language used, study abroad experience, country of study abroad, grade, class, gender, affiliated school, affiliated cram school, affiliated correspondence learning course (learning course in the learning system) , Classroom you belong to, Science or Humanities, Subjects you are studying, Learning credits, Desired school, Career path, Alma mater, Club you belonged to, School, Rank (1st, 2nd grade, etc.), Job title, Number of years of continuous study (hours) ), experience of winning prizes in competitions, etc., experience of participating in competitions, etc. The acquisition method of these pieces of information has already been explained in the twelfth embodiment.

<Embodiment 17 Learning Statistical Dialogue Information Effectiveness Information Acquisition Means>
The ``learning statistical dialogue information effectiveness information acquisition means'' statistically obtains the effectiveness of the dialogue information for at least the population based on the dialogue information of a plurality of users and the held learning effectiveness statistical processing rule. On the other hand, some of them are means possessed by a dialog information validity determination unit that acquires statistical dialog information validity information determined for each common user attribute. As described above, in this system, it is assumed that some attribute information of the user is held in association with the user identification information, and such attributes constitute a population, and By summarizing the validity information of the dialogue information for each population, it is possible to acquire the statistical dialogue information effectiveness information for each user attribute that is at least partially common to the population. "Learning statistical dialogue information effectiveness information" means the effectiveness of dialogue (from low effectiveness to high effectiveness) according to user attributes, etc. as a result of statistical processing, and various dialogues with each effectiveness It is information that expresses the number of types of information as a function, and generally has a normal distribution. FIG. 22 is one example of learning statistical dialogue information effectiveness information (explained in Embodiment 7). In other words, the number of dialogue information with "medium" effectiveness is the largest (the types of dialogue information with average effectiveness are the largest), and the number of dialogue information with "high" and "low" effectiveness is a group of data distributed so that By using this data, it is possible to know what kind of conversational information exhibits how effective it is, and it can be used as a computer. It is more preferable that the learning statistical dialogue information effectiveness information is stored separately for each theme and purpose of using the dialogue information, and a plurality of pieces of information exist for each theme and purpose of using the dialogue information.

<Seventeenth Embodiment Hardware Configuration>
FIG. 49 is a diagram showing the hardware configuration of the seventeenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the seventeenth embodiment, the description of the programs that operate in common with the fifteenth or sixteenth embodiment will be omitted. A "learning effectiveness statistical processing rule holding program" newly added in this embodiment holds learning effectiveness statistical processing rules. The "learning statistical dialogue information effectiveness information acquisition program" acquires learning statistical dialogue information effectiveness information based on the learning effectiveness statistical processing rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-specific dialogue information selection rules, selected dialogue information, learning effectiveness judgment rules, learning effectiveness judgment results, learning effectiveness statistical processing rules, statistical dialogue information effectiveness information for learning, various setting information such as communications (not shown), etc. is held in non-volatile memory, loaded into main memory, and referenced and used during a series of program executions.

<Embodiment 17: Flow of processing>
FIG. 50 is a diagram illustrating an example of the flow of processing according to the seventeenth embodiment. As shown in this figure, first learning user identification information holding step (5001), first learning SNS user related information acquiring step (5002), first learning history information acquiring step (5003), first learning effect information acquiring step (5004), first learning analysis rule holding step (5005), first learning situation information analysis acquisition step (5006), first learning dialogue information storing step (5007), first learning user-by-user dialogue information selection rule holding step ( 5008), first learning dialogue information selection step (5009), first learning dialogue information output step (5010), learning effectiveness judgment rule holding step (5011), learning dialogue information effectiveness judgment step (5012), learning effectiveness A learning effectiveness statistical processing rule holding substep (5013) for holding statistical processing rules, a learning statistical dialogue information effectiveness information acquiring substep (5013) for acquiring statistical dialogue information effectiveness information based on the learning effectiveness statistical processing rules ( 5014).

<Embodiment 18>
<Outline of Embodiment 18 Invention>
An interactive learning promotion system according to Embodiment 18 is characterized by, in addition to the characteristics described in any one of Embodiments 15 to 17, updating user-by-user dialogue information selection rules based on effectiveness judgment results. do.

<Embodiment 18 Configuration of the Invention>
FIG. 51 is a diagram showing an example of the configuration of an interactive learning promotion system according to the eighteenth embodiment. As shown in FIG. 51, the interactive learning promotion system of Embodiment 18 includes a first learning user identification information storage unit (5101), a first learning SNS user related information acquisition unit (5102), a first learning history information acquisition unit (5103), first learning effect information acquisition unit (5104), first learning analysis rule storage unit (5105), first learning situation information analysis acquisition unit (5106), first learning dialogue information accumulation unit (5107), One learning user dialogue information selection rule storage unit (5108), first learning dialogue information selection unit (5109), first learning dialogue information output unit (5110), learning effectiveness judgment rule storage unit (5111), learning dialogue information It consists of an effectiveness determination unit (5112) and an update unit for learning user-specific dialogue information selection rules (5113). In this embodiment, the description of the configuration common to any one of the fifteenth to seventeenth embodiments will be omitted, and only the configuration unique to this embodiment will be described.

<Embodiment 18 User-specific dialog information selection rule update unit>
The ``learning user-by-user dialogue information selection rule update unit'' updates the user-by-user dialogue information selection rule holding unit based on the validity determination result of the learning dialogue information validity determination unit and/or the learning history dialogue information validity determination unit. Update the retained user-by-user interaction information selection rules. Updating means updating the validity associated with interaction information on a per-user basis. As a result of the validity determination, if there is a change in the validity for each user that has been associated with the dialogue information, a process of associating it with the latest validity is performed. FIG. 25 is a diagram showing the operation of the user-by-user dialogue information selection rule updating unit, and the outline has already been explained in the eighth embodiment. As a result, it is possible to select dialogue information that is more effective than before. This selection is also a process of changing the priority selection order of the dialogue information stored in the dialogue information storage units (including the first and second). Effectiveness is determined based on learning effect information, based on learning history information, and other response dialogue information. may be configured to Furthermore, the effectiveness may be expressed as the frequency with which dialogue information should be selected, or the number of times dialogue information should be selected during guidance dialogue. Further, the effectiveness may be configured to be associated with the speaker's avatar or the speech style.

FIG. 52 is a conceptual diagram showing an overview of the function of AI (artificial intelligence) for updating selection rules in the eighteenth embodiment. This interactive learning promotion system holds user-by-user dialogue information selection rules that reflect individual characteristics. The individual characteristics of each user that are reflected here are the form of dialogue information, namely the language used during conversation, the content of dialogue information corresponding to the learning situation information, the timing of output of dialogue information, the output interval of dialogue information, and guidance. It will be reflected in the way dialogues are arranged, the process of not giving up (repeating dialogue information with the same intention), and the selection of avatars that output dialogue information. As shown in the figure, for user X (5201), when learning situation information is A (5202), rule 1 (5203) for selecting dialog information "Let's prepare for tomorrow's quiz", learning situation information B In the case of (5204), rule 2 (5205) that selects the dialogue information "Would you like to study a bit before dinner?" ' is held as a user-by-user dialogue information selection rule. At this time, if learning situation information D (5208) that has not been acquired in the past is acquired, user-specific dialogue information is selected by combining rules relating to learning situation information similar to learning situation information D. . In the example of this figure, since the learning situation information C and other numerical values are the same except that the number of consecutive days of learning for a certain subject is different by 12 days, it is selected for the learning situation information C as similar learning situation information. The dialogue information (5209), which is dialogue information similar to the dialogue information, "Let's study a little after taking a break!" is selected and output. If the learning effect information of "wrong answer to question 3" (5210) is acquired for the output dialogue information, the user has learned only one question (learning history information), and there is no incorrect answer. It is recognized that the Although it was recognized that students learned according to the dialogue information, the content was insufficient, and it was recognized that the motivation to learn was not sufficiently stimulated and increased, so the effectiveness of the selected learning dialogue information was low. , and 2 points are obtained as a learning dialogue information validity judgment result (5211). When learning situation information D is acquired in response to the learning dialogue information effectiveness determination result, a new rule (5212) for selecting dialogue information "Let's study hard after taking a break!" is acquired. Then, the updated user-specific dialogue information selection rule is acquired, and the user-specific dialogue information selection rule held in the user-specific dialogue information selection rule holding unit is updated.

<Embodiment 18 Hardware Configuration>
FIG. 53 is a diagram showing the hardware configuration of the eighteenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, of the programs constituting the hardware of the eighteenth embodiment, the description of the programs that operate in common with any one of the fifteenth to seventeenth embodiments will be omitted. The "learning user interaction information selection rule update program" newly added in this embodiment updates the user interaction information selection rule according to the validity of the interaction information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, learning effectiveness determination rules, learning effectiveness judgment results, updated user-by-user dialogue information selection rules, communication (not shown), and various other setting information are held in a non-volatile memory, It is loaded into the main memory and referenced and used during a series of program executions.

<Embodiment 18: Flow of Processing>
FIG. 54 is a diagram illustrating an example of the flow of processing according to the eighteenth embodiment. As shown in this figure, first learning user identification information holding step (5401), first learning SNS user related information acquiring step (5402), first learning history information acquiring step (5403), first learning effect information acquiring step (5404), first learning analysis rule retention step (5405), first learning situation information analysis acquisition step (5406), first learning dialogue information accumulation step (5407), first learning user-by-user dialogue information selection rule retention step ( 5408), first learning dialogue information selection step (5409), first learning dialogue information output step (5410), learning validity judgment rule holding step (5411), learning dialogue information effectiveness judgment step (5412), validity judgment and an update step (5413) for updating the learning user-specific dialogue information selection rule for updating the user-specific dialogue information selection rule based on the result.

<Embodiment 19>
<Embodiment 19 Outline of the Invention>
In addition to the features of Embodiment 17 or Embodiment 18 based on Embodiment 17, the interactive learning promotion system of Embodiment 19 has the following features: It is characterized by updating the stored user-by-user interaction information selection rule.

<Embodiment 19 Configuration of the Invention>
55 is a diagram showing an example of the configuration of an interactive learning promotion system according to Embodiment 19. FIG. As shown in FIG. 55, the interactive learning promotion system of Embodiment 19 includes a first learning user identification information holding unit (5501), a first learning SNS user related information acquisition unit (5502), a first learning history information acquisition unit (5503), first learning effect information acquisition unit (5504), first learning analysis rule storage unit (5505), first learning situation information analysis acquisition unit (5506), first learning dialogue information storage unit (5507), One learning user dialogue information selection rule storage unit (5508), first learning dialogue information selection unit (5509), first learning dialogue information output unit (5510), learning effectiveness judgment rule storage unit (5511), learning dialogue information an effectiveness judgment unit (5512), a learning effectiveness statistical processing rule holding unit (5513), a learning statistical dialogue information effectiveness information acquiring unit (5514), a learning statistical user dialogue information selection rule updating unit (5515); consists of In this embodiment, the description of the common configuration with the seventeenth or eighteenth embodiment will be omitted, and only the unique configuration of this embodiment will be described.

<Embodiment 19 Learning Statistical User-by-User Dialogue Information Selection Rule Update Unit>
The 'learned statistical user interaction information selection rule updating unit' updates the individual user interaction information selection rule held in the individual user interaction information selection rule holding unit based on the acquired statistical interaction information validity information. Other points are the same as those of the eighteenth embodiment.

<Embodiment 19 Hardware Configuration>
FIG. 56 is a diagram showing the hardware configuration of the nineteenth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the nineteenth embodiment, the description of the programs that operate in common with either the seventeenth embodiment or the eighteenth embodiment based on the seventeenth embodiment will be omitted. . The “learning statistical user interaction information selection rule update program” newly added in this embodiment updates the user individual interaction information selection rule based on the learning statistical interaction information effectiveness information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , dialogue information selection rule for each user, selected dialogue information, learning effectiveness judgment rule, learning effectiveness judgment result, learning effectiveness statistical processing rule, statistical dialogue information effectiveness information for learning, updated dialogue information selection rule for each user, illustrated Various setting information such as non-communication is held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Nineteenth Embodiment Processing Flow>
57 is a diagram depicting an example of the flow of processing according to the nineteenth embodiment; FIG. As shown in this figure, first learning user identification information holding step (5701), first learning SNS user related information acquiring step (5702), first learning history information acquiring step (5703), first learning effect information acquiring step (5704), first learning analysis rule retention step (5705), first learning situation information analysis acquisition step (5706), first learning dialogue information accumulation step (5707), first learning user-by-user dialogue information selection rule retention step ( 5708), first learning dialogue information selection step (5709), first learning dialogue information output step (5710), learning effectiveness judgment rule retention step (5711), dialogue information effectiveness judgment step (5712), learning effectiveness statistics Processing rule holding sub-step (5713), learning statistical dialogue information validity information sub-step (5714), learning statistical user-by-user dialogue information for updating the user-by-user dialogue information selection rule based on the statistical dialogue information effectiveness information and a selection rule update step (5715).

<Embodiment 20>
<Outline of Embodiment 20 Invention>
The twentieth embodiment is an invention that describes the twelfth embodiment in terms of a method, and basically expresses the invention of the twelfth embodiment as a method of operating a computer.

<Embodiment 20 Configuration of the Invention>
As shown in FIG. 79, the interactive learning promotion system of this embodiment includes a learning SNS user-related information acquisition step (7901) for acquiring user's SNS-related information, a user's learning history from an external learning system used by the user, A learning history information acquisition step (7902) for acquiring information, a learning effect information acquisition step (7903) for acquiring user learning effect information from an external learning system used by the user, learning status information by analysis based on learning analysis rules A learning situation information analysis acquisition step (7904) for acquiring a learning situation information selection step (7905) for selecting conversation information to be output from among the accumulated conversation information based on the learning situation information and the user-specific conversation information selection rule (7905) , and a learned dialogue information output step (7906) for outputting the selected dialogue information.

<Embodiment 21>
<Outline of Embodiment 21 Invention>
The twenty-first embodiment is an invention that describes the twelfth embodiment in terms of a method, and basically expresses the category of the invention of the twelfth embodiment as a method of operating a computer.

<Embodiment 21 Configuration of the Invention>
The configuration of the operation program of the interactive learning promotion system shown in Embodiment 21 is the same as the configuration shown in FIG. Description of each configuration is omitted since it has already been described in the twentieth embodiment.

<Embodiment 22>
<Embodiment 22 Outline of the Invention>
The interactive purchase promotion system of the twenty-second embodiment uses purchase history information and advertising transmission history information in addition to the user's remark information and browsing information on SNS, and purchase An object of the present invention is to strengthen a user's purchase motivation by acquiring situation information and outputting a dialogue that matches the purchase situation, which is the extent of the user's current purchase motivation, to the SNS.

FIG. 58 is an image conceptual diagram showing the relationship between the interactive purchase promotion system, various SNSs, advertisements, and the like. When a user (5801) who communicates using SNS1 (5802a) and SNS2 (5802b) on a daily basis designates SNS2 as the SNS using this interactive purchase promotion system (5803), This interactive purchase promotion system outputs interactive information through SNS2 (5804). In addition to SNS user-related information (5805a) that can be acquired through SNS1 and/or SNS user-related information (5805b) that can be acquired through SNS2, this interactive purchase promotion system provides information (5806) about products viewed by the user through a personal computer or the like. , and the advertisement transmission history information (5807) relating to advertisements provided to the user by the company. Furthermore, it may be configured to acquire life log information (5809) that the user has actually visited the store (Embodiment 23).

FIG. 59 is an image conceptual diagram when the interactive purchase promotion system gives purchase promotion advice to a certain user. The interactive purchase promotion system (5901) uses conversational information (“I want to buy a new car soon,” “Next "Is it T's car?" User-specific information (5903) such as confirmation of trial calculation of purchase assessment, DM from a plurality of automobile companies, etc. is automatically acquired (5904). Purchase status information (5906) is obtained by analyzing the obtained information (5905). This interactive purchase promotion system determines a background purpose from the obtained purchase status information and selects appropriate dialogue information for achieving the purpose. For example, if the user wants to continue to purchase the same type of car, appropriate dialogue information for achieving the purpose may be "Good evening! Did you see the new T car? The ride is even more comfortable than before." It seems that the interior of the car is open.It is very popular in the United States, and it takes a month from order to delivery.Fortunately, it seems that the wait is not so long in Japan, but I have a feeling that it will be out of stock soon.I will decide on the next test drive. If you can do it, you'll be relieved!" Using SNS, the dialogue information (5907) is output in a tone suitable for the user to the form terminal that receives the dialogue with the interactive purchase promotion system owned by the user ( 5908).

The first feature of the interactive purchase promotion system is that it uses external information such as comments on SNSs, the company's advertising transmission history, and the user's purchase history to analyze the user's purchase status. Next, as a second feature, the acquired external information is analyzed, the user's "purchase intention" is analyzed, and "current purchase situation information" is analyzed and acquired. Furthermore, as a third feature, the contents of dialogue information such as the most suitable ad ice are selected from the "current purchase situation information" obtained by analysis, and the most suitable tone is matched to the tone with which the user is usually familiar or easily persuaded. Dialogue information, which is advice content selected using tone of voice, is output.

