JP2005332127A - Status prediction system by personal profile and method, program and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a status prediction system by a personal profile which presents information about a user and information extracted based on profile accumulation to the user and its method, a program and a recording medium thereof. <P>SOLUTION: The system is provided with; a sensor 1 for detecting an environmental condition in which a user is placed and outputting it as an electrical signal; a status collection means 2 for collecting environmental conditions detected by the sensor 1 as user's status information; a status information accumulation means for accumulating status information about a user collected by the status collection means 2 as low level status information contained in the personal profile (7); and a meta-status discrimination prediction means 8 which generates a high level status information contained in the personal profile by carrying out cluster sorting of user's former status information accumulated in the status information storage means (7) and a transition pattern which indicates change of status information based on the high level status information, and predicts changes user's present status information by time series based on this transition pattern. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a situation prediction system and method based on a personal profile, a program, and a recording medium, which present to a user information related to the user and information extracted based on profile accumulation.

  Conventionally, profile generation by various methods has been performed. As a technique related to profile generation, “profile collection apparatus and method, sales promotion support system, program, recording medium” (Patent Document 1: Japanese Patent Laid-Open No. 2003-30403) is known. This technique is a method for calculating the number of accesses to a WEB page and its access log, and calculating an interest value related to the WEB page together with input parameters.

  Further, “a user profile generation method and apparatus for providing document information, a generation program, and a recording medium on which the program is recorded” (Patent Document 2: Japanese Patent Application Laid-Open No. 2003-76712) is also known. This is a method of generating a profile and recommending a document with reference records of documents performed by a plurality of users and the degree of coincidence between the evaluation value for the document and the own evaluation value.

Further, a “user service profile information access method” (Patent Document 3: Japanese Patent Application Laid-Open No. 6-232867) is also known. In this technology, in collecting and managing service registration information of a communication network, user service profile information can be searched in a service common access format by means of service, service information level, contract item group / weekly schedule information, and the definition table holding means. Search request means for requesting, and searching for information by converting the request of the search request means into a user service profile information format managed for each access user / service by the definition table holding means, and the search result is the definition table In this method, the data is converted into a common service format by the holding means and returned to the search request means.
JP 2003-30403 A JP 2003-76712 A JP-A-6-232867

  However, the conventional technology related to profile generation has a technology for a specific application or a service provided by a specific provider, and uses information obtained only from the server on the information provider side or only from a specific terminal. .

  For this reason, users can use various information devices while moving places in wide-area activities in real life, and use them for services that automatically present information depending on various situations that can be received on the terminal. In this case, the information necessary for profile generation is extremely insufficient.

  In addition, since future situation changes are not predicted based on the information obtained from the profile, it is possible to acquire some information necessary at that time, but from that point in time the information required in the future is acquired in advance, It was not possible to recommend information that was prepared.

  Many attempts have been made to generate profiles for personal application to date, but these have many problems and cannot be used for presenting context-aware information. The problems are shown below.

(1) Profiles are not standardized In the current information society, various organizations (for example, government organizations, local public bodies, educational institutions, companies, etc.) have created their own personal profiles for the purpose of serving users. Yes. For example, various attempts represented by CRM (customer relationship management) in companies. These are merely collecting and maintaining the minimum data required for each organization to realize their services, and the entities, data contents, and freshness are uneven and simply distributed. In a system in which each profile is exchanged, a unified common profile cannot be generated.

  In addition, in the future, if sensors become smaller and cheaper, networks become faster and cheaper, computers become smaller, faster and cheaper, and a ubiquitous computing environment is realized, detailed data on personal situations can be collected. Thus, since the amount of data becomes enormous in terms of space and time, this problem is easily expected to become even more prominent.

  In addition, when distributed, the reachability to profile data, the access speed, and the chances of being managed by many people and computers increase, which poses a major problem in security management. Therefore, a management method in which profiles are aggregated and shared is desired.

