JP2005100004A - Information providing system, information providing method, and computer program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To recommend contents in order to support self-development. <P>SOLUTION: A recommendation rule to recommend the contents and a recommendation extent to recommend can be set freely and also a user by himself/herself can set up an object. In addition, relative self-diagnostics also becomes possible by creating two or more persons' competency map. It is also possible to display profile information of the contents themselves. Furthermore, the contents and persons can be made as objects of recommendation and searching by handling both contents and the persons on the same map. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an information providing system and information providing method for recommending electronic data contents such as movies, recorded videos, books, etc. according to the user's personal attributes and suitability, and a computer program. The present invention relates to an information providing system, an information providing method, and a computer program for recommending contents in order to support the computer program.

  More specifically, the present invention relates to an information providing system and an information providing method for recommending content according to a goal set by a user, and a computer program. The present invention relates to an information providing system, an information providing method, and a computer program for profiling contents and users, and recommending contents in consideration of the importance of profiles.

  In recent years, computing technologies such as information processing and information communication have improved dramatically, and computer systems have become widespread. Furthermore, there is an increasing demand for network computing technology for interconnecting computers. Under a network connection environment, it is possible to smoothly perform collaborative work such as sharing of computer resources and sharing, distribution, distribution, and exchange of information.

  In recent years, with the widespread use of the Internet and broadband communication networks (xDSL: xDigital Subscriber Line, CATV (Cable TV), wireless networks, etc.), various digital contents including computer files have been actively distributed over the network. ing. In addition, a mechanism is being set up in which digital data such as music data, image data, electronic publications, and even rich content such as moving images can be transmitted without stress to the user.

  Recently, in conjunction with improvements in information processing technology and information communication technology, content for business use, entertainment, and learning / education / training has been packaged or digitized. For example, it is delivered as a teaching material to a learner via media such as video and DVD. Alternatively, teachers, instructors, and students can be connected by a network to provide an interactive learning environment between remote locations. There is also a Web-based learning system (WBT: Web Based Training) in which teaching material contents are stored in a form that can be handled in an information search space such as HTML (Hyper Text Markup Language).

  The amount and quality of contents are becoming more and more rich, but conversely, it is difficult to successfully extract desired or necessary contents from a vast amount of contents. For this reason, even originally useful content is buried without being reusable, and the problem of “disposable” or “deadly stored” has occurred.

  For example, it is considered to use recorded videos of various contents distributed in order to support self-development, such as employee education in a corporate company. However, it is not easy for individual employee users to select what kind of content is used for educational courses. That is, in an environment where a huge amount of content can be easily obtained, it has become extremely difficult for each individual user to select the content necessary for him / herself.

  For example, a proposal has been made for a simulated diagnosis for self-discovery or self-development for a user in a network environment (see, for example, Patent Document 1). This system can support self-diagnosis by questions and self-development. That is, a self-diagnosis AP 13 that performs a simulated diagnosis for supporting self-discovery or self-development and scores the result (primary information) (content use / self-diagnosis score), and content use / self-diagnosis score Information guide table 47, information guide unit 17, and private information for storing secondary information, which is recorded with the type of secondary information that is estimated to be desired by the user regarding the content usage / self-diagnosis score It has company information DB71-7m. The information guide unit 17 refers to the information guide table 47 to guide the user of the type of secondary information corresponding to the content usage / self-diagnosis score notified from the self-diagnosis AP 13, and selects a desired one from the types. When the type of secondary information is selected, the secondary information of that type is acquired from the private company information DBs 71 to 7m and provided to the user. However, the rules and ranges for recommending content cannot be set freely, and the user cannot set goals.

  In addition, an information collecting apparatus that collects new information that is likely to be of interest to individual users and arranges and presents them in order of importance for the user has been proposed (see, for example, Patent Document 2). about). The information collection device includes an information collection unit that collects information via a network, a calculation unit that obtains an importance level for each user with respect to the collected information based on a profile acquired in advance from a plurality of users. And a creation means for creating a list by rearranging each information in the order of importance, information can be collected with the content on the WWW as a target and taking into account the importance according to the profile. However, it is not possible to recommend content that takes into account the importance of the profile.

JP 2002-203028 A JP-A-10-260955

  An object of the present invention is to provide an excellent information providing system, information providing method, and computer program capable of preferably recommending contents in order to support self-development.

