JP6540224B2 - Processing program, processing method and processing apparatus - Google Patents

Description

  The present invention relates to a processing program, a processing method, and a processing apparatus.

  The continuous use of devices and services can be said to be a necessary element for any information and communication technology (ICT). For example, even in an application (for example, a recommendation application or the like) that shows information to the user based on information on the user, it is very important to have the user continuously use it.

  For users using such applications, information is based on excessive personal information etc. in applications where “social distance”, which means sense of feeling close to the service (sense of distance from the mind), etc. If it is presented, the application may be disgusted and may disappoint use.

  For this reason, if it is possible to provide information that matches the social distance between the user and the application, a friendly relationship between the user and the application can be established and maintained. In the related art, there is known a technique for showing social distance as a numerical value by executing a questionnaire or the like for hearing from the user the social distance felt by the user with a plurality of question items (for example, Non-Patent Document 1) Etc.).

Yonnim Lee, Ohbyung Kwon, Intimacy, familiarity and continuity intention: An extended expectation-confirmation model in web-based services, Electronic Commerce Research and Applications 10, 2011.

  However, when a questionnaire or the like is performed to determine the perspective of the social distance between the user and the application, it takes time and effort to create a questionnaire, enter an answer, and the like.

  In one aspect, the present invention aims to provide a processing program, a processing method, and a processing apparatus capable of determining the perspective of social distance felt by a user with respect to an application, a device, and the like.

In one aspect, the processing program causes the computer to determine, based on the data collected by the first information collection device, the first information regarding the state or feeling of the user not apparent from the external observation in a certain time zone And second information related to the state or feeling of the user apparent from the external observation in the certain time zone, which is determined based on data collected by a second information collecting device different from the first information collecting device. And the first storage unit storing the first information and the second information indicates the state or the feeling of the user indicated by the second information in the same time zone. A function of specifying a time zone, a function of presenting to the user a question asking the condition or feeling of the user in the specified time zone, and the user Said user answered said question based on at least one of data collected by said first information collecting device and data collected by said second information collecting device while answering said question The function of determining the condition or feeling of the user at the same time as the determined condition or feeling of the user is common to the condition or feeling of the user indicated by the first information in the specified time zone In this case, it is a program for realizing a function of judging that the social distance between the user and the reply destination is closer than in the case where they are not common .

  It is possible to determine the perspective of the social distance that the user feels to the application, device, etc.

It is a figure showing roughly the composition of the information presentation system concerning a 1st embodiment. It is a figure which shows the utilization condition of the information presentation system of FIG. FIG. 3A is a diagram showing a hardware configuration of the information processing terminal, and FIG. 3B is a diagram showing a hardware configuration of a server. It is a functional block diagram of each part of an information presentation system. It is a flowchart which shows the user effect determination and recording process which concerns on 1st Embodiment. FIG. 6 (a) shows a skin conduction data record DB, and FIG. 6 (b) shows a moving image data record DB. Fig.7 (a) is a figure which shows audio | voice data recording DB, FIG.7 (b) is a figure which shows action log DB. It is a figure which shows the personal information level definition of an action log. It is a figure which shows user effect log DB which concerns on 1st Embodiment. It is a figure which shows the correspondence of a personal information level and a self-disclosure level. FIG. 11A is a diagram showing personal information level definition of the effect determination API, and FIG. 11B is a diagram showing an action log type used for effect determination and the effect determination API definition. It is a flowchart which shows the social distance calculation process which concerns on 1st Embodiment. FIG. 13 (a) is a diagram showing a question sentence generation template list, and FIG. 13 (b) is a diagram showing an effect determination API definition used for response analysis. It is a figure which shows social distance DB. It is a figure showing roughly the composition of the information presentation system concerning a 2nd embodiment. It is a figure which shows the utilization condition of the information presentation system of FIG. It is a flow chart which shows user effect judging and recording processing concerning a 2nd embodiment. It is a figure which shows user effect log DB which concerns on 2nd Embodiment. It is a flowchart which shows the social distance calculation process which concerns on 2nd Embodiment. It is a flowchart which shows the social distance calculation process which concerns on 3rd Embodiment. It is a figure which shows user effect log DB which concerns on 3rd Embodiment. It is a flowchart which shows the social distance calculation process which concerns on 4th Embodiment. It is a figure which shows the utilization condition of the information presentation system which concerns on 5th Embodiment. It is a figure showing eye gaze data record DB. It is a flowchart which shows the social distance calculation process which concerns on 5th Embodiment. It is a figure which shows user effect log DB which concerns on 5th Embodiment. It is a figure which shows user effect log DB which concerns on 7th Embodiment.

First Embodiment
Hereinafter, a first embodiment of the information providing system will be described in detail based on FIGS. 1 to 14. FIG. 1 schematically shows the configuration of an information providing system 100 according to the first embodiment.

  In the first embodiment, “society, which is originally a word meaning the distance between the mind of a person and another group, is a word that represents the distance of the mind between a person and a machine, a service, an application, etc. Target distance shall be used. This social distance, like the sense of distance between people, is fostered through the background and process of past communication. The information providing system 100 according to the first embodiment determines the perspective of the social distance with the application based on the user's answer to the question generated from the user's action or state. In addition, the information providing system 100 controls information provided from the application to the user based on the distance between the determined social distance.

  In the first embodiment, “personal information level” (Not Observable / Observable) shown in FIG. 10 is used as a classification of information related to the user. "Not observable" means information of a portion which can not be observed from the surface of the user (information which can not be recognized by external observation), and includes, for example, the amount of skin electrical activity, the detection result of the line of sight, "Observable" means information of a part that can be known by anyone from the observation of the surface of the user (information understood by external observation), for example, moving image data and audio data acquired by a small video recorder or microphone included.

  Also, in the first embodiment, the “self-disclosure level” (Not Superficial level) shown in FIG. 10 is used as a classification related to the disclosure of the user's state or feeling determined to be a user effect using information classified by each personal information level. / Superficial) is used. "Not Superficial" means self-disclosure (disclosure of one's condition / feeling that is not known to others) that extends to the core of the person's personality and can not be observed from the surface. Also, "Superficial" means self-disclosure about the superficial part of the person (disclosure of one's own state / feeling that anyone can know from observation of the surface). As shown in FIG. 10, personal information levels "Not Observable" and "Observable" correspond to self-disclosure levels "Not Superficial" and "Superficial". A description of the personal information level "Observable (conv)" and the self-disclosure level "Superficial (intimate)" shown in FIG. 10 will be described later.

  Here, it is assumed that the information providing system 100 of the first embodiment is a system in which the guidance given is different for each individual while the user A walks in the building as shown in FIG. As shown in FIG. 1 and FIG. 2, the information providing system 100 includes an information processing terminal 10, information collection devices 20 and 120, an information presentation device 110, and a server 30 as a processing device. Each device included in the information providing system 100 is connected to a wireless communication line, a network 80 such as the Internet. The information providing system 100 according to the first embodiment includes an information processing apparatus (information processing terminal 10, information collecting apparatus 20, 120, information presentation apparatus 110) on the side (user side) where client software is arranged, server software The information processing apparatus (server 30) on the side where the above is arranged is a system that divides and implements the entire processing.

  In the following, presentation to the user realized by the client software means presentation of information according to the user. Also, information collected by the client software from the user is stored in the system in association with the user. That is, the device implementing the client software is access controlled by the client software or server software. Therefore, information collection and information presentation are performed on the assumption that the user A is confirmed by client software or server software.

  The information processing terminal 10 is a terminal on which client software designed for a user is arranged, and is, for example, a guidance board type information terminal as shown in FIG. The information processing terminal 10 may be, for example, a mobile phone, a smartphone, a tablet terminal, a wearable mobile terminal, a PC (Personal Computer), or the like.