(2) Insufficient information required for profile generation Information required for profile generation is roughly classified into static information and dynamic information in terms of time. Static information is, for example, name, gender, address, phone number, etc. Dynamic information is age that changes over time, purchased products, content and storage location of the referenced information, and the human spatial The position (simple coordinates).

  These pieces of information can be recorded in association with each other relatively easily, but from the viewpoint of providing information depending on the situation, there is clearly a shortage of source information. In order for a machine to understand that a person has been placed in a certain situation, the personality of the person, accumulation of knowledge up to the present, surrounding environment, action schedule, etc. are necessary.

  The surrounding environment is not only spatial, but if it is a building, its type, location in the building, living environment such as temperature, humidity, lighting, and sound, atmosphere such as interior, external environment such as climate and weather If there are objects arranged around humans, humans such as acquaintances / others, animals such as pets, and living beings, what kind of communication is being carried out and what has been done as a history is there.

  The personal situation is classified into physical condition information such as pulse and blood pressure, information being referred to, information about information (definition of location, contents, and contents of information). In short, these are all sensing information about the individual and their surroundings from the past to the present, and all of them should be used to generate a profile, but the current profile is A profile is generated only from a limited portion of information about an individual, and no means for collecting all information has been established at present.

(3) Profiles not predicting time-series changes Profiles are low-level situation data (for example, latitude, longitude, position in units of several centimeters, sound, light, numerical values such as product IDs, biological IDs, etc. Text information, images, audio, and meta information of the information), and high-level status data that is calculated by assembling these (for example, spending leisure time at home, working in the office, traveling on the train, in the car) Moving, walking, watching home TV, looking at computer, reading, eating, good / bad weather, etc.) Has been. The conventional profile uses some of these meta status data and a schedule input in advance, and does not perform processing such as predicting these time-series changes.

(4) Other people's knowledge is not automatically provided in the profile Most of the human behavior is periodic. Except for inexperienced behavior, future behavior patterns can be estimated from past profile accumulation to some extent It is. However, sometimes a situation occurs that the individual is not experiencing. Even in this case, if the majority of the situation has already been experienced by someone else, and if you can share that experience and use it for others unconsciously, do not specialize in personal preferences. Although it becomes a general response, profile data can be generated even in inexperienced behavior. Knowledge sharing for conventional profiles is specialized in a very small part of the situation, or it has been a labor-intensive method for knowledge sharing.

  In view of such a problem, the present invention can collect and accumulate past information referred to by personal preference and various sensed information when a user searches and browses information, It is possible to generate a centralized personal profile, judge and predict the situation from the profile accumulation, extract the information most suitable for the situation at that time, select the information for presentation, and enough situation data is accumulated An object is to provide a situation prediction system and method based on a personal profile, a program, and a recording medium capable of providing an optimum information presentation service by searching for and synthesizing similar situations of others even in a state where the person is not To do.

The present invention according to claim 1 predicts a situation according to a personal profile and environmental conditions of the user for information searched and browsed by a user via a network, and generates the information generated based on the prediction. A situation prediction method based on a personal profile for providing via the network,
Detecting the environmental condition by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal;
Collecting the status information by status collection means for collecting the environmental conditions detected by the sensor as status information of the user;
Storing the status information by status information storage means for storing the status information about the user collected by the status collection means as low-level status information included in the personal profile;
Clustering the user's past situation information stored in the situation information storage means to generate high level situation information included in the personal profile, and based on the high level situation information, changes in the situation information Generating a transition pattern to indicate, and performing the prediction by meta-situation determination prediction means for predicting a time-series change of the current situation information of the user based on the transition pattern;
Extracting the information by information extraction means for extracting information that the user searches and browses based on the prediction of the meta-situation determination prediction means;
Identifying the individual by means of personal identification for identifying and providing the user with the information extracted by the information extraction means;
Have

  Further, in the present invention described in claim 2, in the first aspect, when the meta situation determination prediction unit does not reach the prediction due to a lack of the situation information, the meta situation determination prediction means may receive the user's Similar situation information acquisition means for acquiring situation information similar to the situation information and compensating for the shortage is provided.

