JP4844669B2 - Information provision system - Google Patents

Description

  The present invention relates to an information providing system, and more particularly to an information providing system that provides store information regarding various stores using a network.

  In recent years, information providing means is shifting from the conventional information providing method using broadcasting such as television and radio to a new information providing method using a web page on the Internet. In particular, with the widespread use of mobile terminal devices such as mobile phones, users can access necessary information from any location, and convenience is greatly enhanced. In addition, for business operators who provide products and services, store advertisements and guidance information can be widely provided to users via Web pages. When the user goes out, the user can obtain various information about the store to be used by browsing such a Web page in advance.

  In this way, when accessing information using the Internet, it is important to extract information that matches one's request from a large amount of information. For this reason, the user performs a search using a desired keyword using a search site, and accesses a Web page on which necessary information is presented. For example, when eating or shopping, the user can browse Web pages such as Italian restaurants and women's clothing stores by searching using keywords such as “Italian cuisine” and “Women's clothing”.

  Various techniques have been proposed in order to efficiently provide appropriate information to individual users. For example, Patent Document 1 below discloses an information distribution system that collects information indicating individual user's preferences in advance and provides information that matches the individual's preferences. Discloses a method of storing each user's preference level as a profile based on situation information including a companion. Furthermore, Patent Literature 3 below discloses a preference learning device that learns a user's preference based on the user's behavior history.

JP 2003-296358 A JP 2004-326111 A JP 2002-108918 A

  As disclosed in the above-mentioned patent documents, several techniques for grasping individual user's preferences and providing appropriate information to each user have already been proposed. However, since it is difficult for any of the techniques to accurately grasp the preference information of individual users, it is difficult to provide information that accurately reflects user preferences.

  Therefore, an object of the present invention is to provide an information providing system capable of accurately grasping individual user preferences and providing information that accurately reflects the user preferences.

(1) According to a first aspect of the present invention, in an information providing system,
A store information storage unit storing store information about individual stores,
A store evaluation information storage unit for storing store evaluation information including a store ID for specifying a store and an evaluation value of the store for a predetermined specific characteristic item for each of various stores;
A user preference information storage unit that stores user preference information including a user ID for identifying a user and a preference value of the user for a feature item for each of various users;
When a request for providing store information that matches a specific search condition is received from a user, the “user preference information of the user stored in the user preference information storage unit” and the “store evaluation information storage unit Store information that matches the search criteria and is suitable for the user by comparing the preference value and evaluation value of the corresponding feature item for “store evaluation information for various stores” Is selected based on the similarity between the preference value to be compared and the evaluation value, the selected store information is extracted from the store information storage unit, and this is provided to the terminal device of the user. A providing department;
When a plurality of users use a specific store as a group, group configuration information for identifying users constituting the group, a user ID for identifying individual users, and individual users A personal satisfaction information recording unit for accumulating and recording personal satisfaction information including satisfaction,
Based on all or a part of the personal satisfaction information recorded in the personal satisfaction information recording section, use the satisfaction ratio between users under the group usage condition of “use a store in a specific group” for calculation A satisfaction ratio calculation unit that calculates the ratio of the average value of each individual user of the personal satisfaction included in the personal satisfaction information,
Provided,
When the store information provider receives a request to provide store information under a specific group usage condition, each store information candidate is individually selected from the appropriate store information candidates for each individual user according to the specific group usage condition. The store information is selected and provided for each user according to the satisfaction ratio.

(2) According to a second aspect of the present invention, in the information providing system according to the first aspect described above,
An interest store recording unit that stores and records the store ID of the specific store as the store of interest ID for each individual user when the user indicates interest in the specific store;
For each individual user, all or a part of the store IDs recorded in the store of interest store are extracted as store IDs for update, and the store evaluation information including the store ID for update is updated from the store evaluation information storage unit. Preference value update that is extracted as store evaluation information and updates the preference value of the user preference information for the user stored in the user preference information storage unit based on the evaluation value of the update store evaluation information And
Is further provided.

(3) According to a third aspect of the present invention, in the information providing system according to the first aspect described above,
A voting result recording unit for accumulating and recording the voting result when a personal evaluation value for a feature item of a specific store is voted by a user;
For each store, all or part of the voting results recorded in the voting result recording unit are extracted, and based on the extracted voting results, the store evaluation for the store stored in the store evaluation information storage unit An evaluation value update unit for updating the evaluation value of the information;
Is further provided.

(4) According to a fourth aspect of the present invention, in the information providing system,
A store information storage unit storing store information about individual stores,
Store evaluation information including a store ID for specifying a store, a genre code indicating the genre of the store, and an evaluation value of the store for a specific feature item determined in advance corresponding to the genre code A store evaluation information storage unit storing various stores,
User preference information including a user ID for identifying a user, a genre code, and a preference value of the user for a feature item corresponding to the genre code is stored for each of various users. A user preference information storage unit;
When a request for providing store information that matches a specific search condition is received from a user, the “user preference information of the user stored in the user preference information storage unit” and the “store evaluation information storage unit Store information that matches the search criteria and is suitable for the user by comparing the preference value and evaluation value of the corresponding feature item for “store evaluation information for various stores” Is selected based on the similarity between the preference value to be compared and the evaluation value, the selected store information is extracted from the store information storage unit, and this is provided to the terminal device of the user. A providing department;
When a plurality of users use a specific store as a group, group configuration information for specifying users constituting the group, a genre of the used stores, and a user ID for specifying individual users And a personal satisfaction information recording unit for accumulating and recording personal satisfaction information including the user's personal satisfaction level,
Based on the personal satisfaction information recorded in the personal satisfaction information recording unit, the satisfaction ratio between users under the group usage condition of “use a store of a specific genre in a specific group” is used for calculation. A satisfaction ratio calculation unit that calculates the ratio of the average value of each individual user of the personal satisfaction included in the personal satisfaction information;
Provided,
When the store information provider receives a request to provide store information under a specific group usage condition, each store information candidate is individually selected from the appropriate store information candidates for each individual user according to the specific group usage condition. The store information is selected and provided for each user according to the satisfaction ratio.

(5) According to a fifth aspect of the present invention, in the information providing system according to the fourth aspect described above,
An interest store recording unit that stores and records the store ID of the specific store as an interest store ID for each individual user and for each genre when the user indicates interest in the specific store. When,
For each individual user, “all or a part of the store IDs of a predetermined genre to be updated” recorded in the store of interest store is extracted as the store ID for update and updated from the store evaluation information storage unit. The store evaluation information including the store ID is extracted as the update store evaluation information, and the update target for the user stored in the user preference information storage unit is based on the evaluation value of the update store evaluation information. A preference value update unit for updating a preference value of user preference information relating to a predetermined genre,
Is further provided.

(6) According to a sixth aspect of the present invention, in the information providing system according to the fourth aspect described above,
A voting result recording unit for accumulating and recording the voting result for each individual store when a personal evaluation value for a characteristic item of a specific store is voted by a user;
For each store, all or part of the voting results recorded in the voting result recording unit are extracted, and based on the extracted voting results, the store evaluation for the store stored in the store evaluation information storage unit An evaluation value update unit for updating the evaluation value of the information;
Is further provided.

(7) According to a seventh aspect of the present invention, in the information providing system according to the above fourth to sixth aspects,
When each user uses a specific store, an action history information collection unit that collects action history information including the user ID of the user, the genre code of the store, and the usage time;
An action history information storage unit for storing the collected action history information;
A subsequent genre prediction unit that predicts a genre that is likely to be used after a specific user uses a predetermined genre based on the action history information;
Further provided,
The store information providing unit uses the prediction result by the subsequent genre prediction unit to provide store information related to the genre related to the store information as additional information together with the store information corresponding to the provision request from the user. It is what I did.

(8) An eighth aspect of the present invention is the information providing system according to the first to seventh aspects described above,
The store information providing unit has a function of transmitting Web content data to a terminal device operated by a user via the Internet. Store information is stored as Web content data in the store information storage unit. The content ID for specifying the Web content data is used as the store ID.

(9) According to a ninth aspect of the present invention, in the information providing system according to the first to eighth aspects described above,
Store evaluation information containing evaluation values for each of a plurality of N feature items is stored in the store evaluation information storage unit,
User preference information including preference values for each of a plurality of N feature items is stored in the user preference information storage unit,
When the store information providing unit receives a store information provision request from a user, “the preference value for each of the N feature items included in the user preference information of the user is expressed in N-dimensional coordinates. "Preference vector obtained by taking each coordinate axis of system" and "Evaluation value for each of N feature items included in store evaluation information of each store is taken to each coordinate axis of N-dimensional coordinate system" Is compared with the evaluation vector obtained by the above, and the store information is selected based on the degree of approximation of both vectors.

(10) According to a tenth aspect of the present invention, in the information providing system according to the first to ninth aspects described above,
When the store information providing unit provides the store information, the store information providing unit also provides an evaluation value included in the store evaluation information about the store related to the store information.

(11) An eleventh aspect of the present invention is the information providing system according to the above first to tenth aspects,
A first providing step in which the store information providing unit selects a plurality of store information that matches the search condition and is suitable for the user, and provides a list in which only an overview of each selected store information is provided; And a second providing step of providing all the contents of the store information relating to the store designated by the user from the list.

(12) According to a twelfth aspect of the present invention, in the information providing system according to the second or fifth aspect described above,
A first providing step in which the store information providing unit selects a plurality of store information that matches the search condition and is suitable for the user, and provides a list in which only an overview of each selected store information is provided; A second providing step of providing all the contents of the store information relating to the store designated by the user from the list,
When the store information providing unit performs the second providing step based on the user's specification, the store store of interest stores the store ID of the store for which the store information is provided in the second providing step. Is stored and recorded as the store ID of interest for the person.

(13) In a thirteenth aspect of the present invention, in the information providing system according to the second, fifth, and twelfth aspects described above,
When the store of interest record receives a report from a user that he / she is interested in a specific store, or when he / she receives a report that he / she has used a specific store, The store ID is stored and recorded as the store ID of interest.

(14) According to a fourteenth aspect of the present invention, in the information providing system according to the second, fifth, twelfth and thirteenth aspects described above,
The store information providing unit has a function of providing store information to the mobile terminal device possessed by the user,
If the store of interest is detected based on information from the position recognition device having a function of recognizing the position of the mobile terminal device, when the user is detected to be located in a specific store, The store ID of the store is accumulated and recorded as the store ID of interest.

(15) The fifteenth aspect of the present invention is the information providing system according to the second, fifth, twelfth to fourteenth aspects described above,
The store information providing unit has a function of providing store information to the mobile terminal device possessed by the user,
When a store of interest stores a communication between a store installation device installed in a predetermined store and a mobile terminal device, the user receives a notification from the store installation device or the mobile terminal device, and The store ID of the store is accumulated and recorded as the store ID of interest.

(16) According to a sixteenth aspect of the present invention, in the information providing system according to the second, fifth, twelfth to fifteenth aspects,
The interested store recording unit records the time information at the time of recording when recording the interested store ID,
The preference value update unit is configured to extract, as the update store ID, only the store IDs of interest recorded in the store of interest recording unit that are recorded within a predetermined period.

(17) According to a seventeenth aspect of the present invention, in the information providing system according to the second, fifth, and twelfth to sixteenth aspects described above,
The preference value update unit updates the average value of the evaluation values of the update store evaluation information to a new preference value of the user preference information.

(18) According to an eighteenth aspect of the present invention, in the information providing system according to the third or sixth aspect described above,
When the voting result recording unit records the voting result, it also records the time information at the time of recording,
The evaluation value update unit extracts only the voting results recorded in the voting result recording unit and records the evaluation value of the store evaluation information by extracting only those within the predetermined period.

(19) According to a nineteenth aspect of the present invention, in the information providing system according to the third, sixth, and eighteenth aspects described above,
The evaluation value update unit updates the average value of the individual evaluation values included in the extracted voting results as a new evaluation value of the store evaluation information.

(20) In a twentieth aspect of the present invention, in the information providing system according to the first to nineteenth aspects described above,
When the personal satisfaction information recording unit records personal satisfaction information, it also records the time information at the time of recording,
The satisfaction ratio calculation unit calculates the satisfaction ratio by using only the personal satisfaction information recorded in the personal satisfaction information recording unit that is recorded within a predetermined period.

(21) According to a twenty-first aspect of the present invention, in the information providing system according to the first to twentieth aspects described above,
Probability according to the direct ratio of satisfaction ratio for each individual user, or satisfaction ratio for each individual user, from the store information candidates suitable for each individual user. The store information is selected and provided with a probability corresponding to the inverse ratio.

  In the information providing system of the present invention, store evaluation information is set for each individual store, and by comparing with the user preference information set for each individual user, the individual user's preference is accurately determined. It is possible to grasp and provide information that accurately reflects the user's preference. Further, in the case of the invention according to the first embodiment described in §1, the user's preference information is updated based on the store evaluation information about the store in which the user has shown interest. During operation, it will be possible to automatically collect the exact preferences of individual users. Further, in the case of the invention according to the second embodiment described in §6, since the store evaluation information is automatically updated by the vote of the user, the store evaluation information is always alive reflecting the trend. The effect of keeping information is also obtained. On the other hand, in the case of the invention according to the third embodiment described in §7, there is an additional effect that more appropriate information can be provided in consideration of the presence of a companion, which will be described in §8. In the case of the invention according to the fourth embodiment, it is possible to obtain an additional effect that more appropriate information can be provided after the user's behavior is predicted.

