JP5999495B2 - Coupling device and coupling system - Google Patents

Description

  The present invention relates to a coupling device and a coupling system that detect compatibility between users.

  2. Description of the Related Art Social network systems (SNS) that exchange information with others using electronic devices such as PCs, tablets, and smartphones have become widespread. And several techniques for using SNS more conveniently are proposed (refer patent documents 1-4).

Japanese Patent Publication No. 2010-500651 Japanese Patent Publication No. 2008-539528 JP 2003-186974 A JP 2003-108507 A

  Patent Document 1 discloses a technique for evaluating user similarity in an SNS environment. However, in order to implement this technique, it is assumed that all users provide accurate information themselves. If some users provide inaccurate information, accurate grouping becomes impossible and the user's similarity cannot be evaluated correctly.

  Patent Document 2 discloses a technique for parameterizing information related to hobbies provided by each user and detecting compatibility between users, but still depends on the self-reporting of the user, and some users If uncooperative, accurate compatibility detection is not possible.

  In Patent Document 3, the SNS user is input not only with a keyword but also with a psychological feeling between the users who perform compatibility diagnosis by inputting the degree of psychological feeling with respect to the keyword. Although a technique for performing a diagnosis is disclosed, the subjectivity of each user is easy to enter, and an objective determination cannot be made. Therefore, it cannot be said that the reliability of the compatibility diagnosis result is high.

  Patent Document 4 specifies another user Bi who is close to a certain user A based on the number of chats between the users, and another user Bij who is highly similar to this user Bi and its similarity bij. Is specified, and the randomization process is performed on the rank of the user Bij in descending order of similarity from the viewpoint of entertainment, and the finally remaining user is introduced to the user A as the best match user. However, in the technique of Patent Document 4, it is assumed that there is another user Bi equal to the user A and there is a user Bij equal to the user Bi, and the most preferable user is not necessarily introduced to the user A.

  Moreover, in patent document 4, although the word used by chat is used in order to judge compatibility with other users, it is technically difficult to identify a word by performing speech recognition, In addition, since words used in chat change depending on the content of conversation, it is not always possible to make a highly reliable compatibility determination.

  As described above, in the conventional technique, the compatibility between one user who uses SNS and another user cannot be accurately determined.

  By the way, recently, electronic books are rapidly spreading. Electronic books are generally purchased from an electronic book store provided on a network. The electronic book store manages the purchase history of electronic books for each user, and a virtual bookshelf in which purchased electronic books are arranged can be displayed on the screen of the electronic book terminal possessed by each user. Yes.

  Since each user has a different preference for a book, the user's preference and personality can be estimated relatively accurately based on the bibliographic information of the electronic book to be purchased and the number of times of browsing.

  However, in the above-described Patent Documents 1 to 4, it is not assumed at all that the information of the electronic book is used for compatibility diagnosis with other users and determination of the accuracy of SNS exchange.

  The present invention has been made in order to solve the above-described problems of the prior art, and whether or not a plurality of users are suitable for performing exchanges via SNS can be simplified and simplified before actually starting exchanges. The present invention provides a coupling device and a coupling system that can be accurately determined.

In order to solve the above-described problems, in one aspect of the present invention, bibliographic information analysis for analyzing bibliographic information of each electronic book possessed by the user for each user, and browsing status of each electronic book possessed by the user for each user Means for performing at least one of browsing status analysis to be analyzed;
A coupling rate detection unit that detects a coupling rate between the plurality of users based on a rate at which the bibliographic information by the bibliographic information analysis of the plurality of users or / and the browsing status by the browsing status analysis match. A coupling device is provided.

Moreover, in one aspect of the present invention, an information communication device capable of browsing an electronic book possessed by a user, a coupling device that detects a degree of similarity between a plurality of users, and a book information storage that stores bibliographic information of the electronic book A coupling system comprising:
A unique bibliographic information storage device for storing bibliographic information more detailed than the bibliographic information stored in the book information storage device;
The coupling device includes:
Perform at least one of bibliographic information analysis for analyzing the bibliographic information of each electronic book owned by the user for each user and browsing status analysis for analyzing the browsing status of each electronic book owned by the user for each user,
A coupling system comprising: a coupling detection unit configured to detect a coupling rate between the plurality of users based on a rate at which the bibliographic information or / and browsing state analysis based on bibliographic information analysis of the plurality of users match. Provided.

  According to the present invention, it is possible to easily and accurately determine whether or not a plurality of users are suitable for performing exchange through SNS before actually starting exchange.

The block diagram which shows schematic structure of the coupling system 2 provided with the coupling apparatus 1 which concerns on one Embodiment of this invention. The figure which shows an example of a data structure of bibliographic information DB5 which memorize | stores the bibliographic information of an electronic book. The figure which shows an example of a data structure of original bibliographic information DB6 which memorize | stores the original bibliographic information of an electronic book. 5 is a flowchart illustrating an example of a procedure for a user to use an electronic book terminal 3; FIG. 3 is a block diagram illustrating an example of an internal configuration of the coupling device 1. The flowchart which shows an example of the process sequence of the book information analysis part 21 of FIG. The figure which shows an example of the data structure of personality determination DB4 which memorize | stores the process result of the book information analysis part 21. FIG. The flowchart which shows an example of the process sequence of the book browsing analysis part 23 in the coupling apparatus 1. FIG. The figure which shows an example of the data structure of individuality determination DB4 which memorize | stores the process result of the book browsing analysis part. The flowchart which shows an example of the process sequence of the individuality type analysis part 25 in the coupling apparatus 1. FIG. The figure explaining selection of individuality type information. The figure which shows an example of the data structure of individuality determination DB4 which memorize | stores the processing result of the individuality type analysis part 25. FIG. The figure which shows an example of the virtual bookshelf which the bookshelf production | generation part 33 produces | generates. The flowchart which shows an example of the process sequence of the bookshelf structure analysis part 27 in the coupling apparatus 1. FIG. The figure which shows an example of the data structure of personality determination DB4 which memorize | stores the processing result of the bookshelf structure analysis part 27. FIG. The flowchart which shows an example of the process sequence of the bookshelf evaluation analysis part 29 in the coupling apparatus 1. FIG. 4 is a flowchart illustrating an example of a processing procedure of a comprehensive analysis unit 30 in the coupling device 1. The figure which shows an example of the data structure of personality determination DB4 which memorize | stores the processing result of the comprehensive analysis part 30 of FIG. 4 is a flowchart showing an example of a processing procedure of a coupling rate detection unit 31 in the coupling device 1. The flowchart which shows an example of the process sequence of the referral letter production | generation determination process which the coupling apparatus 1 performs. The figure which shows an example of the introduction letter production | generation determination processing result of FIG. The flowchart which shows an example of the process sequence of the introduction letter production | generation part 32. FIG. The figure which shows an example of the referral letter 40 produced | generated by the process of the referral letter production | generation part 32 of FIG. The flowchart which shows an example of the process sequence which produces | generates automatically the face illustration image published on the introduction letter. The flowchart which shows an example of the process sequence of the information provision apparatus 10 which performs advertisement delivery.