  Further, according to a third aspect of the present invention, in any one of the first or second aspect, the meta-situation determination / prediction unit predicts the situation information accumulated in time series using an autoregressive model.

  According to a fourth aspect of the present invention, in any one of the first to third aspects, the low-level status information and the high-level status information are metadata.

  Further, according to a fifth aspect of the present invention, in any one of the first to fourth aspects, the situation collecting means performs information processing by converting all the collected situation information into a cipher.

  Further, the present invention according to claim 6 predicts the situation according to the personal profile and environmental conditions of the user for information searched and browsed by the user via the network, and generates the information based on the prediction. A situation prediction system based on a personal profile for providing information via the network, wherein the environmental condition placed by the user is detected and output as an electrical signal, and detected by the sensor Status collecting means for collecting the environmental conditions as the status information of the user, and status for storing the status information regarding the user collected by the status collecting means as low-level status information included in the personal profile Information storage means, and the past situation information of the user stored in the situation information storage means. Discriminating and generating high-level situation information included in the personal profile, generating a transition pattern indicating a change in the situation information based on the high-level situation information, and generating the current state of the user based on the transition pattern Meta-situation determination prediction means for predicting a time-series change of the situation information, information extraction means for extracting information to be searched and browsed by the user based on the prediction of the meta-situation determination prediction means, Personal identification means for identifying and providing the user's individual with the information extracted by the information extraction means.

  In addition, in the present invention described in claim 7, in claim 6, when the meta-situation determination prediction unit does not reach the prediction due to a lack of the situation information, the meta-situation determination / prediction unit receives the user's Similar situation information acquisition means for acquiring situation information similar to the situation information and compensating for the shortage is provided.

  In addition, according to an eighth aspect of the present invention, in any one of the sixth or seventh aspects, the meta-situation determination / prediction means predicts the situation information accumulated in time series using an autoregressive model.

  Further, in the present invention according to claim 9, in any one of claims 6 to 8, the low-level status information and the high-level status information are metadata.

  Further, according to a tenth aspect of the present invention, in any one of the sixth to ninth aspects, the status collecting unit performs information processing by converting all the status information to be collected into encryption.

  The present invention according to claim 11 predicts a situation according to a personal profile and environmental conditions of the user for information searched and browsed by a user via a network, and generates the information based on the prediction. A situation prediction program based on a personal profile for providing information via the network, wherein the environmental condition is detected by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal. Collecting the status information by status collection means for collecting the environmental conditions detected by the sensor as the status information of the user, and the status information about the user collected by the status collection means. Status information storage for storing as low-level status information included in the personal profile A step of accumulating the situation information by a stage, and generating a high-level situation information included in the personal profile by clustering the user's past situation information accumulated in the situation information accumulation means, A transition pattern indicating a change in the situation information is generated based on the situation information, and the prediction is performed by a meta situation determination prediction unit that predicts a change in the time series of the current situation information of the user based on the transition pattern. Extracting the information by means of an information extraction means for extracting information to be searched and browsed by the user based on the prediction of the meta situation determination prediction means, and the information extracted by the information extraction means Identifying the individual by means of identifying a person for identifying and providing information to the user. To.

  In addition, in the present invention described in claim 12, the meta-situation determination / prediction unit according to claim 11 is configured so that the meta-situation determination / prediction unit determines whether the meta-situation determination prediction unit does not reach the prediction due to lack of the situation information. Similar situation information acquisition means for acquiring situation information similar to the situation information and compensating for the shortage is provided.

  Further, according to a thirteenth aspect of the present invention, in any one of the eleventh and twelfth aspects, the meta-situation determination / prediction means predicts the situation information accumulated in time series using an autoregressive model.

  Further, according to a fourteenth aspect of the present invention, in any one of the eleventh to thirteenth aspects, the low-level status information and the high-level status information are metadata.

  Further, according to a fifteenth aspect of the present invention, in any one of the eleventh to fourteenth aspects, the situation collecting unit performs information processing by converting all the collected situation information into a cipher.