<Embodiment 22 Configuration of the Invention>
FIG. 60 is a diagram showing an example of the configuration of the interactive purchase promotion system of the twenty-second embodiment. As shown in FIG. 60, the interactive purchase promotion system of Embodiment 21 includes a first purchase user identification information storage unit (6001), a first purchase SNS user related information acquisition unit (6002), a first purchase history information acquisition unit (6003), first purchase promotional advertisement transmission history information acquisition unit (6004), first purchase analysis rule storage unit (6005), first purchase purchase status information analysis acquisition unit (6006), first purchase dialogue information accumulation unit ( 6007), first purchasing user-by-user dialogue information selection rule holding section (6008), first purchasing dialogue information selecting section (6009), and first purchasing dialogue information output section (6010).

<Description of Embodiment 22 Configuration>
<Embodiment 22 First purchasing user identification information holding unit>
The 'first purchasing user identification information holding unit' holds user identification information for identifying a user having a purchase history of a specific product using SNS. A "specific product" is a product whose purchase is targeted to be promoted by the interactive purchase promotion system, and "product" in this specification may be either only a product, only a service, or both a product and a service. Commodities include not only commodities that circulate in the market, but also commodities that do not circulate in the market, such as buildings, real estate, arts and crafts, one-of-a-kind paintings, sculptures, folk crafts, antiques, etc. Services generally include In addition to services, it includes various services such as film screenings, theater performances, information provision, consulting, marketing, medical treatment, non-insured voluntary procedures, transportation, transportation, transport, generation and transmission of electricity. The user identification information should be able to identify the user within this interactive purchase promotion system, but the user identification may be performed for each specific product. Name, address, telephone number, e-mail address, ID specially set by the user, date of birth, occupation, age, gender, etc. are generally stored in association with user identification information. physical information of the user (for example, height, weight, average body temperature, average pulse rate, average respiratory rate, average heart rate, average amount of exercise (time, quality, mode, etc.), whether or not the user goes to the gym) One or more of such information may be held. In this interactive purchase promotion system, in addition to or in place of the user's physical information, information identifying specific products for which the user has a purchase history, information related to the user's purchase, currently owned Products or types of products that may be substituted for the specific products you are using or are using, time of purchase of the products you are currently using, income, borrowing status, credit card you are using (including card number), possession Information on stocks held, virtual currency held (type, amount), bank used (account number), family structure, friendships, place of work, years of service, position at work, industry at work, school attended , place of work, place of commuting to school, commuting route, commuting route, school attended, previous place of employment, transportation used for commuting, transportation used for commuting to school, nearest station to home, working hours, holidays, hobbies/preferences (food, drink, clothes, Music, movies, reading, perfumes, colors, watches, cars, personal computers, consumer electronics manufacturers, brands, entertainment, collections, hairstyles, nails, accessories, cigarettes, games, sports, broadcasting stations, TV programs, radio programs, celebrities etc.), subscription information (newspapers, magazines, weekly magazines, bulletins), information on owned products that are not interchangeable with specific products, average purchase price range for each product category, visited stores (purchase of products and services (in association with the presence or absence of), information on customer service at the visited store (content of the conversation, person who responded), etc., may be included. As a lifelog that shows the user's physical condition, heart rate, pulse rate, respiration rate, body temperature, degree of muscle contraction/relaxation, electroencephalogram, blood flow velocity, blood oxygen concentration, blood alcohol content, allergic reaction It may be configured to include one or more of the following: degree, degree of accumulation of fatigue material, and the like. These are obtained from a wearable terminal that is worn on the body and capable of measuring the state of the body, a body data measuring device that is not worn on the body but has a communication function, or the like. Alternatively, physical data stored in a portable memory that is not in communication can be transferred to a portable memory (e.g., USB memory, IC card (including prepaid card with RFID function, etc.), portable disk drive, optical recording medium, magnetic memory, etc.). ) can also be obtained from In the case of a prepaid card, it is possible to obtain data indicating the physical condition by receiving information on the physical condition at the time of medical examination or payment of fees for medical treatment by a doctor.

The user attribute information held in association with the user identification information can be configured to be registered by the user himself/herself when using the interactive purchase promotion system. The interactive purchase promotion system may be configured to be available with this registration. Furthermore, the user attribute information can be transferred or copied from another system already used by the user. For example, data from stores, department stores, supermarkets, online product purchase sites, application-based product purchase systems, etc., household accounting software used by users, and tax accountants and certified public accountants used by users are managed. Information acquired from computer systems, electronic money systems used by users, information from credit card systems used by users, data held by facilities such as training applications, etc., can be used.

(1) If there is a purchase history (or advertisement transmission history or reception history), the first purchase (or viewing or receiving advertisement), or the second and subsequent purchases ( Alternatively, it can be configured to register user attributes when viewing or receiving advertisements. This registration can be configured to register online if the purchase (or viewing of the advertisement) is online. If user attributes are registered for the second and subsequent purchases, in the case of online purchases, a cookie will be sent to the terminal used for the initial purchase (or viewing or receiving advertisements) to facilitate the second and subsequent purchases. It is also possible to retroactively record as a purchase history the access/purchase record that was recorded through the cookie of the purchase web page of the same terminal at the time of registration.
However, if the purchased net itself is registered at a place such as a membership shopping mall or a credit card company's web shopping, the registered user attributes at the time of registration at the shopping mall can be diverted. Furthermore, in the case of using a user attribute, it may be configured such that the user attribute is a mixture of the information to be used and the user attribute registration items at the time of new purchase (viewing and receiving of advertisements). Furthermore, registration can be configured to be web-offline (postcard, letter, e-mail, etc.). In the case of off-line registration, it is also possible to configure so that input work by a person or input by mechanical character reading is performed. In the case of paper media such as mail-order magazines, it is also possible to register user attributes from postcards, letters, websites, etc. when registering as a mail-order member.
The same applies to mail-order sales conducted by credit card companies. In addition, the user attribute registration of users who have no purchase history and have only accessed advertisements should be registered from the advertisement registration application web screen when registering for advertisement push notifications, or by e-mail. may be configured. Furthermore, it is also possible to send a cookie to the computer that browses the advertisement, to acquire various information performed on the computer, and to acquire user attributes stored in the computer. As for the registration of user attributes, if there is a purchase of a product after push notification registration of an advertisement, it is also possible to register more detailed user attributes and use them as user attributes as well.

<Embodiment 22 First purchase SNS user-related information acquisition unit>
The 'first purchase SNS user-related information acquisition unit' acquires, as external information, SNS user-related information, which is user-related information including user-used SNS comments in association with user identification information. Here, the definitions of "SNS user-related information" and "SNS" have already been explained in the first embodiment regarding the interactive health promotion system.

<Embodiment 22 First Purchase History Information Acquisition Unit>
The 'first purchase history information acquisition unit' acquires purchase history information, which is information indicating the purchase history of the specific product in association with the user identification information. The purchase history information includes the point of purchase when the user purchased the specific product in the past, the purchase price, the purchase store information, and the purchase assessment price information of the current product, as well as interactive information output from the interactive purchase promotion system. It also includes the date and time of purchase, the purchase price, and the information on the store where the purchase was made when a specific product is purchased. The purchase history information may be provided by the store where the purchase was made, that is, by a company or the like that practices an approach toward the purchase of a specific product for the user through the use of this system. Also, the purchase history information includes information on the Nth purchase, but the N+1th purchase that has not yet been made. For example, it is a user's action performed between a seller or a manufacturer of a specific product in the pre-purchase stage.

<Embodiment 22 First Purchasing Advertisement Transmission History Information Acquisition Unit>
The 'first purchase advertisement transmission history information acquisition unit' acquires the advertisement transmission history information, which is the transmission history of the advertisement of the specific product that the user may have come into contact with in association with the user identification information. “Publicity advertisement sending history information” is a history of information sent for advertising a specific product. Therefore, for example, TV commercials, newspaper advertisements, magazine advertisements, radio commercials, in-vehicle advertisements, newspaper insert flyers, DM, SNS outgoing news, press release information, in-house newsletters, company websites, magazine feature articles, TV program special features, events, etc. Various types of information are possible. The advertisement sending history includes both those sent by specifying the user and those sent to unspecified people. Information related to these advertising activities is mainly used by users, including mobile terminals, desktop PCs, tablet terminals, notebook PCs equipped with SNS, user attribute information associated with user identification information, Acquired as information on the history of transmission of advertisements from information browsing/viewing history of a company's server (holding information on DM history), etc., which already has a purchase history. Acquisition can be obtained by automatic recognition from tags, automatic recognition of images, included characters, included photos, included voices, included URLs, included broadcast program IDs, and the like. It consists of deterministic information and presumed information. Also, in order to improve the accuracy of the estimation information, it is possible to ask whether the user has viewed the advertisement through the SNS as the dialogue information.

<Embodiment 22 First Purchase Analysis Rule Holding Unit>
The ``first purchase analysis rule holding unit'' acquires purchase status information by analyzing external information, purchase history information, and advertising transmission history information in association with user identification information from the viewpoint of understanding the purchase status. Maintain the primary purchase analysis rule that is the rule for Since the first purchase analysis rule is associated with the user identification information, it becomes a purchase analysis rule that matches the characteristics of the user. Also, the ultimate purpose of this interactive purchase promotion system is to realize voluntary continuation of purchase of a specific product. In order to achieve voluntary continuation of purchases, it is necessary to acquire a habit of purchasing, to improve the willingness to purchase to acquire this habit, and to maintain the acquired habit , it is necessary to maintain the willingness to purchase. This interactive purchase promotion system is an interactive system for realizing improvement and maintenance of willingness to purchase. Therefore, the purchase analysis rule is a rule for each user for analyzing and acquiring purchase status information for each user, which is necessary to improve and maintain purchase motivation.

“Purchase status information” is information indicating how much the user is willing to purchase the specific product, indicating the sense of distance between the user and the specific product. For the calculation of the sense of distance, as "information obtained from external information", the amount of remarks, frequency of remarks, change in the amount of remarks, change in the frequency of remarks, friendship degree of remarks to information related to specific products in SNS , frequency of use, frequency of use, and frequency of consumption of a specific product, which can be inferred from remarks. number of repeat purchases, duration of repeat purchases (years, months, weeks, days), change in repeat purchase intervals, and any one or more of them can be cited as "information obtained from the advertising transmission history information" is the frequency of access to information related to specific products, the amount and speed of accumulation of information related to specific products (links to websites, copies of information on websites, e-mails, attachments to e-mails, introductions on SNS) - Any one or more of accumulated accelerations can be mentioned. Quantification of the sense of distance uses the first purchase analysis rule. This rule is configured to calculate a sense of distance by quantifying and combining external information, purchase history information, and advertising transmission history information.

In order to quantify purchase status information based on information obtained from external information, for example, the amount of remarks in SNS, the sense of distance is closer when the number of remarks is high, and the sense of distance is distant when the number of remarks is low. , and quantified so that the greater the change in the amount of speech or the change in the frequency of speech, the closer the sense of distance, and the less the change, the greater the sense of distance. The degree of friendship such as remarks is quantified so that the higher the degree of friendship, the closer the sense of distance, and the lower the degree of friendship, the greater the sense of distance. The degree of quantification may vary from user to user. This degree of friendship is determined by meaningful analysis of remarks. At that time, the mental state of the user is analyzed, and calculation is made so that the better the mental state, the higher the effectiveness, and conversely, the worse the mental state, the lower the effectiveness. As for the mental state, creating a situation in which words and gestures that make it possible to assume that the uttered words are in a state such as "peace of mind", "mental stability", and "relaxation" are acquired as external information, and maintaining the situation. , can be mentioned. In addition, mental health status is not only good or bad, but also relief, anxiety, gratitude, surprise, excitement, curiosity, sexual curiosity, calmness, impatience (impatient), wonder (confusion), good luck, relaxation, tension, Honor, Responsibility, Respect, Affinity, Admiration, Desire, Fear, Courage, Pleasure, Regret, Satisfaction, Dissatisfaction, Regret, Disgust, Shame, Contempt, Jealousy, Guilt, Murderous Intent, Expectation , superiority, inferiority, resentment, suffering, sadness, sorrow, emotion, anger, resignation, despair, hatred, emptiness, etc. can also In addition, the degree of friendship is calculated according to the degree of attention paid to a specific product, the degree of friendship is acquired according to the degree of interest in a specific product, and the degree of friendship is acquired according to the amount of association with a specific product. , gain friendship based on the amount of desire related to a particular item, gain friendship based on the amount of comparatives related to a particular item, and gain friendship based on the amount of belief in the goodness of a particular item. It can be configured to acquire a degree of friendship, or acquire a degree of friendship according to the strength of a purchase decision regarding a particular product.

In order to quantify purchase status information based on purchase history information, the greater the number of repeat purchases of a specific product, the number of repeat purchases within a predetermined period, and the repeat duration (years, months, weeks, days), the greater the distance. It is quantified so that the sense of distance becomes closer, and conversely, the smaller the distance, the greater the sense of distance. Also, the change in repeat interval can be quantified so that the sense of distance becomes closer when the repeat interval becomes constant or shorter, and quantified so that the sense of distance becomes farther when the repeat interval becomes longer. However, the interval may be evaluated depending on whether the specific product is a mass-consumed product such as beer or a high-end consumer product such as an automobile.

In order to quantify purchase status information based on the information obtained from the advertising transmission history information, the higher the frequency of access to information related to a specific product, the closer the sense of distance. Quantification is performed so that the lower the distance, the greater the sense of distance. Regarding the accumulation amount, accumulation speed, and accumulation acceleration of information related to specific products (links to homepages, copies of information on homepages, e-mails, e-mail attachments, introduction on SNS), the greater the increase, the closer the sense of distance. It is quantified so that the feeling of distance increases as it decreases.
Purchase status information is obtained by combining these three types of information. How each element is weighted depends on the design concept of the system. For example, it is conceivable to assign priority points to purchase history information, then to external information, and finally to advertisement transmission history information. For example, if each of the three types of information has a maximum score of 100 points, weighting is changed for each user based on the user's attributes, the past three types of information, and purchase history information. Between 60% of historical information, 30% of external information, 10% of advertising transmission history information, and 40% of purchasing history information, 40% of external information, and 20% of advertising transmission history information. It is conceivable to set

<Embodiment 22 First Purchasing Status Information Analysis Acquisition Unit>
The ``first purchase/purchase status information analysis/acquisition unit'' includes the acquired external information associated with the user identification information, the purchase history information, the advertisement transmission history information, and the first purchase status information associated with the same user identification information. Acquire purchase status information based on purchase analysis rules. The purchase status information may include the user's mental state type as accompanying information in addition to the quantified value representing the distance to the purchase. The acquired purchase status information may be stored in the first purchase purchase status information analysis/acquisition unit including the past information in a temporal association with the user identification information and the output dialogue information. may be stored as part of the user attribute information stored as information associated with.

<Embodiment 22 First Purchase Dialogue Information Storage Unit>
The 'first purchase dialogue information accumulation unit' accumulates dialogue information to be transmitted according to the purchase status information acquired in association with the user identification information. The dialogue information is a database of all kinds of conversations that may be said in general society. Conversation example sentences, words, still images, videos, robot programs, animations, pictures, avatar pictures, etc. that are the basis for giving advice to users on purchasing or establishing buying habits in this interactive purchase promotion system is held particularly heavily. In addition to a dictionary of general conversational information, it is preferable to have something like a specialized dictionary for purchasing. The language may be stored in a language understood by the user, or the dialogue information may be stored in a standard language such as Japanese, English, Chinese, etc., and configured to be translated and selected according to the language used by the user. You can also Therefore, the foundation is built in advance based on language dictionary database, conversation dictionary database, etc., and furthermore, SNS, information providing site, corporate advertisement site, bulletin board site, telephone call content, etc. are browsed by this interactive learning promotion system. It is preferable to accumulate dialogue information collected from all sources that can be viewed and collected. These may include, for example, dialects, gyarugo, pictograms, emoticons, jargon, coined words, new words, abbreviations, idioms, etc., which are collected by artificial intelligence and gradually improve conversation accuracy (intentions are accurate). It is preferably configured so that the Furthermore, it is conceivable to use specific product names, specific store names, specific company names, specific component names, specific function names, and coined words for purchase promotion advice. Since it is not always possible to obtain specific proper nouns and coined words from the Internet, it is preferable to allow a person to directly input a special language group into the storage unit.