  Hereinafter, embodiments of the present invention will be described in detail.

  FIG. 1 is a block diagram showing a schematic configuration of a coupling system 2 including a coupling device 1 according to an embodiment of the present invention. The coupling system 2 in FIG. 1 includes a coupling device 1, an electronic book terminal 3 possessed by a user, and a personality determination database device (hereinafter referred to as individuality determination) that stores various types of information used to determine the individuality of each user. DB) 4, a bibliographic information database device (hereinafter referred to as bibliographic information DB) 5 that stores standard bibliographic information of electronic books, and a unique bibliographic information database device (hereinafter referred to as original bibliography) that stores original bibliographic information of electronic books. Information DB) 6, an electronic book management server 7 for operating and managing the electronic book store, a member information management database device (hereinafter referred to as member information management DB) 8 for storing member information of users accessing the electronic book store, etc. An electronic book information database device (hereinafter referred to as an electronic book information DB) 9 for storing information on the electronic book purchased by the user, and a coupling An information providing device 10 that provides various types of information such as advertisement information based on the processing results of the processing device 1, and an information providing database device (hereinafter, information providing DB) 11 that stores various types of information provided by the information providing device 10. It has.

  The electronic book terminal 3 may be an electronic device (for example, a PC, a tablet, a smartphone, a mobile phone, or the like) capable of browsing an electronic book, and is not necessarily portable.

  The electronic book terminal 3 and the coupling device 1 send and receive various types of information via the Internet 12. For example, the coupling device 1 may be provided inside a server that operates an SNS site or a company site. Further, a server in which at least two of the coupling device 1, the electronic book management server 7, and the information providing device 10 are integrated may be provided.

  In FIG. 1, the bibliographic information DB 5 and the original bibliographic information DB 6 are provided separately, but they may be integrated into one database device. Further, at least one of the bibliographic information DB 5 and the original bibliographic information DB 6 may be integrated into the coupling device 1. Thus, the functions of the components shown in FIG. 1 may be arbitrarily integrated or separated.

  The personality determination DB 4, the bibliographic information DB 5, the member information management DB 8, the electronic book information DB 9, and the information providing DB 11 do not need to be directly connected to the coupling device 1 or the information providing device 10, but via a network such as the Internet. May be placed in a cloud environment.

  Moreover, the information provision apparatus 10 and information provision DB11 of FIG. 1 are not necessarily essential, and may be abbreviate | omitted.

  The coupling device 1 of FIG. 1 presents to the user A whether or not the user A with the SNS is suitable to exchange with other users through the SNS before starting the exchange. Moreover, the coupling apparatus 1 of FIG. 1 uses the information of the electronic book which each user possesses and browses as an index | index which judges whether it is suitable for performing an alternating current, and is another user suitable for an alternating current? Matching information and a coupling rate are generated as a measure for determining whether or not.

  FIG. 2 is a diagram illustrating an example of a data configuration of the bibliographic information DB 5 that stores the bibliographic information of the electronic book. As illustrated, the bibliographic information stored in the bibliographic information DB 5 includes a book name and a corresponding Japanese book code. The Japanese book code is code information including a general ISBN code. The bibliographic information shown in FIG. 2 is an example, and may be arbitrarily added or changed.

  FIG. 3 is a diagram illustrating an example of a data configuration of the original bibliographic information DB 6 that stores the original bibliographic information of the electronic book. The original bibliographic information in the original bibliographic information DB 6 is bibliographic information uniquely standardized by an electronic book store or a company that manages and operates a virtual bookshelf. For example, as shown in FIG. It consists of first name, author name, genre, category, impression after reading. Among these, the genre, category, and post-reading impression are called individuality type information, and are set by the user after browsing the electronic book as will be described later. For other book names, publisher names, and author names, the publisher providing the electronic book registers corresponding information in advance in the original bibliographic information DB 6. Note that the original bibliographic information in FIG. 3 is an example, and may be arbitrarily added or changed.

  FIG. 4 is a flowchart showing an example of a procedure for the user to use the electronic book terminal 3. When the user accesses the electronic book store, the electronic book management server 7 determines whether or not the user has already been registered as a member (step S1). If it is not yet registered, the electronic book management server 7 displays a member registration input form on the user's electronic book terminal 3 (step S2). In response to this, when the user inputs profile information (name, nickname, gender, date of birth, blood type, origin, career, self-introduction, SNS site name used by the user, etc.) on the electronic book terminal 3, If the electronic book management server 7 conducts the examination and there is no problem, the user's profile information is registered in the member information management DB 8 (step S3).

  If it is determined in step S1 that registration has been completed, or if the member registration process in step S3 is completed, the electronic book management server 7 activates the processing module of the electronic book store (step S4), and displays the service usage screen of the user. It is displayed on the electronic book terminal 3 (step S5). On this service use screen, three selection menus of book purchase, virtual bookshelf display, and book viewer are displayed.

  When the user selects to purchase a book from the initial screen of the electronic book store (step S6), the electronic book management server 7 starts a book purchase process (step S7). In this book purchase processing, a list of electronic books that can be sold is displayed on the user's electronic book terminal 3, payment processing for the electronic book selected by the user, or the like is performed.

  When the user selects the virtual bookshelf display from the initial screen of the electronic book store (step S8), the electronic book management server 7 starts the virtual bookshelf display process (step S9). This virtual bookshelf display process acquires the history information of the electronic book which the user purchased in the past from electronic book information DB, produces | generates the display data for displaying a virtual bookshelf on a user's electronic book terminal 3, and is electronic It transmits to the book terminal 3. Using the electronic book terminal 3, the user can arbitrarily rearrange electronic books purchased in the past on the virtual bookshelf.