  A further object of the present invention is to provide an excellent information providing system, information providing method, and computer program capable of freely setting rules and ranges for recommending content and recommending content in accordance with a user-set goal. Is to provide.

  A further object of the present invention is to provide an excellent information providing system, information providing method, and computer program capable of profiling contents and users respectively and recommending contents in consideration of the importance of profiles. It is in.

The present invention has been made in consideration of the above problems, and a first aspect thereof is an information providing system for providing content information to a user,
Content storage means for storing content to be provided to users;
User profile management means for managing user profiles;
Content profile management means for managing profiles of contents stored in the content storage means;
Search means for searching for a desired user or content according to a comparison of said user profile and / or content profile;
Information presenting means for presenting information related to the content extracted by the content search means to the user;
It is the information provision system characterized by comprising.

  Here, the user profile management means manages at least job type information about the user and capability information including a plurality of capability elements (competencies) about the job type as profiles. The content profile management means manages the compatibility with the job type information possessed by the content and the compatibility with each capability element (competency) for each job type as a content profile.

  In the present invention, the content profile and the user profile are managed in the same format using a two-dimensional space in which competencies that are components of capabilities are mapped on the X axis and occupations having a hierarchical structure are mapped on the Y axis. Like to do. By handling content and people on the same map, both content and people can be recommended and searched. The former is called “content map” and the latter is called “contents diagnosis table” of the user.

  By mapping content on a two-dimensional space, that is, a content map, in which the competency is the X axis and the job type is the Y axis, profile diagnosis of the content group can be easily performed. For example, the profile of a content group can be determined visually by graphing the number of corresponding contents on an arbitrary job axis or on a competency axis. For example, it is possible to determine the quality of the content without actually viewing the content.

  Further, by mapping the user's profile on a two-dimensional space having competency as the X axis and job type as the Y axis, that is, the competency diagnosis table, the user's profile diagnosis can be easily performed. Furthermore, by mapping not only individual users but also multiple user profiles such as teams and groups on the same competency diagnosis table, it is possible to easily grasp the competencies in the group, create team formation and human resource planning, work・ It can be used for assignment.

According to a second aspect of the present invention, there is provided a computer program written in a computer-readable format so that a process for providing content information to a user is executed on a computer system.
A user profile management step for managing the user's profile;
A content profile management step for managing a profile of a predetermined content group;
A search step of searching for a desired user or content according to a comparison of said user profile and / or content profile;
An information presentation step of presenting information about the content extracted in the content search step to the user;
A computer program characterized by comprising:

  The computer program according to the second aspect of the present invention defines a computer program described in a computer-readable format so as to realize predetermined processing on a computer system. In other words, by installing the computer program according to the second aspect of the present invention in the computer system, a cooperative action is exhibited on the computer system, and the information provision according to the first aspect of the present invention is provided. The same effect as the system can be obtained.

  According to the present invention, it is possible to provide an excellent information providing system, information providing method, and computer program capable of recommending contents to support self-development.

  According to the present invention, based on a job type and ability of a user, content that is expected to be necessary for the user is identified and content recommendation information is provided. Therefore, content that is expected to be necessary for the user is recommended, and based on this, the user can easily select and use content that is useful to him / her.

  Further, according to the present invention, content suitable for each user is recommended based on the analysis result of the hierarchy information and job type information input from the user and the answer input from the user. As a result, it is possible to facilitate the sorting operation of the content necessary for the user, and to provide the user with a motivation for content learning. In addition, when used for company employee education, it can motivate employees to learn and promote their skills.

  Furthermore, according to the present invention, it is possible to freely set a recommendation rule for recommending content, a recommended range of recommendation, etc., the user can set a target himself, and by creating a competency map of a plurality of people, Self-diagnosis is also possible. Furthermore, by handling content and people on the same map, both content and people can be targeted for recommendations and searches.

  Further, according to the present invention, a recommendation rule, a recommendation range, and the like can be freely set, and profile information of the content itself can be displayed. Furthermore, by handling content and people on the same map, both content and people can be targeted for recommendations and searches.

  Other objects, features, and advantages of the present invention will become apparent from more detailed description based on embodiments of the present invention described later and the accompanying drawings.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 schematically shows the configuration of a content recommendation system according to an embodiment of the present invention. In the example shown in the figure, the content recommendation system is applied to the provision of content for in-company education, and is configured with a service site 1 composed of a computer server as the core. A user) is accessed by a user terminal 2 such as a personal computer (PC) and acquires content recommendation information.