  The hardware configuration of the information processing terminal 10 is shown in FIG. As shown in FIG. 3A, the information processing terminal 10 includes a central processing unit (CPU) 90, a read only memory (ROM) 92, a random access memory (RAM) 94, and a storage unit (here, a hard disk drive (HDD). ), Network interface 97, display unit 93, input unit 95, portable storage medium drive 99, and the like. The display unit 93 includes a liquid crystal display and the like, and the input unit 95 includes a touch panel and the like. The components of the information processing terminal 10 are connected to a bus 98. The CPU 90 executes the program stored in the ROM 92 or the HDD 96 or the program read by the portable storage medium drive 99 from the portable storage medium 91 to display the information processing unit 12 shown in FIG. Act as

  The information presentation unit 12 presents information to the user. Note that the information presentation unit 12 may perform information presentation by voice or the like via a speaker in addition to information presentation by an image (display on the display unit 93). The type of information presentation to the user depends on the specifications of the information presentation unit 12 (such as the size of the display unit 93 and the allowable file type of the speaker). That is, in the information processing terminal 10, information collection and information presentation are performed on the assumption that the interface used for information presentation is confirmed. The information presentation unit 12 of the information processing terminal 10 presents the information of the application C2 on the display unit 93.

  The information collecting device 20 is, for example, a wrist band type device attached to an arm as shown in FIG. As the information collection device 20, a hair band type device or the like may be employed instead of the wrist band type device. The information collection device 20 includes an information collection unit 22 that collects skin conduction data (skin electrical activity value), and transmits the information to the information processing terminal 10 via the network 80. The technology related to skin electroactivity values can be found in “affdex, Q sensor (skin electrical activity (EDA) sensor), http://qsensor-support.affectiva.com/, http://assistly-production.s3.amazonaws.com /168567/kb_article_attachments/30856/Q_User_Manual_20130329_original.pdf?AWSAccessKeyId=AKIAJNSFWOZ6ZS23BMKQ&Expires=1406699351&Signature=4lXmsO4t6XH%2FKG345KDHAHGoDc%3D&response-content-h. There is.

  The information collection device 120 is a small video recorder installed in a building as shown in FIG. The information collecting apparatus 120 includes an information collecting unit 122 that acquires moving image data, and transmits the acquired moving image data to the server 30.

  The data collected by the information collecting unit 22 122 is not limited to the above, and data for deriving a user reaction, such as voice, a biological signal, an electroencephalogram, etc., can be adopted. Depending on the data, a plurality of pieces of intermediate information for deriving a user reaction may be extracted from data of one type of sensor. For example, in the case of a user-recorded video, information on the change in facial expression can be extracted by focusing on the face part, and information on posture change of the user with respect to the information collecting apparatus 120 can be extracted by focusing on the change in face size.

  The information presentation apparatus 110 includes, for example, a projector and a speaker, and includes an information presentation unit 112 that presents information to a user in a building. The information presentation unit 112 presents information on the assumption that the information presentation interface is confirmed to be a screen or a speaker. The information presentation unit 112 of the information presentation device 110 presents the information of the application C1 on a screen or the like.

  The server 30 is an information processing apparatus in which server software is arranged, aggregates user data, arranges the data, and performs storage, sorting, and various calculations. In addition, the server 30 simultaneously manages content distribution, including control of the presentation form of content to be distributed to the user.

  Here, in the first embodiment, the server 30 makes a short utterance from the user to a question from the machine or the service as to how much social distance the user is in contact with the machine or the service. The determination is made based on whether or not the user teaches "other people's own state / feelings not known".

  The hardware configuration of the server 30 is shown in FIG. As illustrated in FIG. 3B, the server 30 includes a CPU 190, a ROM 192, a RAM 194, a storage unit (such as an HDD) 196, a network interface 197, a portable storage medium drive 199, and the like. The components of the server 30 are connected to a bus 198. The CPU 190 executes a program (including a processing program) stored in the ROM 192 or the HDD 196, or a program (including a processing program) read by the portable storage medium drive 199 from the portable storage medium 191, 30 functions as each part of FIG. Specifically, when the CPU 190 executes a program, the server 30 functions as an information presentation processing control unit 34 as a processing unit, a data management unit 36, and a social distance calculation unit 38. In addition, the function as a determination part, a determination part acquisition part, and a production | generation part is implement | achieved including the social distance calculation part 38. FIG.

  The information presentation process control unit 34 controls the information presentation by the information presentation unit 12, 112. Specifically, based on the calculation result of the social distance calculation unit 38, the information presentation processing control unit 34 controls (differentifies) the information to be presented from the information presentation unit 12, 112 to the user. The content is distributed from the server 30 to the information processing terminal 10 and the information presentation device 110. However, not limited to this, the information processing terminal 10 or the information presentation apparatus 110 may receive external content and present it to the user.

  The data management unit 36 receives the information collected by the information collection devices 20 and 120 (the information collection units 22 and 122), and manages the information in the skin conduction data recording DB 40, the moving image data recording DB 42, and the sound data recording DB 44.

  The social distance calculation unit 38 is based on the information managed by the data management unit 36 (the information stored in the DBs 40, 42, 44, etc.), the distance between the user and the social distance between applications, devices, services, etc. calculate. The social distance calculation unit 38 transmits information on the calculated distance of the social distance to the information presentation processing control unit 34.

  In addition, the detail of each DB which the server 30 has is mentioned later.

  In the information processing terminal 10, the server 30, etc., there may be cases where a plurality of users (or zero users) may be allocated on one device, or a plurality of software on one device. A system may be stored. That is, server software and client software may be implemented on one device. Also, for example, the functions of one software system may be distributed to a plurality of devices, such as, for example, partial functions or partial data separated on other devices. Conversely, the functions represented as a plurality of devices may be realized by one device.

  In the first embodiment, there is a possibility that a plurality of individual services manage user information in relation to display history data and external cooperation data managed on the system in association with the user. For this reason, data corresponding to one user managed on the system may be stored in association with different user IDs. In this case, by associating the user IDs with each other, data linked to different user IDs can be used as data of one user.

(Processing by server 30)
The server 30 executes “user effect determination” that determines the state or feeling of the user from the information transmitted from the information collection units 22 and 122 of the information collection devices 20 and 120 (user effect determination and recording processing). Also, the server 30 generates a question for the user based on the result of the user effect determination, and calculates the perspective of the social distance based on the answer from the user to the question (social distance calculation processing). Further, the server 30 presents, to the information processing terminal 10, information according to the calculated distance of the social distance (information presentation processing). Each processing will be described below.

(1) User Effect Determination / Recording Process Hereinafter, the user effect determination / recording process by the server 30 will be described with reference to the flowchart of FIG. It is assumed that the user A is using the information processing terminal 10 as a premise of this process. In this case, the user A who is also a user of the information processing unit 10 and the information presentation units 12 and 112 of the information presentation apparatus 110 is the information of the application C2 presented on the display unit 93, the information of the application C1 presented on the screen, etc. Shall be used. In addition, skin conduction data and moving image data of the user A who is also a user of the information collection devices 20 and 120 are collected by the information collection devices 20 and 120 (the information collection units 22 and 122) while the user is inside the building. Shall be

  In this case, the skin conduction data and the moving image data collected by the information collection units 22 and 122 of the information collection devices 20 and 120 are collected by the information collection units 22 and 122 once. Then, the data collected once is transmitted from the information collection units 22 and 122 to the information presentation processing control unit 34 of the server 30 at an appropriate timing.

  In addition, the process of FIG. 5 shall be implemented at the timing in which the server 30 received the data more than fixed amount from the information gathering apparatus 20,120. However, not limited to this, the server 30 may periodically perform the process of FIG. 5 at predetermined time intervals.