  When the user selects a book viewer from the initial screen of the electronic book store (step S10), the electronic book management server 7 starts a book viewer process (step S11). In the book viewer process, the main data and bibliographic data of the electronic book that the user desires to browse are transmitted to the electronic book terminal 3. The electronic book terminal 3 receives these data and activates a book viewer.

  Here, the book store module (step S4) displays a menu for selecting services for book purchase (step S6), virtual bookshelf (step S8), and book viewer (step S10) for interactive processing with the user. Although an example has been shown, any one service may be displayed in accordance with an external command. For example, when a recommendation information display command for purchasing a book from the outside is input to the book store (step S4), the book store (step S6) delivers the process only to the book purchase (step S6), and the specific book A purchase page may be displayed. Or when the command for the virtual bookshelf display from the outside is input into the book store (step S4), the book store (step S4) may hand over the process only to the virtual bookshelf to display the virtual bookshelf. Further, when an instruction for starting the book viewer from the outside is input to the book store (step S4), the book store (step S4) passes the processing only to the book viewer (step S10) to display the book viewer. May be. At this time, when specific book information (ID) is designated as an activation parameter, the book viewer (step S10) may be activated in a form in which a specific electronic book is displayed.

  The processing results of steps S6 to S10 described above are stored in the electronic book information DB 9 managed by the electronic book management server 7 as necessary (step S12). More specifically, the electronic book information DB 9 includes purchase history information of electronic books purchased by each user, arrangement information of electronic books in a virtual bookshelf created by each user, and browsing information of electronic books by each user. Store.

  FIG. 5 is a block diagram showing an example of the internal configuration of the coupling device 1. 5 includes a book information analysis unit 21, a book information matching unit 22, a book browsing analysis unit 23, a book browsing matching unit 24, an individuality type analysis unit 25, and an individuality type matching unit 26. A bookshelf configuration analysis unit 27, a bookshelf configuration matching unit 28, a bookshelf evaluation analysis unit 29, a comprehensive analysis unit 30, a coupling rate detection unit 31, a referral letter generation unit 32, and a bookshelf generation unit 33. .

  The book information analysis unit 21 analyzes bibliographic information of each electronic book possessed by each user for each user. The book information matching unit 22 compares the analysis results of the book information analysis unit 21 for each of a plurality of users, and detects the rate at which the bibliographic information matches. The bibliographic information used by the book information analysis unit 21 and the book information matching unit 22 is both bibliographic information stored in the bibliographic information DB 5 and unique bibliographic information stored in the original bibliographic information DB 6.

  The book browsing analysis unit 23 analyzes the browsing status of each electronic book possessed by each user for each user. The book browsing matching unit 24 compares the analysis results of the book browsing analysis unit 23 for each of a plurality of users, and detects the rate at which the browsing status of each user matches. More specifically, the book browsing matching unit 24 compares the bibliographic information of electronic books that are frequently viewed by each user, and detects the rate at which the bibliographic information matches.

  The individuality type analysis unit 25 analyzes individuality type information set by each user after browsing each electronic book. The individuality type matching unit 26 compares the analysis results of the individuality type analysis unit 25 for each of a plurality of users, and detects the proportion of the individuality type information.

  The bookshelf configuration analysis unit 27 analyzes the tendency of the arrangement of each electronic book in the virtual bookshelf for each user. The bookshelf configuration matching unit 28 compares the analysis results of the bookshelf configuration analysis unit 27 for each of a plurality of users, and detects the ratio at which the tendency of the arrangement of the electronic books in the virtual bookshelf matches.

  The bookshelf evaluation / analysis unit 29 detects the ratio of the electronic books publicly set by the user in the total number of the electronic books in the virtual bookshelf, and evaluates the reliability of the user based on the ratio.

  The comprehensive analysis unit 30 comprehensively analyzes each analysis result of the book information analysis unit 21, the book browsing analysis unit 23, the individuality type analysis unit 25, the bookshelf configuration analysis unit 27, and the bookshelf evaluation analysis unit 29.

  The coupling rate detection unit 31 has a rate at which the bibliographic information detected by the book information matching unit 22 matches, a rate at which the browsing status detected by the book browsing matching unit 24 matches, and the individuality type information detected by individuality type matching. The coupling rates of a plurality of users are detected on the basis of the rate at which the electronic books match, and the rate at which the tendency of the arrangement of the electronic books in the virtual bookshelf detected by the bookshelf configuration matching unit 28 matches.

  The introduction letter generation unit 32 generates an introduction letter used to introduce a user with SNS to another user via the network, and includes the analysis result of the comprehensive analysis unit 30 in this introduction letter.

  A book information browsing analysis unit that integrates the book information analysis unit 21 and the book browsing analysis unit 23 shown in FIG. 5, and a book browsing matching unit that also integrates the bibliographic information matching unit and the book browsing matching unit 24. May be provided. The book information browsing analysis unit includes at least a bibliographic information analysis for analyzing bibliographic information of each electronic book held by the user for each user and a browsing status analysis for analyzing the browsing status of each electronic book held by the user for each user. Do one. The book browsing matching unit compares the analysis results of the book information browsing analysis unit for each of a plurality of users, and detects the rate at which the bibliographic information matches. In this case, the coupling rate detection unit 31 and the comprehensive analysis unit 30 detect the coupling rate based on the ratio detected by the book browsing matching unit.

  Coupling rate detection and comprehensive analysis may be performed by performing at least one of bibliographic information analysis, browsing status analysis, bookshelf configuration analysis, and individuality type analysis, and this embodiment is an example of performing comprehensive analysis by combining each analysis. Show.

  FIG. 6 is a flowchart illustrating an example of a processing procedure of the book information analysis unit 21 of FIG. First, bibliographic information (including original bibliographic information) of all electronic books possessed by the user is acquired from the bibliographic information DB 5 and the original bibliographic information DB 6 (step S21).

  Next, each electronic book possessed by the user is classified into a plurality of class information obtained by subdividing each of the bibliographic information acquired in step S21 (step S22). Here, the class information is individual information obtained by subdividing each of the bibliographic information. For example, if the bibliographic information is the publisher shown in FIG. 3, each specific publisher name is each class information. Therefore, in step S22, if the bibliographic information is, for example, a publisher, each electronic book owned by the user is classified for each specific publisher, and if the bibliographic information is, for example, an author, each electronic book is specified. Categorize by author name. Thus, in step S22, all the electronic books possessed by the user are classified into a plurality of class information for each bibliographic information.