This interactive purchase promotion system reflects the individuality of each user and selects and outputs dialogue information so that the conversation becomes natural for the user, thereby making the user feel as if he or she is concerned about the user. It is characterized by making you feel as if you are in contact with a real human being. Therefore, depending on the user's daily conversation, whether to use polite language, casual language with a colloquial tone, dialects such as Osaka dialect or Hakata dialect, and words mixed with English in the document It is preferable that dialogue information is accumulated so that not only the content of the conversation such as whether to use it as an errand, but also the form of the conversation can be selected. The first purchase dialogue information accumulation unit may accumulate dialogue information as different dialogues even if they have the same meaning for each difference in formation of the dialogue. That is, expressions such as "thank you", "thank you", "thank you", "thank you", "thank you", etc. are all stored as different dialogue information as dialogue information expressing gratitude. Alternatively, the first purchase dialogue information storage unit stores only the most basic dialogue information for each meaning, and the first purchase dialogue information output unit, which will be described later, selects basic dialogue information from the first purchase dialogue information storage unit. It is conceivable to convert the dialogue information into a dialogue form that matches the individuality of the user. In this case, a rule for converting the basic dialogue information into a dialogue format suited to the characteristics of each user is included in the user-specific dialogue information selection rule. In this case, the first purchase dialogue information storage unit contains "Would you like to try it?", "Why don't you try it?" Since "LET'S TRY" and the like are all expressions that encourage the experience of a specific product, they are associated with or derived from "Would you like to try it?" as basic dialogue information.

The dialogue information accumulated in the first purchase dialogue information accumulation unit may be configured so as to be displayable on the interface monitor. The dialogue information storage unit management means is the first purchase dialogue information storage unit so that management actions such as addition, change, and deletion of dialogue information can be manually performed from the interface screen on which the accumulated dialogue information is displayed. , or a configuration in which the dialog information storage unit management unit is provided as a new configuration.
It is assumed that the person who manages and provides this interactive purchase promotion system performs the management action of the first purchase dialogue information accumulation unit.

<Twenty-Second Embodiment: Holding Unit for Selecting Dialogue Information by First Purchasing User>
The 'storage unit for selection rule of dialogue information by first purchasing user' holds dialogue information selection rule by user, which is a rule associated with user identification information for selecting accumulated dialogue information based on acquired purchase status information. do. The user-by-user dialogue information selection rule reflects the individuality of each user in order to make the user feel as if he/she is in contact with a real person who cares about him or her. It is a rule for selecting dialogue information so as to have a natural conversation. From external information such as SNS user-generated information, select a conversation format that matches the user's dialogue format, purchase status information analysis Select the content of the conversation based on the acquired purchase status information, and select both are combined to select dialogue information that reflects the individuality of the user. Dialogue formats include polite language, colloquial language, gal language, Osaka dialect, Kyoto dialect, Hakata dialect, Nagoya dialect, Hokkaido dialect, Okinawa dialect, and other regional dialects, etc. A method of selecting from the information selection rules to make the user-specific dialogue information selection rule, and a method of assembling all originals from the user's conversation information are conceivable.

The reason why the interactive purchase promotion system can be recognized by the user as if it were a real and familiar existence is the method of assembling an original interactive form that can more strongly reflect the individuality of the user. However, at the stage when the user starts using this interactive purchase promotion system, the amount of external information accumulated for analyzing the user's individuality is small. Therefore, it automatically selects the default format when there is not enough information to obtain the rules for selecting the original format according to the user's personality. For example, it is conceivable to allow the user to select and register an interactive format so that the interactive format of the user's preference is started. Also, it may be configured to automatically select an appropriate interactive format according to the attributes of the user. User attributes include age, gender, hometown, current address, nationality, language used, conversation (dialogue) style on SNS, conversation (dialogue) style of friends on SNS, preferred clothing type, and preferred movie type. , favorite book type, favorite celebrity type (talent, actor, politician, writer, singer, comedian, historical figure, announcer, character), and the like. When sufficient user external information is accumulated to acquire the first purchase dialogue information selection rule, a unique user-by-user dialogue information selection rule that selects a format according to the user's individuality from the first purchase dialogue information storage unit is created. Configure. The selection rule may be configured such that, if information indicating the user's mental state is included in the purchase status information, the dialogue information to be selected changes according to the mental state.

In order to optimize user-by-user dialogue information selection rules for each user from user's SNS conversation information, it is conceivable to analyze the form of dialogue information. It is conceivable to analyze the conversation styles of friends and family members with whom the user frequently communicates, and to assemble user-specific dialogue information selection rules, rather than simply relying on the user's utterance style. By analyzing and reflecting the manner of speaking of the conversation partner with whom the user actually has a daily conversation, it is possible to give the user a sense of security as if talking with a friend or family member. Therefore, it is possible to make the user feel as if he or she is interacting with a real person who is concerned about the user, and the user is worried about purchasing a new product. , it becomes easier for the user to honestly consult about hesitation, and the user can easily accept advice and suggestions from the system. From this point of view, a wide variety of dialogue information is accumulated, such as dialogue information that conveys affection, dialogue information that conveys favorability, dialogue information that praises the other party, and dialogue information that encourages the other party. preferably.

In addition, the user's personality, such as always responding with negative remarks, but being unable to refuse when asked many times, disliking it exaggeratedly even though it is not really disliked, or disliking it for the time being, can be analyzed using personality diagnosis and attributes. If it is acquired by information, etc., it cannot be said that the output dialogue information is not effective only with a few negative responses from the user, and it takes until the user accepts the output of the same dialogue information on average. If it is recommended as a response to be taken in the result of statistical analysis using personality as an attribute to repeat until a specific number of times is greater than the required number of times, the response is set as a rule for the dialogue information selection unit to select. can be considered. That is, such a never-give-up rule (sub-step, sub-rule) or a never-give-up process can be included in the user-specific dialogue information selection rule, or a process configured by this can be included.

<Embodiment 22 First purchase dialogue information selection unit>
The ``first purchase dialogue information selection unit'' selects dialogue information from the first purchase dialogue information storage unit based on the purchase status information and the stored user-specific dialogue information selection rule, and selects dialogue information based on the characteristics of each user. It converts it into conversational information in an appropriate conversational style. The 'first purchase dialogue information selection unit' selects dialogue information from the first purchase dialogue information storage unit based on the acquired purchase status information and the held user-by-user dialogue information selection rule. When dialogue information is accumulated in the first purchase dialogue information storage unit for each difference in dialogue format, dialogue information that matches the dialogue format and dialogue content selected by the user-specific dialogue information selection rule is selected. Become. If dialogue information is not stored for each difference in dialogue format in the first purchase dialogue information storage unit, and dialogue information is stored for each meaning of the content of the dialogue regardless of the dialogue format, Basic dialogue information is selected from the first purchase dialogue information storage unit according to the dialogue contents specified by the information selection rule, and the selected dialogue information is converted into a dialogue format that matches the dialogue format specified by the user-specific dialogue information selection rule. Convert. In this case, the basic dialogue information may refer to a set of words instead of the words themselves. In this case, identification information is given to dialogue information that expresses gratitude, and this is selected, followed by ``thank you'', ``thank you'', ``thank you'', ``thank you'', and ``thank you''. Configure to select one of the expressions such as "Thank you". In other words, basic dialogue information is selected from the dialogue information storage unit according to the dialogue content specified by the user-specific information selection rule, and the selected dialogue information is used as the dialogue format specified by the user-specific dialogue information selection rule. is converted to an interactive format that matches The above operation becomes the selection of dialogue information. This selection is constructed so that it can be made instantaneously by a computer. Specifically, the speed is such that when an input from a user is received via an SNS, a reply is displayed on the screen without allowing the user to close the SNS screen. As an example, it is about 1 second or less on average.

<Embodiment 22 First Purchase Dialogue Information Output Unit>
The 'first purchase dialogue information output unit' outputs the selected dialogue information to the user identified by the user identification information via the SNS. As described above, the speed at which the first purchase dialogue information output unit outputs dialogue information is the speed at which the user's input can be immediately responded to if necessary. This is because if the user closes the SNS screen, there is a high risk that the call from the system will be left unread without being marked as read. It should be noted that it is not always necessary to respond immediately, and there may be some type of transmission that is output after some time. This is the case, for example, in a conversation to hear the result of advice. The output is a mobile terminal of the user, a fixed terminal such as a desktop personal computer, or the like. The SNS to be output may be an application dedicated to this interactive purchase promotion system, or an SNS service managed and provided by another system that is not dedicated to the interactive purchase promotion system used by the user on a daily basis. good too.

The format of the output is not limited as long as it is a method capable of transmitting information to the user, such as characters, illustrations, sounds, images, and moving images. In order to make it feel as if you are talking to a real person, it is better to use the SNS service that is used for daily communication with real people than to use a dedicated application. The purchase promotion advice and purchase habit establishment advice from the interactive purchase promotion system are naturally displayed among the contents, which is effective. "Effective" means that the advice from the Interactive Learning Acceleration System can be seen naturally on a daily basis, so it is effective in that it does not make people strongly conscious of interacting with the system (inorganic computer or server). This is the reason why The output from the Interactive Learning Acceleration System uses the SNS service of the output destination. With such a configuration, the above effect can be ensured, so that it is more effective. Conversely, chat heads and the like are immediately noticeable on smartphones, etc., and are preferable because they reduce the sense of distance from the present system. The dialogue information to be output is not limited in content and format, such as information including question format, information including advice, greetings, onomatopoeia, and the like.

Furthermore, instead of always using the same output format, combining multiple output methods such as characters, illustrations, voices, images, videos, etc., and avatars generated by computer graphics can be similar to interacting with real people. , will be more effective. Therefore, in addition to outputting dialogue information as characters to the output interface and outputting recorded voice data as dialogue information (utterance), real-time output of dialogue information and response dialogue information using automatic voice call function Acquisition may take place. Furthermore, when a person accesses a sales destination of a specific product using a voice call, if the person's voice call is received by a communication device that uses this interactive purchase promotion system, this dialog will be sent to the output side. Even if there is no user registration for the interactive purchase promotion system, immediately generate and hold user identification information using a telephone number, etc., and recognize that person as a guest user in the interactive purchase promotion system that receives voice calls. It is also possible to configure such that interactive information can be output by voice to the guest user via this voice interactive purchase promotion system. In this case, the guest user merely performs user registration through a voice call to the interactive purchase promotion system at a remote location. The user terminal itself is defined as a guest user in order to distinguish from the case where this interactive purchase promotion system is activated. By giving an identification number in association with user attributes such as number, etc., in subsequent voice calls, guest user attribute information (preferences, speaking style, spacing, hobbies, etc.) accumulated by past voice calls It is possible to output dialogue information reflecting thoughts, etc.). In this case, the output of the dialogue information is generated by an SNS-enabled terminal that is not possessed by the user receiving the voice call, and the voice output is delivered to the guest user via the phone. It can be said that this is an output of dialogue information via SNS.

The output of the dialogue information via the SNS is the output as comments of the user's friends, etc. participating in the SNS. Therefore, since it is preferable to have a conversation as a friend or the like that looks unique to the user as much as possible, it is preferable to use as many names as possible so that the same name does not overlap among users as much as possible. Alternatively, the name may be freely set at the time of initial user registration. Also, the attributes that determine the elements used for conversation selection may be freely set at the time of user registration. For example, it is the gender, age, character, avatar, clothes, life rhythm, hobby, etc. of the system friends.

Further, the dialogue information may be output not only by one character that the present interactive purchase promotion system pretends to be, but also by a plurality of characters. For example, one character can be used as a scolding and another can be used as a comforter. Character settings can also be configured to be selected based on acquired external information, purchase history information, advertising transmission history information, and the like. A suitable character can be selected according to the content (attribute) of conversation information to be output. Therefore, attributes are added to conversation information and stored in the first purchase dialogue information storage unit, and a character corresponding to the attribute information is selected in the first purchase dialogue information output unit to compose a statement on the SNS. Good. The conversation to be selected may include not only a conversation between the user and friends, who are a plurality of system characters, but also a conversation between friends, etc. (characters) who are the system. In this case, the user can obtain motivation for purchase promotion, establishment of purchase habits, etc. from conversations exchanged among friends and the like.

In addition, in cooperation with a location information system of the user terminal, etc., it may be configured to switch utterances of friends, etc., who are the system, according to the location information. For example, when a user goes to Osaka, a friend who speaks Osaka dialect appears, and when a user goes to Kyushu, a friend who speaks Kyushu dialect appears. In this case, the friend in Osaka may be configured to select a conversation on the premise that they have met for the first time in a long time since the last time they went to Osaka (meeting timing situation). For example, when you go out to a distant place and a friend on the system who is set as a friend who lives there appears in the SNS conversation, in the situation that you met for the first time in a long time since the last time you went out, "C's last time It was a camera, but why don't you buy the new C product that was released recently?" Also, when setting friends, etc., which is a common system for a plurality of users, comparison conversations such as "Mr. Mr. Yamada wanted to go camping, so why don't you buy a new car from T and go camping?"

The avatars (characters) of friends and the like do not necessarily have to be people, and may be set as mammals, fish, insects, objects, and the like. The avatar may also be configured to send photos, videos, pictures, etc. to the user depending on the settings. For example, food photos, landscape photos, ideal body photos, videos explaining how to exercise, etc. In addition, you may send us information on equipment, supplements, etc. to promote use. In addition, friends, etc., who are the system, use the above-mentioned avatar schedule, which sets events according to the passage of time, such as being hit by an accident and climbing the stairs of life, to create a sense of reality, warmth, and humanity. may

<Embodiment 22 Hardware Configuration>
FIG. 61 is a diagram showing an example of the hardware configuration of the twenty-second embodiment. As shown in the figure, it can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, as a program constituting the hardware of the twenty-second embodiment, the "first purchasing user identification information holding program" holds user identification information. The "first purchasing SNS user-related information acquisition program" acquires SNS user-related information. This is done through an interface program with SNS. The "first purchase history information acquisition program" acquires user's purchase history information from an external learning system used by the user. The 'first purchase advertisement transmission history information acquisition program' acquires an advertisement transmission history. The "first purchase analysis rule retention program" retains the first purchase analysis rule. The 'first purchase purchase status information analysis acquisition program' acquires purchase status information from external information, purchase history information, and advertising transmission history information based on analysis based on the first purchase analysis rule. The "first purchase dialogue information accumulation program" accumulates dialogue information. The 'holding program for dialogue information selection rules for each first purchasing user' holds dialogue information selection rules for each user. The 'first purchase dialogue information selection program' selects appropriate dialogue information from the accumulated dialogue information based on the acquired purchase status information and the held user-specific dialogue information selection rule. The "first purchase dialogue information output program" outputs the selected dialogue information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, first purchase analysis rule, purchase status Information, dialogue information, dialogue information selection rules for each user, selected dialogue information, various setting information such as communication (not shown), etc. are held in non-volatile memory, loaded into main memory, and referenced and used when executing a series of programs. be.

<Embodiment 22: Flow of Processing>
FIG. 62 is a diagram illustrating an example of the flow of processing according to the twenty-second embodiment. As shown in the figure, a first purchase user identification information holding step (6201) for holding user identification information, a first purchase SNS user related information acquisition step (6202) for acquiring user SNS related information, and purchase history information acquisition. first purchase history information acquisition step (6203) to acquire information on the transmission history of advertisement transmission (6204); first purchase analysis rule retention step ( 6205), a first purchase purchase status information analysis acquisition step (6206) for acquiring purchase status information using the retained first purchase analysis rule, external information, purchase history information, and advertising transmission history information; step (6207) for accumulating first purchase dialogue information, step (6208) for holding first purchase user dialogue information selection rule for storing user dialogue information selection rule, dialogue output based on user dialogue information selection rule It consists of a first purchase dialogue information selection step (6209) for selecting information and a first purchase dialogue information output step (6210) for outputting the selected dialogue information.

<Embodiment 23>
<Outline of Embodiment 23 Invention>
The interactive purchase promotion system of Embodiment 23 is an independent embodiment, but is characterized by having a first purchase behavior/life log information acquisition unit in addition to the functions described in Embodiment 22.

<Embodiment 23 Configuration of the Invention>
FIG. 63 is a diagram showing an example of the configuration of an interactive purchase promotion system according to the twenty-third embodiment. As shown in FIG. 63, the interactive purchase promotion system of Embodiment 23 includes a second purchase user identification information storage unit (6301), a second purchase SNS user related information acquisition unit (6302), a second purchase history information acquisition unit (6303), second acquisition of purchase advertisement transmission history information acquisition unit (6304), second purchase behavior/life log information acquisition unit (6305), second purchase analysis rule storage unit (6306), second purchase purchase status information analysis Acquisition unit (6307), second purchase dialogue information storage unit (6308), second purchase user dialogue information selection rule storage unit (6309), second purchase dialogue information selection unit (6310), second purchase dialogue information output unit (6311).