It is a block diagram which shows the basic composition of the information provision system which concerns on the 1st Embodiment of this invention. It is a top view which shows the example of a display of the shop information stored in the shop information storage part 100 of the information provision system shown in FIG. It is a table | surface which shows an example of the genre defined in the information provision system which concerns on this invention. It is a figure which shows the structural example of the store evaluation information E stored in the store evaluation information storage part 120 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a schematic diagram which shows the concept of the evaluation value contained in the shop evaluation information of the information provision system which concerns on this invention, and the preference value contained in user preference information. It is a figure which shows the structural example of the user preference information T stored in the user preference information storage part 110 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a figure which shows an example of the summary list | wrist of the shop information selected by the selection selection process of the shop information in the shop information provision part 130 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a perspective view of the vector space used for the selection process of store information in the store information provision part 130 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a figure which shows an example of interested store ID recorded in the interested store recording part 150 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a figure which shows an example of the shop evaluation information for an update extracted by the preference value update part 140 of the information provision system which concerns on 1st Embodiment shown in FIG. It is a block diagram which shows the basic composition of the information provision system which concerns on the 2nd Embodiment of this invention. It is a figure which shows an example of the screen for voting shown by the voting result recording part 170 of the information provision system which concerns on 2nd Embodiment shown in FIG. 11 shows an example of the voting result (personal evaluation information) recorded in the voting result recording unit 170 of the information providing system according to the second embodiment shown in FIG. 11 and the store evaluation information updated by the processing of the evaluation value updating unit 160. FIG. It is a block diagram which shows the basic composition of the information provision system which concerns on the 3rd Embodiment of this invention. It is a figure which shows an example of the screen for satisfaction information input shown by the personal satisfaction information recording part 190 of the information provision system which concerns on 3rd Embodiment shown in FIG. It is a figure which shows an example of the input screen which integrated the screen for voting shown in FIG. 12, and the satisfaction information input screen shown in FIG. It is a figure which shows an example of the personal satisfaction information recorded in the personal satisfaction information recording part 190 of the information provision system which concerns on 3rd Embodiment shown in FIG. 14 shows a concept of processing in which the store information providing unit 130 selects store information based on the satisfaction rate ratio calculated by the satisfaction rate calculating unit 180 of the information providing system according to the third embodiment shown in FIG. FIG. It is a block diagram which shows the basic composition of the information provision system which concerns on the 4th Embodiment of this invention. It is a figure which shows an example of the action history information stored in the action history information storage part 220 of the information provision system which concerns on 4th Embodiment shown in FIG. It is a figure which shows an example of the presentation form of the additional information in the information provision system which concerns on 4th Embodiment shown in FIG. It is a figure which shows another example of the presentation form of the additional information in the information provision system which concerns on 4th Embodiment shown in FIG.

  Hereinafter, the present invention will be described based on the illustrated embodiments.

<<< §1. Basic configuration of the first embodiment >>
FIG. 1 is a block diagram showing a basic configuration of an information providing system according to the first embodiment of the present invention. The first embodiment is the most basic embodiment of the present invention, and has a function of accurately grasping each user's preference and providing information that accurately reflects the user's preference.

  As shown in the figure, this information providing system includes a store information storage unit 100, a user preference information storage unit 110, a store evaluation information storage unit 120, a store information provision unit 130, a preference value update unit 140, and an interested store recording unit 150. Consists of components, and has a function of providing store information prepared in the store information storage unit 100 to the user terminals 10, 20, and 30 operated by each user via the Internet 200. Here, for convenience of explanation, each component is shown as an independent block. However, in practice, the information providing system according to the present embodiment is realized by incorporating a dedicated program into a server computer. Each block component shown in the figure is configured by incorporating software for performing each processing described later into hardware such as a CPU and a storage device of the server computer.

  The outline of the operation of this system is as follows. First, the user preference information storage unit 110 stores, for each user, user preference information T including preference values for feature items of each genre, and the store evaluation information storage unit 120 stores information for each store. In addition, store evaluation information E including an evaluation value for the feature item of the genre is stored. The store information providing unit 130 selects store information having store evaluation information E that matches the user preference information T, and provides the selected store information to the user terminal device. Further, when the user browses the specific store information or uses the specific store, the specific store is accumulated in the store of interest recording unit 150 as the store of interest. The preference value update unit 140 updates the user preference information T based on the stored store evaluation information E of the store of interest. Hereinafter, a mechanism for performing such an operation will be described in detail.

  The store information storage unit 100 has a function of storing store information regarding individual stores. Here, store information widely means information on advertisements and guidance of individual stores. In the illustrated embodiment, store information is provided to each user terminal 10, 20, 30 via the Internet 200 by the store information providing unit 130. For this reason, each store information is stored in the store information storage unit 100 as Web content data (for example, a file in HTML format), and the store information providing unit 130 is connected to each user via the Internet 200. It has a function of transmitting this Web content data to the terminals 10, 20, and 30. Each of the user terminals 10, 20, and 30 has a web browser function, and the user can use the web content data (that is, provided) on the display screen of each of the user terminals 10, 20, and 30. Store information).

  FIG. 1 shows an example in which the user terminal 10 is constituted by a mobile phone, the user terminal 20 is constituted by a notebook personal computer, and the user terminal 30 is constituted by a desktop personal computer. Is not limited to these terminal devices, and any terminal device may be used as long as it has a web browser function for receiving and browsing web content data. Further, FIG. 1 shows only three user terminals, but when this information providing system is operated commercially, a larger number of user terminals are used.

  FIG. 2 is a plan view showing a display example of store information stored in the store information storage unit 100 of the information providing system shown in FIG. As described above, in the case of the embodiment shown here, each store information is composed of web content data, and the display examples shown in FIG. 2 are all web page display screens by a web browser. Generally speaking, there are various types of stores such as restaurants, coffee shops and department stores. Therefore, in the embodiment shown here, several genres are defined in order to specify the type of store. FIGS. 2 (a), (b), and (c) are store information of stores (Italian restaurants) that fall into the genre of “Italian cuisine”. FIGS. 2 (d), (e), and (f) Are store information of stores (women's clothing stores) that fall into the genre of “women's clothing”, and FIGS. 2 (g), (h), and (i) are stores that fall into the genre of “movie” ( It is store information of a movie theater.

  For example, the store information “S1301” shown in FIG. 2A is a web page of an Italian restaurant “Ristorante PAT”, and the store information “S1302” shown in FIG. 2B is “boiled spaghetti” It is a web page of an Italian restaurant called “Store XYZ”. Here, codes “S1301” and “S1302” indicating individual store information are content IDs (for example, file names of HTML data) for specifying the Web content data. In the case of the example described here, one piece of store information (Web content data) is information about advertisement or guidance regarding one store, and store information and stores correspond one-to-one. Therefore, in the embodiment described below, an example will be described in which a content ID for specifying Web content data is used as it is as a store ID. For example, an ID code “S1301” is a content ID for specifying Web content data for displaying a Web page as shown in FIG. 2A, and an Italian restaurant “Ristorante PAT” is specified. It is also a store ID for specifying.

  Of course, store information (Web content data) and stores do not necessarily have to correspond one-to-one, and a plurality of store information may be prepared for one store, and information on advertisements and guidance for a plurality of stores. One store information including may be prepared. In this case, since the content ID for specifying individual store information and the store ID for specifying individual stores need to use different ID codes, which content data is information about which store. Prepare some correspondence table so that it can be recognized.

  In the embodiment described here, a genre code is assigned to each genre. For example, FIG. 2 shows the headings “Genre G13: Italian Cuisine”, “Genre G32: Women's Clothing”, and “Genre G41: Movie”, which are genre codes of the genre “Italian Cuisine”. Is G13, the genre code of the genre “women's clothing” is G32, and the genre code of the genre “movie” is G41. For convenience of explanation, here, the first two digits of the four-digit number of the content ID (store ID) are matched with the two-digit number of the genre code of the genre to which the store belongs. For example, the store information S1301 shown in FIG. 2 (a) is store information with “S1301” added as the content ID (store ID), but the first two digits “13” of the four-digit number is the genre code G13. To the two digits “13”.

  FIG. 3 is a table showing an example of a genre defined in the information providing system according to the present invention. In this example, first, the type of each store is roughly divided into major categories, and then a hierarchical structure is defined in which fine genres are defined for each major category. For example, the genre of “Japanese cuisine”, “French cuisine”, “Italian cuisine”, and “Mexican cuisine” is defined in the broad category “meals”, and genre codes G11, G12, G13, and G14 are defined, respectively. . Similarly, the genre of “pure coffee”, “jazz cafe”, and “accompanied cafe” is defined in the large category “cafe”, and genre codes G21, G22, and G23 are respectively defined. Of course, the genre shown in FIG. 3 is shown as an example, and the system designer arbitrarily determines items such as what genre is set and what hierarchical structure is set for the genre. It should be a matter.

  In the present application, the term “store” is used as a word meaning a wide range of facilities and places that provide various products and services to users, and is a narrowly-known term called “shop”. It includes not only stores but also outdoor facilities. For example, the major categories “show” in FIG. 3 define the genres of “movie”, “theater”, “partner”, and “concert”, which are “movie theater”, “theater”, and “concert”. “Hall”, “open-air music field” and the like mean to be included in the “store” in the present application. Similarly, “outdoor amusement park”, “baseball field”, “soccer field”, “golf field”, “pool”, etc. are also “stores” in the present application, such as “hotel”, “inn”, “pension”, etc. Is also a “store” as used herein.

  The store evaluation information storage unit 120 shown in FIG. 1 stores store evaluation information E for various stores whose store information is stored in the store information storage unit 100. This store evaluation information E is information for quantitatively evaluating various features such as features of products and services to be provided, features regarding prices, features of locations provided, features of store staff, etc. for each store. In the present invention, the store evaluation information E is a store ID for identifying the store (in the case of the embodiment described here, as described above, the content ID of the store information is used as the store ID as it is), and the store The information includes a genre code indicating the genre of the store and an evaluation value of the store for a specific feature item determined in advance corresponding to the genre code.

  FIG. 4 is a diagram illustrating a configuration example of the store evaluation information E stored in the store evaluation information storage unit 120. FIGS. 4A to 4I show an example of the store evaluation information for the nine stores whose store information (Web page) is shown in FIGS. 2A to 2I. For example, store evaluation information E1301 shown in FIG. 4 (a) is store information about a store called “Ristorante PAT” whose store information is posted on the Web page of FIG. 2 (a), and store ID “S1301”. , Genre code “G13” and evaluation values of three types of feature items (formality, volume, price). The store evaluation information E1301 includes a genre (Italian cuisine) indicated by the genre code “G13” as a genre of the store specified by the store ID “S1301”, and a characteristic (atmosphere in the store). ) Is 95, the volume (amount of food provided) is 20, and the price (price of the provided item) is 80.

  Here, for convenience of explanation, it is assumed that each evaluation value takes a value in the range of 0 to 100, and when the evaluation value of a specific feature item is 100, the feature is most prominent or the degree of the feature is the highest. When the evaluation value of a specific feature item is 0, it indicates that the feature is the least hidden or the feature level is the lowest. For example, it is evaluated that the Italian restaurant to be evaluated in the store evaluation information E1301 in FIG. 4 (a) is a store with a very formal atmosphere, with a small amount of ingredients and a fairly high price. Will be receiving. On the other hand, the Italian restaurant to be evaluated in the store evaluation information E1302 in FIG. 4 (b) is “boiled spaghetti store XYZ” whose store information is posted on the Web page in FIG. 2 (b). Given that the evaluation values are 20: Volume: 83, Price: 32, it is a store with a fairly casual atmosphere, with a large amount of ingredients and a relatively low price. Will be receiving.

  In addition, if it is a store of the same genre, it is possible to evaluate the same feature item, but it may be inappropriate to apply the same feature item as it is in a store of a different genre. For example, in the case of a store of the same genre of “Italian cuisine”, it is appropriate to evaluate the characteristic items such as form, volume, and price as in the above-described example. However, in the case of stores of different genres such as “women's clothing” and “movies”, it is usually more appropriate to evaluate different feature items.

  Therefore, in the embodiment described here, specific feature items are predetermined for each genre code. For example, the store evaluation information shown in FIGS. 4 (a), 4 (b) and 4 (c) is all about stores of the genre of “Italian cuisine”, and therefore, characteristic items such as form, volume and price are set. The store evaluation information shown in FIGS. 4 (d), (e), and (f) are all about stores of the genre of “women's clothing”, so modern (design of goods handled), Characteristic items such as age (target customer age) and price (price of offered items) are set, and the store evaluation information shown in FIGS. 4 (g), (h), and (i) are all “movies”. Since it is about stores of a certain genre, characteristic items such as relaxed (seats / interior space), shop (fullness of shop), and midnight (number of late-night screenings) are set.

  Of course, what feature items are set in which genres of stores is an item that the system designer should arbitrarily determine, and the same feature items can be set in different genres (for example, FIG. In the example shown in FIG. 4, the feature item “price” is set in both genres of “Italian cuisine” and “women's clothing”). In the example shown in FIG. 4, three feature items are set for any genre, but the number of feature items to be set for each genre is also determined by the system designer. It is a matter to be decided.

  FIG. 5 is a schematic diagram showing the concept of each evaluation value included in the store evaluation information illustrated in FIG. On the left side of the figure, the title of each feature item is described, and on the right side of the figure, a number line indicating an evaluation value of 0 to 100 is drawn. As described above, the feature item set in the present invention may be any item as long as it is a feature that enables some quantitative evaluation. For example, items such as “price” and “age” are originally given as quantitative values, so objective evaluation is possible, but feature items set in the present invention are not necessarily objective evaluation. It is not necessary to make it a simple item. For example, the feature item “Modern” in FIG. 5 is an item indicating a conceptual scale located at both extremes of “Modern” and “Classic”, and when the evaluation value is 100, it is “most modern”. When the evaluation value is 0, it indicates “most classical”. Such an evaluation must be a subjective evaluation, but if a quantitative evaluation is possible, it may be a subjective evaluation.

  In the system according to the present invention, each evaluation value is given by human subjective judgment. Therefore, even for feature items related to objective numerical values such as “price” and “age”, the evaluation value is determined by the subjective judgment of the person to be evaluated. As shown in FIG. 5, evaluation values of “price” and “age” are also expressed by numerical values in the range of 0 to 100, and are not directly related to specific price values or age values. The evaluation criteria such as whether the “price” is high or low varies depending on the person to be evaluated, but in the present invention, it is sufficient if some quantitative evaluation value can be defined. Also, the item “age” shown in FIG. 5 conceptually gives a subjective evaluation of “for middle-aged” or “for younger”. In the end, even for feature items linked to objective numerical values such as “price” and “age”, evaluation values as subjective concepts are practically defined as in the example shown in FIG. It is preferable to do this.

  Next, the user preference information T stored in the user preference information storage unit 110 illustrated in FIG. 1 will be described. This user preference information T is information indicating each preference for various users. In the embodiment shown here, a user ID for identifying a user, a genre code, and this genre code. And the user's preference value for the feature item corresponding to. Here, the feature item corresponding to the genre code matches the feature item set for the store evaluation information E. For example, in the case of the above-described example, three feature items such as form, volume, and price have been set for the genre “Italian cuisine”. Therefore, in the user preference information T, for the genre “Italian cuisine” In the same way, three characteristic items such as form, volume and price are set.

  FIG. 6 is a diagram illustrating a configuration example of the user preference information T stored in the user preference information storage unit 110. The information shown in the figure is user's preference information. That is, the user preference information T A 13 shown in FIG. 6 (a) indicates the user's preference regarding the genre code G13 (Italian cuisine), and the user preference information T A 32 shown in FIG. The user's preference regarding the genre code G32 (women's clothing) is shown, and the user preference information T-41 shown in FIG. 6C shows the preference regarding the user's genre code G41 (movie). The user's preference is expressed by a numerical value called a preference value, and in the case of the embodiment described here, the preference value takes a value in the range of 0 to 100, similar to the evaluation value described above.