  In the process of FIG. 5, first, in step S10, the data management unit 36 receives sensor input information (skin conduction data and moving image data). The data management unit 36 also records sensor input information in the skin conduction data recording DB 40 (FIG. 6A) and the moving image data recording DB 42 (FIG. 6B) together with time stamp information.

  Here, FIG. 6 (a) shows the data structure of the skin conduction data recording DB 40, and FIG. 6 (b) shows the data structure of the moving image data recording DB 42. The skin conduction data recording DB 40, as shown in FIG. 6A, includes fields of "DB recording time", "sensor recording time", "user name", "information collection device ID", and "skin electrical activity value". Have. Among them, the field of “DB recording time” stores information (time stamp) of the date and time when the data is recorded in the skin conduction data recording DB 40, and the field of “sensor recording time” A time stamp of the added skin conduction data acquisition time is stored. Further, identification information (name and the like) of the user is stored in the field of “user name”, and identification information of the information collection device which has collected skin conduction data (FIG. In 6 (a), the symbols used in FIG. 4 are stored. The field of “skin electrical activity value” stores specific numerical values of skin conduction data. In the present embodiment, the code “20” given to the information collecting apparatus 20 in FIG. 4 is stored in the field “information collecting apparatus ID”.

  On the other hand, as shown in FIG. 6B, the moving image data record DB 42 is "DB record time", "Sensor record start time", "Sensor record end time", "User name", "Information collecting device ID" , “Moving image data recording file URI” fields. Information (time stamp) of the recording start date and time of audio data is stored in the field of "sensor recording start time", and information (time stamp) of recording end date and time of audio data is stored in the field of "sensor recording end time" Is stored. For the other fields, data similar to the corresponding fields possessed by the skin conduction data recording DB 40 are stored. 6B, the code "120" assigned to the information collecting apparatus 120 in FIG. 4 is stored as the information collecting apparatus ID. Further, in the field of “moving image data recording file URI”, a URI (Uniform Resource Identifier) indicating the recording location of the moving image data file is stored.

  The sensor input information may include voice data obtained from a microphone installed in the building. When the data management unit 36 acquires voice data, the data management unit 36 stores the acquired voice data in a voice data recording DB 44 as shown in FIG. 7A. The voice data recording DB 44 has fields of “DB recording time”, “sensor recording start time”, “sensor recording end time”, “user name”, “information collection device ID”, and “voice data recording file URI”. . The respective fields are the same as the moving image data recording DB 42, and therefore the description thereof is omitted. In the field of “information collection device ID” in FIG. 7A, the ID of the microphone (actually, a numerical value, a character or the like) is stored.

  Returning to FIG. 5, in the next step S12, the data management unit 36 creates a user's action log based on the sensor input information recorded in each DB, and stores the user's action log in the action log DB 46. More specifically, the data management unit 36 uses the external technology based on the sensor input information and uses the external technology (in the first embodiment, the user's behavior during walking, hand movement, hand sweating) Create a Here, the action log is a history of action of the user accumulated as a log based on sensor input information. Although many proposals have already been made as a method of creating an action log, in the first embodiment, an external technology is called and used. Note that the data management unit 36 may create one action log from one sensor input information, or may calculate one action log from a plurality of (plural or plural types of) sensor input information. Also, the action log may be calculated only from newly acquired sensor input information, or the action log may be calculated including sensor input information recorded in the past.

  The data structure of action log DB46 is shown by FIG.7 (b). The action log DB 46, as shown in FIG. 7 (b), "DB recording time", "user action time", "user name", "information collection device ID", "action log type label", "action log data Each field of Information (time stamp) of the date and time when the action log was recorded in the action log DB 46 is stored in the field of “DB recording time”. Information (time stamp) of the date and time when the user performed an action (for example, the date and time when the sensor input information based on the action log is stored in the DB 40, 44, etc.) is stored in the field of "user action time". Ru. In addition, although "sensor recording start time" of moving image data is diverted as "user action time" in FIG.7 (b), when moving image data are long, the moving image used for action log calculation The time at which the user action was performed may be more accurately identified and recorded from the time frame of In the field of "user name", identification information (name, etc.) of the user who performed the action of the action log is stored, and in the field of "information collection device ID", sensor input information based on the action log is stored. The collected device ID is stored. Furthermore, the fields of “action log type label” and “action log data” store the type (type) of the action log and data of the action log. For example, in the field of “action log type label”, specific information such as action during walking, hand movement, sweating and the like is stored, and in the field of “action log data”, specific information on action is Stored.

  Here, when generating the action log, the data management unit 36 refers to the system data 50 (see FIG. 4). In the system data 50, the personal information level definition of the action log of FIG. 8, the personal information level definition of the effect determination API of FIG. 11 (a), and the action log type and effects used for the effect determination of FIG. The determination API definition, the question sentence generation template list of FIG. 13A, the effect determination API definition used for the response analysis of FIG. 13B, and the like are included. Here, the data management unit 36 refers to the personal information level definition (FIG. 8) of the action log in the system data 50. The personal information level definition of the action log defines in advance the action log creating method to be managed for each user when there is a large amount of action log creating method in the system. In the personal information level definition of the action log of FIG. 8, “personal information level” of each action log type is also defined. The data management unit 36 confirms whether the action log can be obtained using the acquired sensor input information in the personal information level definition of the action log, and generates, for example, the action log during walking from the moving image data. As an example, it is assumed that three lines in each of which specific values are input in FIGS. 6A and 6B are sensor input information newly acquired. In this case, the data management unit 36 uses data from time tx-k to tx up to time tx-k, which is a predetermined time k backward from the data of the last row (data for which sensor recording is performed at time tx). Find the action log at time tx.

  That is, in the case of skin potential data, using the data up to a certain time after the data of “2014/7/12 12 11: 00: 01. 40” in the sensor recording time of FIG. 7/12 11: 00: 01. 040 ”for the action log. The third line of the action log DB 46 in FIG. 7 (b) records the perspiration of the hand of the user A of “2014/7/12 11: 00: 01.040”, and the value is between 0 and 1 here. The level of hand sweating normalized to is recorded as action log data.

  Further, in the first and second lines of the action log DB 46 in FIG. 7B, the motion of the user A is analyzed from the moving image in which the information collecting apparatus 120 captures the state of the user A, and the first line is at the time of walking As a log of the behavior of, it has been recorded where it has stopped for a certain period of time or more. The activity log data in the first line, Stay <where> vegetable_area </ where>, means that there is a rest for a certain period of time or more at this time, and the place where the rest is is the vegetable department.

  The second line is a log of the movement of the hand, recording the movement of holding and lifting an object. Pickup <what> green pepper </ what>, which is action log data, means that at this time there is an action in which an object is picked up and lifted, and the object of action is a green pepper.

  Returning to FIG. 5, in the next step S14, the data management unit 36 executes the user effect determination using the updated action log. In step S16, the effect determination time is determined based on the time information of the action log data used for the user effect determination, and the determined user effect is recorded in the user effect log DB 48. Here, as shown in FIG. 9, the user effect log DB 48 has “DB recording time”, “effect determination time (start)”, “effect determination time (end)”, “user name”, “action log type label / Field for “effect determination type label”, “self disclosure level”, “user effect type label”, and “user effect”.

  For example, it is assumed that an action log having three different action log type labels in FIG. 7B is recorded as the user action log at time tx. Note that the user effect determination may be a method of determining a user effect from one action log, a method of determining a user effect based on a plurality of action logs, and a method of directly using sensor input information. In the first embodiment, as an example, the data management unit 36 performs user effect determination from only one action log.