<Description of Embodiment 23 Configuration>
<Embodiment 23 Concerning the configuration of Embodiment 23 that performs the same function as Embodiment 22>
The ``second purchase user identification information storage unit'' is the first purchase user identification information shown in Embodiment 22, and the ``second purchase SNS user related information acquisition unit'' is the first purchase SNS user related information shown in Embodiment 22. The acquisition unit and the "second purchase history information acquisition unit" are the first purchase history information acquisition unit shown in Embodiment 22, and the "second purchase advertisement transmission history information acquisition unit" is the first purchase history information acquisition unit shown in Embodiment 22. The purchase publicity advertisement transmission history information acquisition section, the "second purchase dialogue information output section" are the first purchase dialogue information output section shown in Embodiment 22, and the "second purchase dialogue information storage section" are shown in Embodiment 22. The first purchase dialogue information storage unit and the "second purchase user dialogue information selection rule storage unit" are the first purchase user dialogue information selection rule storage unit shown in the 22nd embodiment and the "second purchase dialogue information selection rule storage unit". section" has the same functions as the first purchase dialogue information selection section shown in the 22nd embodiment, and has already been described.

<Embodiment 23 Second purchase behavior/life log information acquisition unit>
The 'second purchase behavior/life log information acquisition unit' acquires behavior/life log information, which is information indicating the user's behavior and/or life log in association with the user identification information. "Behavior/life log information" includes GPS information that indicates the user's movement, drive recorder information that indicates the user's movement by car, ETC payment history information, etc. , Settlement history information when payment is made at the place where you go, Visit information to a specific store, Experience information at a specific store, Internet search/viewing history, Free sample request/distribution information, Catalog request/distribution information, Shopping street/shopping mall visit information, shopping street/shopping mall movement information (using indoor positioning technology), in-store line-of-sight movement information (line-of-sight detection by in-store camera), product inquiry information by phone, parking lot usage information, Restaurant usage/reservation information, vending machine usage information, electronic money payment information, online shopping usage information, taxi (especially self-driving) ride information, home delivery order information, attraction usage information, home time information, beauty salon usage information, massage usage Information, hospital usage information, movie usage information, esthetic usage information, coupon (especially electronic) usage information, paid content usage information (especially via the Internet), video viewing history, transportation usage history, etc. include. Furthermore, as a life log that indicates the user's physical condition, heart rate, pulse rate, respiration rate, body temperature, degree of muscle contraction/relaxation, electroencephalogram, blood flow velocity, blood oxygen concentration, blood alcohol content, allergies It may be configured to include one or more of the degree of reaction, the degree of accumulation of fatigue substances, and the like.

The user attribute information held in association with the user identification information can be configured to be registered by the user himself/herself when using the interactive purchase promotion system. The interactive purchase promotion system may be configured to be available with this registration. Furthermore, the user attribute information can be transferred or copied from another system already used by the user. For example, data from stores, department stores, supermarkets, product purchase sites on the web, product purchase systems using applications, etc. with usage history, household accounting software used by users, and tax accountants and certified public accountants used by users are managed. Information acquired from computer systems, electronic money systems used by users, information from credit card systems used by users, data held by facilities such as training applications, etc. can be used.

(1) If there is a purchase history (or advertisement transmission history or reception history), the first purchase (or viewing or receiving advertisement), or the second and subsequent purchases ( Alternatively, it can be configured to register user attributes when viewing or receiving advertisements. This registration can be configured to register online if the purchase (or viewing of the advertisement) is online. If user attributes are registered for the second and subsequent purchases, in the case of online purchases, a cookie will be sent to the terminal used for the initial purchase (or viewing or receiving advertisements) to facilitate the second and subsequent purchases. It is also possible to retroactively record as a purchase history the access/purchase record that was recorded through the cookie of the purchase web page of the same terminal at the time of registration.
However, if the purchased net itself is registered at a place such as a membership shopping mall or a credit card company's web shopping, the registered user attributes at the time of registration at the shopping mall can be diverted. Furthermore, in the case of using a user attribute, it may be configured such that the user attribute is a mixture of the information to be used and the user attribute registration items at the time of new purchase (viewing and receiving of advertisements). Furthermore, registration can be configured to be web-offline (postcard, letter, e-mail, etc.). In the case of off-line registration, it is also possible to configure so that input work by a person or input by mechanical character reading is performed. In the case of paper media such as mail-order magazines, it is also possible to register user attributes from postcards, letters, websites, etc. when registering as a mail-order member.
The same applies to mail-order sales conducted by credit card companies. Furthermore, the user attribute registration of users who have no purchase history and have only accessed advertisements should be registered from the advertisement registration application web screen when registering for advertisement push notifications, or by e-mail. may be configured. Furthermore, it is also possible to send cookies to the computer that browses the advertisement, to acquire various information performed on the computer, and to acquire user attributes stored in the computer. As for the registration of user attributes, if there is a purchase of a product after push notification registration of an advertisement, it is also possible to register more detailed user attributes and use them as user attributes as well.

<Embodiment 23 Second Purchase Analysis Rule Holding Unit>
The ``Second purchase analysis rule storage unit'' analyzes external information, purchase history information, advertisement transmission history information, and behavior/life log information in association with user identification information from the viewpoint of understanding the purchase status. hold a second purchase analysis rule that is a rule for acquiring purchase status information through The second purchase analysis rule uses the behavior/life log information to generate information indicating how much the user is willing to purchase the specific product, indicating the distance between the user and the specific product. For example, in the behavior/life log, values are assigned to general behavior/life logs that can be taken as general behavior/life logs without specifying the user, and are stored in a database or the like in relation to the purchase of a specific product. Logs can be scored in relation to specific products. For example, if a specific car of Company T is a specific product, the behavior/life log of visiting the dealer of that car is given a high value, and the test drive of that car at that dealer is even higher. A value is attached. Values need not be assigned to all behavior/life logs in relation to specific products, and values may be assigned to some of them. Therefore, it is not necessary to design so that everything acquired as a user's behavior/life log has meaning in relation to a specific product. In addition, the relationship between the behavior/life logs of many or one user and the purchase history information of many or one user is calculated by artificial intelligence or the like, and attached to the behavior/life log stored in the database. It is conceivable to update the value given in relation to the specific product. Note that the calculation of this relationship may be analyzed for each user attribute.

<Embodiment 23 Second Purchasing Situation Information Analysis Acquisition Unit>
The ``second purchase purchase status information analysis/acquisition unit'' obtains external information associated with the user identification information, purchase history information, advertising transmission history information, behavior/life log information, and the same user identification information. Obtain purchase status information based on the primary purchase analysis rule associated with the . The function of the second purchase/purchase status information analysis/acquisition unit is the same as that of the first purchase/purchase/purchase status information analysis/acquisition unit shown in the twenty-second embodiment, and has already been described. It should be noted that how much the value calculated from the behavior/life log information is weighted to contribute to the value of the purchase status information depends on the design concept of the system.

<Embodiment 23 Hardware Configuration>
FIG. 64 is a diagram showing the hardware configuration of the twenty-third embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the twenty-third embodiment, the description of the programs that operate in common with the programs of the twenty-second embodiment will be omitted. A "second purchase behavior/life log information acquisition program" newly added in the present embodiment acquires behavior/life log information. The "second purchase purchase status analysis acquisition program" acquires purchase status information from external information, purchase history information, advertisement transmission history information, and behavior/life log information by analysis based on the second purchase analysis rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertisement transmission history information, behavior/life log information, second Purchasing analysis rules Purchasing status information, dialogue information, dialogue information selection rules for each user, selected dialogue information, various setting information such as communication (not shown), etc. referenced and used.

<Embodiment 23: Flow of processing>
FIG. 65 is a diagram illustrating an example of the flow of processing according to the twenty-second embodiment. As shown in this figure, a second purchase user identification information holding step (6501), a second purchase SNS user related information acquisition step (6502), a second purchase history information acquisition step (6503), a second purchase advertisement transmission history Information acquisition step (6504), second purchase behavior/life log information acquisition step (6505) for acquiring second purchase behavior/life log information, second purchase analysis rule retention step (6505), second purchase purchase status information analysis Acquisition step (6507), second purchase dialogue information storage step (6508), second purchase dialogue information selection rule retention step (6509), second purchase dialogue information selection step (6510), second purchase dialogue information output step (6511).

<Embodiment 24>
<Summary of Embodiment 24 Invention>
The interactive purchase promotion system of Embodiment 24 is characterized by having a function of judging the effectiveness of output interactive information in addition to the features described in Embodiment 22 or 23.

<Embodiment 24 Invention Configuration>
FIG. 66 is a diagram showing an example of the configuration of an interactive purchase promotion system according to Embodiment 23, which is dependent on Embodiment 22. FIG. As shown in FIG. 66, the interactive purchase promotion system of Embodiment 23 includes a first purchase user identification information storage unit (6601), a first purchase SNS user related information acquisition unit (6602), a first purchase history information acquisition unit (6603), 1st purchase promotional advertisement transmission information acquisition unit (6604), 1st purchase analysis rule storage unit (6605), 1st purchase purchase status information analysis acquisition unit (6606), 1st purchase dialogue information storage unit (6607) ), first purchase user-by-user dialogue information selection rule storage unit (6608), first purchase dialogue information selection unit (6609), first purchase dialogue information output unit (6610), purchase validity determination rule storage unit (6611), It consists of a purchase dialogue information effectiveness judgment unit (6612). In this embodiment, the description of the configuration common to the twenty-second or twenty-third embodiment will be omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 24 Configuration>
<Embodiment 24 Purchasing Effectiveness Judgment Rule Holding Unit>
The ``purchase validity determination rule storage unit'' stores a purchase validity determination rule that is a rule for determining whether dialogue information is effective based on purchase status information acquired with respect to output dialogue information. The purchase validity determination rule determines validity based on the purchase status information of the specific product related to the purchase status information that caused the selection of the output dialogue information. In particular, it is possible to estimate the effectiveness of the output dialogue information based on how the sense of distance from the specific product (strength of willingness to purchase the specific product) changes based on the purchase status information of the specific product. When a specific product is purchased based on dialogue information, the purchase history recorded in the purchase history information and the purchased information indicated in the purchase status information are the same information. The validity of the dialogue information may be determined based on this configuration, and this configuration is substantially included in the present embodiment.

The 'Purchase Effectiveness Judgment Rule' has a background purpose of how to improve or maintain the purchase situation based on the purchase situation information, and is dialogue information that has a positive impact to achieve the background purpose. It is a rule for judging the effectiveness of the relationship between dialogue information and a specific product from the viewpoint of whether or not there was. As with the interactive health promotion system and the interactive learning promotion system, the purchasing effectiveness judgment rule may be configured so that the effectiveness of the guiding dialogue and the evaluation of the user's negative reaction can be judged. Descriptions of guidance dialogues, evaluations of user's negative reactions, and personality types have already been made in the sixth embodiment. By judging the effectiveness of the guiding dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule or the never-give-up process. It is possible to enhance the system of dialogue methods such as being attacked by various means.

<Twenty-fourth Embodiment Purchase Dialogue Information Validity Determining Unit>
The ``purchase dialogue information validity determination unit'' determines the validity of the dialogue information based on the output dialogue information, the purchase status information obtained for this dialogue information, and the purchase dialogue information validity determination rule. . The validity of the interactive information is configured to be indicated by the value. The most effective cases are, for example, "when there is a purchase of a specific product" and "when there is a continuous purchase contract for a specific product". It may be rich in variety depending on the arithmetic logic. The expression format as a numerical value may be a numerical value with no upper limit, or the effectiveness may be expressed within a numerical range with upper and lower limits. Also, the validity value may be configured to take not only positive values but also negative values. This is the case where the dialogue information is counterproductive toward the purchase of a specific product. One example is a case where the value indicated by the purchase status information is lower than before the dialogue information is output. In place of or in addition to the purchase status information, purchase history information may be used to determine the validity of the dialogue information.

<Embodiment 24 Hardware Configuration>
FIG. 67 is a diagram showing the hardware configuration of the twenty-fourth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs that constitute the hardware of the twenty-fourth embodiment, the programs that operate in common with the twenty-second or twenty-third embodiment have already been explained, and the explanation thereof will be omitted. As a program added to this embodiment, a "purchase validity determination rule retention program" retains purchase validity determination rules. The "purchase dialogue information effectiveness judgment program" judges the effectiveness of the outputted dialogue information based on the purchase effectiveness judgment rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, first purchase analysis rule, purchase status Various setting information such as information, dialogue information, user dialogue information selection rules, selected dialogue information, purchase effectiveness judgment rules, purchase effectiveness judgment results, communication (not shown), etc. are held in non-volatile memory and loaded into main memory. It is referenced and used when executing a series of programs.

<Twenty-fourth Embodiment Processing Flow>
FIG. 68 is a diagram illustrating an example of the flow of processing according to the twenty-fourth embodiment. As shown in this figure, first purchasing user identification information holding step (6801), first purchasing SNS user related information acquisition step (6802), first purchase history information acquisition step (6803), first advertisement transmission history information Acquisition step (6804), first purchase analysis rule retention step (6805), first purchase purchase status information analysis acquisition step (6806), first purchase dialogue information accumulation step (6807), first purchase user-by-user dialogue information selection rule Holding step (6808), first purchase dialogue information selection step (6809), first purchase dialogue information output step (6810), purchase validity judgment rule holding step (6811) holding purchase validity judgment rule, purchase validity and a purchase dialogue information validity judgment step (6812) for judging the validity of the dialogue information based on judgment rules.

<Outline of Embodiment 25 Invention>
The interactive purchase promotion system of the twenty-fifth embodiment, in addition to the features described in the twenty-fourth embodiment, is characterized by performing statistical dialog information validity determination by statistical processing of big data.

<Embodiment 25 Invention Configuration>
FIG. 69 is a diagram showing an example of the configuration of the interactive purchase promotion system of the twenty-fifth embodiment. As shown in FIG. 69, the interactive purchase promotion system of the twenty-fifth embodiment includes a first purchase user identification information storage unit (6901), a first purchase SNS user related information acquisition unit (6902), a first purchase history information acquisition unit (6903), 1st advertising transmission history information acquisition unit (6904), 1st purchase analysis rule storage unit (6905), 1st purchase purchase status information analysis acquisition unit (6906), 1st purchase dialogue information storage unit (6907) ), first purchasing user-specific dialogue information selection rule storage unit (6908), first purchase dialogue information selection unit (6909), first purchase dialogue information output unit (6910), purchase validity judgment rule storage unit (6911), It consists of a purchase dialogue information effectiveness determination unit (6912), purchase effectiveness statistical processing rule holding means (6913), and statistical purchase dialogue information effectiveness information acquisition means (6914). In this embodiment, the description of the configuration common to the twenty-fourth embodiment is omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 25 Configuration>
<Embodiment 25 Purchasing Effectiveness Statistical Processing Rule Holding Means>
"Purchase effectiveness statistical processing rule holding means" holds purchase effectiveness statistical processing rules that are rules for statistically processing the effectiveness of interactive information of multiple users for each user attribute, which is partly common to the population. This is a means of the purchase dialogue information effectiveness judgment unit. The most representative example of "for each user attribute that is partially common to the population" is users who have a common user attribute that they want to promote the purchase of a specific product. This is because the effectiveness of dialogue information cannot be compared if there is no commonality among specific products. However, the products do not necessarily have to be exactly the same, as long as they have a certain degree of commonality. Specifically, it becomes a population consisting of users who have a common specific product with a purchase history, a common specific product with an advertisement sending history, or users who have a common user attribute. Therefore, the population may be divided into small groups by performing narrowing down on the condition that not only the specific product is common but also other user attributes are common. However, it is not always the case that each user has the same sense of distance to a specific product, that is, does not necessarily have the same purchase status (indicated by the purchase status information) at the time of statistical processing of purchase effectiveness. The processing is statistically processed including the past purchase status information of the population of users, the dialogue information output corresponding to the purchase status information, and changes in the purchase status information obtained as a result of outputting the dialogue information. In addition, if the validity judgment result including the past history is stored in association with the dialogue information, statistical processing of the effectiveness associated with the dialogue information is performed without obtaining the change of the purchase status information. may be configured. Further, the purchase history information may be used in place of or in addition to the purchase status information to statistically process the effectiveness of the dialogue information.

<Regarding purchase effectiveness statistical processing rules>
"Purchase Effectiveness Statistical Processing Rule" means a rule for acquiring the statistical effectiveness of certain dialogue information and a rule for determining the identity of dialogue information that differs for each user and is arranged according to user attributes. and consists of two. In addition, it is conceivable that the purchasing effectiveness statistical processing rule can be configured so that the statistical effectiveness can be determined also for the introductory dialogue and the evaluation of the user's negative reaction. The introductory dialogue information, evaluation of negative reactions, and description of personality types have been described in Embodiment 6 of the interactive health promotion system. By judging the effectiveness of the guidance dialogue and the evaluation of the user's negative reaction, it becomes possible to more accurately reflect the user's attributes in the above-mentioned never-give-up rule or the never-give-up process. It is possible to enhance the system of dialogue methods such as being attacked by various means.

The population can be further narrowed down according to the user attributes in the population of users who have purchase histories of specific products. For example, a user has an attribute of owning a product that can be substituted for a specific product. Statistical analysis according to further narrowed-down user attributes is also possible. In addition, the interactive information that has been statistically confirmed to be highly effective for users with specific attributes can be selected by the system actively or at the appropriate timing.