  As can be seen by comparing with the store evaluation information of the same genre shown in FIG. 4, the characteristic items of the user preference information (FIG. 6 (a)) regarding “Italian cuisine” are the form, volume, and price. This matches the feature item of the store evaluation information (FIGS. 4A to 4C) regarding “Italian cuisine”. Similarly, the feature items of the user preference information (FIG. 6 (b)) relating to “women's clothing” are modern, age, and price, which are the store evaluation information relating to “women's clothing” (FIG. 4 (d) to ( The feature items of the user preference information relating to “movie” (FIG. 6 (c)) correspond to the feature items of f))), which are relaxed, a store, and midnight, and this is the store evaluation information relating to “movie” (FIG. 4). It matches the feature items (g) to (i)).

  However, the store evaluation information E shown in FIG. 4 indicates the evaluation value of each feature item for each store, but the user preference information shown in FIG. It shows the preference value for each genre. As described above, the preference value included in the user preference information T and the evaluation value included in the store evaluation information E are slightly different in meaning. Common in terms of showing quantitative values within the range. For example, in the user preference information T A13 shown in FIG. 6A, the user A prefers a store with an atmosphere almost intermediate between formal and casual with respect to the genre of “Italian cuisine” (formal: 45), the amount of food is good (volume: 78), and the price is slightly cheaper (price: 42).

  FIG. 6 shows user preference information for the three genres of the user A, but in the user preference information storage unit 110, users for other genres of the user A may be included as necessary. Preference information T is also stored. In addition, the user preference information T is similarly stored not only for the user A but also for other users such as the user B and the user. Of course, it is not necessary to prepare user preference information T of all genres for each user, and it is sufficient to prepare user preference information T for each genre of interest for each user. Here, for convenience, an example in which the kanji characters “A”, “O”, and “A” are used as user IDs of “A”, “O”, and “A” will be described. However, in general, for each individual user, A user ID consisting of symbols using alphabets is defined.

<<< §2. Store information provision processing of the first embodiment >>
Now, as described above, regarding the same genre, when the feature item of the store evaluation information and the feature item of the user preference information are made the same, the process of comparing the preference value and the evaluation value for the same feature item is performed. Can do. The store information providing unit 130 illustrated in FIG. 1 has a function of selecting and providing store information that matches each user's preference by performing such comparison processing. That is, when the store information providing unit 130 receives a request for providing store information that matches a specific search condition from the user, the store information providing unit 130 displays “the user preference of the user stored in the user preference information storage unit 110. Information T "and" store evaluation information E about various stores stored in the store evaluation information storage unit 120 "are compared with each other including the same genre code. As a result, store information that matches the given search condition and is suitable for the user is selected, the selected store information is extracted from the store information storage unit 100, and this is extracted from the user. The processing provided to the terminal device is executed.

  The basic search function itself by the store information providing unit 130 is the same as the function of a general search engine used in a Web page search site. For example, when a user inputs some keyword as a search condition, store information related to this keyword is searched from store information (content data for Web pages) stored in the store information storage unit 100. Will be. In order to enable such a search process, for each piece of store information stored in the store information storage unit 100, a search keyword can be picked up from the contents and saved. That's fine. Since the function of such a general search engine is a well-known technique, detailed description is omitted here.

  In the embodiment shown here, when a user makes a request for providing desired store information to the store information providing unit 130, first, after logging in by entering the user ID, the user inputs a search keyword. Do. Therefore, when the store information providing unit 130 receives a store information provision request from a user, the store information providing unit 130 can identify the user, matches the given search condition, and is suitable for the user. Store information can be selected.

  FIG. 7 shows a case in which after the user A logs in to the store information providing unit 130, the words “Italian”, “restaurant”, and “Shibuya” are entered as search keywords and a store information provision request is made. It is a figure which shows an example of the outline | summary list of the shop information shown from the shop information provision part 130. FIG. When the user A inputs the keywords “Italian”, “Restaurant”, and “Shibuya”, the store information providing unit 130 first stores store information (contents) that hits the keyword by the function of a general search engine. Data). Subsequently, the store evaluation information E corresponding to the individual store information obtained as a search result is read from the store evaluation information storage unit 120, while the user preference information T of the same genre for the user A is stored in the user preference information. The data is read from the unit 110, compared with each other, and selected.

  The display example shown in FIG. 7 is a summary list of store information selected in this way. The items listed in this summary list are only a part (summary part) of the contents of each store information. However, when the user who browses this summary list clicks on the store part of interest, The original full text of the store information will be displayed. For example, when the user clicks on the title part of “1. Boiled spaghetti store XYZ” displayed first in the list, the original Web page as shown in FIG. 2B is displayed. It will be. Thus, as a search result, first, an overview list is first presented, and when a user specifies one store from the list, the technology for displaying the original store information of the store as a Web page has already been developed. Since this is a known technique, a detailed description is omitted here.

  Here, the store information S1301, S1302, shown in FIGS. 2 (a), (b), and (c) for the keywords “Italian”, “Restaurant”, and “Shibuya” due to the function of a general search engine. Consider the case where S1303 is hit and extracted. In this case, the store information providing unit 130 first stores store evaluation information E1301, E1302, and E1303 (FIGS. 4 (a), (b), and (c)) corresponding to the stores from the store evaluation information storage unit 120. read out. Since the genre code in these store evaluation information is G13 (Italian cuisine), the store information providing unit 130 searches the user preference information storage unit 110 for the same user ID: Then, the user preference information T A 13 (FIG. 6A) having the same genre code: G13 is read out. Then, by comparing the two, selection is made as to whether or not each of the store information S1301, S1302, and S1303 is suitable for the user A.

  According to the user preference information T A13 shown in FIG. 6A, the user A has a preference value of 45: Volume: 78, Price: 42 for the genre “Italian cuisine”. Can be recognized. Therefore, the store information providing unit 130 selects an item having an evaluation value close to each of the preference values from the store evaluation information E1301, E1302, and E1303 shown in FIGS. 4 (a), (b), and (c). The store information corresponding to the selected store evaluation information is included in the summary list. The outline of the store information “1. Boiled spaghetti store XYZ” displayed at the top of the list in FIG. 7 is selected in this way.

  For the keywords “Italian”, “Restaurant”, and “Shibuya”, the store information S3202 (store information of the genre “women's clothing”) shown in FIG. In this case, the store evaluation information corresponding to this is the store evaluation information E3202 shown in FIG. Therefore, each evaluation value of the store evaluation information E3202 is compared with the preference value of the user preference information T-32 (FIG. 6B) related to the same genre. In addition, when the user preference information which concerns on the same genre is not prepared, a comparison with a preference value and an evaluation value cannot be performed. If comparison is not possible in this way, the store information may be disqualified and may not be selected as a target to be provided to the user. Conversely, a new genre of store information may be provided to the user. You may make it select as.

  Eventually, the store information providing unit 130 selects a large number of store information stored in the store information storage unit 100 through two screens, and finally presents the selected store information in the overview list for presentation. Will do. Here, the first sieve is a search condition (keyword in the case of the above example) input by the user, and the second sieve is a comparison between the user preference information T and the store evaluation information E. Thus, since only the store information examined through the two sieves is presented to the user, it is possible to provide information reflecting the user's preference.

  The criteria for selection by the second sieve are the similarity between the user preference information T to be compared and the store evaluation information E, that is, the approximation between the preference value and the evaluation value of each feature item to be compared. It will be a degree. In the case of the embodiment shown here, a preference vector defined by each preference value and an evaluation vector defined by each evaluation value are defined, and the selection by the second sieve is performed based on the degree of approximation of both. It is carried out. Let me illustrate this with a specific example.

  Now, according to the first sieve (for example, input of keywords “Italian”, “Restaurant”, “Shibuya”), three store information S1301, S1302, shown in FIGS. Consider the case where S1303 is selected. The second sieve is a process of selecting only those suitable for the user from among these three store information. Specifically, the user preference information T A 13 shown in FIG. This means that the three store evaluation information E1301, E1302, and E1303 shown in FIGS. 4A, 4B, and 4C are compared with each other (the same genre code is compared). ). This comparison is performed on the vector space shown in FIG. This vector space is a three-dimensional coordinate space with three types of feature items defined for the genre of “Italian cuisine”, form, volume, and price on each coordinate axis. As shown in the figure, each coordinate axis has an evaluation value. Or the value of 0-100 which is the setting range of a preference value is defined.

  Both the user preference information T and the store evaluation information E can be defined as vectors in this vector space. For example, the user preference information T A13 shown in FIG. 6 (a) is defined as a preference vector Vt0 from the origin O to the point T0 indicated by the coordinate values (45, 78, 42), as shown in FIG. 4 (a). The store evaluation information E1301 shown is defined as an evaluation vector Ve1 from the origin O to the point E1 indicated by the coordinate value (95, 20, 80), and the store evaluation information E1302 shown in FIG. The store evaluation information E1303 shown in FIG. 4C is defined as a coordinate value (53, 62, 51) from the origin O, defined as an evaluation vector Ve2 toward the point E2 indicated by the value (20, 83, 32). It is defined as an evaluation vector Ve3 toward the point E3.

  The degree of approximation of the two vectors can be defined by the Euclidean distance in the coordinate space of the two end points. For example, the degree of approximation between the preference vector Vt0 and the evaluation vector Ve1 is indicated by the distance between the two points T0-E1. The shorter the distance, the higher the degree of approximation. The selection by the second sieve can be performed based on the degree of approximation (distance between tip points) between the user preference vector and the evaluation vector of each store. The selection criteria can be set in various ways. For example, if the criterion “select only store information related to stores whose tip-to-point distance is equal to or less than a predetermined value α (approximate degree is equal to or higher than a predetermined level)” is close to the user's preference value. A selection is made based on an absolute criterion of whether or not it has an evaluation value. On the other hand, if the criterion of “sorting in ascending order of the distance between the tip points and selecting only the store information relating to the top m stores as the presentation target” is set, the store information passing through the first sieve Among them, selection based on a relative criterion of selecting m pieces of store information in descending order of approximation is performed.

  As described above, when there are three feature items, vectors are compared on the three-dimensional coordinate space as shown in FIG. 8, but when there are four feature items, the four-dimensional coordinate space is present. The vector may be compared above. Similarly, store evaluation information E including evaluation values for each of a plurality of N feature items is stored in the store evaluation information storage unit 120, and a plurality of N feature items are stored in the user preference information storage unit 110. When the user preference information T including the preference value for each of the above is expanded to the general theory in which the user preference information T is stored, the second screen may be selected by the following method. That is, when the store information providing unit 130 receives a store information provision request from a user, “the preference value for each of the N feature items included in the user preference information T of the user is determined. , “Preference vector obtained by taking each coordinate axis of N-dimensional coordinate system” and “evaluation value for each of N feature items included in store evaluation information E of each store that passed through the first sieve” Is compared with an evaluation vector obtained by taking each coordinate axis of the N-dimensional coordinate system ”, and store information may be selected based on the degree of approximation (distance between tip points) of both vectors.

  In addition, when presenting a plurality of store information passing through the second sieve as an outline list as shown in FIG. 7, the information is sorted in descending order of vector approximation (in order of shortest distance between tip points). Therefore, it is preferable to present it. This is because a user who has received a list as shown in FIG. 7 usually tends to preferentially select and click an item at the top of the list. If the items are sorted and presented in descending order of the degree of approximation, the higher the degree of approximation, the higher the probability of being selected.

<<< §3. Update processing of first embodiment >>>
Now, in §1 and §2, the basic functions of the store information storage unit 100, the user preference information storage unit 110, the store evaluation information storage unit 120, and the store information provision unit 130 in the information providing system shown in FIG. It has been stated that the functions of these units can provide information that reflects user preferences. However, in order to accurately grasp the user's preference and to provide information that accurately reflects the user's preference, the above components alone are not sufficient. The reason is that it is practically difficult to prepare user preference information T that accurately grasps individual user preferences in the user preference information storage unit 110. Of course, there has also been an operation that allows users to input hobbies and interests through questionnaire surveys on Web pages. However, in such surveys, as described in §1 It is difficult to collect detailed user preference information.

  For example, FIG. 6 illustrates user preference information for three genres of user A. In this example, since three feature items are set for each genre, in order to prepare user preference information for the three genres, a range of 0 to 100 is set for each of the nine feature items in total. A predetermined preference value to be taken must be set. When the number of feature items for each genre is larger or when it is necessary to prepare preference information for a large number of genres, the number of preference values to be set further increases. Moreover, since the preference value of each user is information that can only be known by the individual user, in order to prepare the user preference information T for each user in the user preference information storage unit 110, individual usage It is necessary for the user to input preference value settings. It is not realistic for the user to perform such a laborious input operation as a questionnaire. Further, since the user's preference changes with the passage of time, it is necessary to frequently correct the preference value in order to accurately grasp the user's preference at each time point. It is extremely difficult to impose such efforts on individual general users.

  A significant feature of the information providing system according to the present invention is that a mechanism for automatically updating the user preference information T of each user stored in the user preference information storage unit 110 is provided. The preference value update unit 140 and the store of interest recording unit 150 shown in FIG. 1 are components for realizing this mechanism.

  The interested store recording unit 150 performs a process of accumulating and recording the store ID of the specific store as the interested store ID for each individual user when the user indicates an interest in the specific store. A specific method for recognizing the fact that “the user has expressed interest in a specific store” will be described later, but whenever the user is interested in a specific store, the store ID of the store is It will be accumulated and recorded in the store of interest recording unit 150. In the case of the embodiment shown here, as described above, the content ID for specifying the store information (Web content data) is used as it is as the store ID. Will be accumulated and recorded.

  FIG. 9 is a diagram illustrating an example of an interested store ID recorded in the interested store recording unit 150. The example shown in the figure shows the recorded contents of one specific user (for example, user A), and such recording is performed for each individual user in the store of interest recording unit 150. Will be. In the illustrated example, the store ID of interest is recorded for each genre, and when recording the store ID of interest, time information at the time of recording is also recorded. Specifically, FIG. 9 shows an example in which store IDs of interest are recorded together with time information for the genre “G13: Italian cuisine” and the genre “G32: women's clothing”. For example, for the genre “G13: Italian cuisine”, the recorded content “S1380 (2006/11/25)” has the store ID “S1380” (content ID) recorded as the store ID of interest on November 25, 2006. It shows the facts. This means that this user showed an interest in the store corresponding to the store ID “S1380” on November 25, 2006. Note that in this application, “showing interest in a store” is not only when directly showing interest in the store itself but also indirectly showing interest in the store by showing interest in the web content of the store. This also includes the cases shown.

  Eventually, when the record as shown in FIG. 9 has been performed in the store of interest recording unit 150, the user has so far made “S1380” and “S1364” for the genre “G13: Italian cuisine”. , “S1302” indicates an interest in the store specified by the store ID of interest, and “G32: women's clothing” indicates an interest in the store specified by the store ID “S3203” and “S3218”. It will be.