Next, the number Xk of electronic books classified for each class information (k is a variable for identifying each class information, k is an integer not less than 0 and not more than the total number n of class information) is measured. Is divided by the total number N of electronic books possessed by the user, Pk = (Xk / N) × 100 is calculated (step S23).
That is, in step S23, the ratio Pk is calculated for each class information for each bibliographic information of the electronic book. If the bibliographic information is a publisher, an identification variable is determined for each publisher, such as class k = 0 is XX publishing, k = 1 is □□ publishing, X0 is XX publisher, X1 is □ □ Indicates the number of books each publisher has. P0 indicates the ratio of possessing electronic books of XX publishers, and P1 indicates □□ publishers.

  Next, for each bibliographic information, a plurality of class information obtained by subdividing each bibliographic information is ranked in descending order of the ratio (step S24). For example, when the bibliographic information is a publisher, ranking is performed in order from publishers with the largest number of books owned by the user.

  Next, the ratio of each class information ranked in step S24 and the rank information are stored in the individuality determination DB 4 (step S25).

  In this way, the book information analysis unit 21 classifies all electronic books possessed by each user into a plurality of class information obtained by subdividing the bibliographic information for each bibliographic information, and records the electronic books belonging to each class information. Calculate the ratio of the number divided by the total number. Thereby, the kind of electronic book which each user possesses can be grasped | ascertained by the ratio according to class information of each bibliographic information.

  FIG. 7 is a diagram illustrating an example of the data configuration of the individuality determination DB 4 that stores the processing result of the book information analysis unit 21. As shown in the figure, each of a plurality of bibliographic information (publisher, author, sales object, issue form, major classification, middle classification) is subdivided into a plurality of class information. A percentage of the total number of electronic books possessed is stored as a percentage. For example, in the example of FIG. 7, if the bibliographic information is issued, 60% is a comic and 20% is a book with respect to the total number of electronic books possessed by the user.

  FIG. 8 is a flowchart illustrating an example of a processing procedure of the book browsing analysis unit 23 in the coupling device 1. First, the book information (for example, book code etc.) of the electronic book which a user browses is acquired (step S31). Next, the number of times the user has browsed the electronic book is measured for each electronic book (step S32). Next, the electronic books are ranked in descending order of browsing (step S33).

  Next, for each of a plurality of electronic books that fall within a predetermined number of ranks from the highest rank, as with the book information analysis unit 21 in FIG. The number Xk of electronic books classified into a plurality of subdivided class information and classified into each class information (k is a variable for identifying each class information, k is an integer not less than 0 and not more than the total number n of class information) ) To calculate a ratio Qk = (Xk / S) × 100 with respect to the total number S of electronic books falling within a predetermined number of ranks from the highest rank (step S34).

  Next, the titles of the electronic books that are ranked in the descending order of the number of browsing times and the class information obtained by subdividing each bibliographic information are ranked in the descending order of the number of browsing times and are positioned in the high rank. The ratio corresponding to the class information is stored in the individuality determination DB 4 (step S35).

  As described above, the book browsing analysis unit 23 ranks electronic books in descending order of the number of times the electronic book browsed by each user is browsed, and selects a plurality of electronic books positioned in a higher rank for each bibliographic information. Are divided into a plurality of subdivided class information, and the ratio of the number of electronic books belonging to each class information divided by the total number S of electronic books falling within a predetermined number of ranks is calculated. Thereby, while being able to grasp | ascertain the electronic book with many browsing frequency of each user with rank information, the kind of electronic book with many browsing frequency can be grasped | ascertained by the ratio according to class information of each bibliographic information.

  FIG. 9 is a diagram illustrating an example of a data configuration of the individuality determination DB 4 that stores the processing result of the book browsing analysis unit 23. As shown in the figure, the titles are stored in the order of the most frequently viewed pages, and each of a plurality of bibliographic information (publisher, author, sales target, issue form, major classification, middle classification) is classified into a plurality of class information. Subdivided, each class information stores a percentage of the total number of electronic books possessed by the user as a percentage. For example, in the example of FIG. 9, if the bibliographic information is a large classification, among electronic books that are frequently viewed, electronic books related to “art / life” account for 70% of the total number, and “engineering / industrial” is related. E-books account for 20% of the total.

  FIG. 10 is a flowchart showing an example of a processing procedure of the individuality type analysis unit 25 in the coupling device 1. First, the book information (for example, book code) of the electronic book which a user browses is acquired (step S41). After the user browses the electronic book from which the book information has been acquired, the user is caused to input personality type information about the electronic book (step S42). The personality type information is class information obtained by subdividing some original bibliographic information. For example, as shown in FIG. 11, the user arbitrarily selects each of the original bibliographic information such as genre, category, and impression after reading. Provide possible class information and let the user choose. The class information selected by the user corresponds to the individuality type information.

  For example, in the example of FIG. 11, regarding the genre, three selectable class information items “science / technology”, “program”, and “information” are provided to the user, and one of them is selected. In addition, for the category, three types of class information “Robot”, “C language”, and “Introduction” are provided, and for the individuality type, three types of “Funny”, “Learn” and “Difficult” are selected. Provide possible class information.

  Next, the number Xk of electronic books corresponding to the individuality type information selected by the user (k is a variable for identifying each individuality type information, and k is an integer not less than 0 and not more than the total number n of individuality type information) is measured. Then, a ratio Rk = (Xk / N) × 100 obtained by dividing the number Xk by the total number N of electronic books possessed by the user is calculated (step S43).

  Next, the individuality type information is ranked in descending order of each ratio Rk (step S44), the individuality type information is arranged in order of rank for each of the original bibliographic information, and stored in the individuality determination DB 4 together with the ratio of each individuality type information. (Step S45).

  Thus, since the individuality type analysis unit 25 calculates a ratio for each individuality type information set after browsing by the user, the electronic book having the individuality type information that each user likes can be grasped.

  FIG. 12 is a diagram illustrating an example of a data configuration of the individuality determination DB 4 that stores the processing result of the individuality type analysis unit 25. In the example of FIG. 12, if the original bibliographic information is a genre, 30% of the electronic books possessed by the user are SF items and 10% are action items.