User attribute information is configured to be stored in a user attribute information storage unit or the like in association with user identification information. The user attribute information held in the attribute information holding unit may be updated. Furthermore, it may be configured such that a character diagnosis test, which will be described later, is performed regularly or irregularly (using character diagnosis dialogue information, etc.) to update this retained user attribute information. Furthermore, with respect to the user's personality that constitutes the initial user attribute information, a median value is assigned after each personality type is scored and held, or a questionnaire is given to the users and the questionnaire results are held. It is conceivable to configure so as to Further, the personality may be configured such that the conversation information of the SNS is analyzed by the conversation information analysis unit based on the conversation information analysis rule and the personality is determined. Since a huge amount of conversations with friends or the like is stored in SNS, it can be used effectively. Furthermore, it may be configured to analyze reading tendencies, movie taste tendencies, music tastes, hobbies, favorite celebrities and celebrities, etc., introduced on the SNS, and determine personality. Furthermore, it is possible to diagnose the character by analyzing the place where the user checked in, the photograph in which the user himself/herself is included or not, and the like. Check-in locations include commercial facilities (department stores, supermarkets, convenience stores, home appliance mass retailers, fast fashion, esthetic salons, beauty salons), entertainment facilities, stadiums, restaurants, museums, parks, stations, ports, airports, national parks, Personality can be analyzed in public parks, etc. For example, they are active, like shopping, quiet, and the like. Personality analysis can be performed based on whether there are many group photos, whether there are many photos of one person, whether there are many landscape photos, and whether there are many food photos. It should be noted that the personality analysis rule can be designed according to the design policy. In addition, it is also possible to analyze the user's character according to the character of a friend connected via SNS. The method for acquiring these pieces of user attribute information is the same as the method already described in the twenty-second and twenty-third embodiments.

<Embodiment 25 Purchasing Statistical Dialogue Information Effectiveness Information Acquisition Means>
'Purchase statistical dialogue information effectiveness information acquisition means' statistically obtains the effectiveness of dialogue information for at least a population based on the dialogue information of a plurality of users and the stored purchase effectiveness statistical processing rule. On the other hand, some of them are means possessed by a dialog information validity determination unit that acquires statistical dialog information validity information determined for each common user attribute. As described above, in this system, it is assumed that some attribute information of the user is held in association with the user identification information, and such attributes constitute the population, and the attributes are common. By summarizing the validity information of the dialogue information for each population, it is possible to acquire statistical purchasing dialogue information effectiveness information for each user attribute that is at least partially common to the population.

"Purchasing statistical dialogue information effectiveness information" means the effectiveness of dialogue (from low effectiveness to high effectiveness) according to user attributes, etc., as a result of statistical processing, and various dialogues with each effectiveness It is information that expresses the number of types of information as a function, and is generally normally distributed. In other words, the number of dialogue information with "medium" effectiveness is the largest (the types of dialogue information with average effectiveness are the largest), and the number of dialogue information with "high" and "low" effectiveness is a group of data distributed so that By using this data, it is possible to know what kind of conversational information exhibits how effective it is, and it can be used as a computer. It is more preferable that the purchase statistical dialogue information validity information is stored separately for each theme and purpose of using dialogue information, and a plurality of pieces of information exist for each theme and purpose of using dialogue information. FIG. 22 is one example of purchase statistical dialogue information validity information, and has already been described in the seventh embodiment.

<Twenty-fifth Embodiment Hardware Configuration>
FIG. 70 is a diagram showing the hardware configuration of the twenty-fifth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the twenty-fifth embodiment, the programs that operate in common with the twenty-fourth embodiment have already been explained, and the explanation thereof will be omitted. As a program added to this embodiment, a "purchase effectiveness statistical processing rule holding program" holds purchase effectiveness statistical processing rules. The ``purchase statistical dialogue information validity information acquisition program'' acquires purchase statistical dialogue information validity information based on the purchase validity statistical processing rule. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, first purchase analysis rule, purchase status Information, dialogue information, dialogue information selection rules for each user, selected dialogue information, purchase effectiveness judgment rules, purchase effectiveness judgment results, purchase effectiveness statistical processing rules, statistical dialogue information effectiveness information for purchases, communications (not shown), etc. is held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Twenty-fifth Embodiment Processing Flow>
FIG. 71 is a diagram illustrating an example of the flow of processing according to the twenty-fifth embodiment. As shown in this figure, first purchasing user identification information holding step (7101), first purchasing SNS user related information acquiring step (7102), first purchase history information acquiring step (7103), first advertising transmission history information Acquisition step (7104), first purchase analysis rule retention step (7105), first purchase purchase status information analysis acquisition step (7106), first purchase dialogue information accumulation step (7107), first purchase user-by-user dialogue information selection rule holding step (7108), first purchase dialogue information selection step (7109), first purchase dialogue information output step (7110), purchase validity judgment rule holding step (7111), purchase dialogue information validity judgment step (7112), Purchasing effectiveness statistical processing rule retention sub-step (7113) for retaining purchase effectiveness statistical processing rules, Purchase statistical dialogue information valid for obtaining purchasing statistical dialogue information effectiveness information based on purchase effectiveness statistical processing rules and a sexual information acquisition sub-step (7114).

<Embodiment 26>
<Outline of Embodiment 26 Invention>
The interactive purchase promotion system of the twenty-sixth embodiment, in addition to the features described in the twenty-fourth or twenty-fifth embodiment, is characterized by updating the user-by-user interactive information selection rule based on the purchase validity judgment result.

<Embodiment 26 Configuration of the Invention>
FIG. 72 is a diagram showing an example of the configuration of an interactive purchase promotion system according to the twenty-sixth embodiment. As shown in FIG. 72, the interactive purchase promotion system of Embodiment 26 includes a first purchase user identification information storage unit (7201), a first purchase SNS user related information acquisition unit (7202), a first purchase history information acquisition unit (7203), 1st advertising transmission history information acquisition unit (7204), 1st purchase purchase analysis rule storage unit (7205), 1st purchase status information analysis acquisition unit (7206), 1st purchase dialogue information storage unit (7207) ), first purchase user-by-user dialog information selection rule storage unit (7208), first purchase dialog information selection unit (7209), first purchase dialog information output unit (7210), purchase validity determination rule storage unit (7211), It consists of a purchase dialogue information effectiveness determination unit (7212) and a dialogue information selection rule update unit for each purchasing user (7213). In this embodiment, the description of the common configuration with the twenty-fourth or twenty-fifth embodiment will be omitted, and only the unique configuration of this embodiment will be described.

<Twenty-sixth Embodiment User-by-User Dialogue Information Selection Rule Update Unit>
The 'updating unit for purchasing user-specific dialogue information selection rule' updates the individual user-specific dialogue information selection rule held in the individual user-specific dialogue information selection rule holding unit based on the purchase validity determination result. Updating means updating the validity associated with interaction information on a per-user basis. As a result of the validity determination, if there is a change in the validity for each user that has been associated with the dialogue information, a process of associating it with the latest validity is performed. FIG. 25 is a diagram showing the function of the user-by-user dialogue information selection rule updating unit, and the outline has already been explained in the eighth embodiment. As a result, it is possible to select dialogue information that is more effective than before. This selection is also a process of changing the priority selection order of the dialogue information stored in the dialogue information storage units (including the first and second). The validity may be configured to be held according to the validity determined based on the purchase status information, the validity determined based on other response dialogue information, and the information based thereon. Furthermore, the effectiveness may be expressed as the frequency of selection as dialogue information, or the number of times of selection as dialogue information during guidance dialogue. Further, the effectiveness may be configured to be associated with the speaker's avatar or the speech style.

FIG. 73 is a conceptual diagram outlining the function of AI (artificial intelligence) for updating selection rules in the twenty-sixth embodiment. This interactive purchase promotion system holds user-by-user dialogue information selection rules that reflect individual characteristics. The individual characteristics of each user that are reflected here include the form of dialogue information, namely, the language used during conversation, the content of dialogue information corresponding to purchase status information, the timing of output of dialogue information, the output interval of dialogue information, and guidance. It will be reflected in the way dialogues are arranged, the process of not giving up (repeating dialogue information with the same intention), and the selection of avatars that output dialogue information. As shown in the figure, for user X (7301), when purchasing status information A (7302), rule 1 (7303) for selecting dialogue information "There is a promotional video here", purchase status information B (7304) ), rule 2 (7305) that selects dialogue information such as "Why don't you try driving?" Let's assume that rule 3 (7307) for selecting dialogue information "Yo!" is held as a user-by-user dialogue information selection rule. At this time, assuming that purchase status information D (7308) that has not been obtained in the past is acquired, user-specific dialogue information is selected by combining rules relating to purchase status information D and similar purchase status information. . In the example of this figure, since the purchase status information A and other numerical values are the same, except for the number of views, which is 4 different, the similar purchase status information is based on the purchase status information A. Is there anything?” is selected and output (7309). When purchase status information such as "I watched a promotional video but stopped in the middle" (7310) is acquired for the output dialogue information, it is recognized that the user acted in accordance with the dialogue information, but the contents of the purchase status information are obtained. was insufficient, and it is acknowledged that the desire to buy was not sufficiently stimulated and increased. Therefore, it is recognized that the effectiveness of the selected dialogue information was low, and 2 points are obtained as a result of determining the validity of purchase dialogue information (7311). In response to the purchase dialogue information validity determination result, when the purchase status information D is acquired, a new rule (7312 ), the updated user-specific dialogue information selection rule is obtained, and the user-specific dialogue information selection rule held in the user-specific dialogue information selection rule holding unit is updated.

<Twenty-sixth Embodiment Hardware Configuration>
FIG. 74 is a diagram showing the hardware configuration of the twenty-sixth embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the twenty-sixth embodiment, the programs that operate in common with the twenty-fourth or the twenty-fifth embodiment have already been explained, and the explanation thereof will be omitted. As a program added to the present embodiment, a "purchasing user-by-user dialog information selection rule update program" updates the user-by-user dialog information selection rule based on the purchase validity determination result. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, first purchase analysis rule, purchase status Information, dialog information, user-specific dialog information selection rules, selected dialog information, purchase validity determination rules, purchase validity determination results, updated user-specific dialog information selection rules, communications (not shown), and various other setting information are stored in non-volatile memory. , loaded into main memory, and referenced and used during a series of program executions.

<Twenty-sixth Embodiment Processing Flow>
FIG. 75 is a diagram illustrating an example of the flow of processing according to the twenty-sixth embodiment. As shown in this figure, first purchasing user identification information holding step (7501), first purchasing SNS user related information acquisition step (7502), first purchase history information acquisition step (7503), first advertisement transmission history information Acquisition step (7504), first purchase analysis rule retention step (7505), first purchase purchase status information analysis acquisition step (7506), first purchase dialogue information accumulation step (7507), first purchase user-by-user dialogue information selection rule holding step (7508), first purchase dialogue information selection step (7509), first purchase dialogue information output step (7510), purchase validity judgment rule holding step (7511), purchase dialogue information validity judgment step (7512), and an update step (7513) for purchasing user-specific dialogue information selection rule for updating the user-specific dialogue information selection rule based on the purchase validity judgment result.

<Embodiment 27>
<Outline of Embodiment 27 Invention>
The interactive purchase promotion system of the twenty-seventh embodiment has the features of the twenty-fifth embodiment or the twenty-sixth embodiment based on the twenty-fifth embodiment. It is characterized by updating the stored user-by-user interaction information selection rule.

<Embodiment 27 Configuration of the Invention>
FIG. 76 is a diagram showing an example of the configuration of an interactive purchase promotion system according to the twenty-seventh embodiment. As shown in FIG. 76, the interactive purchase promotion system of Embodiment 27 includes a first purchase user identification information storage unit (7601), a first purchase SNS user related information acquisition unit (7602), a first purchase history information acquisition unit (7603), first advertisement transmission history information acquisition unit (7604), first purchase analysis rule storage unit (7605), first purchase purchase status information analysis acquisition unit (7606), first purchase dialogue information storage unit (7607) ), first purchasing user-specific dialogue information selection rule storage unit (7608), first purchase dialogue information selection unit (7609), first purchase dialogue information output unit (7610), purchase validity determination rule storage unit (7611), Purchasing dialogue information validity determination unit (7612), purchase effectiveness statistical processing rule holding means (7613), purchase statistical dialogue information effectiveness information acquiring means (7614), purchase statistical user-by-user dialogue information selection rule updating unit (7615) ) and consists of In this embodiment, the description of the common configuration with the twenty-fifth embodiment or the twenty-sixth embodiment based on the twenty-fifth embodiment is omitted, and only the unique configuration of the present embodiment will be described.

<Embodiment 27 Purchasing Statistical User-by-User Dialogue Information Selection Rule Update Unit>
The ``purchase statistical user dialogue information selection rule update unit'' updates the user-specific dialogue information selection rule held in the user-specific dialogue information selection rule storage unit based on the acquired statistical purchase dialogue information effectiveness information. . The updating is basically the same as that of the twenty-sixth embodiment.

<Embodiment 27 Hardware Configuration>
FIG. 77 is a diagram showing the hardware configuration of the twenty-seventh embodiment. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. As shown in this figure, among the programs constituting the hardware of the twenty-seventh embodiment, the programs that operate in common with the twenty-fifth embodiment or the twenty-sixth embodiment based on the twenty-fifth embodiment have already been explained. omitted. As a program added to the present embodiment, a ``purchase statistical user dialogue information selection rule update program'' updates the user-specific dialogue information selection rule based on the statistical purchase dialogue information effectiveness information. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, first purchase analysis rule, purchase status Information, dialogue information, dialogue information selection rule for each user, selected dialogue information, purchase effectiveness judgment rule, purchase effectiveness judgment result, purchase effectiveness statistical processing rule, purchase statistical dialogue information effectiveness information, updated dialogue information for each user Various setting information such as selection rules and communication (not shown) are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Twenty-seventh Embodiment Processing Flow>
FIG. 78 is a diagram illustrating an example of the flow of processing according to the twenty-seventh embodiment. As shown in this figure, first purchasing user identification information holding step (7801), first purchasing SNS user related information acquiring step (7802), first purchase history information acquiring step (7803), first advertising transmission history information Acquisition step (7804), first purchase analysis rule retention step (7805), first purchase purchase situation information analysis acquisition step (7806), first purchase dialogue information storage step (7807), first purchase user-by-user dialogue information selection rule retention step (7808), first purchase dialogue information selection step (7809), first purchase dialogue information output step (7810), purchase validity judgment rule retention step (7811), purchase dialogue information validity judgment step (7812), Purchasing effectiveness statistical processing rule retention substep (7813), purchase statistical dialogue information effectiveness information acquisition substep (7814), updating user-by-user dialogue information selection rules based on the acquired statistical purchase dialogue information effectiveness information Purchasing Statistical User-by-User Dialogue Information Selection Rule Update Step (7815).

<Embodiment 28>
<Summary of Embodiment 28 Invention>
The twenty-eighth embodiment is an invention that describes the twenty-second embodiment in terms of a method, and basically expresses the category of the invention of the twenty-second embodiment as a method of operating a computer.

<Embodiment 28 Configuration of the Invention>
As shown in FIG. 80, the interactive learning promotion system of this embodiment includes a purchase SNS user-related information acquisition step (8001) for acquiring user SNS-related information, a purchase history information acquisition step (8002) for acquiring purchase history information. ), a purchase advertisement transmission history information acquisition step (8003) for acquiring advertisement transmission history information, purchase status information is obtained using the retained purchase analysis rules, external information, purchase history information, and advertisement transmission history information. Purchasing purchase situation information analysis acquisition step (8004), purchase dialogue information selection step (8005) for selecting dialogue information to be output based on dialogue information selection rules for each purchasing user, purchase dialogue information output for outputting the selected dialogue information and a step (8006).

<Embodiment 29>
<Outline of Embodiment 29 Invention>
The twenty-ninth embodiment is an invention that describes the twenty-second embodiment in terms of method, and basically expresses the category of the invention of the twenty-second embodiment as a computer operating program.

<Embodiment 29 Configuration of the Invention>
The configuration of the operation program of the interactive purchase promotion system shown in Embodiment 29 is the same as the configuration shown in FIG. Description of each configuration is omitted since it has already been described in the twenty-eighth embodiment.