  The preference value update unit 140 performs a process of updating the user preference information T in the user preference information storage unit 110 based on the information accumulated and recorded in the store of interest recording unit 150. That is, the preference value updating unit 140 extracts “interested store ID of a predetermined genre to be updated” recorded in the interested store recording unit 150 as an update store ID for each user, and stores evaluation Store evaluation information E including the update store ID is extracted from the information storage unit 120 as update store evaluation information, and is stored in the user preference information storage unit 110 based on the evaluation value of the update store evaluation information. The preference value of the user preference information T related to a predetermined genre to be updated for the user is updated.

  This process will be described with reference to a specific example shown in FIG. Here, the store of interest ID recorded in the store of interest recording section 150 shown in FIG. 9 is recorded for the user A, and the genre “G13: Italian cuisine” of the user A is updated. Consider a case where update processing is performed as a target. First, the preference value update unit 140 extracts “interested store ID of a predetermined genre to be updated” recorded in the interested store recording unit 150 as an update store ID. That is, since the update target in this case is the genre “G13: Italian cuisine”, the store IDs “S1380”, “S1364”, and “S1302” are updated store IDs from the store of interest recording unit 150 shown in FIG. Extracted. Subsequently, store evaluation information “E1380”, “E1364”, and “E1302” including the update store IDs “S1380”, “S1364”, and “S1302” from the store evaluation information storage unit 120 are used as the update store evaluation information. Extracted. The upper part of FIG. 10 shows an example of the update store evaluation information extracted in this way. Finally, based on the evaluation value of the update store evaluation information extracted in this way, the genre “G13: Italian cuisine” to be updated for the user A stored in the user preference information storage unit 110. The preference value of the user preference information T A13 is updated. The lower part of FIG. 10 shows an example of the user preference information T A 13 updated in this way.

  The user preference information T1 obtained by such update processing sufficiently reflects the preference of the user A. Each store evaluation information “E1380”, “E1364”, and “E1302” shown in the upper part of FIG. 10 indicates the evaluation value of each feature item related to the store in which the user A is interested. Therefore, the preference value regarding each feature item of the user A is expected to be close to the evaluation value of each feature item of these stores. Therefore, the preference value update unit 140 determines a new preference value for each feature item of the user preference information T A 13 based on the update store evaluation information “E1380”, “E1364”, and “E1302”. Process it.

  In the embodiment shown here, the average value of the evaluation values for each feature item of the update store evaluation information “E1380”, “E1364”, and “E1302” is calculated for the same feature item of the user preference information T A13. An update process is performed to obtain a favorable preference value. For example, the preference value 36 of the feature item “formality” of the user preference information T A 13 shown in the lower part of FIG. 10 is the update store evaluation information “E1380”, “E1364”, This is a value obtained as an average value of the evaluation values 38, 50, and 20 of the feature item “formality” of “E1302”.

  In addition, when performing the update process mentioned above, instead of extracting “all the interested store IDs of a predetermined genre to be updated” recorded in the interested store recording unit 150 as the update store ID, the interested store record “Part of an interest store ID of a predetermined genre to be updated” recorded in the unit 150 may be extracted as an update store ID. In particular, in the case of the embodiment described here, as described above, the store of interest recording unit 150 records time information at the time of recording when recording the store of interest ID. Therefore, the preference value update unit 140 can extract only the store IDs recorded in the store of interest recording unit 150 that are recorded within a predetermined period as the store ID for update.

  For example, if only the store IDs of interest recorded within the past 3 months are extracted as update store IDs based on the current time, only the evaluation values of stores that have shown interest during the last 3 months are referred to. Updates are possible. In general, user preferences often change over time. The store of interest recording unit 150 sequentially stores the store of interest ID, but the store of interest ID recorded one year ago may no longer be of interest to the user. is there. If only the store IDs of interest recorded within the past three months are extracted as update store IDs as in the above example, user preference information that reflects only the latest new preferences can always be updated. become. Of course, in this case, the store ID of interest recorded three months or more ago may be sequentially deleted.

  It is also possible to obtain the weighted average value using the time of recording the store ID of interest. In the example shown in FIG. 10, the simple average value of each evaluation value is updated as a new preference value. For example, a higher weight is given to the evaluation value for the store ID that is recorded more recently. In this way, if the weighted average value is calculated and updated as a new preference value, user preference information weighted more recently can be obtained.

<<< §4. Interest recognition process of first embodiment >>>
Subsequently, some specific methods for recognizing the fact that “the user has expressed interest in a specific store” by the store of interest recording unit 150 will be described. As described in §2, the store information providing unit 130 presents, for example, a summary list of store information as shown in FIG. 7 to the user terminal. And if the user who browsed this summary list performs operation which clicks on the store part which is interested, the original store information full text will be displayed. For example, if the user clicks on the title part “1. Boiled spaghetti store XYZ” in FIG. 7, the screen shifts to the original Web page as shown in FIG.

  The above-described processing executed by the store information providing unit 130 eventually results in “a list that selects a plurality of store information that matches the search condition and is suitable for the user, and lists only an overview of each selected store information. The process comprises two steps: a “first providing step to be provided” and a “second providing step for providing all contents of store information relating to a store designated by the user from this list”. Here, it is important that the transition to the second providing step is performed based on a user's designation operation (click operation).

  For example, when the user performs an operation of clicking on the title portion “1. Boiled spaghetti store XYZ” in FIG. 7, this means that the user has expressed interest in the store. . In this case, this user will enter the “volume full score”, “from lunch 650 yen” described in the explanation of “boiled spaghetti store XYZ” in this summary list, It is presumed that the store showed interest in the store with reference to characteristics such as “ Thus, when the second providing step is performed by the store information providing unit 130 based on the user's specification, the store ID of the store for which the store information is provided in the second providing step is used as the use information. What is necessary is just to make it accumulate and record as interested store ID about a person. Specifically, when the store information providing unit 130 executes the second providing step, the store ID of the store designated by the user is specified to the store of interest recording unit 150 (in this embodiment, content ID) may be transmitted.

  Another method for recognizing “interest by the user” is a method in which the user himself / herself reports that he / she is interested in a specific store. For example, when a user encounters a web page of interest when browsing web pages (store information) of various stores provided from the store information providing unit 130 using a terminal device, What is necessary is just to report to the store information provision part 130 by some method that it was interested in the web page under browsing. For example, when the store information providing unit 130 provides Web content data of each store to the user terminal, data for displaying the “interest” button is transmitted together, and the user presses the “interest” button. When clicked, it should be handled as if there was a report indicating interest. When the click on the “interest” button is detected, if the store information providing unit 130 transmits the store ID related to the Web page that the user is currently browsing to the store of interest recording unit 150, the store ID is stored. It can be recorded in the store of interest recording unit 150 as the store of interest ID.

  Of course, the “interest by the user” is not only indicated by browsing the Web page by the user. For example, when a user actually uses a specific store (for example, when he actually eats at a restaurant), he / she reports to the store recording unit 150 to that effect. It is possible to recognize that the user is interested in the store, and store the store ID of the store in the store of interest recording unit 150. Specifically, when the store information providing unit 130 provides Web content data of each store as a Web page to the user terminal, a specific Web page is registered in the store information providing unit 130 by a user operation. You should be able to do that. Then, if the user finds a store that he / she wants to use while browsing the Web pages of various stores, the user can perform an operation of registering the Web page of the store. Then, when the store is actually used, the registered Web page may be called to report that the store is actually used on the Web page. If there is such a report, if the store ID related to the Web page is transmitted to the store of interest recording unit 150, the store ID is recorded in the store of interest recording unit 150 as the store of interest ID. Can do.

  Alternatively, if the user has a mobile terminal device (for example, a mobile phone) and the store information providing unit 130 provides store information to the mobile terminal device, the mobile terminal By detecting the position of the device, it is possible to determine that a specific store has been used. That is, a position recognition device having a function of recognizing the position of the portable terminal device is prepared, and information on the recognized position is transmitted from the position recognition device to the store of interest recording unit 150. The store of interest recording unit 150 can recognize that the user has visited the location of the specific store based on the information on the location. In this case, the user uses the store. The store ID of the store can be accumulated and recorded as the store ID of interest.

  For example, when the user has a portable terminal device with a GPS function, the portable terminal device can recognize its own position (for example, latitude / longitude information) using this GPS function. . Therefore, the mobile terminal device reports its position information to the store of interest recording unit 150 at a predetermined timing or a predetermined cycle. On the other hand, the interested store recording unit 150 stores position information (for example, latitude and longitude information) of each store. Then, when the location information reported from the mobile terminal device matches the location information of a specific store, the store of interest recording unit 150 uses the store by the user who owns the mobile terminal device. The store ID of the store can be accumulated and recorded as the store ID of interest. In order to make a more accurate determination, a determination is made that the store has been used only when the location of the store stays for a predetermined time or longer (for example, in the case of a restaurant, the time required for a meal or longer). You may do it.

  Further, when the store has a large site such as an amusement park, it is possible to determine that the user has used the store (amusement park) even if the position information is considerably low in accuracy. Therefore, the same determination can be made without using a highly accurate position recognition device such as GPS. For example, since a mobile phone communicates with a base station at a predetermined cycle, if each base station reports the fact that “the user has communicated with a mobile phone possessed by a specific user”, the base station The current position of a specific user can be recognized with an accuracy according to the installation density. Therefore, it can be recognized that the store has been used for a store having a wide site such as an amusement park.

  Another approach is that, when communication is performed between a store installation device installed in a predetermined store and a mobile terminal device possessed by the user, the store of interest recording unit 150 may store the store installation device or mobile phone. This is a method of receiving a notification from the terminal device and determining that the user has used the store. Also in this case, the store ID of the store can be accumulated and recorded as the store ID of interest.

  Specifically, in many stores, a payment processing device (for example, a billing processing device for a credit card or a prepaid card) that performs payment processing for the usage of the store is installed. Recently, a technology for providing a credit card or prepaid card function to a mobile terminal device such as a mobile phone has been put into practical use, and a user can use a mobile terminal device owned by the user and a payment processing device installed in a store. Can be processed wirelessly for payment processing. When the user executes the payment process in the store by such a method, the fact that the mobile terminal device possessed by the user has communicated with the payment processing device installed in the store is referred to as the mobile terminal device. Or from the payment processing device to the store of interest recording unit 150. Then, the interested store recording unit 150 can grasp the fact that which user used which store, and can store and record the store ID of the store as the interested store ID.

  Note that the store installation device having the function of communicating with the mobile terminal device possessed by the user is not limited to the above-described payment processing device. For example, a mobile terminal device such as a mobile phone is used as a path for passing through an entrance gate such as an amusement park or a movie theater. In this case, a gate management device that wirelessly communicates with a mobile terminal device possessed by the user is installed at the entrance gate. Therefore, when a user passes through an entrance gate where such a gate management device is installed and enters a store, the mobile terminal device possessed by the user communicates with the gate management device installed in the store. The fact that it has been made is reported from the portable terminal device or the gate management device to the store of interest recording unit 150. Then, the interested store recording unit 150 can grasp the fact that which user used which store, and can store and record the store ID of the store as the interested store ID.

<<< §5. Operation procedure of the first embodiment >>
So far, the function of each component of the information providing system according to the first embodiment shown in FIG. 1 has been described individually. Here, the operation procedure of the entire system will be described.

  In order to operate this system, store information for each store (Web content data for presenting a Web page in this embodiment) is first prepared in the store information storage unit 100. There is a need. However, since the store information storage unit 100 does not have to be dedicated to this system, in practice, an existing Web server can be used as it is. In other words, many stores currently have web page sites using their own web servers. The store information storage unit 100 shown in FIG. 1 can use a collection of existing Web servers that provide these sites as they are, and therefore it is not necessary to install a new Web server to construct this system. .

  On the other hand, the user preference information storage unit 110 and the store evaluation information storage unit 120 are components unique to the present system, and need to be newly installed in constructing the present system. As described in §1, in the user preference information storage unit 110, it is necessary to store user preference information T for each individual user and for each genre, and store evaluation information In the storage unit 120, it is necessary to store the store evaluation information E for each store (in the case of the embodiment shown here, for each individual Web content).

  As described in §3, the user preference information T in the user preference information storage unit 110 is automatically updated by the preference value update unit 140 while the system is operated. However, some user preference information T needs to be prepared in the initial operation stage. Therefore, in practice, some default value is defined as the preference value of all feature items of all genres of all users, and the user preference information T in which this default value is defined is used as the user preference information storage unit. It may be stored in 110. For example, if preference value = 50 (intermediate value of the numeric value range of preference values) is set as a default value, any feature item of any genre of any user is set to preference value = 50 in the initial operation stage. Will be. The same applies to those who become new users after the operation of this system. For such a new user, user preference information T with preference values = 50 of all feature items may be prepared and stored in the user preference information storage unit 110.

  Of course, instead of setting the default value in the initial stage, it is also possible to conduct an individual user survey and have the initial value of the preference value for each feature item set by itself. However, as described above, conducting such a questionnaire survey imposes a great deal of effort on each user, so it is practically preferable to set a default value at the initial stage as described above. . Even if the default value is set at the initial stage, the user preference information T has the correct preference value reflecting the preference of each user at that time if the first update process by the preference value update unit 140 is executed. The problem will not arise because it will be corrected.

  Note that the timing of the update process by the preference value update unit 140 can be variously set according to the operation mode of the system. For example, every time a new store ID is recorded in the store-of-interest recording unit 150, it is possible to perform a process of updating the user preference information T related to the user and the genre related to the store of interest ID. Alternatively, it is also possible to define a schedule for updating only once a week for each individual user, and appropriately update according to this schedule.

  On the other hand, in the store evaluation information storage unit 120, it is necessary to store store evaluation information E for each store. Therefore, in the case of the system according to the first embodiment, the system operation manager performs the work of preparing the store evaluation information E for each store by the time the system starts operating. While browsing each store information (Web content data) in the store information storage unit 100, an operation of inputting a genre code and an evaluation value for each feature item may be performed. In some cases, an evaluation value can be determined by actually visiting a store. However, in practice, it is preferable to construct a system according to the second embodiment described in §6. In the system according to the second embodiment, the evaluation value of each store is automatically determined by the user's voting action. Therefore, at the initial stage of operation, for all feature items of all stores, for example, It is sufficient to give a default value such as evaluation value = 50.

<<< §6. Configuration and Features of Second Embodiment >>>
The feature of the first embodiment described so far is that, as described in §3, the user preference information T in the user preference information storage unit 110 is automatically updated by the preference value update unit 140. Is a point. The second embodiment described here further relates to a system to which a function for automatically updating the store evaluation information E in the store evaluation information storage unit 120 is added.