  FIG. 13 is a diagram illustrating an example of a virtual bookshelf generated by the bookshelf generator 33. The bookshelf generation unit 33 generates display data for displaying a virtual bookshelf in which a plurality of electronic books possessed by the user are arranged on the display screen of the electronic book terminal 3 capable of browsing the electronic books possessed by the user, It transmits to the electronic book terminal 3. Moreover, the bookshelf production | generation part 33 may determine the arrangement | sequence of the electronic book in a virtual bookshelf automatically for every bibliographic information (including original bibliographic information) of an electronic book, or purchase date order.

  The user can arbitrarily change the arrangement of the electronic books in the virtual bookshelf by operating the electronic book terminal 3. When the user gives an instruction to change the arrangement of the electronic books in the virtual bookshelf, the bookshelf generation unit 33 that has received the instruction may perform processing for changing the arrangement of the electronic books, or change the arrangement in the electronic book terminal 3. Processing may be performed.

  In the example of FIG. 13, the left half of the virtual bookshelf shows an example in which electronic books are arranged by genre, and the right half shows an electronic book arranged by browsing rank. The electronic book G1 in the virtual bookshelf is a book with the highest browsing frequency, and it is desirable that the book with a high browsing frequency is arranged at a position that can be easily reached by the user.

  In FIG. 13, it is possible to set for each electronic book whether the electronic book in the virtual bookshelf is open to other users or not. For example, a hatched electronic book indicates that it is set to be non-public, and a white electronic book indicates that it is set to be public. Thereby, only the electronic book set publicly in the virtual bookshelf is visually recognized by other users. The publication setting of the electronic book may be performed for each bibliographic information (for example, genre) of the electronic book instead of for each electronic book.

  FIG. 14 is a flowchart illustrating an example of a processing procedure of the bookshelf configuration analysis unit 27 in the coupling device 1. First, bibliographic information (including original bibliographic information) of each electronic book placed in the virtual bookshelf is acquired from the bibliographic information DB 5 and the original bibliographic information DB 6 (step S51).

  Next, each electronic book placed in the virtual bookshelf is classified into class information obtained by subdividing each bibliographic information (step S52).

  Next, among the electronic books placed in the virtual bookshelf, the electronic book with the highest browsing rank is searched, and each electronic book placed around the searched electronic book is subdivided into each of the bibliographic information. The number Xk of electronic books classified into each class information (k is a variable for identifying each class information, k is an integer not less than 0 and not more than the total number n of class information) is measured. Then, a ratio Sk = (Xk / M) × 100 with respect to the total number M of electronic books placed around the searched electronic book is calculated (step S53).

  Next, the bookshelves are evaluated by ranking the class information obtained by subdividing the bibliographic information of each electronic book placed around the electronic book having the higher browsing rank in descending order of the ratio (step S54). And the ratio and rank information for every class information which are the results of step S54 are memorize | stored in individuality determination DB4 (step S55).

  As described above, the bookshelf configuration analysis unit 27 divides the M electronic books placed around the electronic books that are frequently viewed in each user's virtual bookshelf into a plurality of pieces of bibliographic information that are divided into pieces of bibliographic information. Classifying into class information, the ratio of the number of electronic books belonging to each class information divided by M is calculated, and class information is ranked in descending order of ratio. Thereby, while being able to grasp | ascertain the browsing tendency of each user, it can grasp | ascertain what kind of electronic book each user tends to arrange in a virtual bookshelf in what order.

  FIG. 15 is a diagram illustrating an example of the data configuration of the individuality determination DB 4 that stores the processing result of the bookshelf configuration analysis unit 27. In the example of FIG. 15, around the e-book with the highest browsing rank in the virtual bookshelf, SF items are 30% and action items are 10% by category, and robot items are 20% by category. It shows that 5% of youth is placed, 30% of fun things are by type, and 20% of learning things are placed.

  FIG. 16 is a flowchart illustrating an example of a processing procedure of the bookshelf evaluation analysis unit 29 in the coupling device 1. First, bibliographic information (including original bibliographic information) of each electronic book placed in the virtual bookshelf is acquired from the bibliographic information DB 5 and the original bibliographic information DB 6 (step S61).

  Next, a ratio T = (X / N) × 100 of the number X of electronic books set publicly in the virtual bookshelf with respect to the total number N of electronic books possessed by the user is calculated (step S62).

  Next, if the public setting ratio T exceeds 50, “+” evaluation is made, and if it is 50 or less, “−” evaluation is made (step S63).

  Each time the total number of electronic books held by the user increases by one digit, the evaluation is expressed in five stages (for example, S, A, B, C, D) (step S64). Next, by combining the evaluation results of steps S63 and S44, the evaluation information of the public setting and the evaluation information of the total number of electronic books possessed by the user are stored in the individuality determination DB 4 (step S65). For example, when the total number N = 1000 and the ratio T = 800, the evaluation information “+ B” is stored in the individuality determination DB 4.

  Thus, the bookshelf evaluation analysis part 29 can grasp | ascertain the reliability of each user with the ratio of the electronic book by which the publication | publishing setting was carried out in a virtual bookshelf.

  5, 7, 10, 14, and 16 described above, each of the book information analysis unit 21, the book browsing analysis unit 23, the individuality type analysis unit 25, the bookshelf configuration analysis unit 27, and the bookshelf evaluation analysis unit 29. Although an example in which the analysis result is stored in the individuality determination DB 4 has been described, instead of storing it in the same database device, it may be distributed and stored in several database devices.

  FIG. 17 is a flowchart illustrating an example of a processing procedure of the comprehensive analysis unit 30 in the coupling device 1. First, the analysis results of the book information analysis unit 21, the book browsing analysis unit 23, the individuality type analysis unit 25, the bookshelf configuration analysis unit 27, and the bookshelf evaluation analysis unit 29 described above are acquired (step S71).

  Next, each analysis result is statistically analyzed (step S72). Then, it is determined that the higher the class information and the higher-ranked electronic books, the higher the user's interest (step S73), and the ratio is quantified and stored in the individuality determination DB 4 for each bibliographic information (including original bibliographic information). (Step S74).