  The data in the fourth row (fourth) from the top of FIG. 9 is the end time of the time section in which the previous user effect determination was performed using the action log of the action log type level “action during walking” (affect Judgment time (end): 2014/7/12 11: 00: 00.000) or user action time 2014/7/12 of the first line (first one) from the top of the action log DB 46 in FIG. 7 (b) Data (action log) of 00: 01.040 is extracted, and the result of user effect determination is shown using the action log.

  The data management unit 36 records the previous effect determination time (end) in the “effect determination time (start)” field of the user effect log DB 48. In addition, the data management unit 36 records the last user action time of the data used for the effect log determination in the field of “effect determination time (end)”.

  Further, the data management unit 36 determines the self-disclosure level based on how much the personal information level information has been used to determine the effect, and records the self-disclosure level in the “self-disclosure level” field of the user effect log DB 48. .

  Specifically, when the action log type label is the action during walking, the data management unit 36 refers to the personal information level definition (FIG. 8) of the action log included in the system data 50, and the action log type label The self-disclosure level (Superficial) corresponding to the personal information level (Observable) of is identified from FIG. 10, and the identified self-disclosure level is recorded in the “self-disclosure level” field of the user effect log DB 48.

  In the field of “user effect type label” of the user effect log 48, it is clearly indicated what kind of user effect is recorded. Even if the "action log type label / effect determination type label" used in the user effect determination is different, it is easy to determine the match / mismatch of the user effect for the user effect log for which the user effect type label matches. It can be treated as a data group.

  In step S14, the data management unit 36 uses the personal information level definition of the effect determination API of FIG. 11 (a) and the action log type and effect determination API definition used for the effect determination of FIG. 11 (b). The user reaction quantification technique of is called to create a user effect (interest / interest / Positive / Neutral / Negative etc.) based on sensor input information. The personal information level definition of the effect determination API of FIG. 11A defines the personal information level of the effect determination API, the data type of sensor input information, and the information collection device ID. Further, the action log type and the effect determination API definition used for the effect determination in FIG. 11B define which action log type is used for the effect determination and which effect determination API is used for each user. Many proposals have been made for quantifying the user reaction, and in the first embodiment, estimation of the user's positive emotion or negative emotion is performed based on skin conduction data and moving image data.

In addition, as an effect judgment method using data that can not be known from observation of the superficial part of the person, "iMotions, Attention Tool API, http://imotionsglobal.com/software/attention-tool-api/" Eh T. Solovey, "Thomas Fritz, Andrew Begel, Sebastian C. Muller, Serap Yigit-Elliott, Manuela Zuger, Using Psycho-Physiological Measures to Assess Task Difficulty in Software Development, ICSE '14, 2014.", "Erin T. Solovey, Marin Zec, Enrique, Abdon Garcia Perez, Bryan Reimer, Bruce Mehler, Classifying Driver Workload Using Physiological and Driving Performance Data: Two Field Studies, CHI 2014, 2014. and the like can be used. In addition, “Emotient, Emotient API, http: //www.emotient API, http: //www.emotient” is a self-disclosure for the superficial part of the person, that is, a determination method of the disclosure of one's own state / feeling that anyone can know from the observation of the surface. .com / products "," Mary Ellen Foster, Andre Gaschler and Manuel Giuliani, How Can I Help You? Comparing Engagement Classification Strategies for a Robot Bartender, ICMI 2013, 2013. "," Chiew Seng Sean Tan, Johannes Schoning, Kris Luyten " Karin Coninx, Informing Intelligent User Interfaces by Inferring Affecting States from Body Postures in Ubiquitous Computing Environments, IUI '13, 2013. "
Etc. can be used.

  In addition, although the example which performs a user effect determination using an action log was given in the above, there may be an implementation which performs a user effect determination directly from sensor input information. In this case, the effect determination API to be used is described in the action log type used for the effect determination and the effect determination API definition (FIG. 11B). Here, the user A can perform the user effect determination using the expression analysis API. In such effect determination API, the personal information level individually, which sensor input information and which collecting device data are used, as in the personal information level definition of the effect determination API (FIG. 11A). Defined in the system. Therefore, as in the case where the user effect determination is performed using the action log, even when the user effect determination is performed using the user effect determination API, the result can be recorded in the user effect log DB 48.

(2) Social Distance Calculation Process Next, the social distance calculation process will be described in detail with reference to the flowchart of FIG. Note that the processing in FIG. 12 may be performed periodically at predetermined time intervals, or may be performed immediately before the information presentation processing control unit 34 of the server 30 starts information presentation via the information presentation units 12 and 112. It is also good.

  In the process of FIG. 12, first, in step S30, the social distance calculation unit 38 confirms the user effect log DB 48. Then, the social distance calculation unit 38, among the data of the same time zone, data (including the time zone) in which user effects different (classified into another class) are recorded in Superficial and Not Superficial. Extract.

  In the first embodiment, the type of the value of the user effect is Positive / Neutral / Negative, and Neutral means a case where it can not be determined with either value. Therefore, in the first embodiment, cases classified into another class are cases classified into either Positive or Negative.

  In step S30, specifically, the social distance calculation unit 38 sets the Superficial data and the Not Superficial data as in the fifth and sixth (the fifth and sixth lines) data from the user effect log DB 48 of FIG. And extract time zones that are classified into separate classes of positive and negative. The extracted time zone is a time zone in which the user effect determined based on the observable data and the user effect determined based on the Not observable data are different from each other. It is a time zone in which the state / feeling may be different from the “your state / feeling not known to others”.

  Next, in step S32, data relating to the extracted time zone is extracted from the action log DB 46 or the like, and a question sentence asking for an effect in the time zone is generated. Specifically, the social distance calculation unit 38 extracts the information possessed for the extracted time zone from the action log DB 46 shown in FIG. 7 and is shown in FIGS. 6 (a) and 6 (b). The sensor input information recorded from each sensor is extracted.

  For example, it is assumed that a period of 2014/7/12 11: 00: 00.000 to 2014/7/12 11: 00: 01.040 is extracted as a time zone. In this case, the social distance calculation unit 38 refers to the action log DB 46 of the extracted time zone, and the action at the time of walking is “Stay <where> vegetable_area </ where>” or the hand movement is Extract what was "Pickup <what> green pepper </ what>".

  Then, the social distance calculation unit 38 selects, from among the templates prepared in advance in the question sentence generation template list shown in FIG. 13A included in the system data 50, the one that can use the extracted information. In this case, the social distance calculation unit 38 may select the templates registered in the question sentence generation template list in order from the top or randomly. Here, since the information of [where] is extracted as an example, it is assumed that the social distance calculation unit 38 selects the first template of FIG. After that, the social distance calculation unit 38 uses the records of the places tagged with <where> and </ where> recorded as action log data, and applies them to the template, “<where> vegetable_area </ When you were at where>, do you have something like that? " As to the place, English words may be used as they are, or bilingual words may be listed in order to make a more natural speech, and speech may be made after language translation is performed according to the user.

  Next, in step S34, the social distance calculation unit 38 asks the user a question using the generated question sentence via the information processing terminal 10 or the like, and records the answer from the user as sensor input information. Further, in step S36, the social distance calculation unit 38 performs user effect determination.

  Here, sensor input information is constantly acquired by the sensor as shown in FIG. 6A, FIG. 6B, or FIG. 7A, and is collected from the information collection devices 20 and 120 to the server 30. It is recorded data. In addition, there are a plurality of effect determinations that can be used in the system, and the effect determinations that can be used for the user effect determination at the time of response use the information that the user is presenting to the other party of the conversation with high accuracy. It is necessary to have the feature of performing the effect determination. For this reason, in the present embodiment, it is necessary to evaluate the effect determination API used in advance and define it in the system data 50.