  The present invention according to claim 16 predicts a situation according to a personal profile and environmental conditions of the user for information searched and browsed by a user via a network, and generates the information based on the prediction. A recording medium recording a situation prediction program based on a personal profile for providing information via the network, wherein the environment is detected by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal. A step of detecting a condition, a step of collecting the situation information by a situation collection means for collecting the environmental condition detected by the sensor as the situation information of the user, and the user collected by the situation collection means The situation information regarding is stored as low-level situation information included in the personal profile Storing the status information by status information storage means for generating a high-level status information included in the personal profile by clustering the user's past status information stored in the status information storage means A meta-situation determination prediction that generates a transition pattern indicating a change in the situation information based on the high-level situation information and predicts a change in the time series of the current situation information of the user based on the transition pattern. A step of performing the prediction by means, a step of extracting the information by an information extraction means for extracting information to be searched and browsed by the user based on the prediction of the meta-situation determination prediction means, and the information extraction means Identifying the individual by means of identifying a person for identifying and providing the user's individual with the information extracted by A step that records the status prediction program according to personal profile characterized by having a.

  In addition, in the present invention described in claim 17, the meta situation determination prediction unit according to claim 16, wherein the meta situation determination prediction means does not reach the prediction due to a lack of the situation information from a user other than the user from the user. A situation prediction program based on a personal profile is recorded, which comprises situation information similar to the situation information, and comprising similar situation information acquisition means for compensating for the shortage.

  The present invention according to claim 18 is characterized in that, in any one of claims 16 and 17, the meta-situation determination / prediction means predicts the situation information accumulated in time series using an autoregressive model. Record the situation prediction program by personal profile.

  According to a nineteenth aspect of the present invention, there is provided the situation prediction program according to any one of the sixteenth to eighteenth aspects, wherein the low-level situation information and the high-level situation information are metadata. Record.

  Further, the present invention according to claim 20 is the personal profile according to any one of claims 16 to 19, wherein the status collection means converts all the status information to be collected into a cipher and processes the information. Record the situation prediction program.

  According to the present invention, when a user searches and browses information, it is possible to collect and accumulate past information referred to by personal preference and various sensed information. It is possible to generate, judge the situation from the profile accumulation and predict it, extract the information most suitable for the situation at that time, select the information for presentation, and even in the state where the situation data is not accumulated enough It is possible to provide a situation prediction system and method based on a personal profile, a program, and a recording medium capable of providing an optimum information presentation service by searching for and synthesizing similar situations of others.

<First Embodiment>
FIG. 1 is a configuration diagram for explaining the overall configuration according to the first embodiment of the present invention. FIG. 1 shows various sensors 1, status collection means 2, encryption means 3, transfer means 4, transfer destination resolution means 5, decryption means 6, status storage means 7, and meta status determination. 8, information reference means 9, personal identification means 10, and reference information 11 are shown.

  Various sensors 1 are arranged to detect an environment around a user (user) who searches and browses information via a network (not shown). The various sensors 1 are installed in, for example, an IC card owned by a user or a mobile portable terminal. In addition to these carry-on items, it is also assumed that various sensors 1 are arranged in a room where a user is present, each room at home, or the like. These various sensors 1 detect the surrounding environment where they are arranged as status information. The detected environmental elements are various electric signals obtained by converting temperature, humidity, position, fragrance, image, acceleration, and the like into electric signals.

  Here, FIG. 2 is a configuration diagram for explaining the various sensors 1, the status collection unit 2, and the encryption unit 3. As shown in FIG. 2, the various sensors 1 include an electronic tag sensor 100, a temperature sensor 101, a humidity sensor 102, a sound sensor 103, a scent sensor 104, and an image sensor 105 that constitute the electronic tag sensor 100. , An acceleration sensor 106, a position sensor 107, and the like. In addition to the individual sensors illustrated, other sensors (not illustrated) are further provided as necessary.