  FIG. 18 is a diagram showing an example of the data configuration of the individuality determination DB 4 that stores the processing result of the comprehensive analysis unit 30 in FIG. In FIG. 18, the analysis results of the book information analysis unit 21, the book browsing analysis unit 23, the individuality type analysis unit 25, and the bookshelf configuration analysis unit 27 are represented by the ratio by class information. The result is expressed as “+ B”. In FIG. 18, comprehensive evaluation is stored for some of the original bibliographic information. For example, for the original bibliographic information called genre, the sports information is 30% in the book information analysis, the information is 30% in the book browsing analysis, the SF is 30% in the individuality type analysis, and the SF is 30% in the bookshelf composition analysis. Therefore, a comprehensive judgment was made and an evaluation result of “I am interested in SF” was obtained. Similarly, by category, the result that the ratio of robots with the highest percentage of class information was obtained by multiple analysis processes, so the evaluation result “Read robot relations well” was obtained. Similarly, in the impression after reading, the result that the individuality type information has the highest “pleasant” ratio was obtained by a plurality of analysis processes, and therefore, an evaluation result “fun type” was obtained.

  FIG. 19 is a flowchart illustrating an example of a processing procedure of the coupling rate detection unit 31 in the coupling device 1. First, information about each user who is a target for detecting a coupling rate is acquired (step S81). Here, an example will be described in which a certain user (hereinafter referred to as own user) detects a coupling rate with another user.

  The ranking of the class information on the higher rank side among the book information analysis results for the own user, and the class on the higher rank side (for the N1 rank from the highest rank) for each bibliographic information among the book information analysis results for other users The ranking of information is compared with the ranking of class information on the higher rank side (from the highest rank to the upper N1) among the book information analysis results for other users, and the number of matching class information is n1 For example, the matching ratio A = (n1 / N1) × 100 is calculated. (Step S82).

  As a specific example, an item of book information to be compared is shown as a publisher. Same if the top three e-books owned by user 1 are XX, □□, △△, and the top three e-books owned by user 2 are XX, △△, ☆☆ Since the publishers are XX and △△, the matching ratio is 2/3.

  A may be calculated and added for all items of bibliographic information, or may be calculated for any item.

  Next, among the bibliographic information of the book browsing analysis results for the user, the ranking of the class information on the higher rank side (upper N1) and the higher rank side (upper N1) of the book browsing analysis results for other users. ) Is compared, and if the number of matching class information is n1, then a matching ratio B = (n1 / N1) × 100 is calculated (step S83).

  B may be calculated and added for all items of the bibliographic information, or may be calculated for any item.

  Next, the ranking of individuality type information on the higher rank side (from the highest rank to N1 rank) among the individuality type analysis results for the own user and the higher rank side (highest among the individuality type analysis results for other users). The ranking of the individuality type information of N1 ranks from the higher rank) is compared, and if the number of class information of matching individuality types is n1, the matching ratio Ck = (n1 / N1) × 100 is calculated ( Step S84).

  C may be calculated for all personality type class information and may be added together, or may be calculated for any item.

  Next, the ranking of the class information on the higher rank side (for the N1 rank from the highest rank) among the book shelf configuration analysis results for the own user, and the higher rank side (the highest rank among the book shelf configuration analysis results for other users) The class information ranking of N1 ranks from the rank) is compared, and if the number of matching class information is n1, a matching ratio D = n1 / N1 × 100 is calculated (step S85).

  D may be calculated for all items of the bibliographic information and may be added together, or may be calculated for any item.

  Next, if the number of items that match the setting information of other users in the setting information that the user wants to interact with (for example, N1 items such as region, hobby, favorite book genre, etc.) is n1, The ratio E = (n1 / N1) × 100 is calculated (step S86).

  Next, using the ratios (matching information) calculated in steps S82 to S86 described above, a coupling rate F = (A + B + C + D + E) / 5 between the user and another user is calculated (step S87).

  Next, each matching information calculated in steps S82 to S86 described above and the coupling rate calculated in step S87 described above are stored in the individuality determination DB 4 (step S88).

  The coupling rate calculated by the coupling rate detection unit 31 of FIG. 19 can be used to determine whether or not to automatically send the user's introduction letter to other users.

  FIG. 20 is a flowchart illustrating an example of a processing procedure of a referral letter generation determination process performed by the coupling device 1. First, the coupling rate is calculated by the processing procedure of FIG. 19 (step S91). Next, it is determined whether or not the calculated coupling rate exceeds a predetermined value (step S92). When the predetermined value is exceeded, an introduction letter is automatically generated by the introduction letter generating unit 32 (step S93), and when the predetermined value is not exceeded, the process is terminated without automatically generating the introduction letter.

  FIG. 21 is a diagram illustrating an example of the result of the referral letter generation determination process of FIG. FIG. 21 shows an example in which a plurality of other users are ranked according to the coupling rate, and an introduction letter is sent only to the users ranked first and second.

  FIG. 22 is a flowchart illustrating an example of a processing procedure of the introduction letter generating unit 32. First, the user information is acquired from the member information management DB 8 and the individuality determination DB 4 (step S101). Next, the user's profile information (for example, name, gender, date of birth, birth, career, self-introduction, ID of the SNS site being used, etc.) is posted on the introduction letter (step S102).

  Next, the face illustration image of the user is posted on the introduction letter (step S103). Next, link information (link information to the SNS site, link information to the virtual bookshelf of the user, link information to other users who are interacting, link information to the personality type information of the user, etc.) Is posted (step S104).

  Next, the comprehensive analysis result of the user is posted on the introduction letter (step S105). Next, the matching information and the coupling rate between the user and other users are posted in the introduction letter (step S106).

  Next, a button permitting a link (exchange) with another user is posted on the introduction letter (step S107).

  FIG. 23 is a diagram illustrating an example of an introduction letter 40 generated by the processing of the introduction letter generation unit 32 of FIG. In the introduction letter 40 of FIG. 23, the analysis result by the comprehensive analysis unit 30 is illustrated by a radar chart 41. In addition, the user's face illustration image (avatar image) 42, profile information 43, self-introduction 44, bookshelf evaluation analysis result 45, link information 46 to the virtual bookshelf, and the user are subscribed to the introduction letter 40. Link information 47 to the SNS site, comprehensive analysis result 48, coupling rate 49, link button 50 for interacting with the own user, link button 51 to other users interacting with the own user, the own user's A link button 52 to the individuality determination table is posted. When the link information 46 to the virtual bookshelf is selected, the bookshelf with the public setting of the user introduced in the introduction letter is displayed. Specifically, the identifier of the introducer and a command necessary for displaying the virtual bookshelf are sent to the book store module (step S4). Upon receiving the command, the book store module (step S4) performs processing necessary for bookshelf generation through the virtual bookshelf (step S8) in the virtual bookshelf processing (step S9) and displays the result. Thereby, it is possible to display the bookshelf of the book in which the public bookcase of the reference destination is set to be open. In displaying the bookshelf, the class information classified by the book information analysis unit 21 may be designated and displayed.