<Embodiment 30>
The interactive purchase promotion system shown in the thirtieth embodiment, in addition to the features described in the twenty-second to twenty-seventh embodiments, is a user who has a history of transmitting advertisements for a specific product instead of a user who has a purchase history for the specific product. It is an interactive purchase promotion system that

<Embodiment 30>
<Overview of Embodiment 30>
The interactive purchase promotion system of the thirtieth embodiment uses purchase history information (including the case where there is no purchase history) and advertising transmission history information in addition to the user's remark information and browsing information on the SNS, so that the user's purchase To strengthen the user's purchase motivation by acquiring purchase status information indicating the heightened motivation for purchase and outputting to the SNS a dialogue that matches the purchase situation, which is the degree of the user's current motivation for purchase. With the goal. It is preferable that user attributes are stored in this system, and registration of user attributes of users who have only accessed advertisements is registered from the advertisement registration application web screen when registering for advertisement push notifications. Alternatively, it may be configured to register by e-mail. Furthermore, it is also possible to send a cookie to the computer that browses the advertisement, to acquire various information performed on the computer, and to acquire user attributes stored in the computer. As for the registration of user attributes, if there is a purchase of a product after push notification registration of an advertisement, it is also possible to register more detailed user attributes and use them as user attributes as well.

<Embodiment 30 Configuration of the Invention 1>
Configuration 1 of the invention of the interactive purchase promotion system of Embodiment 30 basically replaces the second of Embodiment 22, FIG. 60 with the third. The interactive purchase promotion system of the thirtieth embodiment includes a third purchase user identification information storage unit, a third purchase SNS user related information acquisition unit, a third purchase history information acquisition unit, a third purchase advertisement transmission history information acquisition unit, a third 3rd purchase analysis rule storage unit, 3rd purchase purchase status information analysis acquisition unit, 3rd purchase dialogue information storage unit, 3rd purchase user dialogue information selection rule storage unit, 3rd purchase dialogue information selection unit, 3rd purchase dialogue information and an output unit.

<Embodiment 30 Configuration of the Invention 2>
Configuration 2 of the interactive purchase promotion system of the thirtieth embodiment basically replaces the second of the twenty-third embodiment and FIG. 63 with the fourth. The interactive purchase promotion system of configuration 2 of the thirtieth embodiment of the invention includes a fourth purchase user identification information storage unit, a fourth purchase SNS user related information acquisition unit, a fourth purchase history information acquisition unit, and a fourth purchase advertisement transmission history Information Acquisition Unit, 4th Purchasing Behavior/Life Log Information Acquisition Unit, 4th Purchasing Analysis Rule Storage Unit, 4th Purchase Purchasing Status Information Analysis Acquisition Unit, 4th Purchasing Dialogue Information Storage Unit (4th Purchasing User Dialogue Information Selection It consists of a rule holding unit, a fourth purchase dialogue information selection unit, and a fourth purchase dialogue information output unit.

<Embodiment 30 Configuration of the Invention Others>
In addition to the configuration 1 of the invention and the configuration 2 of the invention described above, the additional configurations for the 22nd and 23rd embodiments described in the 24th, 25th, 26th, and 27th embodiments are similarly added. It may be an additional configuration.

<Description of Embodiment 30 Configuration>
<Embodiment 30 Third purchase user identification information holding unit Fourth purchase user identification information holding unit>
The 'holding unit for third purchasing user identification information and fourth purchasing user identification information holding unit' hold user identification information for identifying users who use SNS and have information on the transmission of advertisements for specific products. Other points are the same as those described in the first and second purchasing user identification information storage units.

<Embodiment 30 Other configurations>
Other configurations of the thirtieth embodiment are basically the same as those of any one of the twenty-second to twenty-seventh embodiments.

<Embodiment 31>
<Outline of Embodiment 31 Invention>
This embodiment is an invention related to an interactive learning promotion system. In addition to the features of the interactive learning promotion system described in Embodiments 12 to 16, the invention of this embodiment obtains the validity of the output dialogue information from the user's response dialogue information to the output dialogue information. It is characterized by

<Embodiment 31 Configuration of the Invention>
An example of the configuration of the interactive learning promotion system of Embodiment 31 is the configuration of Embodiment 12 shown in FIG. 36, the configuration of Embodiment 13 shown in FIG. 39, or the configuration of Embodiment 14 shown in FIG. is not an essential configuration), the configuration newly includes a learned response dialogue information acquisition unit, a learned response validity determination rule holding unit, and a learned response dialogue information validity determination unit. A description of the configuration common to any one of the twelfth to sixteenth embodiments will be omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 31 Configuration>
<Embodiment 31 Learning Response Dialogue Information Acquisition Unit>
The 'learned response dialogue information acquisition unit' acquires response dialogue information for the output dialogue information. The response dialogue information is information indicating the user's reaction to the dialogue information. For example, response dialogue information as character information output by the user through SNS, user learning behavior appearing in learning history information and learning effect information, response dialogue information by voice uttered by the user, life log information such as the user's heart rate and brain waves , and response dialogue information related to user behavior that can be incorporated into this system from GPS or other external information equipment. Furthermore, it is also possible to configure such that a question is issued to confirm which utterance (dialogue information) of this interactive learning promotion system the response dialogue information of the user is the response dialogue information. Not only actions and voices that can be recognized in a positive direction, but also the observation of no state such as silence, no reaction, ignoring, turning off the power, disconnecting communication, etc. Since it can be said that it is an appropriate response, it can be said that it is the user's response dialogue information. Since the response dialogue information is used to determine the effectiveness of the output dialogue information as described later, the output dialogue information Acquired in association with identification information is conceivable. Also, the response dialogue information itself can be included in the learning SNS user-related information, or can be included in the dialogue information accumulated in the dialogue information accumulation unit. Furthermore, since the response dialogue information directly expresses the user's individuality and dialogue style, it can be used for analysis of user attributes or stored as user attribute information.

This system is structured so that when the system outputs dialogue information, the user freely returns response dialogue information. The user's response dialogue information to the output dialogue information does not need to be acquired at a time close to each other, and it is possible that the user outputs response dialogue information to the output several days ago. Further, it is not necessary for the user's response dialogue information to be in a one-to-one relationship with the output dialogue information. In order to determine which of the output dialogue information the user has transmitted the response dialogue information, it is conceivable to associate the output dialogue information with the response dialogue information transmitted by the user until the next dialogue information is output. be done. Alternatively, the system can output advisory dialog information that encourages the user to take certain actions via an introductory dialog toward a background goal. This is because, as part of the interactive format, the user's preferred language, expression method, and conversation method can be considered. The user is made to recognize what kind of action is rational or effective to take today, and the user is advised to proceed with the action." In this case, starting with talking about the weather and giving advice on how to proceed is recognized as one story, recognized in units of output dialogue blocks, and a series of user response dialogues acquired in the process. It is conceivable that it is associated with information.

<Embodiment 31 Learning Response Validity Judgment Rule Holding Unit>
The ``learned response validity determination rule storage unit'' stores learned response validity determination rules for determining whether output dialogue information is effective based on response dialogue information acquired for output dialogue information. Hold. "Learning Response Validity Judgment Rule" is a rule that judges the effectiveness of the output dialogue information by judging whether the user acted and thought according to the dialogue information from the dialogue information including question utterances. be. This system judges the effectiveness of output dialogue information depending on whether the user's response to the dialogue information is positive or negative.

For example, as a method for judging the effectiveness of response dialogue information for output dialogue information, the types of expressions that can be judged as positive responses (e.g., statements that show willingness, statements that accept, statements that , goal-setting remarks, etc.) and types of expressions that can be judged as negative reactions (refusal expressions, unmotivated expressions, excuses, negative remarks, postponed remarks, no reaction (unread and read) (including all cases), etc.), and depending on the case, there is a method of classifying into one or more validity judgment types of neutral expression types (for example, seasonal greetings, small talk, onomatopoeia, etc.). The number of classification types and the number of categories can be set based on the system operation policy.

The process of classifying the obtained response dialogue information into each type may be performed at the acquisition stage of the learned response dialogue information acquisition unit, or may be performed according to the learned response effectiveness judgment rule held by the learned response effectiveness judgment rule holding unit. It can be the content. In either configuration, in order to distribute the response dialog information as shown below to the validity judgment types, it is necessary to judge the identity of the response dialog information and the validity judgment types. will have. In the following description, it is assumed that acquired dialogue information is classified into each type by the learning response validity determination rule holding unit.

The learned response dialogue information validity determination rule is composed of at least two rules, a rule for determining the semantic content of the response dialogue information and a rule for judging the validity of output dialogue information. Furthermore, a case where a rule for classifying the semantic content of response dialogue information into validity judgment types is provided independently, and a rule for classifying the semantic content of response dialogue information into the effectiveness judgment type are provided independently. It may be configured to be included in either a rule for determining the contents or a rule for judging the validity of the output dialogue information.

User response dialogue information is issued by the user and cannot be managed and controlled by the system, so what words are used, what expressions are used, and in what dialogue format has not been determined. For example, to convey the fact that "I don't want to study", various expressions such as "I'm tired of studying", "I really hate it", "Don't be stupid", "I refuse", "I'm sorry", "I'm kidding", etc. can be used. A rule for specifying that these expressions are all "negative expressions" is a rule for determining the meaning of the response dialogue information. The manner and breadth of this semantic content category can be set based on the operating policy of the system. The width may also be configured to be hierarchically selectable. As a hierarchical structure, for example, the top level is the semantic content of the user's response dialogue, and the lower level is the expression when directly expressed. It is conceivable that there are words, equivalent words, and imperative forms of expression, and that there are various expressions in dialects, etc. below them, and that there are various indirect expressions (euphemisms, metaphors, etc.) below them. For example, using the above example, ``I will not do'' is acquired as various indirect expressions, and since no special processing has been done as an expression method for dialects, etc., it falls under the standard word ``I do not do''. As a basic expression in standard Japanese, it corresponds to the polite language of "Ishimasu", and as a direct expression, it corresponds to the expression of "Yaranai". As the semantic content of the response dialog, the semantic content of "does not comply with the output dialog information" is determined. The above is the rule for determining the semantic content of the user's response dialogue information. Furthermore, from the semantic content of the user's response dialogue information that does not follow the output dialogue information, it is considered that the output dialogue information is "negative expression" in the above example, and it is classified as a negative type. Belonging is confirmed.

As the effectiveness judgment rule, for example, for each element of the effectiveness judgment type, an evaluation value of the strength of the reaction on the effectiveness judgment type to the user's dialogue information is calculated. A method of comprehensively acquiring the validity determination result from the evaluation value is conceivable. As a method of measuring the strength of the reaction in the validity judgment type, a method of calculating points by assigning points in advance to options at various stages selected in identity determination and making a comprehensive judgment on the points is conceivable. . As for the points given to the options of these various stages, a method of giving general numerical values and a method of giving different points to each user reflecting user attributes are conceivable. Alternatively, it is conceivable to vary the weighting of various levels for each user when calculating the strength of reaction on the effectiveness judgment pattern. The numerical value of the strength of the reaction on the effectiveness judgment type acquired in this way becomes the effectiveness judgment result. In addition, when it corresponds to the type of neutral expression, the information for judging the effectiveness is insufficient, and the judgment result may be that the effectiveness cannot be judged.

In addition, since one piece of response dialogue information may contain expressions that should be classified into multiple types, a certain response dialogue information may contain multiple effectiveness judgment types and the strength of reactions on the effectiveness judgment types. It is conceivable to obtain an evaluation value of the degree of sturdiness. In this case, the effectiveness judgment result is calculated from the acquired evaluation values of the degree of reaction strength in the plurality of effectiveness judgment types. At this time, check points such as the use of conjunctions such as "but", "but", and "as expected", the structure of the entire statement such as the first and second sentences, and the structure of the sentence such as the beginning and end of the sentence. A configuration is conceivable in which the utterances included in one piece of response dialogue information are determined and ranked, such as main utterances and secondary utterances. Depending on the rank, different weighting may be applied when calculating the validity determination result. The difference in weighting by rank can be a common value depending on the system, or can be set differently for each user according to user attributes.

In addition, the expression in the above example is an expression that is used in situations other than when you do not want to study. For example, when outputting dialogue information recommending that a user who usually studies for two hours should stop studying and go to sleep because he/she seems to be in poor physical condition, "I hate it," "Don't be silly," "No," and "Don't be silly." Some of the above examples of expressions, such as, are expressions that express "willing to continue studying". In this case, in the sense that the response dialogue information is not followed, it can be considered as a simple judgment that a negative expression is judged as an effectiveness judgment type. However, in relation to the background purpose of this interactive learning promotion system of making learning a habit, it is also possible to judge that the student has a regular habit of studying. In this way, in relation to the background purpose, there may be situations in which it is contradictory whether or not to follow the dialogue information. is also possible. First, after the semantic content of the user's response dialogue information is determined, it is classified whether the output dialogue information encourages behavior that objectively matches the background purpose or encourages behavior that does not objectively match. do. Here, objectively meeting the background purpose means promoting formal and regular study behavior. Background To be objectively inconsistent means not to formally encourage regular study behavior. If the activity is consistent with the background purpose, the evaluation value of the degree of strength of the reaction in judging the validity of the background purpose, which is the same as the effectiveness judgment type of the semantic content of the response dialogue information. will be obtained. On the other hand, if the output dialogue information encourages an action that does not match the background purpose, the effectiveness of the semantic content of the response dialogue information will be reversed in terms of positive and negative responses in judging the effectiveness of the background purpose. An evaluation value of the degree of strength is obtained.

When judging effectiveness, including the relationship with the background purpose, it is necessary to comprehensively judge the evaluation value of the strength of the response in the effectiveness judgment type and the degree of the strength of the reaction in the judgment of the effectiveness of the background purpose. Become. These two factors may be weighted differently in the determination. The difference in weighting may be commonly set in the system, or may be different according to user attributes. For example, for a user who often gets sick from working too hard, it is desirable to have good study habits that do not make him sick. Since it is important, the strength of the reaction in determining the effectiveness of the background purpose is emphasized, and the evaluation value of the degree of the strength of the reaction in the effectiveness judgment type: the strength of the reaction in the judgment of the effectiveness of the background purpose It is conceivable that the evaluation value of the degree of is set to 2 to 3. Alternatively, for users who usually make excuses and hardly study, it is important to practice the behavior of the day even if it is a little unreasonable. It is conceivable that the evaluation value of the degree of the strength of the reaction in the effectiveness judgment type: the evaluation value of the degree of the strength of the reaction in the judgment of the effectiveness of the background purpose is 3 to 2. .

Furthermore, since there may be a discrepancy between the response dialogue information and the actual learning behavior, it is also beneficial to use learning history information and learning effect information as information that assists the response dialogue information in judging the effectiveness of the dialogue information. is. In other words, although the response dialogue information is sending the meaning content of "I will do it soon", the history information of learning is not acquired in the learning history information, or the answer is appropriate as a learning result It is a case where only the actual situation can be seen. In such a case, it means that false response dialogue information has been output. For example, it should be treated as a statement classified into negative validity judgment types such as "negative statement" and "refusal statement". Therefore, in such a case, it is required to determine the degree of agreement or contradiction between the user's learning history information or learning effect information and the response dialogue information. The determination of matching with the response dialogue information is made by determining whether or not the semantic content of the output dialogue information matches with the learning history information or learning effect information. This judgment can be made by comparing the evaluation value of the strength of the reaction on the validity judgment type of the response dialogue information. As a method of obtaining an evaluation value of the degree of strength of reaction on the same effective ridge judgment type as the response dialogue information from the learning history information and the learning effect information, the above-mentioned learning effectiveness judgment rule and / and learning history effectiveness A method of calculating using a value calculated by a rule similar to the judgment rule is conceivable.

<Embodiment 31 Learning Response Dialogue Information Validity Judging Unit>
The ``learned response dialogue information validity determination unit'' determines the validity of the dialogue information based on the output dialogue information, the response dialogue information obtained for this dialogue information, and the learning response validity determination rule. . It is conceivable that the user and this interactive learning promotion system output dialogue information and acquire response dialogue information a plurality of times until the user is allowed to perform a certain learning action. The effectiveness of the output dialogue may be evaluated for a series of dialogue chunks for executing a certain action, or for each dialogue on a one-to-one basis. and may be determined by both. In order to stimulate the user's motivation, this interactive learning promotion system sets a goal of making the user perform a certain action, and repeats multiple approaches as part of a dialog format according to the user's attributes until the goal is achieved. It is possible to have a no-give-up rule or/and a no-give-up rule as described above. If the user needs to be persuaded, it is conceivable to repeat the same thing over and over and output dialogue information that explains the rationality of the action. If so, it will output dialogue information requesting actions in various ways. Therefore, the system can recognize a series of phrases from starting a conversation with a certain goal to finally obtaining a result of realizing or not realizing the goal.

<Embodiment 31 Hardware Configuration>
The hardware configuration of Embodiment 31 is the configuration of Embodiment 12 shown in FIG. 37, the configuration of Embodiment 13 shown in FIG. 40, or the configuration of Embodiment 14 shown in FIG. ) is the basis. A description of a program that operates in common with any one of the twelfth to sixteenth embodiments will be omitted. The "learned response dialogue information acquisition program" newly added in this embodiment acquires the user's response dialogue information corresponding to the output dialogue information. The "learned response validity determination rule retention program" retains learned response validity determination rules. The ``learned response dialogue information validity determination program'' determines the validity of the output dialogue information based on the learned response validity determination rule. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, response dialogue information, learning response effectiveness judgment rules, learned response effectiveness judgment results, communication (not shown), and various other setting information are held in a non-volatile memory and stored in a main memory. , and referenced and used during a series of program executions.