  In addition, the status collection unit 2 is a signal collection unit 200 for electronic tag sensors that receives a signal output from the electronic tag sensor 100, a status collection unit 201 for temperature sensors that receives a signal output from the temperature sensor 101, and a signal from the humidity sensor 102. Humidity sensor status collecting means 202 that receives the output, sound sensor status collecting means 203 that receives the signal output from the sound sensor 103, scent sensor status collecting means 204 that receives the signal output from the scent sensor 104, and image sensor The image sensor status collecting means 205 that receives the signal output from the 105, the acceleration sensor status collecting means 206 that receives the signal output from the acceleration sensor 106, and the position sensor status collecting means 207 that receives the signal output from the position sensor 107. Etc. In addition to the individual sensor status collection means shown in the figure, other sensor status collection means (not shown) are provided as necessary.

  The situation collecting means 2 having such a configuration obtains sensing information which is an electrical signal output with a low abstraction level from various sensors 1, and collects the sensing information collection time, position, sensor owner, sensor ID, and electronic Metadata such as a personal ID for identifying the individual user sensed by the tag sensor is added, and this is sent to the encryption means 3 as status information.

  It should be noted that the sensing information collected by the status collection means 2 may be periodically collected (for example, set once / second to once / hour), or may be set by the user via a network. When information is retrieved and browsed, sensing information may be collected at the timing of requesting the latest information.

  Referring to FIG. 1, the situation information output from situation collecting unit 2 is input to encryption unit 3. The reason why this encryption means 3 is arranged is that the data relating to the personal situation of the user is information that is classified as private information secretly, and when such personal information is distributed on an open network, it is read by others. This is because it is essential to ensure security in order to avoid this. For this reason, the status information is encrypted in the encryption means 3 and sent to the transfer means 4.

  As shown in FIG. 3, the transfer unit 4 is arranged to transfer status information to the status storage unit 7 via the global network 20. A transfer execution unit 401 and a transfer destination acquisition unit 402 are arranged inside the transfer unit 4. The status information sent from the encryption unit 3 is searched by the transfer destination acquisition unit 402 via the global network 20, and the status storage unit 7 is acquired as the transfer destination. The acquisition of the transfer destination corresponds to, for example, an IP address or a URL in the Internet or the like. The transfer destination thus obtained is transmitted to the transfer execution means 401, and the transfer execution means 401 transfers the encrypted status information to the status storage means 7 via the global network 20.

  3 is transmitted when the various sensors 1, the status collection unit 2, the encryption unit 3, and the transfer unit 4 move together with the movement of the user. The situation storage means 7 on the side of receiving the situation information is also provided to cope with the case of moving.

  When both the transmitting side and the receiving side are moving, the IP address and URL of the transmitting side and the receiving side may dynamically change accordingly. In order to cope with such a change, the addresses on the transmission side and the reception side are rewritten and updated each time the address is changed as it moves. In addition, when the solution request for acquiring the transfer destination address is issued from the transfer device 4 or the like, the transfer destination resolution unit 5 responds to the request based on the unique ID assigned to the electronic tag sensor 100. The personal forwarding destination address and URL information specified by the unique ID are returned to the forwarding means 4.

  The transfer destination resolution unit 5 includes a response unit 501, a transfer destination management unit 502, and a transfer destination DB 503 therein. The response unit 501 is provided for performing a response with the transfer unit 4 via the global network 20. The transfer destination management unit 502 is connected to the transfer destination DB 503 and manages information on transfer destinations stored in the transfer destination DB 503. In this information management, in addition to a transfer destination stored in advance, a dynamically changed IP address, URL, and the like are also stored, and output is performed in response to a call.

  Referring to FIG. 1, the metadata-attached status information sent from transfer means 4 is sent to information storage means 7 after the decryption means 6 decrypts the cipher. In this information storage means 7, as shown in FIG. 4, the status information added with metadata in the status DB 704 is indexed and stored. The status reading means 703 issues a query and sends a response in response to the request. The situation DB management / operation means 702 performs interpolation by interpolation on the missing data portion of the situation DB 704. The status information stored here is information included in the personal profile related to the individual user, and is stored as low-level status information.