  Here, the effect determination API usable in the response analysis is defined in the form of the effect determination API definition used for the response analysis in FIG. 13 (b). In the definition of FIG. 13B, fields of “high accuracy order”, “effect determination API”, “sensor input information”, and “information collection device ID” are provided. In the field of "high precision order", the smaller the API with the higher precision of response analysis, the smaller the number is input. The other fields are the same as the fields included in the definition of FIG. The social distance calculation unit 38 confirms, based on the sensor input information that it has, whether it is possible to use the effect determination API having a high accuracy rank. For example, when moving image data and voice data obtained from the information collecting apparatus 120 are recorded in the system, the user effect determination at the time of response is performed using the detailed face image / voice analysis API. Determine the available effect determination API.

  Next, in step S38, the social distance calculation unit 38 performs a perspective determination of the social distance.

  In this case, the social distance calculation unit 38 determines that the response user effect determined in step S36 matches “the state / feeling of oneself not known to others” in the time zone extracted in step S30. In the case, it is determined that the social distance is short. On the other hand, if they do not match, it can not be said that the social distance is short, so the social distance calculation unit 38 determines that the social distance is long.

  In the time zone extracted from the user effect log DB 48 of FIG. 9, the data of the Superficial self-disclosure level is positive, and the data of the Not Superficial self-disclosure level is “negative. There is a possibility that the state / feelings are different between my state / feelings and my own state / feelings not known to others, and the user asked the feeling of the time zone by the question sentence In the case where the user self-discloses "a person's own state / feeling not known to others", it is determined that the social distance is short.

  In step S38, as shown in FIG. 14, the social distance calculation unit 38 records the distance between the determined social distances. The social distance DB 52 in FIG. 14 has fields of “DB recording time”, “social distance calculation section start time”, “user name”, “application ID”, and “distance of social distance”. For example, when the social distance is short, “SD” is input in the “distance of social distance” field, and when it is far, “LD” is input. At this time, the social distance calculation unit 38 records the perspective of the social distance as that for the application that threw the question sentence (in this embodiment, for the application C2). In addition, the social distance calculation unit 38 records the oldest time stamp of the data used by the user effect log in the above as the social distance calculation section start time. Further, the time when the recording process is performed is recorded in the social distance DB 52 as a DB recording time.

(3) Information Presentation Process by Server 30 Next, the information presentation process by the server 30 (information presentation process control unit 34) will be described. The information presentation processing control unit 34 restricts the information to be used in the use range according to the distance of the social distance, and performs information presentation.

  In the present embodiment, since the perspective of the social distance between the user A and the service provided in the building is clarified in the process of (2), the information presentation processing control unit 34 determines the social distance based on the perspective. Control the information provided to user A (different).

  For example, when the fifth social distance distance (SD) from the top of FIG. 14 is determined, the information presentation processing control unit 34 determines information related to the privacy of the user A because the social distance is short. Can be provided, and more appropriate information can be provided to the user A. In this way, it is possible to provide the user with information according to the distance between the user and the social distance between the application, the service, and the device.

  As described above in detail, according to the first embodiment, the social distance calculation unit 38 responds to the generated question with a content including information that the user is not known other than the user It is judged whether or not the user answers the contents including information unknown to other than the user than when the user answers the contents not including information unknown to the other than the user. It is determined that the social distance between the user and the answer destination (application or service) is close (S38). As a result, it is possible to automatically and accurately determine the perspective of the social distance based on the user's answer.

  Further, in the first embodiment, the information presentation processing control unit 34 changes the content of the information to be provided to the user based on the perspective of the social distance, so information not corresponding to the social distance with respect to the user is It is possible to suppress presentation. As a result, appropriate information is presented to the user, so that it is possible to prevent the user from having a bad impression on the application or service. In addition, applications and services can continuously provide information while maintaining a good relationship with the user.

  Further, in the first embodiment, since the action log of the user is acquired and the question is generated based on the acquired information, the question necessary to determine the social distance can be automatically generated. .

  Further, in the first embodiment, the social distance calculation unit 38 determines, among the action log of the user, information (user effect) on the state or feeling of the user not apparent from the external observation and the user apparent from the external observation The question is generated based on the user's action log in a time zone which is a different type from the information on the state or feeling of the. Thereby, it is possible to accurately determine the perspective of the social distance between the user and the application or the like based on the answer to the question from the user.

  In the first embodiment, information on the user's state or feeling when the user gives an answer is information on the user's state or feeling not apparent from the external observation and the user's state apparent from the external observation Alternatively, based on which of the information related to the feeling is matched, it is determined whether or not the user has made a content response including information that is unknown only to the user. Thereby, the perspective of the social distance can be accurately determined based on the determination result.

  In the first embodiment described above, the case where the information that the user is not known other than the user is the action log whose self-disclosure level is "Not Superficial" is not limited to this. For example, it may be information (information such as hobbies and preferences) that the user recognizes as not being disclosed to others. That is, the social distance calculation unit 38 makes a question related to the information that the user recognizes that the user does not disclose to the other person, and the content of the user answering the question is the other person. It may be determined that the social distance is short if it contains information that is recognized as not being disclosed.

Second Embodiment
Next, a second embodiment will be described based on FIG. 15 to FIG. In the second embodiment, the user effect log is used with classification other than the classification of whether the self-disclosure level extends to the core of the person's personality and is similar to self-disclosure of a portion that can not be observed from the surface. Is different from the first embodiment described above in that

  In the second embodiment, as shown in FIG. 15, the information providing system 100 'includes an information processing terminal 10' and an information collecting apparatus 20 connected to the information processing terminal 10 '. The information processing terminal 10 'is a terminal (for example, a smartphone or a mobile phone) which a user (user B) always carries, as shown in FIG. Further, the information collection device 20 is a device mounted on the arm or the like of the user B, as in the first embodiment. The information processing terminal 10 ′ and the information collection device 20 are communicably connected by Bluetooth (registered trademark) or the like. The other configuration is the same as that of the first embodiment.

  In the present embodiment, there is an application C0 used by the information processing terminal 10 ′ that the user B always carries, and the user B is presented by the information presentation device 110 while walking through one building. Space varies depending on the individual. In the present embodiment, the information collecting apparatus 120 collects audio data as well as moving image data (see FIG. 7A).

  Here, the data management unit 36 of the server 30 generates a user effect log based on the action log type used for the effect determination shown in FIG. 11B and the effect determination API definition DB.

  In this case, as shown in the personal information level definition DB of the action log of FIG. 8 and the personal information level definition DB of the effect determination API of FIG. The information that the behavior of is Observable, the hand sweating is Not Observable, and the speech analysis API is Observable (conv) is used at the time of action log generation or effect analysis. Note that, as shown in FIG. 10, Observable (conv) means information of a part that anyone can know from observation of the surface (if it is a dialogue partner). The personal information level (Observable (conv)) corresponds to the self disclosure level (Superficial (intimate)). Superficial (intimate) means self-disclosure about the surface part of the person (with respect to the conversation partner), that is, disclosure of one's own state / feeling that anyone can know from the observation of the surface (if it is the conversation partner).

  These personal information levels are defined at the discretion of the administrator for each system in terms of which sensor is collected and what kind of person's action is handled. In the present embodiment, the action at the time of walking is collected using moving image data obtained by photographing the user remotely by the information collection device 120. Further, the voice analysis API uses voice data collected by a portable terminal (information processing terminal 10 '), and perspiration of a hand corresponds to bioelectric potential data (skin electrical activity amount) collected by the information collecting apparatus 20. Use to collect.

  In the present embodiment, the data management unit 36 executes the process of FIG. Specifically, after executing steps S10 and S12 in the same manner as in the first embodiment, the data management unit 36 executes user effect determination processing as described below in step S114.