  The service server 1 and the user terminal 2 are communicatively connected via a network such as the Internet, and these host devices execute predetermined computer programs by computer hardware, thereby various functions as described later. To perform processing related to content profiling and search, and provision and acquisition of recommendation information.

  The profile engine 19 is a device that analyzes and analyzes job information and ability information of employee users. In the example illustrated in FIG. 1, the profile engine 19 may be configured in the service server 1 although it is provided as a separate device that performs analysis processing in response to a request from the service server 1.

  The service server 1 is a device that provides an intermediary service related to content provision between the content provider 3 and the employee department and the education department (actually the terminal of the person in charge) 4 of the company to which the employee user belongs.

  In addition, the service server 1 can provide various contents such as magnetic tape, CD, and DVD in various file description formats such as MPEG (Moving Picture Experts Group) and PDF (Portable Document Format) from the content provider 3. Media that are necessary to be converted into electronic data, converted into electronic data, registered in the content database 10, and paid to the content provider 3 for content usage according to the use of employee users. , Providing usage ranking information for each content as a content report.

  In addition, the service server 1 accepts an application for a content providing service from the corporate education department 4, collects a basic charge for the number of employees related to the use of the service, and pays a content usage fee according to the actual content usage of the employee user. In addition, it collects and provides the company education department 4 with log analysis information regarding the content usage status of employee users.

  In addition, the service server 1 acquires profile information of the employee user from the employee user (user terminal) 2, and provides a list of recommended content information as a content recommendation to the employee user (user terminal). Also, the contents (actual data) of the contents are provided. A method for creating and presenting content recommendation information will be described later.

  As shown in FIG. 2, the content database 10 includes a content number 10a for identifying each content, content information 10b including a content name and an outline of the content, hierarchical information 10c of users targeted by the content, and content as a target. The user's job type information 10d and the user's behavior characteristic information 10e suitable for the content are recorded in association with each other.

  In addition, the content database 10 manages each content according to the suitability with the job type information held by the content and the ability level suitable for each job type. The ability is composed of a plurality of ability elements, that is, competency (competency element), but in this embodiment, the stage of ability is treated as a ability level value for each competency. Also, job types can be handled as a hierarchical structure.

  In the present embodiment, information related to content is managed using a “content map” as shown in FIG. 3 in a format that facilitates searching. In the content map shown in the figure, a row is provided for each occupation type (the occupation type is mapped to the X axis), and a column is provided for each ability level of the competency element (competency). Mr. Piten's ability level is mapped to the Y axis). Then, the content is mapped to the capability level column in the corresponding capability element on each corresponding job category axis. Of course, one content may be mapped onto two or more job types.

  In the map table shown in FIG. 3, a row is provided for each job type such as job1, job2, and job3, and a column is provided for each ability level lev1, lev2, and lev3 for each ability element such as comp1, comp2, and comp3. Yes. In the job type job2 row, contents A, B, C, D, E, F, G, H, and I are mapped in order from the left as contents that match the ability level for each ability element. Of course, two or more contents may be simultaneously mapped to the same ability element and the same ability level of the same occupation.

  By mapping content on a two-dimensional space, that is, a content map, in which the competency is the X axis and the job type is the Y axis, profile diagnosis of content groups in the content database 10 can be easily performed. . For example, the profile of a content group can be determined at a glance by graphing the number of corresponding contents on an arbitrary job axis or on a competency axis. For example, the quality of the content can be determined without actually viewing the content.

  In the present embodiment, the content profile and the user profile are mapped in the same format using a two-dimensional space in which the competency that is a component of ability is mapped to the X axis) and the job types having a hierarchical structure are mapped to the Y axis. To manage. By handling content and people on the same map, both content and people can be recommended and searched. The content profile mapped in the two-dimensional space is the above-described “content map” (see FIG. 3). Similarly, the competency diagnosis result of the user obtained through the analysis of the question answer can be mapped to a two-dimensional space in which the competency is the X axis and the job type is the Y axis. This will be described later. .

  The recorded information in the content database 10 may be provided from the content provider 3 or may be created in the service site 1. In any case, a content map or equivalent information is recorded in the content database 10 as pre-processing for the content providing service described later for all the content provided by the service server 1.

  The content database 10 also records the content (entity) of each content. In the present embodiment, the content entity is configured as a data set different from the table of the association information 10a to 10e, and the actual data 10f and the association information table are associated with the content number 10a as a reference.