  FIG. 11 is a block diagram showing a basic configuration of an information providing system according to the second embodiment. The system according to the second embodiment is obtained by adding an evaluation value update unit 160 and a vote result recording unit 170 to the system shown in FIG. Therefore, the functions of these two new components will be described below.

  First, the voting result recording unit 170 is a component having a function of accumulating and recording the voting result for each individual store when a user evaluates a personal evaluation value for a feature item of a specific store. is there. Specifically, the voting result recording unit 170 presents a voting web page to the user terminal and the individual evaluation value (voting value) of each user on the voting web page. It can comprise by the input part which inputs, and the memory | storage part which memorize | stores a voting result.

  FIG. 12 is a diagram showing an example of a voting screen (Web page) presented on the screen of the user terminal by the voting result recording unit 170. The illustrated example is a screen for the user A to vote for an evaluation value related to a store called “boiled spaghetti store XYZ”. When the user A gives an instruction to vote for the store “boiled spaghetti store XYZ” from the user terminal to the voting result recording unit 170, the web page display for illustration as shown in FIG. Data is transmitted from the voting result recording unit 170 to the user terminal. On this Web page, the user A has 0-100 items for each of the characteristic items for the store “Boiled spaghetti store XYZ” to be evaluated, that is, three items of formality, volume, and price. Enter a personal evaluation value within the range.

  In the example shown in FIG. 12, in order to facilitate the input operation of the personal evaluation value, the title of each feature item is displayed on the left side, and the number line indicating the evaluation value of 0 to 100 is displayed on the right side. It is like that. A marker indicated by a black inverted triangle is arranged at a predetermined position on the number line, and the user drags the marker left and right using a mouse or the like to fall within a range of 0 to 100. Desired personal evaluation values can be set. When the user sets a desired personal evaluation value for each feature item, and finally clicks the “vote” button, the personal evaluation value set by the user is used as personal evaluation information for the store. The result is recorded in the voting result recording unit 170.

  When operating the system according to the second embodiment, when each store is actually used, it is necessary to ask each user to cooperate in voting a personal evaluation value for the store. . If the user who responds to the cooperation accesses the voting result recording unit 170 from the user terminal, inputs the user ID and the store ID to be evaluated, and gives an instruction to vote. Good.

  An example of the voting result (personal evaluation information) recorded in the voting result recording unit 170 is shown in the upper part of FIG. The three types of personal evaluation information shown here relate to the store “Boiled spaghetti store XYZ” identified by the store ID “S1302”, and each of the three users of A, B and B It is the result of voting by. Each individual evaluation information includes a store ID, a user ID, and an individual evaluation value (an individual user evaluation value for each feature item). For example, in the case of the personal evaluation information E1302 shown at the leftmost, it is composed of data of “store ID: S1302”, “user ID: A”, “individual evaluation value: form 18, volume 85, price 41”. Yes.

  This voting may be performed anonymously. In that case, the user does not need to input the user ID at the time of voting, and does not need to include the user ID in the personal evaluation information. However, in practice, it is preferable to have a user ID specified for voting in order to prevent mischievous voting by mischief. Of course, each individual evaluation value is a value that is arbitrarily determined based on a subjective impression when an individual user uses the store, so that a difference occurs between individuals. However, if a large number of users vote, the accuracy of the evaluation will be improved accordingly.

  In this way, the voting result recording unit 170 accumulates and records voting results by a large number of users for each store. Therefore, the evaluation value updating unit 160 extracts the voting result recorded in the voting result recording unit 170 for each store, and is stored in the store evaluation information storage unit 120 based on the extracted voting result. The process which updates the evaluation value of the store evaluation information E about the said store which is located is performed.

  The lower part of FIG. 13 is a diagram illustrating an example of the store evaluation information E updated by the process of the evaluation value update unit 160. In the embodiment shown here, the average value of the individual evaluation values for each characteristic item of the personal evaluation information “E1302 A”, “E1302 B”, and “E1302 丙” is used as a new value for the same characteristic item of the store evaluation information E1302. An update process is performed as an evaluation value. For example, the evaluation value 21 of the feature item “formality” of the store evaluation information E1302 shown in the lower part of FIG. 13 is the personal evaluation information “E1302 A”, “E1302 B”, “E1302 丙” shown in the upper part of FIG. Is the value obtained as the average value of the evaluation values 18, 22, and 23 of the feature item “formality”.

  In addition, when performing the update process mentioned above, instead of extracting "all the voting results for each individual store" recorded in the voting result recording unit 170, "a part of the voting result for each individual store" May be extracted and used for updating. For example, if the voting result recording unit 170 records the time information at the time of recording when the voting result is recorded, the evaluation value update unit 160 may record the vote recorded in the voting result recording unit 170. Of the results, it is possible to extract only those whose recording time is within a predetermined period and update the evaluation value of the store evaluation information. Therefore, for example, if only the voting results recorded within the past three months are extracted and used for updating based on the current time, it is possible to update referring only to the individual evaluation values during the last three months. Become. Therefore, even when the store is renewed and the store is newly opened, the evaluation value of each feature item can be held at the latest evaluation value. Of course, in this case, the voting results recorded three months or more ago may be deleted sequentially.

  It is also possible to obtain a weighted average value using the time when the voting result is recorded. In the example shown in FIG. 13, the simple average value of each individual evaluation value is updated as a new evaluation value. For example, a larger weight is given to the personal evaluation value related to the voting result recorded more recently. If the weighted average value is calculated in such a manner as to be added and updated as a new evaluation value, store evaluation information weighted more recently can be obtained.

  Various settings can be made for the timing of the update processing by the evaluation value update unit 160 according to the operation mode of the system. For example, every time a new voting result (personal evaluation information) is recorded in the voting result recording unit 170, it is possible to perform a process of updating the store evaluation information E of the store related to the voting result. Alternatively, it is also possible to define a schedule for updating only once a week for each store, and to update appropriately according to this schedule. As described above, since automatic updating is performed, even if the default value is set as the evaluation value of the store evaluation information E of each store at the initial operation stage of the system, the system is operated. Each evaluation value is automatically corrected to an appropriate value.

  As described above, in the system according to the second embodiment described here, not only the user preference information T is automatically updated by the preference value update unit 140 but also the store evaluation information E by the evaluation value update unit 160. Will also be automatically updated. As described above, the evaluation value in the store evaluation information E is used for the update process of the user preference information T by the preference value update unit 140. In the system according to the second embodiment, since the evaluation value in the store evaluation information E is updated and always maintained at an appropriate value, the content of the user preference information T updated using this value is also appropriate. Synergistic effects are expected to be maintained.

  By the way, in §4, several specific methods of interest recognition processing (processing for recognizing that the user has expressed interest in a specific store) by the store of interest recording unit 150 are exemplified. In the second embodiment described here, when a user uses a specific store, the voting result recording unit 170 is voted for the store. This voting action is nothing but an indication of intention that the user is “interested in the store”. Therefore, when there is such a vote, the voting result recording unit 170 records the voting result and also notifies the interested store recording unit 150 that “a specific user votes for a specific store. Report to the effect. If it does so, the interested store recording part 150 which received the report can record the said store ID as an interested store ID about the said user.

<<< §7. Configuration and Features of the Third Embodiment >>>
The third embodiment described here relates to an information providing system that enables handling in consideration of companion preference. When a user uses various stores, it is usually used with a companion. As described above, when a specific store is used as a group of a plurality of users, a user who is a store according to his / her preference is satisfied, but does not match his / her preference. Users who were stores will be less satisfied. In the system according to the third embodiment described here, when each user uses a store as a group, the satisfaction degree about the store is reported, and this satisfaction is taken into consideration and provided to each user. It has a function of selecting store information.

  FIG. 14 is a block diagram showing a basic configuration of an information providing system according to the third embodiment. The system according to the third embodiment is obtained by adding a satisfaction ratio calculation unit 180 and a personal satisfaction information recording unit 190 to the system according to the first embodiment shown in FIG. Therefore, the functions of these two new components will be described below.

  First, the personal satisfaction information recording unit 190, when a plurality of users use a specific store, group configuration information that identifies users constituting the group, the genre of the store used, and individual users Has a function of accumulating and recording personal satisfaction information including a user ID for identifying the user ID and the personal satisfaction level of the user. Specifically, the personal satisfaction information recording unit 190 presents a web server for presenting a personal satisfaction information input web page to the user terminal, and an input for inputting the personal satisfaction information of each user on the web page. And a storage unit for storing the inputted personal satisfaction information.

  Here, let us consider a case where two users A and B use a “boiled spaghetti store XYZ” together. In this case, a group consisting of two users named “A, B” used the store, but from the user's level, the store was used with B. From the user's point of view, it means that the store was used with Party A. Therefore, we ask both parties to report their satisfaction after use.

  FIG. 15 is a diagram showing an example of a personal satisfaction information input screen (Web page) presented on the screen of the user terminal by the personal satisfaction information recording unit 190. The example shown in the figure is a screen for the user A to input the degree of satisfaction regarding the store “boiled spaghetti store XYZ”. When the user A gives an instruction to the personal satisfaction information recording unit 190 from the user terminal to input the satisfaction degree about the store “Boiled spaghetti store XYZ”, the Web page as shown in the figure Display data is transmitted from the personal satisfaction information recording unit 190 to the user terminal. User A enters the degree of satisfaction of the companion and Party A on this Web page.

  The companion information is handled as a user ID in the personal satisfaction information recording unit 190. However, in the case of the embodiment shown here, in order to simplify the input operation, the user's information is in advance. The companion is registered, and on the input screen, the registered companion name is presented as a list, and the input operation for identifying the companion is completed simply by selecting the desired companion name. is there. In the Web screen shown in FIG. 15, a list of pre-registered companion names will be displayed in the right column of “accompaniment person:”. The operation of selecting is performed.

  On the other hand, the personal satisfaction is defined as a numerical value within the range of 0-100. In the example shown in FIG. 15, in order to facilitate the input operation of the personal satisfaction, a number line indicating an evaluation value of 0 to 100 is displayed, and a marker indicated by a black inverted triangle is displayed at the predetermined position. I try to arrange it. The user can input a desired individual satisfaction level within a range of 0 to 100 by dragging the marker left and right using a mouse or the like. When the user moves the marker to a desired position and clicks the “input” button, the personal satisfaction information input by the user is recorded in the personal satisfaction information recording unit 190.

  In addition, when using the system which merged 3rd Embodiment described here and 2nd Embodiment mentioned above, the screen required for voting required in 2nd Embodiment and satisfaction required in 3rd Embodiment It is preferable to integrate the information input screen. FIG. 16 is a diagram showing an example of an input screen in which the voting screen shown in FIG. 12 and the satisfaction information input screen shown in FIG. 15 are integrated. In this input screen, “satisfaction” is handled in the same row as “formality”, “volume”, and “price”. Of course, in the processing of the system, “satisfaction” and “formality”, “volume”, and “price” are completely different parameters. As described in §6, the latter is a personal evaluation value used for the update process by the evaluation value update unit 160, whereas the former is used for a selection operation by the store information providing unit 130 as described later. Is the value to be However, when viewed from the user side, all are numerical values in the range of 0 to 100, and it is convenient to handle them in the same row on the user interface as in the example shown in FIG. On the input screen shown in FIG. 16, the user A sets values for four items “formality”, “volume”, “price”, and “satisfaction”, and clicks the “vote” button.

  The user's input operation has been described above with reference to the input screen examples in FIGS. 15 and 16, but the same input operation is also executed by the user B. In this case, an input is made with the setting of “user: B, companion: A”. Thus, even when a plurality of users accompany each other and use the store, each user is asked to input personal satisfaction information for each individual user.

  FIG. 17 is a diagram illustrating an example of the personal satisfaction information recorded in the personal satisfaction information recording unit 190 through the input operations of both A and B. FIG. 17 (a) shows personal satisfaction information M1 recorded by the user's input operation. "User ID: Party A", "Accompanying Party ID: Party B", "Store ID: S1302", "Genre Code: G13 ”and“ personal satisfaction: 85 ”. This personal satisfaction information M1 indicates a matter that the personal satisfaction of the user A is 85 when using the store of the genre code G13 specified by the store ID S1302 in the group of user A and B. Information. On the other hand, FIG. 17B shows the personal satisfaction information M1 B recorded by the user's input work, in which the “user ID” and the “accompanied ID” are interchanged, and the personal satisfaction value is 23. Is different from the personal satisfaction information M1.

  In addition, although store ID is contained in each personal satisfaction information M1 A and M1 O shown in FIG. 17, this store ID may be omitted. The essential items of personal satisfaction information are group configuration information that identifies users who make up a group that uses a specific store, a genre code that indicates the genre of the store that was used, a user ID for specifying individual users, Personal satisfaction of the user. In the case of the example shown in FIG. 17 (a), “user ID: A” and “accompanying person ID: B” function as group configuration information. In the case of the example shown in FIG. 17 (b), “User ID: B” and “Accompanying person ID: A” function as group configuration information.

  The satisfaction rate ratio calculation unit 180 is based on the personal satisfaction information M recorded in the personal satisfaction information recording unit 190 under the group usage condition of “use a specific genre store in a specific group”. A process of calculating the satisfaction ratio between users is performed. Let's illustrate this with a specific example.

  Consider a case where the personal satisfaction information M1 A and M1 B as shown in FIGS. 17A and 17B are recorded in the personal satisfaction information recording unit 190. FIG. These pieces of information correspond to a group use condition “use a store of a specific genre in a specific group”. Specifically, it corresponds to the group use condition “use the store of genre code G13 in the group of user A & B”. Therefore, based on these pieces of information, a ratio of “85:23” is obtained as a satisfaction ratio between users under the group usage condition. The meaning of this ratio is that in the past usage record under the group usage condition of “use the store of genre code G13 in the group of user A & B, The fact is that B's personal satisfaction is 23. In other words, the satisfaction level of Party A is quite high, but the level of satisfaction of Party B is quite low under the usage conditions.

  In the example shown in FIG. 17, a set of personal satisfaction information of A in the unique group usage condition of “use a store of genre code G13 in the group of user A & B”, and the personal satisfaction level of B Since only one set of information exists, the satisfaction ratio of “85:23” can be calculated by taking the ratio of the individual satisfaction levels 85 and 23 as they are. However, in practice, there may be a plurality of sets of personal satisfaction information for each user under the same group usage conditions. For example, if user A and B dine at three “Italian cuisine” restaurants, personal satisfaction information will be collected for each individual restaurant (total 6 personal satisfaction information will be obtained). . In this case, the group usage conditions are the same in all cases. In such a case, the ratio of the average value of each individual user of the personal satisfaction included in the personal satisfaction information used for the calculation may be calculated as the satisfaction ratio. For example, if the individual satisfaction levels of the three houses are 85, 80 and 75 and the personal satisfaction levels of the three houses are 23, 25 and 30, respectively, ((85 + 80 + 75) / 3) :( 23 + 25 + 30) / 3) = 80: 26.