  That is, in step S114, the data management unit 36 obtains the user effect from the normalized score with the most positive state being 1 and the most negative being 0. As the user effect determination technology, the existing technology is used as in the first embodiment. In addition, as effect judgment using data known to the other party of conversation, “ME Hoque et. Al, Robust Recognition of Emotion from Speech, 6th International Conference on Intelligent Virtual Agents (IVA), 2006.” or “ Chiew Seng Sean Tan, Johannes Schoning, Kris Luyten, Karin Coninx, Informing Intelligent User Interfaces by Inferring Affecting States from Body Postures in Ubiquitous Computing Environments, IUI '13, 2013. "and" Yale Song, Louis-Philippe Morency, Randall Davis " , Learning a Sparse Codebook of Facial and Body Microexpressions for Emotion Recognition, ICMI 2013, 2013. ”can be adopted.

  Next, in step S116, the data management unit 36 refers to the personal information level Observable / Observable (conv) / Not Observable used at the time of action log generation and effect analysis, and also superimposes the self-disclosure level of the user effect log. Record one of the corresponding classifications of / / Superficial (Intimate) / Not Superficial. The type of the user effect uses a label, here, NormScore (Positive-Negative), which indicates that a normalized score is recorded. As the value of the user effect, a numerical value between 0 and 1 is used using an external user effect determination technique. Then, the data management unit 36 accumulates user effect logs of a plurality of self-disclosure levels together with time stamp information as shown in FIG.

  Also, in the second embodiment, the social distance calculation unit 38 executes the social distance perspective determination along the flowchart of FIG. 19. In step S130 of FIG. 19, the social distance calculation unit 38 extracts a time zone in which the user effects do not match in all the classifications at the self-disclosure level used. It should be noted that it may be defined in advance by the system as to from what point of the user effect that is the normalized score to which point it is determined to be matched or not matched. For example, it is divided into three from 0 to 1 and classified into Class 1 = 0 to 0.3, Class 2 = 0.4 to 0.6, Class 3 = 0.7 to 1, etc. Depending on the data, a score may be assigned to each class by using Not Superficial as Class 1, Superficial (Intimate) as Class 2, and Not Superficial as Class 3. Alternatively, the width of each class is determined in advance by (maximum value of score (= 1) -minimum value of score (= 0)) / number of divided classes (= 3) / 2, and the user effect of the extracted time zone Classes may be defined with values as the median of each class. In this embodiment, assuming that the class width is 0.16, when the median of each class is 0.1, 0.4, 0.9, each class is Class 1 = 0 to 0.26, Class 2 = 0 .24 to 0.56, Class 3 = 0.74 to 1 In this case, there is an overlapping range between Class 1 and Class 2. Therefore, the overlapping range is not used because it is an area where it is difficult to separate the result of user effect analysis, and Class 1 = 0 to 0.23, Class 2 = 0.27 to 0.56, Class 3 = 0.74 Adjustment may be performed as in 1.

  The social distance calculation unit 38 executes step S32, step S34, and step S36 in FIG. 19 in the same manner as the first embodiment. Then, in step S38, the social distance calculation unit 38 matches the user effect determined at the time of response to the question with the user effect determined using the Not Superficial data of the extracted time zone (the value of the user effect is Determine whether it is a value in Class 3). When the value of the user effect is a value within Class 3, the social distance calculation unit 38 determines that the social distance is short. In other cases, it is assumed that the social distance is medium distance if the class 2 matches, and the social distance is long if the class 1 matches. As described above, by evaluating the perspective of the social distance not only far / close but also into multiple levels, it is possible to match the level of information presentation to the perspective level of this social distance.

Third Embodiment
Next, a third embodiment will be described based on FIG. 20 and FIG. In the third embodiment, among the plurality of time zones in the user effect log DB 48, a plurality of time zones having different user effects at different self-disclosure levels are extracted as in the first embodiment. It is different from

  Specifically, when the social distance calculation unit 38 determines the distance of the social distance based on the user effect stored in the user effect log DB 48 (FIG. 20), the question sentence is generated in step S230. Extract multiple time zones to be targeted. The extraction condition in this case is that the user effects (Positive / Neutral / Negative) determined from the "Not Superficial" data and the "Superficial" data do not match in the entire extracted time zone. In such a time zone, even when a plurality of time zones are extracted, an effect at the time of user response and a user effect of Not Superficial self-disclosure level recorded according to the contents answered by the user It is possible to determine the perspective of the social distance depending on whether or not there is a match.

  An example of the user effect log DB 48 of the present embodiment is shown in FIG. The first and second time zones from the top of FIG. 21 are the time zones in which the Not Superficial data and the user effect that is the Superficial data do not match in the multiple time zones mentioned as the extraction conditions described above. (T1), and the third and fourth time zones from the top (T2). In this case, at time zone t1, the user effect of the Superficial self-disclosure level is Positive, and at time zone t2, the user effect inferred from the data of the Not Superficial self-disclosure level is Negative, and other than that is clear. It has been recorded as neutral. Therefore, at t1 and t2, since the user effect does not match between the Not Superficial data and the Superficial data, these time zones are extracted at step S230.

  The subsequent processes (S32 to S38) of FIG. 20 are the same as those of the first embodiment (FIG. 12). In addition, in question sentence generation (S32), in order to ask the user more naturally the plurality of questions generated for each of the plurality of time zones, the social distance calculation unit 38 makes one question sentence a plurality of question sentences. It may be converted to Further, although the case where the self-disclosure level is one of the two levels of Superficial and Not Superficial has been described above, the present invention is not limited to this. Similar processing can be performed even when there are three or more self-disclosure levels as in the second embodiment.

Fourth Embodiment
Next, a fourth embodiment will be described based on FIG. In the fourth embodiment, among a plurality of time zones in the user effect log DB 48, a time zone (one or more) having user effects continuing for a predetermined time or more for each different self disclosure level is extracted. The points are different from the first embodiment.

  In this case, in step S330 in FIG. 22, the social distance calculation unit 38 extracts a time zone that is a target for generating a question sentence under the condition that the duration of the user effect is long.

  Specifically, the social distance calculation unit 38 refers to the user effect log DB 48, and the same user effect is continuously recorded in the Not Superficial and the time zone in which the same user effect is continuously recorded in the Superficial. Search for the time zone you are in Then, for the searched Superficial and Not Superficial, the longest time zone overlapping time zone is extracted from the cases where the user effects do not match.

  When extracting a time zone that has the longest overlap of time zones, it is not necessary for the user effects of Superficial / Not Superficial data in each time zone to be completely unmatched. As in the third embodiment, it is also possible to include the case where the user effect does not match between the Not Superficial data and the Superficial data in the entire extracted time zone.

  If a time zone is extracted on the condition that the duration of the user effect is long, a similar time zone may be selected each time in the question sentence generation. In this case, the user may get bored by asking the same question each time. In such a case, data of a time zone used once for generating a question sentence may be stopped from being used for generating a question sentence for a certain period of time. The other processes are the same as in the first embodiment.

  As described above, in the fourth embodiment, an extremely short time is not extracted as a time zone used to determine the perspective of the social distance. This reduces the possibility of the user's response to a question for determining the perspective of the social distance becoming vague due to the fact that the duration of the user effect is short and the user has no memory left. It becomes possible.

Fifth Embodiment
Next, a fifth embodiment will be described based on FIG. 23 to FIG. In the fifth embodiment, the social distance calculation unit 38 calculates the user effect certainty using a plurality of user effect logs in a time zone in which the self-disclosure level is common, and generates a user effect certainty in the question sentence generation. The point of extracting a high time zone is different from the first embodiment.