  Note that the actual data 10f that requires a relatively large storage capacity is a database separate from the association information table, and the two are linked by reference to extract the actual content data 10f corresponding to the content information 10b in the association information table. May be provided to employee users.

  As described above, the profile information acquired from the employee user by the service server 1 is stored in the profile database 11 of the service server 1, and based on this stored information, log analysis information for each employee user is stored in the corporate education department. 4 is provided.

  As shown in FIG. 4, the profile database 11 includes user information 11a (see FIG. 6) including user names, hierarchy information, job type information, and the like acquired by user input described later, and user input described later. Question answer information 11b (see FIG. 7) of the user who is earned by the analysis, analysis result information 11c (see FIG. 8) by the profile engine 19 to be described later, content recommendation history information 11d to the user to be described later (See FIG. 9) is recorded in association with each employee user. The history information 11d is information of the content learned by the user (including the case where it has been selected as a learning target or during learning) among the recommended content, so that the content once learned is not re-recommended. use.

  Further, when the user terminal 2 receives provision of content from the service server 1, the service server 1 accumulates the provision history for each provided content in the access database 12, and based on the accumulated information, the content provider 3 generates ranking information for each content to be provided, and creates a content usage status (that is, a learning status) for each employee user included in the log analysis information provided to the corporate education department 4.

  As shown in FIG. 5, the access database 12 includes a content number 12a and an access history 12b in association with each content. The access history 12b includes information (name and the like) for identifying the employee user who has used the content, the degree of use of the content by the employee user, and the like.

  When the content entity is provided as stream data to the user terminal 2, the degree of use of the content can be measured, for example, as an access time by an employee user or a video access section. However, the method of providing the actual content data may be a method of causing the user terminal 2 to download the actual content data. In this case, permission management of access to the content is performed by the service server 1. Access history can be acquired.

  6 to 9 show display screen displays on the user terminal 2 for obtaining user profile information, content recommendation, and content distribution. Hereinafter, the processing operation of the content recommendation system according to the present embodiment will be described along the screen display with reference to each drawing.

  The user terminal 2 includes an application such as a browser that displays a user interface including a mouse and a keyboard that accepts an operation input from the user, a menu page and a content list page provided from the service server 1, and a display, a network It is assumed that a network interface for performing data communication with the service server 1 via the network is provided.

  The service server 1 is assumed to include a network interface 13 that performs data communication with the user terminal 2 via a network and a search engine 14 that performs a search process from the content database 10.

  When an employee user wants to obtain content recommendations, the user terminal 2 accesses the service server 1 and first obtains a personal data registration page as shown in FIG. 6 from the service server 1. It is displayed on the screen of the user terminal 2.

  The employee user is given an ID and password in advance for access to the service server 1, and authentication by ID and password is performed when the user terminal 2 accesses the service server 1. Further, in this embodiment, the corporate education department 4 gives each employee user a point to be subtracted every time the content is used according to the hierarchy or job type. When the access user does not have this point remaining amount, the service server 1 refuses access, thereby facilitating budget management required for employee education using paid content.

  The personal data registration page shown in the figure includes, as user information, a column 51 for selecting and inputting user hierarchy information in addition to a column for inputting information for identifying an employee user such as name, gender, date of birth, etc. A column 52 for selecting and inputting the occupation type is provided. When the employee user inputs his / her information in these fields and presses the “input completion” button 53, the information input on the page is transmitted to the service server 1.

  The job type information input on the personal data registration page is a key for selecting content when generating content recommendation information. FIG. 10 illustrates job classifications used in this embodiment.

  When the service server 1 completes the acquisition of the user information through the personal data registration page, the service server 1 then transmits the behavior / thought characteristic check sheet page to the user terminal 2 and displays it on the screen of the user terminal 2.

  FIG. 7 shows a configuration example of the behaviour / thought characteristic check sheet page. In the illustrated behavior / thought characteristic check sheet page, there are listed a number of questions for measuring user aptitude such as “I've been surprised” and “I feel more comfortable on the surface”. For each question, check boxes for answers such as “applicable”, “neither”, and “not applicable” are provided. The user answers these questions on the terminal screen when the employee user checks the check boxes. When the “input complete” button 62 is pressed, the information input on the page is transmitted to the service server 1.