  FIG. 23 is merely an example of the introduction letter 40, and the specific information posted on the introduction letter 40 may be changed as appropriate.

  FIG. 24 is a flowchart showing an example of a processing procedure for automatically generating a face illustration image (avatar image) to be posted on the introduction letter 40. First, the user information is acquired from the member information management DB 8 and the personality determination DB 4 (step S111).

  Next, an appropriate image is automatically selected from a plurality of face component images prepared in advance based on the profile information and the personality determination information included in the acquired user information (step S112).

  The facial part image consists of part images such as eyes, mouth, hairstyle, eyebrows, eyelids, and facial contours that characterize the human face. Which part image is selected based on the combination of profile information and individuality determination information. Create a table in advance.

  Next, a face illustration image is automatically generated by combining the face part images automatically selected in step S112 (step S113). The generated face illustration image is pasted on an introduction letter 40 shown in FIG.

  As described above, the coupling device 1 according to the present embodiment possesses the book information analysis unit 21, the book browsing analysis unit 23, the individuality type analysis unit 25, the bookshelf configuration analysis unit 27, and the bookshelf evaluation analysis unit 29. Percentage of electronic books by class information, rank information of electronic books with a large number of browsing times, percentage of electronic books with a large number of browsing times by class information, ratio of personality type information preferred by users, electronic books in a virtual bookshelf Can be understood and the reliability of each user.

  In addition, in order to calculate the ratio (matching information) that matches these analysis results with the analysis results of other users and the coupling rate indicating the compatibility between them, the compatibility with other users is expressed by a specific numerical value. Can be expressed as Therefore, it is possible to accurately determine whether or not another user is suitable for the exchange through the SNS before starting the SNS.

  In addition, by posting these analysis results, matching information, and coupling rates in the self-introduction letter 40, it is possible to give other users information on whether or not they are suitable for exchange through SNS. Can be provided.

  By the way, if the individuality determination DB 4 that stores the analysis results of the book information analysis, the book browsing analysis, the individuality type analysis, the bookshelf configuration analysis, and the bookshelf evaluation analysis described above is used, optimal advertisement distribution can be performed for each user. .

  Advertisement distribution is performed by the information providing apparatus 10 in the coupling system 2 of FIG. Various information media are stored in the information providing DB 11 in FIG. 1, and the information providing apparatus 10 accesses the individuality determination DB 4 to acquire the individuality determination result of each user, and provides the optimal advertisement for each user. I do.

  FIG. 25 is a flowchart illustrating an example of a processing procedure of the information providing apparatus 10 that performs advertisement distribution. First, a client who requests advertisement distribution sets advertisement distribution target information (step S121). Next, information on each user is acquired from the member information management DB 8 and the individuality determination DB 4 (step S122). Next, a user who performs advertisement distribution is automatically selected based on the acquired information on each user and the advertisement distribution target information set in step S121 (step S123). Next, the advertisement requested by the client is distributed to the automatically selected user (step S124).

  In this way, by using the individuality determination DB 4 generated by the coupling device 1, it is possible to grasp the preferences of each user, so that it is possible to provide advertising information only to users who are likely to be interested, and to increase the advertising effect Can do.

  At least a part of the coupling device 1 and the coupling system 2 described in the above-described embodiment may be configured by hardware or software. In the case of software configuration, a program for realizing at least a part of the functions of the coupling device 1 and the coupling system 2 is stored in a recording medium such as a flexible disk or a CD-ROM, and is read and executed by a computer. Also good. The recording medium is not limited to a removable medium such as a magnetic disk or an optical disk, but may be a fixed recording medium such as a hard disk device or a memory.

  Moreover, you may distribute the program which implement | achieves at least one part function of the coupling apparatus 1 and the coupling system 2 via communication lines (including wireless communication), such as the internet 12. Further, the program may be distributed via a wired line or a wireless line such as the Internet 12 or stored in a recording medium in a state where the program is encrypted, modulated, or compressed.

  The aspect of the present invention is not limited to the individual embodiments described above, and includes various modifications that can be conceived by those skilled in the art, and the effects of the present invention are not limited to the contents described above. That is, various additions, modifications, and partial deletions can be made without departing from the concept and spirit of the present invention derived from the contents defined in the claims and equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 Coupling apparatus, 2 Coupling system, 3 Electronic book terminal, 4 Individuality determination DB, 5 Bibliographic information DB, 6 Original bibliographic information DB, 7 Electronic book management server, 8 Member information management DB, 9 Electronic book information DB, 10 Information providing apparatus, 11 information providing DB, 21 book information analyzing unit, 22 book information matching unit, 23 book browsing analyzing unit, 24 book browsing matching unit, 25 personality type analyzing unit, 26 personality type matching unit, 27 bookshelf configuration analyzing unit , 28 bookshelf configuration matching unit, 29 bookshelf evaluation analysis unit, 30 comprehensive analysis unit, 31 coupling rate detection unit, 32 introduction letter generation unit, 33 bookshelf generation unit

Claims (13)