  In addition, personal satisfaction information is sequentially recorded in the personal satisfaction information recording unit 190, but when the satisfaction ratio calculation unit 180 calculates the satisfaction ratio, it is recorded in the personal satisfaction information recording unit 190. Instead of calculating using all of the personal satisfaction information under a specific usage condition, the calculation may be performed using a part thereof. For example, if the personal satisfaction information recording unit 190 records the time information at the time of recording when recording the personal satisfaction information, the satisfaction rate calculation unit 180 records the information in the personal satisfaction information recording unit 190. It is possible to calculate the satisfaction rate ratio by extracting only the personal satisfaction information that has been recorded within the predetermined period. For example, if only the personal satisfaction information recorded within the past three months is extracted and used for the calculation based on the current time, the calculation can be made with reference to only the personal satisfaction information for the last three months. . Of course, in this case, the personal satisfaction information recorded more than three months ago may be deleted sequentially. Of course, it is also possible to obtain the weighted average value using the recording time of the personal satisfaction information.

  The satisfaction ratio calculation timing by the satisfaction ratio calculation unit 180 can be variously set according to the operation mode of the system. For example, each time new personal satisfaction information is recorded in the personal satisfaction information recording unit 190, it is possible to perform a process of calculating a satisfaction rate ratio under a predetermined use condition related to the personal satisfaction information. Alternatively, for each usage condition, a schedule for updating only once a week can be set, and updating can be appropriately performed according to this schedule, or when a request is received from the store information providing unit 130 The satisfaction rate ratio regarding the use conditions related to the request can be calculated each time.

  Of course, each group usage condition differs for each member of the group, and also differs depending on the genre of the store to be used. Therefore, for example, the satisfaction ratio under the group usage condition “use the store of the genre code G13 in the group“ user A & B ”is defined separately, and“ user A & B The satisfaction ratio under the group use condition of “use a store of genre code G21 in the group” is also defined separately.

  Here, the reason for making the group usage conditions different for each member of the group is that the answer to the proposition “who takes the initiative in selecting a store” is considered to differ depending on the combination of users. For example, the group “User A & B” tends to select stores, whereas the group “User A & B” tends to select stores exclusively. There will be many. Also, the reason why the group usage conditions are made different for each genre of stores is that the answer to the proposition “who takes the initiative in selecting a store” is considered to differ depending on the genre of the store. For example, even in the same group, “User A & B”, “A” takes the initiative to select “Italian food” stores, and “B” takes the initiative to select “Women's clothing” stores. There will be many.

  Thus, the value of the satisfaction ratio between users under each group usage condition calculated by the satisfaction ratio calculation unit 180 is used for selection of store information in the store information providing unit 130. That is, when the store information providing unit 130 receives a store information provision request under a specific group use condition, the store information provision unit 130 extracts store information suitable for each individual user according to the specific group use condition as a candidate. After that, store information extracted as candidates is selected and provided according to the satisfaction ratio under the group usage conditions.

  This will be explained in more detail with reference to specific examples. In the system shown in FIG. 14, the store including the companion information “accompanying person: O” and the keyword “Italian restaurant Shibuya” from the terminal device operated by the user A to the store information providing unit 130. Suppose that an information provision request has been made (in order to make such a provision request possible, a keyword input field and a companion name input field are prepared on the screen of a Web page for inputting a search instruction. Just keep it.) This provision request is ultimately a request for provision of store information under a unique group use condition of “use a store of genre code G13 (Italian cuisine) in the group of user A & B”.

  Upon receiving such a request, the store information providing unit 130 selects and finally selects a large number of store information stored in the store information storage unit 100 through two screens as described in §2. The store information is posted on the summary list and presented. Here, the first sieve is a sieve based on the keyword, and the second sieve is a sieve based on a comparison between the user preference information T and the store evaluation information E. However, since the provision request including the companion information is based on the assumption that the store is scheduled to be used in the group as in the above example, the selection process by the second sieve is originally performed in the group. Should be a process that reflects all the preferences of individual users that make up the. That is, in the case of the above example, the selection should be made in consideration of both the user preference information T of user A and the user preference information T of user B.

  Therefore, in the third embodiment, the second sieving is performed separately for each individual user. That is, store information suitable for each individual user is extracted as a candidate. The left side of FIG. 18 shows store information candidates extracted for user A, and the right side of FIG. 18 shows store information candidates extracted for user B. Of course, the user preference information T for user A and the user preference information T for user B stored in the user preference information storage unit 110 are different. The candidates listed on the left side of FIG. 18 are candidates extracted using the former (candidates extracted by sieving based on the comparison between the user preference information T and store evaluation information E). The candidates listed on the right side of the figure are candidates extracted using the latter (candidates extracted by sieving based on a comparison between the user preference information T and each store evaluation information E).

  As described above, when the second sieve is applied to each user separately, naturally, the candidate extracted as a result is also different for each user. Therefore, in the third embodiment, a third sieve is further applied to further select these extraction candidates. The satisfaction ratio calculated by the satisfaction ratio calculation unit 180 is used for the selection process of the third sieve.

  In the case of the above example, since the store information provision request is made under the group use condition of “use the store of genre code G13 (Italian cuisine) in the group of user A & B”, the group use condition The store information extracted as candidates is selected (third screening) according to the satisfaction rate ratio. For example, if the satisfaction ratio “M (E): M (O)” under the group usage condition is calculated as “85:23”, according to the ratio “85:23”, The selection may be made so that the extraction candidates for A and B are included. Here, when performing “selection according to the ratio”, specifically, the following two policies can be considered.

  The first policy is to select store information with a probability corresponding to the inverse ratio of the satisfaction rate ratio for each individual user from among the store information candidates extracted for each individual user. For example, in the example shown in FIG. 18, when store information is selected with a probability corresponding to the inverse ratio of the satisfaction ratio “M (O): M (O)” = “85:23”, The selection probability is 23 / (85 + 23), and the probability that the selection candidate is selected from among the extraction candidates shown in the right side of the figure is 85 / (85 + 23). become.

  This first policy is based on the idea of “adjusting so that equal satisfaction is obtained for each user”. In the case of the above example, a result of satisfaction ratio “M (A): M (O)” = “85:23” is obtained. This is a group “User A & B, and genre code G13. As a result of using the store of (Italian cuisine) so far, the satisfaction degree of the former is 85, whereas the satisfaction degree of the second party is only 23 ". In other words, it shows the fact that “as a result of using Italian restaurants in Party B, the satisfaction level of Party A is quite high, but the satisfaction level of Party B is quite low”. Therefore, if we take the idea of “adjusting so that each user can get equal satisfaction,” the next time you use an Italian restaurant at Party B, you will find a store that will satisfy you as much as possible. The conclusion is to be recommended. If store information is selected with a probability corresponding to the inverse ratio of the satisfaction ratio, store information that matches the preference of Party A is selected with a probability of 23 / (85 + 23), whereas store information that matches the preference of Party B Is selected with a probability of 85 / (85 + 23), and store information that matches the taste of the second party is preferentially selected.

  On the other hand, according to the second policy, store information is selected with a probability corresponding to the direct ratio of the satisfaction rate ratio for each individual user from among the store information candidates extracted for each individual user. It is a policy. For example, in the example shown in FIG. 18, if store information is selected with a probability corresponding to the direct ratio of the satisfaction ratio “M (O): M (O)” = “85:23”, The selection is performed such that the probability of being selected from the extraction candidates is 85 / (85 + 23) and the probability of being selected from the extraction candidates for the second shown in the right side of the drawing is 23 / (85 + 23). Become.

  This second policy is based on the idea of “respecting the leaders in selecting past stores”. In the case of the above example, a result of satisfaction ratio “M (A): M (O)” = “85:23” is obtained. This is a group “User A & B, and genre code G13. As a result of using the Italian restaurant so far, the satisfaction of the former is 85, whereas the satisfaction of the second is only 23 ". In other words, it shows the fact that “If you use an Italian restaurant in Party B, you have the initiative to choose a store”. Therefore, if you take the idea of “respecting the leaders of past store selection”, it is highly likely that the next time you use an Italian restaurant at Party B, you will select the store with the initiative. The conclusion is that you should recommend a store that suits your taste as much as possible. If store information is selected with a probability corresponding to the positive ratio of the satisfaction ratio, store information that matches the preference of Party A is selected with a probability of 85 / (85 + 23), whereas store information that matches the preference of Party B It will be selected with a probability of 23 / (85 + 23), and store information that matches the preference of the former will be preferentially selected.

  Whether to adopt the first policy (inverse ratio) or the second policy (direct ratio) will generally be a problem that depends on the relationship of the users who make up the group. Therefore, in practice, it is sufficient to set in advance which policy is to be adopted, depending on whether the second party is a lover, a couple, a colleague, or a classmate.

  It should be noted that several methods are conceivable when the store information integrated by performing the third screening is presented as an outline list as shown in FIG. In the first method, since the degree of approximation is examined on the vector space as shown in FIG. 8 in the second sieving, sorting is performed in descending order of the degree of approximation (in order of short distance between the tip points of the vectors). And arrange them in a list. In this method, the candidates on the left side and the candidates on the right side in FIG. The second method is a method in which candidates for users with a low satisfaction rate ratio are arranged at the end of the list. In the case of the above example, the candidates extracted for the second party are arranged first in the list. This is a method that is consistent with the idea of “adjusting so that equal satisfaction is obtained for each user”. The third method is a method in which candidates for users with a high satisfaction rate ratio are arranged at the end of the list. In the case of the above example, the candidates extracted for the former are arranged at the top of the list. This is a method that is consistent with the idea of “respecting the leaders in choosing past stores”.

  As described above, the third embodiment has been described by taking the use of a store by a group of A and B as an example. However, this embodiment can also be applied to a group of three or more people. For example, when the store is used by three people of Kai Oto, each may enter personal satisfaction information into the personal satisfaction information recording unit 190. In this case, for example, on the input screen of Class A, it is only necessary to make an input with the companion as the second party. Further, the satisfaction rate ratio is given by three number ratios, such as “M (A): M (B): M (B)”.

<<< §8. Configuration and Features of the Fourth Embodiment >>>
Usually, when a user tries to obtain some information by accessing the Internet, it is often intended to take some action. For example, when accessing a web page of a restaurant, it is considered that the user intends to eat. In addition, when accessing a Web page of a movie theater, it is considered that the user intends to go to the movie. In addition, unique behavior patterns are often established for individual users.

  For example, some users have a daily behavior pattern of eating at a restaurant after watching a movie with a companion, and talking about the contents of the movie. Some users will enjoy the daily behavior pattern of having fun. In the former case, it would be meaningful to provide meal information when requested by the user for movie information. However, in the latter case, there is a possibility that the meal has already been completed when the movie information is requested by the user, so it may not be useful to provide meal information along with the movie information. There will be.

  The system according to the fourth embodiment described in §8 is a system having a function of providing accurate information in consideration of daily behavior patterns for individual users.

  FIG. 19 is a block diagram showing a basic configuration of an information providing system according to the fourth embodiment. The system according to the fourth embodiment is obtained by adding a subsequent genre prediction unit 210, an action history information storage unit 220, and an action history information collection unit 230 to the system according to the first embodiment shown in FIG. . Therefore, the functions of these three new components will be described below.

  First, the behavior history information collection unit 230 collects behavior history information including the user ID of the user, the genre code of the store, and the usage time when each user uses a specific store. It has the function to do. For example, when user A uses “boiled spaghetti store XYZ”, “user ID: A”, “genre code: G13”, “use time: 2006/11/25/17: 53” Action history information including such data is collected (the usage time data need not necessarily include the hourly data as long as the use order of the stores can be specified). In short, the action history information is information indicating “when and who used which genre of shops”.

  In order to collect such information, it is necessary to recognize that “a specific user has used a specific store”. For example, various methods described in §4 (for example, a store for a user) A method for reporting the fact of use, a method for recognizing the position of a mobile terminal device with a GPS function, and a method for recognizing that communication has occurred between a store-installed device and a mobile terminal device owned by the user. Etc.) may be used. Alternatively, if the second embodiment described in §6 or the third embodiment described in §7 is used in combination, the user can perform predetermined items on the Web screen as shown in FIG. Can be recognized as “a specific user has used a specific store”.

  The behavior history information collected by the behavior history information collection unit 230 in this way is stored in the behavior history information storage unit 220. FIG. 20 is a diagram illustrating an example of the action history information stored in the action history information storage unit 220. As shown in the figure, a separate and independent storage area is secured for each user. In the storage area shown in FIG. 20 (a), action history information related to the user A is stored. In the storage area shown, action history information regarding the user B is stored.

  In the case of the example shown in FIG. 20, the action history information for each user sets a continuous time frame in units of 24 hours for each day of the week, and the genre code as a permutation on the time axis within this continuous time frame. The data is a list of major classifications (see FIG. 3). For example, FIG. 20 (a) shows a storage example of action history information related to the user A. In the figure, for convenience, only the columns for Sunday and Monday are shown, but in reality, columns for Tuesday to Saturday are also provided, and the action history information regarding the user A is classified for each day of the week. Stored.

  For example, in the data “2006/10/08”, “show”, “meal” shown in the first line of the Sunday column, the user A becomes “show” on October 8, 2006. This shows the fact that after using a store belonging to the genre of the broad category, a store belonging to the genre of the broad category “meal” is used. Of course, instead of using a large classification such as “show” or “meal”, a code of the genre itself such as “Italian food” or “movie” may be used.

  Now, when action history information as shown in FIG. 20 is collected, an action pattern for each individual user can be predicted. For example, looking at the user's behavior pattern on Sunday, it can be seen that there is a habit of “meal” after watching “show”. In other words, as a user's Sunday action, when a store of the genre “show” is used, the store of the genre “meal” is likely to be used subsequently. Therefore, the subsequent genre prediction unit 210 may use a specific genre after a specific user uses a predetermined genre based on the behavior history information stored in the behavior history information storage unit 220. A process for predicting a high genre is performed.

  On the other hand, the store information providing unit 130 uses the prediction result of the subsequent genre to add store information related to the subsequent genre of the genre related to the store information together with the store information corresponding to the provision request from the user. It can be provided as information. In other words, when user A requests store information related to “show”, the store information is provided as requested, and after using the store related to “show”, stores of the genre “meal” are provided. It is predicted that it will be used, and store information of the genre “meal” is provided as additional information.