  Referring to FIG. 5, the meta situation determination unit 801 provided in the meta situation determination prediction unit 8 stores the multi-dimensional situation information obtained from the situation reading unit 703 as a factor in the meta situation / factor DB 803. Compared with the factor data, if it is the most dominant compared with other situations, it is determined that the meta situation is applicable. Here, the situation information processed by the meta situation determination / prediction means 8 is processed as high-level situation information included in the personal profile by clustering the user's past situation information accumulated in the situation information accumulation means 7. Is done.

  Since the situation information is received as stream data, the meta situation prediction means 804 predicts the future series using an autoregressive model, and the input of the meta situation determination means 801 is set as the predicted future situation information series. A future determined meta status stream is generated. The factor updating unit 802 updates the weight value indicating the relationship between the meta situation and the situation information that is the estimation factor, and the reference threshold for the calculation.

  Referring to FIG. 6, according to the meta situation received from the meta situation determination / prediction means 8, the information recommendation unit 901 refers best from the meta situation stream in the current and future meta situations and the situation corresponding to the individual. Recommendation is made from the information 11 referring to the information, and the information output means 902 outputs it as a screen or a sound. The personal identification means 10 identifies the individual user by the unique ID information assigned to the electronic tag sensor 100 and the like, biometric authentication such as the fingerprint of the user, or the secret code that only the user individual knows if there is no such information. Information can be presented only to specific users. The information referred to by the information reference means 9 stores the information location and content in the situation storage means 7 and becomes situation information that will be input to the meta situation determination prediction means 8 from the next time.

<Second Embodiment>
FIG. 7 is an explanatory diagram for explaining the situation information compensation when the situation information accumulation is insufficient according to the second embodiment of the present invention. In FIG. 7, it is assumed that past situation information similar to the situation information related to the current user A is not sufficiently accumulated in the situation accumulation means A-7 of the user A. In this case, the meta status determination prediction unit A-8 cannot determine the meta status. Therefore, the status storage unit A-7 issues a request to the transfer unit A-4, and the transfer unit A-4 sends a request for a status similar to the status information to the status storage unit B-7.

  The request destination from the transfer means A-4 is executed via the transfer destination resolution means 5. The transfer destination solving means 5 searches for the user B from the transfer destination DB 503 (see FIG. 3). According to the retrieved IP address of user B, the transfer unit A-4 connects to the user B and executes a request for providing similar status information to the status storage unit B-7.

  When the user B receives the situation information provision request from the user A to the situation storage unit B-7, the user B extracts higher-level situation information having a high similarity to the current situation information of the user A. The extracted status information is encrypted by the encrypting means B-3 or the like, then transferred via the transferring means B-4, and decrypted by the decrypting means A-6. The decrypted data is stored in the situation value storage A-7. By such a procedure, a shortage of situation information similar to the current shortage situation of the user A is compensated for by the user B, whereby the meta situation discrimination prediction means A-8 can discriminate the meta situation.

  In the first embodiment and the second embodiment of the present invention described above, for example, when you go to work, news that you often see at work is displayed. On the other hand, after returning home, personal hobby information is displayed. Services that can be displayed on a personal computer can be constructed and provided. In addition, it is possible to realize a service that automatically presents sales center sales information frequently visited by the user before the user actually goes to the shopping center.

  In addition, when a user tries to visit a famous tourist spot for the first time, necessary information such as traffic information and weather at the destination is optimally selected according to the current situation of the user, and a service that is presented is realized. be able to.

  In addition, when users search and browse information, past information referred to by personal preferences and various types of sensed information can be aggregated and stored, making it possible to generate a centralized personal profile. , It is possible to judge and predict the situation from the profile accumulation, extract the most appropriate information for the situation at that time, select the information for presentation, and the similarity of others even when the situation information is not sufficiently accumulated It is possible to provide a situation prediction system and method based on a personal profile, a program, and a recording medium, which can provide an optimum information presentation service by searching and synthesizing situations.