Means for performing at least one of bibliographic information analysis for analyzing the bibliographic information of each electronic book possessed by the user for each user and browsing status analysis for analyzing the browsing status of each electronic book possessed by the user for each user; ,
A coupling rate detection unit for detecting a coupling rate between the plurality of users based on a ratio of the bibliographic information by the bibliographic information analysis of the plurality of users and / or the ratio of the browsing statuses by the browsing status analysis. ,
In the bibliographic information analysis, each electronic book possessed by the user is allocated to any of a plurality of class information obtained by subdividing each of the bibliographic information, and the user possesses the number of electronic books corresponding to each class information. A coupling device , wherein a ratio divided by the total number of electronic books is detected and ranked in descending order . Means for performing at least one of bibliographic information analysis for analyzing the bibliographic information of each electronic book possessed by the user for each user and browsing status analysis for analyzing the browsing status of each electronic book possessed by the user for each user; ,
A coupling rate detection unit for detecting a coupling rate between the plurality of users based on a ratio of the bibliographic information by the bibliographic information analysis of the plurality of users and / or the ratio of the browsing statuses by the browsing status analysis. ,
The browsing status analysis ranks each electronic book in descending order of the number of browsing based on the measurement result of the number of browsing of each electronic book held by the user, and corresponds to a predetermined number of ranks in the order of the large number of browsing. Each electronic book is classified into one of class information, and a ratio obtained by dividing the number of electronic books corresponding to each class information by the number of electronic books possessed by the user falling into the predetermined number of ranks is detected. A coupling device characterized in that the ratios are ranked in descending order. Means for comparing individual analysis results for each of the plurality of users by means of individuality type analysis for analyzing individuality type information set by a user after browsing each electronic book, and detecting a rate at which the individuality type information matches And comprising
The coupling rate detecting section is further based on said rate of personality type information matches, the coupling device according to claim 1 or 2, characterized in that for detecting the coupling factor between the plurality of users . The individuality type information comprises a plurality of information prepared in advance that can be arbitrarily set by the user,
In the individuality type analysis, the number of electronic books set by the user is measured for each of the individuality type information set by the user after browsing each electronic book, and this number of electronic books possessed by the user is measured. The coupling device according to claim 3 , wherein a ratio divided by the total number is detected, and the ratio is ranked in descending order. Means for generating display data for displaying a virtual bookshelf in which a plurality of electronic books possessed by the user are arranged on a display screen of an information communication device capable of browsing the electronic books possessed by the user;
By the bookshelf composition analysis which analyzes the tendency of the arrangement of each electronic book in the virtual bookshelf for each user,
Comparing the results of analyzing the trend of the arrangement of the electronic books for each of the plurality of users, and a means for detecting the proportion of the trends in the arrangement of the electronic books in the virtual bookshelf,
The coupling rate detecting unit further claim 3 tendency of arrangement of the electronic book in the virtual bookshelf based on the percentage that matches, and detecting the coupling factor between the plurality of users Or the coupling apparatus of 4 . The trend of the arrangement of the electronic books includes bibliographic information and individuality type information of a plurality of electronic books placed around a specific electronic book selected based on the number of times the user browses among the electronic books in the virtual bookshelf. 6. The coupling device according to claim 5 , wherein the coupling device is extracted by analysis. A means for detecting a ratio of electronic books set by the user in the total number of electronic books in the virtual bookshelf and executing a bookshelf evaluation analysis for evaluating the reliability of the user based on the ratio; The coupling device according to claim 5 or 6 . A comprehensive analysis unit that comprehensively analyzes each analysis result of the bibliographic information analysis, the browsing status analysis, the individuality type analysis, the bookshelf configuration analysis, and the bookshelf evaluation analysis;
An introductory letter generation unit that generates an introduction letter used to introduce a user to another user via a network, and includes an analysis result of the comprehensive analysis part in the introduction letter. 8. The coupling device according to 7 . Based on the analysis results of the bibliographic information analysis, the browsing status analysis, the individuality type analysis, the bookshelf configuration analysis, and the bookshelf evaluation analysis, one of a plurality of types of face illustration images is selected and the introduction letter is selected. The coupling device according to claim 8 , further comprising an avatar generation unit that is superimposed on the avatar. Coupling system comprising: an information communication device capable of browsing an electronic book possessed by a user; a coupling device that detects a degree of similarity among a plurality of users; and a book information storage device that stores bibliographic information of the electronic book. In
A unique bibliographic information storage device for storing bibliographic information more detailed than the bibliographic information stored in the book information storage device;
The coupling device includes:
Perform at least one of bibliographic information analysis for analyzing the bibliographic information of each electronic book owned by the user for each user and browsing status analysis for analyzing the browsing status of each electronic book owned by the user for each user, a coupling ratio detecting unit that the user of the bibliographic information analysis bibliographic information or / and the viewing state analysis detects the coupling ratio between users from the ratio of the plurality of matching, the possess,
The browsing status analysis ranks each electronic book in descending order of the number of browsing based on the measurement result of the number of browsing of each electronic book held by the user, and corresponds to a predetermined number of ranks in the order of the large number of browsing. Each electronic book is classified into one of class information, and a ratio obtained by dividing the number of electronic books corresponding to each class information by the number of electronic books possessed by the user falling into the predetermined number of ranks is detected. Coupling system characterized by ranking the proportions in descending order . Coupling system comprising: an information communication device capable of browsing an electronic book possessed by a user; a coupling device that detects a degree of similarity among a plurality of users; and a book information storage device that stores bibliographic information of the electronic book. In
A unique bibliographic information storage device for storing bibliographic information more detailed than the bibliographic information stored in the book information storage device;
The coupling device includes:
Perform at least one of bibliographic information analysis for analyzing the bibliographic information of each electronic book owned by the user for each user and browsing status analysis for analyzing the browsing status of each electronic book owned by the user for each user, A coupling rate detection unit that detects a coupling rate between the plurality of users from a rate at which the bibliographic information or / and browsing status analysis by the user's bibliographic information analysis match,
The browsing status analysis ranks each electronic book in descending order of the number of browsing based on the measurement result of the number of browsing of each electronic book held by the user, and corresponds to a predetermined number of ranks in the order of the large number of browsing. Each electronic book is classified into one of class information, and a ratio obtained by dividing the number of electronic books corresponding to each class information by the number of electronic books possessed by the user falling into the predetermined number of ranks is detected. Coupling system characterized by ranking the proportions in descending order . The coupling device compares the analysis result of the individuality type information for each of the plurality of users with the means for analyzing the individuality type information set by the user after browsing each electronic book. And a means for detecting a ratio of matching,
The coupling system according to claim 10 or 11, wherein the coupling rate detection unit further detects a coupling rate between the plurality of users based on a rate at which the individuality type information matches. . An analysis result of the bibliographic information analysis, an analysis result of the browsing situation analysis, and an individuality determination storage device that stores an analysis result of the individuality type information,
An advertisement distribution device that provides advertisement information corresponding to a user's individuality type to the information communication device of the user based on information stored in the personality determination storage device. The coupling system described.