  For example, User A makes a request to provide store information with a search using a keyword such as “Movie Shibuya” to the store information providing unit 130 on Sunday, and as a result, matches the user's preference. A summary list of store information is presented, and on this summary list, the user clicks on the title part “Theatre XX”, so the “Teater XX” store (movie theater) Assume that store information D1 is to be presented. In this case, the store information providing unit 130 gives an instruction “predict the genre following the user's Sunday“ show ”” to the subsequent genre prediction unit 210. In response to this instruction, the subsequent genre prediction unit 210 refers to “the user's Sunday action history” stored in the action history information storage unit 220, and enters “the user's Sunday“ show ”. It is predicted that the “following genre” is “meal” and reports this to the store information providing unit 130. Therefore, the store information providing unit 130 selects store information D2 that belongs to the genre of “meal” and matches the taste of the user A as additional information. For this purpose, the store evaluation information storage unit 120 is searched, and a store ID (content ID) having a meal genre code is selected that matches the taste of the user A. Then, in response to the request of the user A, when providing the store information D1 of the store “Theatre OO”, store information D2 belonging to the “meal” genre selected as additional information is also provided. .

  FIG. 21 is a diagram illustrating an example of a specific form of providing the above example. In this example, store information D1 is first displayed on the terminal device operated by the user A as shown in FIG. 21 (a). The store information D1 is original store information requested by the user A (that is, store information that matches the keyword “movie Shibuya”). However, as shown in the figure, the store information providing unit 130 adds a transition button B made up of a character string “special notice”. When the user A clicks the transition button B, the store information D2 is displayed as shown in FIG. 21 (b). That is, in the case of the presentation form shown in FIG. 21, first, the store information providing unit 130 transmits Web page data in which the transition button B is added to the store information D1 as requested by the user A, and the transition button B is clicked. In such a case, the Web page data of the store information D2 is transmitted as additional information.

  On the other hand, FIG. 22 is a figure which shows an example of another provision form about the above-mentioned example. In this example, the store information providing unit 130 performs processing for creating and providing new Web page data by fusing additional information with store information as requested by the user A. As a result, the store information D3 as shown is presented. This store information D3 is basically store information related to the theater “Theatre XX”, but as shown in the figure, it is an addition consisting of a character string “Currently being held at a pasta fair at Ristorante PAT” Information A is added. This additional information A is information extracted from part of the store information D2 (see FIG. 21 (b)) belonging to the genre of “meal” predicted as the subsequent genre. The user A can obtain a display as shown in FIG. 22 simply by requesting store information related to “movie”. This display includes additional information A together with store information related to the “movie” according to the request. This additional information A is “meal” that the user A is expected to execute after “movie”. It is store information related to.

  21 and 22 show examples of specific presentation forms of additional information. Of course, the presentation form of additional information is not limited to these examples, and various other forms are available. Can be presented. For example, the display screen of the user terminal may be divided into two so that store information related to “movie” and store information (additional information) related to “meal” are displayed simultaneously. Alternatively, a small window is displayed on a part of the screen on which store information related to “movie” is displayed, and store information (additional information) related to “meal” is displayed in the window. Forms are also possible.

  Note that the prediction by the subsequent genre prediction unit 210 can be performed based on the following several algorithms, for example. The first algorithm is a method for selecting a genre in which the number of executions performed immediately after a “specific genre” in the past is equal to or greater than a predetermined reference value as a “subsequent genre for the specific genre” for a specific user. . For example, in the example shown in FIG. 20 (a), if the reference value is set to 3 for each day of the week, the number of times “meal” is executed immediately after “show” is 3 times for Sunday. Therefore, the genre “meal” is selected as the genre subsequent to the genre “show”. On the other hand, in the case of the example shown in FIG. 20B, for Sunday, the number of times that “coffee” was executed immediately after “show” was two times, and the number of times that “meal” was executed immediately after “show” was Since it is once, in the case of the same standard, a subsequent genre is not selected (in this case, no additional information is provided).

  It is also possible to make predictions with slightly relaxed conditions. Specifically, an action in which the number of executions performed in the past immediately after the “specific genre” or several times later becomes a predetermined reference value or more may be selected as the “subsequent genre for the specific genre”. Here, the meaning of “executed several times later” does not mean “immediately after”, but may mean that another action may be interposed. For example, action history information in the order of “shopping”, “show”, “meal”, and “coffee” is stored in the fifth row of the Sunday column in FIG. Here, “coffee” does not correspond to an action performed immediately after (once after) “show”. However, it corresponds to the action executed by “after 2 times”. Therefore, in the case of Sunday in FIG. 20B, the condition “after two times” is set as “several times later”, the reference value is set to 3, and immediately after “specific genre” or 2 If a genre that has been executed three times or more is selected as a “subsequent genre”, the number of times that “coffee” is executed immediately after the “show” or two times later is three times. Therefore, “Café” will be selected as the genre following “Show”.

  Of course, there may be a plurality of genres selected as “subsequent genres”. For example, if both “meal” and “coffee” are selected as the genre of “show”, both the store information related to “meal” and the store information related to “coffee” are added information. You can provide as. However, if the number of additional information is too large, it will be annoying for the user, so in practice, only one genre with the highest number of times or only some of the top genres will be selected as “subsequent genres”. Is preferred.

  It is also possible to select the “subsequent genre” on the basis of the ratio executed in the past instead of the number executed in the past. For example, if the genre performed immediately after or twice after the “show” is aggregated, the “meal” is 3 times, the “coffee” is 1 time, and the “sport” is 1 time. The ratio of the genre performed immediately after or two times after is “meal” is 60%, “coffee” is 20%, and “sports” is 20%. Therefore, for example, if a genre having this ratio of 50% or more is selected as the “subsequent genre”, “meal” is selected as the “subsequent genre”.

  In practice, it is preferable to perform the selection based on the ratio rather than the selection based on the number of times. This is because, when the number of samples of behavior history information collected by the behavior history information collection unit 230 increases, the number of behaviors that exceed the reference value increases when selection based on the number of times is performed. This is because if the selection is made based on the standard, the number of actions exceeding the standard value will not increase.

  It should be noted that both the case where the number of times is used as a reference and the case where the ratio is used as a reference can be said in common. However, the number of actions performed immediately after is counted more heavily than the number of actions performed two times later. It is also possible to perform aggregation in consideration of the weighting. For example, if the number of times performed immediately after is multiplied by a factor of 2 and the number of times performed twice after is multiplied by a factor of 1, the number of times performed immediately after is counted more heavily. Is possible.

  As already explained in the example shown in FIG. 20, when actually predicting the “following genre”, it recognizes the day of the week of prediction and refers to the action history information related to the same day of the week as the recognized day of the week. It is preferable to predict the “subsequent genre”. This is because the behavior pattern of ordinary people is often different for each day of the week. Of course, instead of carrying out separate handling for each day of the week, it is also possible to carry out two kinds of handling, Saturday and Sunday. Or, for holidays, it is possible to operate in the same manner as Sundays.

  Further, when actually predicting the “subsequent genre”, it is preferable to determine that “executed immediately or several times later” within a continuous time frame set in units of 24 hours. For example, action history information in the order of “show” and “meal” is stored in the first line of Sunday in FIG. 20 (a), and “coffee”, “show”, “ The action history information in the order of “meal” is stored, but the action order to be considered when predicting the “following genre” is completed for each row (that is, within a continuous time frame set in units of 24 hours). Do not consider the order across rows. That is, from the information on the first line, it is possible to recognize the behavior pattern that “meal” was performed immediately after “show”, and from the information on the second line, “show” immediately after “coffee”. Or the action pattern of “meal” immediately after the “show” can be recognized, but the last “meal” on the first line and the “cafe” on the second line It is not appropriate to recognize the behavior pattern that “coffee” was performed immediately after “meal” based on the temporal context of. This is because an ordinary person's behavior pattern should normally be grasped on a daily basis.

<<< §9. Other variations >>
Finally, other modifications of the present invention will be described.

(1) Modified example in which genre division is not performed In the embodiments described so far, in order to handle individual stores (Web content data) divided into several genres, store evaluation information E and user preference information are used. The genre code is included in T, and the comparison between the two is performed between those including the same genre code. However, when carrying out the present invention, it is not always necessary to categorize stores except for the fourth embodiment described in §8, and it is not essential to use genre codes. For example, in the case of operating as a system that provides only restaurant information of restaurants, all the store information to be handled belongs to the genre of restaurants, so there is no need to divide the genre. Of course, even in this case, it is meaningful to divide the genre into subdivisions such as Japanese cuisine, French cuisine, and Italian cuisine.

(2) Modified Example for Presenting Evaluation Values FIGS. 2A to 2I show display examples of store information for various stores. In the store evaluation information storage unit 120, each of these items is displayed. Store evaluation information about the store is prepared, and an evaluation value related to a predetermined feature item is stored for each store. Therefore, when the store information providing unit 130 provides the store information, it is convenient to provide the evaluation value included in the store evaluation information about the store related to the store information. Then, the user can grasp the evaluation values shown in FIGS. 4 (a) to (i) together with the store information as shown in FIGS. 2 (a) to (i). Can be used for reference.

(3) Combination of first to fourth embodiments So far, the second to fourth embodiments have been described as a system in which new features are added to the system of the first embodiment as a base. The systems of the first to fourth embodiments can be used in any combination. For example, a system combining the second embodiment and the third embodiment, a system combining all of the first to fourth embodiments, and the like can be realized.

(4) Search condition used for selection of store information providing unit The store information providing unit 130 of the information providing system according to the present invention receives a request for providing store information that matches a specific search condition from a user. Sometimes, it fulfills a function of selecting store information that matches the search condition and is suitable for the user. That is, the store information providing unit 130 selects a large number of store information stored in the store information storage unit 100 through two screens. The first screen is a selection based on the criterion “matches a specific search condition”, and the second screen is a selection based on the criterion “suitable for users”. Here, as described above, the second sieve is performed based on the comparison between the user preference information T and the store evaluation information E.

  On the other hand, as the “specific search condition” serving as the reference for the first sieve, in the embodiments described so far, an example in which the condition “matches the keyword input by the user himself” is set. For example, when a user makes a request for providing store information by inputting the keywords “Italian”, “Restaurant”, and “Shibuya”, store information related to these keywords is selected in the first sieve. It will be. However, the “specific search condition” which is the first screening criterion in the information providing system according to the present invention is not limited to the condition “matches the keyword input by the user itself”. Various conditions can be set.

  For example, the condition “matches the genre input by the user” can be set as the search condition. In this case, when making a request for providing store information, the user may perform an input designating a genre such as “Italian cuisine” or “Women's clothing”. In this case, the store information providing unit 130 performs a search based on a genre code, not a search based on a keyword. Of course, a large category such as “meal”, “coffee”, and “shopping” may be designated as a search condition.

  The “specific search condition” does not necessarily have to be input by the user. For example, if “user's current location” is set as a search condition, the first sieve criterion is “store information that matches the user's current location”. In this case, since the “user's current position (for example, latitude / longitude information)” can be automatically recognized by various methods, it is not always necessary for the user to input it. As a method for causing the system to recognize the “user's current position”, as exemplified in §4, a method for allowing a user to report the fact of store use, and a method for recognizing the position of a mobile terminal device with a GPS function A method of recognizing that communication has been performed between the store installation device and the mobile terminal device possessed by the user can be used. Therefore, if “user's current location” is set as a search condition, the store information providing unit 130 automatically recognizes the current location of each user by the above method and matches each user with the current location. The store information to be selected can be selected. For example, when providing store information to a user who is recognized as being in “Shibuya”, store information of stores in the “Shibuya” area may be selected in the first screening process.

  Of course, it is possible to use a combination of a search condition such as a keyword or genre and a search condition such as the current position. For example, if it is possible to recognize that the current location of the user who has requested the provision of store information by inputting the keywords “Italian” and “Restaurant” is “Shibuya”, the “Shibuya” district in the first screening process It is only necessary to select store information of an Italian restaurant that has a store.

  As another search condition, “user schedule” may be set as the search condition, and “store information that matches the user schedule” may be selected in the first screening. In this case, the user is allowed to register his / her action schedule in advance in the store information providing unit 130 (or a server device outside the system of the present application). For example, a personal calendar that allows the user to enter and browse a schedule is provided to the user terminal in the form of a Web page so that each user can register a monthly schedule and the like. Then, the store information providing unit 130 can recognize which user is planning what kind of action when and by referring to the registered content, so this schedule is used as a search condition. The first sieving process can be performed.

  For example, it is assumed that a plan of “a meal on a wedding anniversary from 6:00 pm on November 20, 2006” is registered as a schedule of a certain user. In this case, if there is a request for providing store information from the user on “November 20, 2006”, the schedule “Marriage Day Meal” is used as a search condition, and the store information about the restaurant in the first screening is used. Can be selected. For example, a search may be performed using the keywords “marriage anniversary” AND “meal”. Of course, not only the date “November 20, 2006” but also the time may be considered. For example, if store information related to a schedule set within 6 hours from the time when a request is received from the user is selected by the first screening, in the above example, “November 20, 2006 When there is a request from noon to 6 pm, a search is performed using the keywords “marriage anniversary” AND “meal”. In addition, in the case of a user whose schedule is set for each day of the week, such as “Everyday on Fridays”, the store information regarding the restaurant is selected by the first screening when requested on “Friday”. You can also. On the other hand, in the case of a user whose schedule is set for each time zone, such as “every day, lunch from noon”, for example, refer to the schedule set within one hour from the current time. In this case, when there is a request from “11 am to noon”, the store information regarding the restaurant can be selected by the first screening. In this way, the first screening can be performed based on the date, time, and day of the week when the store information provision request is made.

(5) Accompaniment Recognition In §8, as a fourth embodiment, daily behavior patterns for each individual user are collected, and based on the results of this collection, the action is executed after a behavior related to a certain genre. He described a method for predicting expected genres. That is, as shown in FIG. 19, the action history information collection unit 230 collects action history information indicating “when and who used the store of which genre” and stores it in the action history information storage unit 220. Next, based on this action history information, the subsequent genre prediction unit 210 determines which genre is likely to be performed next when a specific user performs an action related to one genre. Predictive processing is performed.

  This subsequent genre prediction is based on the assumption that the “following genre” is predicted by referring to the past behavior patterns of individual users. In general, the behavior pattern differs depending on the difference. For example, even if the behavior pattern is the same user, the behavior pattern when going out with a fiancee, the behavior pattern when going out with a colleague of the company, and the behavior pattern when going out with a classmate at the university may be different. Many.

  Therefore, if the action history information collection unit 230 collects action history information indicating “when, who, who, and which genre the store was used” and stores it in the action history information storage unit 220, The genre prediction unit 210 can predict the subsequent genre in consideration of the accompanying person. For example, the action history information shown in FIG. 20 (a) shows the action pattern for user A, but “action history information when accompanying user B” or user If you collect “action history information when you are accompanied by 丙” separately if you are accompanied by 甲, if you can recognize that you are currently going out with 乙In addition, it is possible to predict the “subsequent genre” based on the “behavior history information at the time of attendance”, and it is possible to make a more appropriate prediction.