The block diagram for demonstrating the whole structure by 1st Embodiment which concerns on the prediction system by the personal profile of this invention is shown. The block diagram for demonstrating the various sensors by the 1st Embodiment which concerns on the prediction system by the personal profile of this invention, a condition collection means, and an encryption means is shown. The block diagram for demonstrating the transfer means and the transfer destination solution means by 1st Embodiment which concerns on the prediction system by the personal profile of this invention is shown. The block diagram for demonstrating the condition storage means by 1st Embodiment which concerns on the prediction system by the personal profile of this invention is shown. The block diagram for demonstrating the meta situation discrimination | determination prediction means by 1st Embodiment which concerns on the prediction system by the personal profile of this invention is shown. The block diagram for demonstrating the information reference means and individual identification means by 1st Embodiment which concerns on the prediction system by the personal profile of this invention is shown. The block diagram for demonstrating the compensation of the situation information when the situation information accumulation | storage is inadequate by 2nd Embodiment which concerns on the prediction system by the personal profile of this invention is shown.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Various sensors 2 Status collection means 3 Encryption means 4 Transfer means 5 Transfer destination solution means 6 Decryption means 7 Status storage means 8 Meta situation determination 9 Information reference means 10 Individual identification means 11 Referenced information

Claims (20)

A person who predicts the situation according to the personal profile and environmental conditions of the user for information searched and browsed by the user via the network, and provides the information generated based on the prediction via the network A situation prediction method using a profile,
Detecting the environmental condition by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal;
Collecting the status information by status collection means for collecting the environmental conditions detected by the sensor as status information of the user;
Storing the status information by status information storage means for storing the status information about the user collected by the status collection means as low-level status information included in the personal profile;
Clustering the user's past situation information stored in the situation information storage means to generate high level situation information included in the personal profile, and based on the high level situation information, changes in the situation information Generating a transition pattern to indicate, and performing the prediction by meta-situation determination prediction means for predicting a time-series change of the current situation information of the user based on the transition pattern;
Extracting the information by information extraction means for extracting information that the user searches and browses based on the prediction of the meta-situation determination prediction means;
Identifying the individual by means of personal identification for identifying and providing the user with the information extracted by the information extraction means;
A situation prediction method based on a personal profile, characterized by comprising: The meta-situation determination / prediction means includes:
In the case where the prediction is not reached due to the lack of the situation information, the situation information similar to the situation information of the user is obtained from a user other than the user, and similar situation information acquisition means for compensating for the lack The situation prediction method according to claim 1, comprising: a personal profile according to claim 1. The meta-situation determination / prediction means includes:
3. The situation prediction method according to claim 1, wherein the situation information accumulated in time series is predicted by an autoregressive model. The low level status information and the high level status information are:
It is metadata, The situation prediction method by the personal profile in any one of Claims 1-3 characterized by the above-mentioned. The situation collecting means includes
The situation prediction method according to any one of claims 1 to 4, wherein all the situation information to be collected is converted into a cipher for information processing. A person who predicts the situation according to the personal profile and environmental conditions of the user for information searched and browsed by the user via the network, and provides the information generated based on the prediction via the network A situation prediction system using a profile,
A sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal;
Status collection means for collecting the environmental conditions detected by the sensor as status information of the user;
Status information storage means for storing the status information about the user collected by the status collection means as low-level status information included in the personal profile;
Clustering the user's past situation information stored in the situation information storage means to generate high level situation information included in the personal profile, and based on the high level situation information, changes in the situation information A meta-situation determination / prediction unit that generates a transition pattern to be shown and predicts a time-series change of the current situation information of the user based on the transition pattern;
Information extraction means for extracting information that the user searches and browses based on the prediction of the meta-situation determination prediction means;
Personal identification means for identifying and providing the user's individual with the information extracted by the information extraction means;
A situation prediction system using a personal profile. The meta-situation determination / prediction means includes:
In the case where the prediction is not reached due to the lack of the situation information, the situation information similar to the situation information of the user is obtained from a user other than the user, and similar situation information acquisition means for compensating for the lack The situation prediction system according to claim 6, comprising: a personal profile according to claim 6. The meta-situation determination / prediction means includes:
8. The situation prediction system according to claim 6, wherein the situation information accumulated in time series is predicted by an autoregressive model. The low level status information and the high level status information are:
It is metadata, The situation prediction system by the personal profile in any one of Claims 6-8 characterized by the above-mentioned. The situation collecting means includes
The situation prediction system based on a personal profile according to any one of claims 6 to 9, wherein all the situation information to be collected is converted into a cipher and processed. A person who predicts the situation according to the personal profile and environmental conditions of the user for information searched and browsed by the user via the network, and provides the information generated based on the prediction via the network A situation prediction program using a profile,
Detecting the environmental condition by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal;
Collecting the status information by status collection means for collecting the environmental conditions detected by the sensor as status information of the user;
Storing the status information by status information storage means for storing the status information about the user collected by the status collection means as low-level status information included in the personal profile;
Clustering the user's past situation information stored in the situation information storage means to generate high level situation information included in the personal profile, and based on the high level situation information, changes in the situation information Generating a transition pattern to indicate, and performing the prediction by meta-situation determination prediction means for predicting a time-series change of the current situation information of the user based on the transition pattern;
Extracting the information by information extraction means for extracting information that the user searches and browses based on the prediction of the meta-situation determination prediction means;
Identifying the individual by means of personal identification for identifying and providing the user with the information extracted by the information extraction means;
A situation prediction program based on a personal profile, characterized by comprising: The meta-situation determination / prediction means includes:
In the case where the prediction is not reached due to the lack of the situation information, the situation information similar to the situation information of the user is obtained from a user other than the user, and similar situation information acquisition means for compensating for the lack The situation prediction program according to claim 11, comprising: a personal profile according to claim 11. The meta-situation determination / prediction means includes:
The situation prediction program according to any one of claims 11 and 12, wherein the situation information accumulated in time series is predicted by an autoregressive model. The low level status information and the high level status information are:
The situation prediction program according to any one of claims 11 to 13, which is metadata. The situation collecting means includes
The situation prediction program according to any one of claims 11 to 14, wherein the situation information to be collected is all converted into encryption to be processed. A person who predicts the situation according to the personal profile and environmental conditions of the user for information searched and browsed by the user via the network, and provides the information generated based on the prediction via the network A recording medium that records a situation prediction program based on a profile,
Detecting the environmental condition by a sensor for detecting the environmental condition placed by the user and outputting it as an electrical signal;
Collecting the status information by status collection means for collecting the environmental conditions detected by the sensor as status information of the user;
Storing the status information by status information storage means for storing the status information about the user collected by the status collection means as low-level status information included in the personal profile;
Clustering the user's past situation information stored in the situation information storage means to generate high level situation information included in the personal profile, and based on the high level situation information, changes in the situation information Generating a transition pattern to indicate, and performing the prediction by meta-situation determination prediction means for predicting a time-series change of the current situation information of the user based on the transition pattern;
Extracting the information by information extraction means for extracting information that the user searches and browses based on the prediction of the meta-situation determination prediction means;
Identifying the individual by means of personal identification for identifying and providing the user with the information extracted by the information extraction means;
The recording medium which recorded the situation prediction program by the personal profile characterized by having. The meta-situation determination / prediction means includes:
In the case where the prediction is not reached due to the lack of the situation information, the situation information similar to the situation information of the user is obtained from a user other than the user, and similar situation information acquisition means for compensating for the lack The recording medium which recorded the situation prediction program by the personal profile of Claim 16 characterized by the above-mentioned. The meta-situation determination / prediction means includes:
18. The recording medium recording the situation prediction program according to claim 16 or 17, wherein the situation information accumulated in time series is predicted by an autoregressive model. The low level status information and the high level status information are:
19. A recording medium recording a situation prediction program based on a personal profile according to claim 16, wherein the recording medium is metadata. The situation collecting means includes
20. The recording medium recorded with the situation prediction program according to any one of claims 16 to 19, wherein all the situation information to be collected is converted into encryption for information processing.

Images