<Flow of Embodiment 31 Processing>
An example of the processing flow of the interactive learning promotion system of Embodiment 31 is the configuration of Embodiment 12 shown in FIG. 38, the configuration of Embodiment 13 shown in FIG. 41, or the configuration of Embodiment 14 shown in FIG. part is not an essential configuration.) is based on the flow of processing. A description of steps for performing information processing common to the twelfth to sixteenth embodiments will be omitted. As steps newly added in this embodiment, a response dialogue information obtaining step for obtaining response dialogue information for the output dialogue information, a learned response validity determination rule retaining step for retaining learned response validity determination rules, and a learning response valid and a learning response dialogue information effectiveness judgment step for judging effectiveness of the outputted dialogue information based on the gender judgment rule.

<Embodiment 32>
<Embodiment 32 Outline of Invention>
This embodiment is an invention related to an interactive learning promotion system. In addition to the features of the interactive learning promotion system described in Embodiments 12 to 16, the invention of this embodiment statistically processes the effectiveness of output dialogue information obtained based on response dialogue information. and learning response statistical dialogue information validity information acquisition means for acquiring learning response statistical dialogue information validity.

<Embodiment 32 Configuration of the Invention>
An example of the configuration of the interactive learning promotion system of Embodiment 32 is the configuration of Embodiment 12 shown in FIG. 36, the configuration of Embodiment 13 shown in FIG. 39, or the configuration of Embodiment 14 shown in FIG. It is not an essential configuration.) is the basis. A description of the configuration common to any one of the twelfth to sixteenth embodiments is omitted. The components newly added in this embodiment are learning response effectiveness statistical processing rule holding means and learning response statistical dialogue information effectiveness information acquisition means.

<Description of Embodiment 32 Configuration>
<Embodiment 32 Learning Response Effectiveness Statistical Processing Rule Holding Means>
The ``learning response effectiveness statistical processing rule holding means'' is a means possessed by the learning response dialogue information effectiveness judging section, and stores the effectiveness of the dialogue information of a plurality of users for the population, with some of the user attributes being common. It holds learning response effectiveness statistical processing rules, which are rules for statistical processing for each response. Basically, the effectiveness of the statistical processing described in the seventeenth embodiment is determined using response dialogue information, and response dialogue information is used instead of learning effect information and learning history information. Others are common.

<Embodiment 32 Learning Response Statistical Dialogue Information Effectiveness Information Acquisition Means>
The ``learned response statistical dialogue information effectiveness information obtaining means'' statistically obtains at least the effectiveness of the dialogue information based on the dialogue information of a plurality of users and the stored learned response effectiveness statistical processing rule. It is a means possessed by the learning response dialogue information effectiveness judgment unit for obtaining learning response statistical dialogue information effectiveness information judged for each user attribute that is partially common to the group.

<Embodiment 32 Hardware Configuration>
The hardware configuration of the thirty-second embodiment is the configuration of the twelfth embodiment shown in FIG. 37, the configuration of the thirteenth embodiment shown in FIG. 40, or the fourteenth embodiment shown in FIG. ) is the basis. A description of a program that operates in common with any one of the twelfth to sixteenth embodiments will be omitted. A program newly added in the present embodiment, the “learned response statistical processing rule holding program” holds learned response statistical processing rules. The "learned response statistical dialogue information validity information acquisition program" acquires learned response statistical dialogue information validity information based on the learned response statistical processing rule. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-specific dialogue information selection rule, selected dialogue information, response dialogue information, learned response effectiveness determination rule, learned response effectiveness determination result, learned response statistical processing rule, learned response statistical dialogue information effectiveness information, communication (not shown) Various setting information such as .

<Embodiment 32 Flow of processing>
An example of the processing flow of the interactive learning promotion system of Embodiment 32 is the configuration of Embodiment 12 shown in FIG. 38, the configuration of Embodiment 13 shown in FIG. 41, or the configuration of Embodiment 14 shown in FIG. part is not an essential configuration.) is based on the flow of processing. A description of steps for performing information processing common to any one of the twelfth to sixteenth embodiments will be omitted. As steps newly added in this embodiment, a learning response effectiveness statistical processing rule holding substep for holding a learned response effectiveness statistical processing rule, and a learned response statistical dialogue information validity and a learning response statistical interaction information validity information obtaining substep of obtaining information.

<Embodiment 33>
<Embodiment 33 Outline of Invention>
Embodiment 33 is an invention relating to an interactive learning promotion system. In addition to the feature of the invention of Embodiment 31 or 32, it is characterized in that the user-by-user dialogue information selection rule is changed based on the learned response dialogue information effectiveness determination result.

<Embodiment 33 Configuration of the Invention>
An example of the configuration of the interactive facilitation system of Embodiment 33 is based on the configuration of Embodiment 31 or Embodiment 32. A description of the configuration common to the 31st or 32nd embodiment is omitted. The configuration newly added in the present embodiment is a learning response user-by-user interaction information selection rule update unit.

<Description of Embodiment 33 Configuration>
<Embodiment 33 Learning Response User-Specific Dialogue Information Selection Rule Update Unit>
The ``learning response user-specific dialogue information selection rule update unit'' updates the user-specific dialogue information selection rule holding unit based on the determination result of the learning response dialogue information validity determination unit according to the 32nd embodiment. Update interaction information selection rules. Dialogue information with relatively low effectiveness reduces the probability of being selected and the situations in which it is selected (if the dialogue information is associated with the hierarchical structure of the acquired learning , etc.), and if the effectiveness is relatively high, the opposite process is performed. The processing is basically the same as that of the eighteenth embodiment, except that the response dialogue information is used.

<Embodiment 33 Hardware Configuration>
The hardware configuration of the thirty-third embodiment is based on the hardware configuration of the thirty-first or thirty-second embodiment. A description of a program that operates in common with the 31st or 32nd embodiment will be omitted. A new program added in the present embodiment, “learning response user-specific dialogue information selection rule update program” updates the user-specific dialogue information selection rule based on the validity determination result. The present invention can basically be configured with a general-purpose computer, a program, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, response dialogue information, learning response effectiveness judgment rules, learned response effectiveness judgment results, updated user-by-user dialogue information selection rules, communication (not shown), and various other setting information are non-volatile. stored in the physical memory, loaded into the main memory, and referenced and used during the execution of a series of programs.

<Embodiment 33 Flow of processing>
An example of the processing flow of the interactive learning promotion system of Embodiment 33 is based on the processing flow of Embodiment 31 or Embodiment 32. A description of steps for performing information processing common to the 31st or 32nd embodiment is omitted. As a step newly added in this embodiment, there is provided a learning response user-by-user interaction information selection rule update step for updating the user-by-user interaction information selection rule based on the validity determination result.

<Embodiment 34>
<Outline of Embodiment 34 Invention>
Embodiment 34 is an invention relating to an interactive learning promotion system. In addition to the features of Embodiment 32 or Embodiment 33 based on Embodiment 32, learning response statistical user-specific dialogue information for updating user-specific dialogue information selection rules based on learning response statistical dialogue information validity determination information It is characterized by having a selection rule updating unit.

<Embodiment 34 Configuration of the Invention>
An example of the configuration of the interactive learning promotion system of Embodiment 34 is based on Embodiment 32 or Embodiment 33 based on Embodiment 32. A description of the configuration common to the 32nd embodiment or the 33rd embodiment based on the 32nd embodiment is omitted. The configuration newly added in this embodiment is a learning response statistical user interaction information selection rule updating unit.

<Embodiment 34 Learning Response Statistical User-by-User Dialogue Information Selection Rule Update Unit>
The function of the ``learned response statistical user dialogue information selection rule update unit'' is to update the user-divided dialogue information selection rule based on the learned response statistical dialogue information effectiveness information of the thirty-second embodiment. Regarding updating, the same processing as already described is performed. The processing is basically the same as that of the nineteenth embodiment except that the response dialogue information is used.

<Thirty-fourth Embodiment Hardware Configuration>
The hardware configuration of the thirty-fourth embodiment is based on the hardware configuration of the thirty-second embodiment or the thirty-third embodiment based on the thirty-second embodiment. A description of the program that operates in common with the 32nd embodiment or the 33rd embodiment dependent on the 32nd embodiment will be omitted. A program newly added in the present embodiment, "learned response statistical user interaction information selection rule update program" updates the user individual interaction information selection rule based on the learned response statistical interaction information effectiveness information. The present invention can basically be configured with a general-purpose computer, a program, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), learning history information, learning effect information, learning analysis rules, learning status information, and dialogue information. , Dialogue information selection rule for each user, Selected dialogue information, Response dialogue information, Learning response effectiveness judgment rule, Learning response effectiveness judgment result, Learning response statistical processing rule, Learning response statistical dialogue information effectiveness information, Update by user Dialogue information selection rules, various setting information such as communication (not shown), etc. are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Thirty-fourth Embodiment Processing Flow>
An example of the processing flow of the interactive learning promotion system of the thirty-fourth embodiment is based on the hardware configuration of the thirty-second embodiment or the thirty-third embodiment based on the thirty-second embodiment. The description of the steps for performing common information processing with the 32nd embodiment or the 33rd embodiment based on the 32nd embodiment will be omitted. As a step newly added in this embodiment, there is a step of updating the learning response statistical user interaction information selection rule for updating the individual user interaction information selection rule based on the learning response statistical interaction information effectiveness information.

<Embodiment 35>
<Outline of Embodiment 35 Invention>
Embodiment 35 is an invention relating to an interactive purchase promotion system. In addition to the features of the invention described in the twenty-second to twenty-fourth embodiments, a purchase response dialogue information acquisition unit and a purchase response validity determination rule for judging the validity of the dialogue information output based on the user's response dialogue information It is characterized by having a holding section and a purchasing response dialogue information validity judgment section.

<Embodiment 35 Configuration of the Invention>
An example of the configuration of the interactive purchase promotion system of the thirty-fifth embodiment is based on the configuration of the twenty-second embodiment shown in FIG. 60 or the configuration of the twenty-third embodiment shown in FIG. This configuration newly includes a rule holding section and a purchasing response dialogue information effectiveness judgment section. A description of the configuration common to any one of the twenty-second to twenty-fourth embodiments will be omitted, and only the configuration unique to this embodiment will be described.

<Description of Embodiment 35 Configuration>
<Embodiment 35 Purchasing Response Dialogue Information Acquisition Unit>
The 'purchase response dialogue information acquisition unit' acquires response dialogue information for the output dialogue information. The response dialogue information is information indicating the user's reaction to the dialogue information. For example, text information output by the user through SNS, pictograms and picture stamps output by the user, voice response, moving images, still images, behavior / life log information (for example, user's heart rate and brain waves, GPS and other external information equipment (information related to user behavior that can be incorporated into this system), and the like. The user's awareness is not limited to actions and voices that can be recognized in a positive direction, but also observation of a state of nothingness such as silence, no response, ignoring, turning off the power, and disconnecting communication. Since it can be said that it is an appropriate response, it can be said that it is the user's response dialogue information. Since the response dialogue information is used to determine the effectiveness of the output dialogue information as described later, the output dialogue information Acquired in association with identification information is conceivable. Further, the response dialogue information itself can be included in the purchasing SNS user-related information, or can be included in the dialogue information accumulated in the dialogue information accumulation unit. Furthermore, since the response dialogue information directly expresses the user's individuality and dialogue format, it can be used for analysis of user attributes or stored as user attribute information. This system is structured so that when the system outputs dialogue information, the user freely returns response dialogue information. This point is the same as that described in the thirtieth embodiment.

<Embodiment 35 Purchasing Response Validity Judgment Rule Holding Unit>
The ``learned response validity determination rule storage unit'' stores a purchase response validity determination rule that is a rule for determining whether dialogue information is effective based on response dialogue information acquired with respect to output dialogue information. "Purchase Response Validity Judgment Rule" judges from the dialogue information whether the user has taken the intended action based on the dialogue information and whether the intended concept has been formed by the user, and judges the effectiveness of the output dialogue information. It's a rule. User's response to the output dialogue information Output dialogue information for purchase of a specific product depending on whether the dialogue information is a positive reaction in relation to the specific product or a negative reaction in relation to the specific product It is a system for judging effectiveness.

For example, as a method of judging the effectiveness of response dialogue information for dialogue information output to a user for purchasing a specific product, the type of expression that can be judged as a positive response in relation to the specific product (e.g. , remarks of acceptance, remarks of agreement, remarks of positive proposal, remarks of setting goals, etc.) and types of expressions that can be judged as negative reactions in relation to specific products (expressions of refusal, expressions of lack of motivation, excuses, etc.) , negative remarks, postponing remarks, no response (including both unread and read cases), and in some cases neutral expressions (for example, seasonal greetings, small talk, onomatopoeia, etc.) A method of classifying into one or more validity judgment types is conceivable. The number of classification types and the number of categories can be set based on the system operation policy.

The process of classifying the acquired response dialogue information into each type may be performed at the stage of acquisition by the purchase response dialogue information acquisition unit, or may be performed in the purchase response validity judgment rule stored in the purchase response validity judgment rule holding unit. It can be the content. In either configuration, in order to distribute the response dialog information as shown below to the validity judgment types, it is necessary to judge the identity of the response dialog information and the validity judgment types. will have. In the following description, it is assumed that the purchase response validity determination rule storage unit classifies acquired dialogue information into each type.

The purchase response dialogue information validity judgment rule consists of at least two rules: a rule for determining the meaning and contents of the response dialogue information, and a rule for judging the effectiveness of the dialogue information output for the purchase of a specific product. be done. Furthermore, there are cases where rules for classifying the semantic content of response dialogue information into effectiveness judgment types in relation to specific products are independently provided, and where the semantic content of response dialogue information is classified into effectiveness judgment types in relation to specific products. It is conceivable that the rule for classifying into 2 is included in either the rule for determining the semantic content of the response dialogue information or the rule for judging the validity of the output dialogue information. The details of the validity determination rule are the same as those described in the thirtieth embodiment.

<Embodiment 35 Purchase Response Dialogue Information Effectiveness Determination Unit>
The "purchase response dialogue information validity determination unit" judges the validity of the dialogue information based on the output dialogue information, the response dialogue information obtained for this dialogue information, and the purchase response dialogue validity determination rule. The specific contents are the same as those of the 31st embodiment.

<Thirty-fifth Embodiment Hardware Configuration>
The hardware configuration of the thirty-fifth embodiment is based on the configuration of the twenty-second embodiment shown in FIG. 61 or the configuration of the twenty-third embodiment shown in FIG. A description of a program that operates in common with any one of the twenty-second to twenty-fourth embodiments will be omitted. The "purchase response dialogue information acquisition program" newly added in this embodiment acquires user response dialogue information corresponding to the output dialogue information. The "purchase response validity determination rule retention program" retains purchase response validity determination rules. The 'purchase response dialog information validity determination program' determines the validity of the output dialog information based on the purchase response validity determination rule. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, advertising transmission history information, purchase analysis rules, purchase status information, Dialogue information, dialogue information selection rules for each user, selected dialogue information, response dialogue information, purchase response effectiveness determination rules, purchase response effectiveness determination results, communication (not shown), and various other setting information are held in a non-volatile memory. It is loaded into the main memory and referenced and used during a series of program executions.

<Thirty-fifth Embodiment Processing Flow>
An example of the processing flow of the interactive purchase promotion system of Embodiment 35 is based on the configuration of Embodiment 22 shown in FIG. 62 or the configuration of Embodiment 23 shown in FIG. A description of steps for performing information processing common to the twenty-second to twenty-fourth embodiments will be omitted. The steps newly added in this embodiment include a purchase response dialogue information acquisition step for acquiring user response dialogue information to the output dialogue information, a purchase response validity judgment rule retention step for holding purchase response validity judgment rules, and a and a purchasing response dialogue information validity judging step for judging the validity of the outputted dialogue information based on a response validity judging rule.

<Embodiment 36>
<Outline of Embodiment 36 Invention>
This embodiment is an invention relating to an interactive purchase promotion system. In addition to the features of the interactive purchase promotion system described in Embodiments 22 to 24, the invention of this embodiment statistically processes the effectiveness of dialogue information output based on response dialogue information. It is characterized by having purchase response effective processing rule holding means and purchase response statistical dialogue information effectiveness information obtaining means for obtaining purchase response statistical dialogue information effectiveness information.

<Embodiment 36 Configuration of the Invention>
An example of the configuration of the interactive purchase promotion system of Embodiment 36 is based on the configuration of Embodiment 22 shown in FIG. 60 or the configuration of Embodiment 23 shown in FIG. A description of the configuration common to any one of the twenty-second to twenty-fourth embodiments is omitted. The configuration newly added in this embodiment is purchase response effectiveness statistical processing rule holding means and purchase response statistical dialogue information effectiveness information acquisition means.