  However, in order to perform prediction in consideration of the accompanying person, it is necessary not only to grasp the behavior of each user but also to recognize the accompanying person of the action. As a specific method for causing the action history information collecting unit 230 to collect action history information including companion information, the “method by self-declaration of each member” is the simplest method. When each member reports himself / herself, information indicating the accompanying person “with whom” may be included. Alternatively, the above-described “method for inputting a schedule in advance” may be used. In this case, when the schedule is input, information indicating the accompanying person “with whom” may be included.

  In addition, if the companion has a mobile phone with GPS, the location information of the companion can be obtained if the system automatically reports the location information recognized by the GPS to the system. Since it is possible, it becomes possible to recognize the person who exists in the same position as the person as the accompanying person. Or it is also possible to collect companion information by a store installation device. For example, if the entrance / exit gate device of the same facility is used, it is possible to obtain information regarding the entrance / exit of the accompanying person as well as the person, so that the companion can be recognized by the report from the entrance / exit gate device. In addition, if a communication device that distributes restaurant cards, coupons, etc. as electronic data is installed in a store facility such as a restaurant, the portable terminal device owned by the accompanying person will also receive the electronic data. Thus, if the information identifying the store contained in the electronic data and the identification code of the accompanying person are automatically reported from the portable terminal device or the communication device to the system, the same store as the person concerned The person who is in can recognize the companion. The same applies to the case where electronic data including information identifying a store is received from a two-dimensional code printed on a medium such as a leaflet placed in a facility by a portable terminal device possessed by the accompanying person. It is.

  Another method is a method of using a communication function between portable terminal devices possessed by individual users. Recently used mobile terminal devices have a function of communicating with another mobile terminal device using infrared rays, Bluetooth (registered trademark), wireless LAN, or the like. Therefore, if the mobile terminal device owned by the person and the mobile terminal device owned by the accompanying person can communicate with each other as described above (if any information can be directly exchanged between the terminals, any form of If it is possible to perform direct communication using a communication function), it is possible to obtain information for identifying a companion through this direct communication. For example, if the infrared communication function is used, an identification code for identifying the accompanying person stored in the accompanying person's portable terminal device can be obtained by performing a predetermined communication operation with both the portable terminal devices facing each other. , It can be taken into the person's mobile terminal device side. Therefore, when the action history information is transmitted from the personal mobile terminal device to the action history information collecting unit 230 by the various methods described so far, information including an identification code for identifying the accompanying person is transmitted. Is possible.

  In addition, when omnidirectional communication functions such as Bluetooth (registered trademark) and wireless LAN can be used, it is possible to collect identification codes for identifying accompanying persons without intentional communication operation by the user. is there. For example, if both mobile terminal devices have a function of searching and communicating with other mobile terminal devices existing in the vicinity at a predetermined cycle (for example, every 5 minutes), no intentional communication operation is performed. However, the identification code of the partner user can always be obtained from the mobile terminal device in the vicinity, and the latest information “who are currently with” can always be updated.

  Further, these methods can be combined with the above-described “method for inputting a schedule in advance”. In other words, if a schedule with a companion identification code (a schedule specifying who the action is to be performed with) is registered in advance, “accompanied identification code actually taken in the store” and “registered” When the companion identification code in the scheduled schedule matches, it can be automatically determined that the action related to the schedule has actually been executed.

  Note that the various methods for recognizing a companion described above can also be applied to the third embodiment described in §7. In the third embodiment, for example, when the user A plans to use some store together with the companion B, a request for providing store information under the group use condition “user A & B” is provided. The store information is selected in consideration of the user preference information of both users A and B. Therefore, if there is a store information request from the user A, if the above-mentioned various methods can automatically recognize that the companion of the user A is B, the user A himself will It is possible to select store information in consideration of user preference information of both Party A and Party B without actively communicating “something” to the store information providing unit 130.

10: User terminal (mobile phone)
20: User terminal (notebook computer)
30: User terminal (desktop personal computer)
100: Store information storage unit 110: User preference information storage unit 120: Store evaluation information storage unit 130: Store information provision unit 140: Preference value update unit 150: Store of interest recording unit 160: Evaluation value update unit 170: Voting result recording Unit 180: Satisfaction ratio calculation unit 190: Personal satisfaction information recording unit 200: Internet 210: Subsequent genre prediction unit 220: Behavior history information storage unit 230: Behavior history information collection unit A: Additional information B: Transition button DOO: Store information EXX: Store evaluation information E1, E2, E3: Tip point of evaluation vector GXX: Genre code MXX: Personal satisfaction information SXX: Store ID (content ID)
TOO: user preference information T0: tip points of preference vectors Ve1, Ve2, Ve3: evaluation vector Vt: preference vector A, B, B: user ID

Claims (21)

A store information storage unit storing store information about individual stores,
A store evaluation information storage unit for storing store evaluation information including a store ID for specifying a store and an evaluation value of the store for a predetermined specific characteristic item for each of various stores;
A user preference information storage unit that stores user preference information including a user ID for specifying a user and a preference value of the user for the feature item for each of various users;
When a request for providing store information that matches a specific search condition is received from a user, “the user preference information of the user stored in the user preference information storage unit” and “the store evaluation information storage” By comparing the preference value and the evaluation value of the corresponding feature item for “store evaluation information for various stores stored in the department”, the search condition is satisfied and suitable for the user The store information is selected based on the degree of approximation between the preference value and the evaluation value to be compared, the selected store information is extracted from the store information storage unit, and this is stored in the terminal device of the user. A store information provider,
When a plurality of users use a specific store as a group, group configuration information for identifying users constituting the group, a user ID for identifying individual users, and individual users A personal satisfaction information recording unit for accumulating and recording personal satisfaction information including satisfaction,
Based on all or a part of the personal satisfaction information recorded in the personal satisfaction information recording unit, a satisfaction ratio between users under a group usage condition of “use a store in a specific group” is calculated. A satisfaction ratio calculation unit that calculates the ratio of the average value of each individual user of the personal satisfaction included in the personal satisfaction information to be used;
With
When the store information providing unit receives a request for providing store information under a specific group usage condition, from among candidate store information suitable for each individual user according to the specific group usage condition, An information providing system characterized by selecting and providing store information according to the satisfaction ratio for each individual user. In the information provision system of Claim 1,
An interest store recording unit that stores and records the store ID of the specific store as the store of interest ID for each individual user when the user indicates interest in the specific store;
For each individual user, all or a part of the store IDs recorded in the store of interest store are extracted as store IDs for update, and store evaluation including the store ID for update from the store evaluation information storage unit Information is extracted as update store evaluation information, and the preference value of the user preference information for the user stored in the user preference information storage unit is updated based on the evaluation value of the update store evaluation information A preference value update unit,
An information providing system further comprising: In the information provision system of Claim 1,
A voting result recording unit for accumulating and recording the voting result when a personal evaluation value for a feature item of a specific store is voted by a user;
For each individual store, all or a part of the voting results recorded in the voting result recording unit are extracted, and based on the extracted voting results, the stores stored in the store evaluation information storage unit An evaluation value update unit for updating the evaluation value of the store evaluation information;
An information providing system further comprising: A store information storage unit storing store information about individual stores,
Store evaluation information including a store ID for specifying a store, a genre code indicating the genre of the store, and an evaluation value of the store for a specific feature item determined in advance corresponding to the genre code A store evaluation information storage unit storing various stores,
User preference information including a user ID for identifying a user, a genre code, and a preference value of the user for the feature item corresponding to the genre code is stored for each of various users. A user preference information storage unit,
When a request for providing store information that matches a specific search condition is received from a user, “the user preference information of the user stored in the user preference information storage unit” and “the store evaluation information storage” By comparing the preference value and the evaluation value of the corresponding feature item for “store evaluation information for various stores stored in the department”, the search condition is satisfied and suitable for the user The store information is selected based on the degree of approximation between the preference value and the evaluation value to be compared, the selected store information is extracted from the store information storage unit, and this is stored in the terminal device of the user. A store information provider,
When a plurality of users use a specific store as a group, group configuration information for specifying users constituting the group, a genre of the used stores, and a user ID for specifying individual users And a personal satisfaction information recording unit for accumulating and recording personal satisfaction information including the user's personal satisfaction level,
Based on the personal satisfaction information recorded in the personal satisfaction information recording unit, the satisfaction ratio between users under the group usage condition of “use a store of a specific genre in a specific group” is used for calculation. A satisfaction ratio calculation unit that calculates the ratio of the average value of each individual user of the personal satisfaction included in the personal satisfaction information,
With
When the store information providing unit receives a request for providing store information under a specific group usage condition, from among candidate store information suitable for each individual user according to the specific group usage condition, An information providing system characterized by selecting and providing store information according to the satisfaction ratio for each individual user. The information providing system according to claim 4,
An interest store recording unit that stores and records the store ID of the specific store as an interest store ID for each individual user and for each genre when the user indicates interest in the specific store. When,
For each individual user, “all or a part of the store IDs of the predetermined genre to be updated” recorded in the store of interest store is extracted as an update store ID, and the store evaluation information storage unit The store evaluation information including the update store ID is extracted as the update store evaluation information, and based on the evaluation value of the update store evaluation information, the user stored in the user preference information storage unit A preference value update unit for updating a preference value of user preference information related to the predetermined genre to be updated,
An information providing system further comprising: The information providing system according to claim 4,
A voting result recording unit for accumulating and recording the voting result for each individual store when a personal evaluation value for a characteristic item of a specific store is voted by a user;
For each individual store, all or a part of the voting results recorded in the voting result recording unit are extracted, and based on the extracted voting results, the stores stored in the store evaluation information storage unit An evaluation value update unit for updating the evaluation value of the store evaluation information;
An information providing system further comprising: In the information provision system in any one of Claims 4-6,
When each user uses a specific store, an action history information collection unit that collects action history information including the user ID of the user, the genre code of the store, and the usage time;
An action history information storage unit for storing the collected action history information;
A subsequent genre prediction unit that predicts a genre that is likely to be used subsequently after a specific user uses a predetermined genre based on the behavior history information;
Further comprising
The store information providing unit provides store information related to the subsequent genre of the genre related to the store information as additional information together with the store information corresponding to the provision request from the user, using the prediction result by the subsequent genre prediction unit. An information providing system characterized by In the information provision system in any one of Claims 1-7,
The store information providing unit has a function of transmitting Web content data to a terminal device operated by a user via the Internet. Store information is stored as Web content data in the store information storage unit. An information providing system using a content ID for specifying the Web content data as a store ID. In the information provision system in any one of Claims 1-8,
Store evaluation information containing evaluation values for each of a plurality of N feature items is stored in the store evaluation information storage unit,
User preference information including preference values for each of a plurality of N feature items is stored in the user preference information storage unit,
When the store information providing unit receives a store information provision request from a user, “the preference value for each of the N feature items included in the user preference information of the user is expressed in N-dimensional coordinates. "Preference vector obtained by taking each coordinate axis of the system" and "Evaluation value for each of the N feature items included in the store evaluation information of each store is taken as each coordinate axis of the N-dimensional coordinate system" The information providing system characterized in that the evaluation information obtained by the comparison is compared and the store information is selected based on the degree of approximation of both vectors. In the information provision system in any one of Claims 1-9,
An information providing system characterized in that, when the store information providing unit provides store information, it also provides an evaluation value included in store evaluation information about the store related to the store information. In the information provision system in any one of Claims 1-10,
A first providing step in which the store information providing unit selects a plurality of store information that matches a search condition and is suitable for a user, and provides a list in which only an overview of each selected store information is provided; And a second providing step of providing all contents of the store information relating to the store designated by the user from the list. In the information provision system according to claim 2 or 5,
A first providing step in which the store information providing unit selects a plurality of store information that matches a search condition and is suitable for a user, and provides a list in which only an overview of each selected store information is provided; A second providing step of providing all the contents of the store information relating to the store designated by the user from the list,
When the store information providing unit performs the second providing step based on the user's designation, the store ID of the store for which the store information is provided in the second providing step is An information providing system characterized by accumulating and recording an interest store ID for a user. In the information provision system in any one of Claim 2, 5, 12,
When the store of interest record receives a report from a user that he / she is interested in a specific store, or when he / she receives a report that he / she has used a specific store, The information providing system characterized by accumulating and recording the store ID as the store ID of interest. In the information provision system in any one of Claims 2, 5, 12, and 13,
The store information providing unit has a function of providing store information to the mobile terminal device possessed by the user,
When the store of interest recording unit detects that the user is located in a specific store based on information from a position recognition device having a function of recognizing the position of the mobile terminal device, the user And storing the store ID of the store as an interested store ID. In the information provision system in any one of Claims 2, 5, 12-14,
The store information providing unit has a function of providing store information to the mobile terminal device possessed by the user,
When a store of interest stores a communication between a store installation device installed in a predetermined store and the mobile terminal device, receiving a notification from the store installation device or the mobile terminal device, An information providing system for storing and recording the store ID of the store as an interested store ID for the user. In the information provision system in any one of Claims 2, 5, 12-15,
The interested store recording unit records the time information at the time of recording when recording the interested store ID,
An information providing system, wherein the preference value update unit extracts only the store IDs recorded in the store of interest store as the store IDs for update from the store IDs recorded within a predetermined period. In the information provision system in any one of Claims 2, 5, 12-16,
An information providing system in which a preference value update unit updates an average value of evaluation values of update store evaluation information to a new preference value of user preference information. In the information provision system according to claim 3 or 6,
When the voting result recording unit records the voting result, it also records the time information at the time of recording,
An information providing system, wherein the evaluation value update unit extracts only the voting results recorded in the voting result recording unit within a predetermined period and updates the evaluation value of the store evaluation information . The information providing system according to any one of claims 3, 6 and 18,
An information providing system in which an evaluation value update unit updates an average value of individual evaluation values included in an extracted voting result as a new evaluation value of store evaluation information. In the information provision system in any one of Claims 1-19,
When the personal satisfaction information recording unit records personal satisfaction information, it also records the time information at the time of recording,
An information providing system in which a satisfaction rate ratio calculation unit calculates a satisfaction rate ratio using only personal satisfaction information recorded in a personal satisfaction information recording unit that is recorded within a predetermined period. . In the information provision system in any one of Claims 1-20,
Probability according to the direct ratio of satisfaction ratio for each individual user, or satisfaction ratio for each individual user, from the store information candidates suitable for each individual user. An information providing system characterized by selecting and providing store information with a probability corresponding to the inverse ratio of.

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