  In the fifth embodiment, as an example, it is assumed that line-of-sight data is included as Not Superficial data, and data is accumulated in a line-of-sight data recording DB (held by server 30) as shown in FIG. Do. The line-of-sight data is collected by the line-of-sight tracking unit of the wearable information processing terminal 210 worn by the user A as shown in FIG. It is assumed that the user A uses the application C0 in the information processing terminal 210. The application C0 is an application that presents a 3D space personalized to the user, and also presents and processes an interaction with a companion software agent that walks in the space. Further, the application C0 collects voice and moving image data through the information collecting apparatus 120 which is a small video recording device, and collects line-of-sight data through the line-of-sight tracking unit of the information processing terminal 210. Communication between the server 30 and the information processing terminal 210 and the information collecting apparatus 120 is established in the information presentation and information collection. Further, when the user A starts using the service in the building, the data acquired by the information processing terminal 210 and the information collecting device 120 is sent to the server 30 and stored by the server 30.

  Furthermore, the user A uses the application C1 that performs optimal presentation for coexistence of multiple users in the same space in the building. The application C1 can perform information presentation through projection of information on a wall, floor or hollow (air) of a building through the information presentation device 110.

  In the fifth embodiment, the social distance calculation unit 38 determines the distance between social distances based on the accumulated user effect log DB 48 (see FIG. 25). In the process of FIG. 25, in step S430, the social distance calculation unit 38 extracts a time zone for which a question sentence is to be generated, on the condition that the user effect certainty factor is high.

  Here, the user effect certainty factor is an index indicating how high a user effect matches when there are a plurality of user effect logs at the self-disclosure level in the same time zone.

  FIG. 26 shows an example of the user effect log DB 48 in the fifth embodiment. In the user effect log DB 48 shown in FIG. 26, two data are recorded at each of the Superficial and Not Superficial self-disclosure levels, and in the Superficial, Neutral and Positive, and in the Not Superficial Negative are recorded. From this, the user effect certainty factor can be calculated such that Positive is 1/2 (or Neutral is 1/2) in Superficial and Negative is 2/2 in Not Superficial. If there is a time zone in which the user effect certainty factor is higher than that in another time slot, the time zone in which the user effect certainty factor is high is extracted as a question sentence generation time slot. The comparison between time zones of the user effect certainty factor may use an average value of Superficial and Not Superficial, or may use the user effect certainty factor of only the priority personal information level.

Sixth Embodiment
Next, a sixth embodiment will be described. The sixth embodiment is different from the first embodiment in that a user effect is recorded together with time stamp information corrected to a time when a user effect is expected to occur.

  Depending on the data used for the effect determination, there may be a gap between the time when the action was observed and the time when the user effect occurred. Here, hand sweating recorded in the action log DB 46 of FIG. 7B will be described as an example. In FIG. 7B, the perspiration level of the hand is recorded when the user action time is t_act1 = 2014/7/12 11: 00: 01.040, and the corresponding user effect log is the effect determination time (start ) Is recorded as t_affs = 2014/7/12 11: 00: 00.000, and the effect determination time (end) is t_affe = 2014/7/12 11: 00: 01.040. In the first embodiment described above, t_affs and t_affe are determined based on which time range of action log is used to determine, but when the user feels stressed, hand sweating is sensed There is a time lag before. Such time lag also exists in brain waves and the like. Therefore, when a time lag is known for each type of action log, the data management unit 36 sets t_affs + tl and t_affe + tl as effect determination time (start) and effect determination time (end) when the time lag is tl. , And may be recorded in the user effect log DB 48. By doing this, the time zone can be extracted based on the time zone in which the user actually felt the effect (S30 in FIG. 12), so a question is drawn that more accurately determines the social distance. It becomes possible to do (S32 of FIG. 12).

Seventh Embodiment
Next, a seventh embodiment will be described based on FIG. In the seventh embodiment, the degree of stability of the user effect is calculated based on how stable the user effect was in comparison with the time zones before and after that and the change in the user effect, and the user sentence generation in the question sentence generation The point of extracting a time zone having a high degree of effect stability is different from that of the first embodiment.

  Specifically, the social distance calculation unit 38 extracts a time zone for which a question sentence is to be generated on the condition that the user effect stability is high. Here, user effect stability refers to how much the user effect is stable using a plurality of user effect logs in the same time zone common to the self-disclosure level as compared with time zones before and after that It is an indicator that indicates whether or not In the seventh embodiment, the evaluation value is calculated depending on how stable the certainty factor described in the fifth embodiment is.

  FIG. 27 shows an example of data of the user effect log DB 48 for describing the seventh embodiment. For example, data having an effect determination time (start) = 2014/7/16 16: 00: 00.000 and an effect determination time (end) = 2014/7/16 11: 05: 00.000 shown in FIG. It is assumed that the time zone of the first data) is a time zone which is a candidate of a time zone to be extracted for generating a question sentence. In this case, when calculating the user effect certainty factor, in the case of the Superficial, the Neutral is 1/2 and the Positive is 1/2, and in the Not Superficial, the Neutral is 1/2 and the Negative is 1/2. The confidence in this previous time zone is 1/2 for Neutral, 1/2 for Positive and 1/2 for Not Superficial, and 2/2 for Not Superficial. If you calculate the change from the previous time zone, Not Superficial is 1 / 2-1 / 2 = 0 for Neutral, 1 / 2-1 / 2 = 0 for Positive, and Super = 0-1 / 2 =-for Superficial. 1/2, Negative is 2 / 2-1 / 2 = 1/2. The smaller this change value, the more stable the user effect is recorded in that time zone. Therefore, when a plurality of time zones are candidates as time zones for generating a question sentence in step S30 of FIG. 12, the social distance calculation unit 38 calculates and compares the stability levels of the respective time zones. The time zone with high degree of stability is extracted as the time zone for question sentence generation.

  In addition, when comparing the degree of stability, the absolute value of the change may be totally compared, or only the data of the self-disclosure level of interest is used for comparison (for example, only the degree of stability of Not Superficial You may compare and use. As a result, it is possible to avoid using data for a time zone in which a user effect log suitable for question sentence generation is accidentally recorded only in one time zone for question sentence generation. Therefore, it is possible to extract a time zone in which a user effect suitable as a time zone used for social distance perspective determination is recorded.

  The above processing functions can be realized by a computer. In that case, a program is provided which describes the processing content of the function that the processing device should have. The above processing functions are realized on the computer by executing the program on the computer. The program in which the processing content is described can be recorded on a computer readable recording medium (except for the carrier wave).

  In the case of distributing the program, for example, the program is sold in the form of a portable recording medium such as a DVD (Digital Versatile Disc), a CD-ROM (Compact Disc Read Only Memory) or the like in which the program is recorded. Alternatively, the program may be stored in the storage device of the server computer, and the program may be transferred from the server computer to another computer via a network.

  The computer executing the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing in accordance with the program. The computer can also execute processing in accordance with the received program each time the program is transferred from the server computer.

  Each embodiment mentioned above is an example of a preferred implementation of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention. For example, the types of sensors for acquiring user information described in the first and second embodiments, various definitions of the system data 50, and the like are only examples, and the present invention is not limited to the above embodiments.