<Description of Embodiment 36 Configuration>
<Embodiment 36 Purchasing Response Effectiveness Statistical Processing Rule Holding Means>
"Purchase response effectiveness statistical processing rule holding means" is a purchase response effectiveness statistical processing rule that is a rule for statistically processing the effectiveness of dialogue information of multiple users for each user attribute that is partially common to the population. is means possessed by the purchase response dialogue information validity determination unit that holds . The details are the same as those described in the twenty-fifth embodiment, except that the response dialogue information is used.

<Embodiment 36 Purchasing Statistical Dialogue Information Effectiveness Information Acquisition Means>
'Purchase statistical dialogue information effectiveness information acquisition means' statistically obtains the effectiveness of dialogue information for at least a population based on the dialogue information of a plurality of users and the stored purchase effectiveness statistical processing rule. On the other hand, some of them are means possessed by a dialog information validity determination unit that acquires statistical dialog information validity information determined for each common user attribute. This is the same as the twenty-fifth embodiment except that response dialogue information is used.

<Thirty-sixth Embodiment Hardware Configuration>
The hardware configuration of the thirty-sixth embodiment is based on the configuration of the twenty-second embodiment shown in FIG. 61 or the configuration of the twenty-third embodiment shown in FIG. A description of a program that operates in common with any one of the twenty-second to twenty-fourth embodiments will be omitted. A program newly added in this embodiment, the "purchase response statistical processing rule retention program", retains purchase response statistical processing rules. The "purchase response statistical dialogue information validity information acquisition program" acquires purchase response statistical dialogue information validity information based on the purchase response statistical processing rule. As shown in this figure, the present invention can basically be configured with a general-purpose computer, programs, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, purchase effect information, purchase analysis rules, purchase status information, and dialogue information. , dialogue information selection rule for each user, selected dialogue information, response dialogue information, purchase response effectiveness judgment rule, purchase response effectiveness judgment result, purchase response statistical processing rule, purchase response statistical dialogue information effectiveness information, communication (not shown) Various setting information and the like are held in a nonvolatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Thirty-sixth Embodiment Processing Flow>
An example of the processing flow of the interactive purchase promotion system of Embodiment 36 is based on the configuration of Embodiment 22 shown in FIG. 62 or the configuration of Embodiment 23 shown in FIG. A description of steps for performing information processing common to the twelfth to sixteenth embodiments will be omitted. As steps newly added in this embodiment, a purchase response effectiveness statistical processing rule holding substep for holding the purchase response effectiveness statistical processing rule, and a purchase response statistical dialogue information effectiveness and a purchasing response statistical interaction information validity information obtaining substep of obtaining information.

<Embodiment 37>
<Outline of Embodiment 37 Invention>
Embodiment 37 is an invention relating to an interactive purchase promotion system. In addition to the features of the thirty-fifth or thirty-sixth embodiment, this invention is characterized by changing the user-by-user dialogue information selection rule based on the purchase response dialogue information validity determination result.

<Embodiment 37 Configuration of the Invention>
The configuration of the interactive facilitation system of the thirty-seventh embodiment is based on the configuration of the thirty-fifth or thirty-sixth embodiment, and further includes an updating unit for selecting interactive information for each purchase response user. A description of the configuration common to the thirty-fifth or thirty-sixth embodiment is omitted.

<Description of Embodiment 37 Configuration>
A characteristic configuration of this embodiment is a purchase response user-by-user interaction information selection rule update unit. This part updates the purchasing response user-specific interaction information selection rule using the effectiveness of the user-specific response interaction information when the thirty-fifth embodiment is used as the basis. When the thirty-sixth embodiment is used as a basis, the purchasing response user-by-user information selection rule is updated based on the purchase response statistical dialogue information effectiveness information. The basic processing is the same as that of the twenty-sixth embodiment except that the response dialogue information is used.

<Embodiment 37 Hardware Configuration>
The hardware configuration of the thirty-seventh embodiment is based on the thirty-fifth or thirty-sixth embodiment. A description of a program that operates in common with the thirty-fifth or thirty-sixth embodiment will be omitted. A program newly added in the present embodiment, "Purchase Response User-Specific Dialogue Information Selection Rule Update Program" updates the user-specific dialogue information selection rule based on validity information. The present invention can basically be configured with a general-purpose computer, a program, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, purchase effect information, purchase analysis rules, purchase status information, and dialogue information. , user-by-user dialogue information selection rules, selected dialogue information, response dialogue information, purchase response effectiveness judgment rules, purchase response effectiveness judgment results, updated user-by-user dialogue information selection rules, communications (not shown), and various other setting information are non-volatile. stored in the physical memory, loaded into the main memory, and referenced and used during the execution of a series of programs.

<Thirty-seventh Embodiment Processing Flow>
An example of the processing flow of the interactive purchase promotion system of the thirty-seventh embodiment is based on the processing flow of the thirty-fifth or thirty-sixth embodiment. A description of steps for performing information processing common to the thirty-fifth or thirty-sixth embodiment will be omitted. As a step newly added in this embodiment, there is a purchase response user-specific dialogue information selection rule update step for updating the user-specific dialogue information based on the validity determination result.
<Embodiment 38>
<Outline of Embodiment 38 Invention>
Embodiment 38 is an invention relating to an interactive purchase promotion system. In addition to the features of Embodiment 36 or Embodiment 37 based on Embodiment 36, purchase response statistical user interaction information for updating user-specific interaction information selection rules based on purchase response statistical interaction information validity determination information It is characterized by having a selection rule updating unit.

<Embodiment 38 Configuration of the Invention>
An example of the configuration of the interactive purchase promotion system of the thirty-eighth embodiment is based on the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment. A description of the configuration common to either the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment will be omitted. A configuration newly added in the present embodiment is a purchase response statistical user interaction information selection rule update unit.

<Embodiment 38 Purchasing Response Statistical User-by-User Dialogue Information Selection Rule Update Unit>
The ``purchase response statistical dialogue information selection rule updating unit'' updates the user-specific dialogue information based on the purchase response statistical dialogue information validity information acquired by the purchase response statistical dialogue information validity information acquiring means of the thirty-sixth embodiment. Update information selection rules. This is the same as the thirty-seventh embodiment except that response dialogue information is used.

<Embodiment 38 Hardware Configuration>
The hardware configuration of the thirty-eighth embodiment is based on the hardware configuration of the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment. A description of a program that operates in common with the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment will be omitted. A program newly added in the present embodiment, "Purchase Response Statistical User-Specific Dialogue Information Selection Rule Update Program" updates the user-specific dialogue information selection rule based on purchase response statistical dialogue information effectiveness information. The present invention can basically be configured with a general-purpose computer, a program, and various devices. The operation of a computer basically takes the form of loading programs and data recorded in a non-volatile memory into a main memory and executing processes with the main memory, a CPU, and various devices. Communication with the device is performed through an interface connected to the bus line. The more detailed operation of the program implements the operation described in the description of each configuration, so please refer to that for details. These programs are executed sequentially or constantly based on a series of program execution instructions copied from the nonvolatile memory to the main memory. The data includes user identification information (user attribute information associated with this in some cases), external information (including SNS user-related information), purchase history information, purchase effect information, purchase analysis rules, purchase status information, and dialogue information. , dialog information selection rule by user, selected dialog information, response dialog information, purchase response effectiveness judgment rule, purchase response effectiveness judgment result, purchase response statistical processing rule, purchase response statistical dialogue information effectiveness information, update by user Dialogue information selection rules, various setting information such as communication (not shown), etc. are held in a non-volatile memory, loaded into the main memory, and referenced and used when executing a series of programs.

<Thirty-eighth embodiment processing flow>
An example of the processing flow of the interactive purchase promotion system of the thirty-eighth embodiment is based on the processing flow of the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment. A description of steps for performing information processing common to the thirty-sixth embodiment or the thirty-seventh embodiment based on the thirty-sixth embodiment will be omitted. As a step newly added in this embodiment, there is a purchase response statistical dialog information selection rule update step for updating the user-specific dialog information selection rule based on the purchase response statistical dialog information effectiveness information.

<Embodiment 39>
<Outline of Embodiment 39 Invention>
This system attempts to interactively promote the purchase of a specific product by targeting users who have a history of transmitting advertisements for a specific product instead of users who have a history of purchasing a specific product. It is basically the same as the 35th to 38th embodiments.

<Embodiment 39 Configuration of the Invention>
The invention is basically the same as the inventions shown in the thirty-fifth to thirty-eighth embodiments, and the description thereof is omitted.

It is possible to suggest the direction of user's behavior by interactive communication, and it is possible to show an effective function in all human activities that depend on individual activities. For example, health management apps, learning promotion apps, sales promotion systems, nursing care robots, monitoring systems, employment management, configuration programs in welfare facilities, driving skill promotion programs, mental stability programs for users of long-distance transportation such as airplanes and bullet trains, It can be used for the mental care system of disaster victims, the management of the communication environment through the Internet, and so on.

0201 interactive health promotion system 0202 user 0203 SNS user-related information 0207 interaction information 3501 interactive learning promotion system 3502 user 3503 SNS user-related information 3505 learning system 3508 interaction information 5901 interactive purchase promotion system 5902 user 5903 SNS user-related information 5907 interaction information

Claims (12)

User identification information that identifies a user who uses SNS and has a purchase history of a specific product, including name, address, telephone number, email address, ID specially set by the user, date of birth, occupation, age, and gender , user's physical information related to health (for example, height, weight, average body temperature, average pulse rate, average breathing rate, average heart rate, average amount of exercise (time, quality, mode, etc.), gym a first purchase user identification information holding unit that holds one or more of (presence or absence of regular visits) associated with one or more; A first purchase SNS user-related information acquisition unit for acquiring user-related information as external information; an acquisition unit, a first purchase advertisement transmission history information acquisition unit that acquires, in association with user identification information, advertisement transmission history information that is a transmission history of the advertisement of the specific product that the user may have come into contact with, and a user A first purchase that is a rule for acquiring purchase status information by analyzing external information, purchase history information, and advertising transmission history information in association with identification information from the viewpoint of grasping the purchase status of the specific product. A first purchase analysis rule holding unit holding analysis rules, acquired external information associated with user identification information, purchase history information, advertising transmission history information, and a second purchase analysis rule associated with the same user identification information A first purchase purchase status information analysis acquisition unit that acquires purchase status information based on one purchase analysis rule, and a first purchase that accumulates dialogue information to be transmitted according to the purchase status information acquired in association with user identification information A dialogue information storage unit, and dialogue information selection by first purchasing user holding dialogue information selection rules for each user, which are rules associated with user identification information for selecting accumulated dialogue information based on acquired purchase status information. Based on the rule storage unit, the acquired purchase status information, and the stored user-by-user dialogue information selection rule, dialogue information in a dialogue format suited to the characteristics of each user is selected from the first purchase dialogue information storage unit. An interactive purchase promotion system comprising: a first purchase dialogue information selection unit; and a first purchase dialogue information output unit for outputting the selected dialogue information to a user identified by user identification information via the SNS. . User identification information that identifies a user who uses SNS and has a purchase history of a specific product, including name, address, telephone number, email address, ID specially set by the user, date of birth, occupation, age, and gender , user's physical information related to health (for example, height, weight, average body temperature, average pulse rate, average breathing rate, average heart rate, average amount of exercise (time, quality, mode, etc.), gym a second purchasing user identification information holding unit that holds one or more of (presence or absence of frequent visits) associated with one or more; A second purchase SNS user-related information acquisition unit that acquires user-related information as external information, and second purchase history information that acquires purchase history information that is information indicating the purchase history of the user's specific product in association with user identification information. an acquisition unit, a second purchase advertisement transmission history information acquisition unit that acquires, in association with user identification information, advertisement transmission history information that is a transmission history of advertisements for the specific product that the user may have come into contact with, and a user A second purchase behavior/life log information acquisition unit that acquires behavior/life log information that is information indicating a user's behavior and/or life log in association with identification information; external information in association with user identification information; Holds a second purchase analysis rule that is a rule for acquiring purchase status information by analyzing information, advertisement transmission history information, and behavior/life log information from the viewpoint of understanding the purchase status of the above-mentioned specific product. the second purchase analysis rule holding unit, the acquired external information associated with the user identification information, the purchase history information, the advertising transmission history information, the behavior/life log information, and the same user identification information associated with A second purchase purchase status information analysis acquisition unit that acquires purchase status information based on a second purchase analysis rule that is set, and dialogue information that should be transmitted according to the purchase status information acquired in association with user identification information is accumulated. A second purchase dialogue information storage unit, and a second purchase user-by-purchase user holding a dialogue information selection rule for each user, which is a rule associated with user identification information for selecting accumulated dialogue information based on the acquired purchase status information A second purchase dialogue information storage unit stores dialogue information in a dialogue format suited to the characteristics of each user based on the dialogue information selection rule storage unit and the acquired purchase status information and the stored user-by-user dialogue information selection rule. and a second purchase dialogue information output unit for outputting the selected dialogue information to the user identified by the user identification information via the SNS. Purchase promotion system. A purchase effectiveness judgment rule storage unit that holds a purchase effectiveness judgment rule that is a rule for judging whether dialogue information is effective based on purchase status information acquired for output dialogue information, and output dialogue information and a purchase dialogue information effectiveness judgment unit for judging effectiveness of the dialogue information based on the purchase status information acquired for the dialogue information and the purchase effectiveness judgment rule. 3. The interactive purchase promotion system according to 2. The purchase dialogue information validity determination unit stores a purchase effectiveness statistical processing rule that is a rule for statistically processing the effectiveness of dialogue information of a plurality of users for each user attribute that is partially common to a population. Based on the validity statistical processing rule holding means, the interaction information of a plurality of users, and the held purchase effectiveness statistical processing rule, statistically at least part of the effectiveness of the interaction information for the population 4. The interactive purchase promotion system according to claim 3, further comprising purchase statistical dialogue information validity information acquiring means for acquiring statistical purchase dialogue information validity information determined for each common user attribute. Purchasing user-specific dialogue for updating the user-specific dialogue information selection rule held in the purchasing user-specific dialogue information selection rule holding unit (which may be the first or second) based on the judgment result of the purchase dialogue information effectiveness judging unit 5. The interactive purchase promotion system according to claim 3, further comprising an information selection rule update section. Based on the acquired statistical purchase dialogue information validity information, the user-specific dialogue information selection rule held in the purchasing user-specific dialogue information selection rule holding unit (which may be the first or second purchase user-specific dialogue information selection rule) is updated. 6. An interactive purchase promotion system according to claim 4 or claim 5 depending on claim 4, further comprising an interactive information selection rule updating unit. 7. The interactive purchase promotion system according to claim 1, wherein a user having a history of transmitting advertisements for a specific product is used instead of a user having a purchase history for the specific product. A purchase response dialogue information acquisition unit that acquires response dialogue information for the output dialogue information, and a purchase response validity judgment rule that is a rule for judging whether the response dialogue information acquired for the output dialogue information is effective. The validity of the dialogue information is judged based on the stored purchase response validity determination rule storage section, the output dialogue information, the response dialogue information acquired for this dialogue information, and the purchase response validity determination rule. 4. The interactive purchase promotion system according to claim 1, further comprising a purchase response dialogue information effectiveness judgment unit. A purchase response dialogue information acquisition unit that acquires response dialogue information for the output dialogue information, and a purchase response validity judgment rule that is a rule for judging whether the response dialogue information acquired for the output dialogue information is effective. The validity of the dialogue information is judged based on the stored purchase response validity determination rule storage unit, the output dialogue information, the response dialogue information acquired for this dialogue information, and the purchase response validity determination rule. a purchase response dialogue information effectiveness judgment unit, and the purchase response dialogue information effectiveness judgment unit statistically processes the effectiveness of the dialogue information of a plurality of users for a population, partly for each common user attribute. Based on the purchase response effectiveness statistical processing rule holding means for holding the purchase response effectiveness statistical processing rule, which is a rule to purchase response statistical dialogue information effectiveness information acquisition means for acquiring purchase response statistical dialogue information effectiveness information in which effectiveness of dialogue information is determined for at least a population at least partly for each common user attribute; 4. An interactive purchase promotion system according to claim 1, further comprising: Purchasing response user who updates the user-specific dialogue information selection rule held in the purchasing user-specific dialogue information selection rule holding unit (which may be the first or second) based on the judgment result in the purchase response dialogue information effectiveness judging unit 10. An interactive purchase promotion system according to claim 8 or 9 , further comprising an updater for another dialogue information selection rule. Based on the acquired purchase response statistical dialogue information validity information, purchase response statistical 11. The interactive purchase promotion system according to claim 9 or claim 10 depending on claim 9 , further comprising a user-by-user interactive information selection rule updating unit. 12. The interactive purchase promotion system according to claim 8 to claim 11 , wherein a user having a history of transmitting advertisements for a specific product instead of a user having a history of purchasing the specific product.

Images