In addition, the following additional remarks are further disclosed regarding the description of the above 1st-7th embodiment.
(Supplementary Note 1) It is determined whether or not the user has responded to the question including the content including information unknown to the user.
When the user answers a content including information that is not known other than the user, the use is more than when a response that does not include information that is not known other than the user is reported Judged that the social distance between the person and the answeree is short,
A processing program causing a computer to execute processing.
(Supplementary Note 2) The processing program according to Supplementary Note 1, wherein the information not known to persons other than the user is information regarding the state or feeling of the user that is not clear from the external observation of the user.
(Supplementary Note 3) The processing program according to Supplementary Note 1 or 2, further causing the computer to execute processing for differentiating the content of the information to be provided to the user based on the determination result of the determination processing. .
(Supplementary Note 4) Information on the user's action history is acquired,
The processing program according to any one of appendices 1 to 3, wherein the processing further causes the computer to execute the processing of generating the question based on the information acquired in the acquisition processing.
(Supplementary Note 5) In the process of generating the question, among the information on the user's action history, the information on the state or feeling of the user not apparent from the external observation and the state of the user apparent from the external observation The processing program according to claim 4, wherein the question is generated based on information on the user's action history at a time when the information on feeling is different from the information on the feeling.
(Supplementary Note 6)
Information on the condition or feeling of the user when the answer is made is information on the condition or feeling of the user not apparent from external observation, and information on the condition or feeling of the user apparent from external observation The processing program according to Supplementary Note 5, wherein it is determined whether or not the user has made a response including content that is not known to the other than the user based on which of the two is common.
(Supplementary Note 7) The processing program according to Supplementary note 5 or 6, wherein, in the process of generating the question, the question is generated based on information on the action history of the user at a plurality of times.
(Supplementary Note 8) In response to a question, it is determined whether or not the user has made an answer containing content that is not known to anyone other than the user.
When the user answers a content including information that is not known other than the user, the use is more than when a response that does not include information that is not known other than the user is reported Judged that the social distance between the person and the answeree is short,
A processing method characterized in that a computer executes processing.
(Supplementary Note 9) The processing method according to Supplementary note 8, wherein the information not known to persons other than the user is information relating to the state or feeling of the user that is not clear from the external observation of the user.
(Supplementary Note 10) The processing method according to Supplementary Note 8 or 9, further causing the computer to execute a process of making the content of the information to be provided to the user different based on the determination result of the determination process. .
(Supplementary note 11) The information on the action history of the user is acquired,
10. The processing method according to any one of appendices 8 to 10, wherein the computer further executes a process of generating the question based on the information acquired in the process of acquiring.
(Supplementary Note 12) In the process of generating the question, information on the state or feeling of the user which is not clear from external observation and information on the user's state apparent from external observation among the information on the action history of the user The processing method according to claim 11, wherein the question is generated based on information on the user's action history at a time when the information on feeling is different from the information on the feeling.
(Supplementary Note 13)
Information on the condition or feeling of the user when the answer is made is information on the condition or feeling of the user not apparent from external observation, and information on the condition or feeling of the user apparent from external observation It is determined whether the said user gave the reply of the content containing the information which is not known other than the said user based on which is common, The processing method of Additional remark 12 characterized by the above-mentioned.
(Supplementary Note 14) The processing method according to supplementary note 12 or 13, wherein, in the process of generating the question, the question is generated based on information on the action history of the user at a plurality of times.
(Supplementary Note 15) A determination unit that determines whether or not a user has made an answer to a question including content that is unknown to the user.
When the user answers a content including information that is not known other than the user, the use is more than when a response that does not include information that is not known other than the user is reported Judgment unit that judges that the social distance between the person and the answeree is short,
Processing device comprising:
(Supplementary Note 16) The processing device according to Supplementary Note 15, wherein the information not known to persons other than the user is information regarding the state or feeling of the user that is not clear from the external observation of the user.
(Supplementary Note 17) The processing device according to Supplementary Note 15 or 16, further comprising: a processing unit that makes the content of the information provided to the user different based on the determination result of the determination unit.
(Additional remark 18) The acquisition part which acquires the information about the user's action history,
15. The processing apparatus according to any one of the above 15 to 17, further comprising: a generation unit that generates the question based on the information acquired by the acquisition unit.
(Supplementary Note 19) The generation unit relates to information on the state or feeling of the user that is not clear from external observation among information on the action history of the user, and relates to the state or feeling of the user apparent from external observation The processing device according to appendix 18, wherein the question is generated based on information on the action history of the user at a time when the information is a different type.
(Supplementary Note 20) The determination unit
Information on the condition or feeling of the user when the answer is made is information on the condition or feeling of the user not apparent from external observation, and information on the condition or feeling of the user apparent from external observation It is determined whether the said user gave the reply of the content containing the information which is not known other than the said user based on which is common, The processing apparatus of Additional remark 19 characterized by the above-mentioned.
(Supplementary Note 21) The processing device according to Supplementary note 19 or 20, wherein the generation unit generates the question based on information on the action history of the user at a plurality of times.

30 server (processing unit)
34 Information presentation processing control unit (processing unit)
38 Social distance calculation unit (judgment unit, judgment unit, acquisition unit, generation unit)

Claims (6)

On the computer
First information on a user's state or feeling that is not apparent from external observation in a certain time zone, which is determined based on data collected by the first information collection device, and first information different from the first information collection device Refer to a first storage unit that stores second information related to the user's state or feeling apparent from external observation in the certain time zone, which is determined based on data collected by the second information collection device A function of specifying a time zone in which the state or feeling of the user indicated by the first information and the state or feeling of the user indicated by the second information in the same time zone are different;
A function of presenting, to the user, a question that asks the user's state or feeling during the specified time zone;
The user is said based on at least one of data collected by the first information collecting device while the user answers the question and data collected by the second information collecting device. A function of determining the state or feeling of the user when answering a question;
When the determined state or feeling of the user is in common with the state or feeling of the user indicated by the first information in the specified time zone , the user and the answer destination are better than in the case where they are not common Function to judge that the social distance between
Processing program for realizing . The processing program according to claim 1 , further causing the computer to realize the function of changing the content of the information to be provided to the user based on the result of the determination. A function of generating the question based on information on the user's behavior in the specified time zone with reference to a second storage unit that stores information on the user's behavior in the certain time zone; The processing program according to claim 1 or 2 for making a computer further implement . The function of generating the question specifies a plurality of time zones in which the state or feeling of the user indicated by the first information and the state or feeling of the user indicated by the second information are different in the same time zone , based on information about the user's behavior in a plurality of the time periods identified, processing program according to claim 3, characterized in that it comprises a function for generating the question. First information on a user's condition or feeling that is not apparent from external observation in a certain time zone, which is determined based on data collected by the first information collection device, and a specific unit included in the computer; Storing, based on data collected by a second information collecting device different from the information collecting device of the second information, the second information on the state or feeling of the user apparent from the external observation in the certain time zone Specify a time zone in which the state or feeling of the user indicated by the first information and the state or feeling of the user indicated by the second information are different in the same time zone with reference to the first storage unit ,
A query unit included in the computer presents, to the user, a question inquiring a state or feeling of the user in the specified time zone;
The determination unit included in the computer is at least one of data collected by the first information collection device and data collected by the second information collection device while the user answers the question. Based on the condition or feeling of the user when the user answers the question, the first information in the specified time zone indicates the determined condition or feeling of the user When it is in common with the state or feeling of the user, it is judged that the social distance between the user and the reply destination is closer than in the case where they are not common .
A processing method characterized by First information on a user's state or feeling that is not apparent from external observation in a certain time zone, which is determined based on data collected by the first information collection device, and first information different from the first information collection device Refer to a first storage unit that stores second information related to the user's state or feeling apparent from external observation in the certain time zone, which is determined based on data collected by the second information collection device A specifying unit that specifies a time zone in which the state or feeling of the user indicated by the first information and the state or feeling of the user indicated by the second information in the same time zone;
A question unit for presenting, to the user, a question for asking the user's state or feeling in the specified time zone;
The user is said based on at least one of data collected by the first information collecting device while the user answers the question and data collected by the second information collecting device. The condition or feeling of the user determined when the user answered the question, the condition or feeling of the determined user is indicated by the condition or feeling of the user indicated by the first information in the specified time zone If the common, than without common, a determination unit for social distance between the user and the response destination is determined to close,
Processing device comprising:

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