  When the service server 1 receives the user information including the hierarchy information and the job type information and the question answer information provided from the employee user as described above, the service server 1 uses the received information as the user information 11a and the question answer information 11b of the profile database 11. And the received question answer information is provided to the profile engine 19 to perform analysis processing based on the question answer, and the analysis result of the obtained user profile is recorded in the analysis result information 11c of the profile database 11 To do.

  The profile engine 19 obtains capability information possessed by the user as one result of the analysis processing. An ability consists of multiple ability elements. In FIG. 11, ability elements are listed, but in the example shown, the ability elements are roughly classified into major classifications, and each classification is composed of a plurality of competency indicators. The user ability information is composed of ability level values representing how much ability the user has for each ability element.

  In this embodiment, the content profile and the user profile are the same using a two-dimensional space in which competencies, which are components of ability, are mapped to the X axis (row) and job types having a hierarchical structure are mapped to the Y axis (column). It is managed with a map of the format. That is, the competency diagnosis result as one of the user profile analysis results by the profile engine 19 is managed using a competency diagnosis table configured in almost the same format as the content map (see FIG. 3). By handling the content and user profiles on the same map, both the content and the user can be targeted for recommendation and search.

  FIG. 12 shows a configuration example of the competency diagnosis table. A row is provided for each occupation type, and a column is provided for each ability level of the ability element (competency). Then, on the line of the corresponding job type of the user, a message to that effect (“◯” in the figure) is entered in a column corresponding to the user's current ability level value for each ability element. In the illustrated example, the job type of the user is job2, and the user currently has ability level values lev1, lev3, and lev2 for the ability elements comp1, comp2, and comp3, respectively.

  By mapping a user's profile on a two-dimensional space having competency as the X axis and job type as the Y axis, that is, the competency diagnosis table, the user's profile diagnosis can be easily performed. Furthermore, by mapping not only individual users but also multiple user profiles such as teams and groups on the same competency diagnosis table, it is possible to easily grasp the competencies in the group, create team formation and human resource planning, work・ It can be used for assignment.

  You may make it transmit the analysis result by the profile engine 19 to the user terminal 2 of an answer origin. The analysis result includes a behavior analysis result 74 as well as the basic analysis result 71, stress analysis advice 72, career design advice 73, and the user terminal 2 receives the received analysis as shown in FIG. Display the results on the screen. For example, the behavior characteristic analysis result 74 includes “decision” and “creativity”. Along with individual ability elements (behavior characteristic evaluation items) such as “cooperation”, level evaluation of each of these items is included. Accordingly, the employee user can directly know what his / her own behavioral characteristics are and what the weakness item is.

  Further, the service server 1 inputs the user profile analysis result obtained by the profile engine 19 to the search engine 14, and performs the search processing of the content database 10 using the content and the job type information and capability information of the user as keys. Execute.

  In the present embodiment, the content search processing is performed by using the same 2 for the content profile and the user profile, with the competency that is a component of the capability as the X axis (row) and the job type having a hierarchical structure as the Y axis (column). It is executed by mapping to a dimensional space and collating each two-dimensional space, that is, a content map with a competency diagnosis table. By handling the content and user profiles on the same map, both the content and the user can be targeted for recommendation and search. It is also possible to diagnose content and user profiles in a two-dimensional space (described above).

  In addition to the user competency diagnosis result, the profile of the recommendation to the user and the target profile based on the diagnosis result are similarly mapped on a two-dimensional space with the competency as the X axis and the job type as the Y axis. It can be used for efficient search. Also, the recommendation profile can be filtered or weighted in a two-dimensional space. Hereinafter, weighting of the recommended area, the target area, the recommended area after filtering, and the recommended area in the two-dimensional space will be described.

(1) First, a content profile (see FIG. 3) is created by mapping a content profile onto a two-dimensional space having competency as the X axis and job type as the Y axis.

(2) Next, the analysis result of the question answer to the user is mapped on a two-dimensional space with the competency as the X axis and the job type as the Y axis, and a competency diagnosis table (see FIG. 12) is created.

(3) Next, by applying the following rule 1 to the competency diagnosis table, a recommendation area is created in a two-dimensional space. FIG. 13 shows a recommendation area obtained by applying rule 1 to the competency diagnosis table shown in FIG.

Rule 1:
On the job type axis corresponding to the user, the fact that it corresponds to the recommendation (“◯” in the figure) is entered in the column above the ability level of the user within each competency.

(4) Next, a target area to be recommended is created. FIG. 14 shows a state in which the target area is mapped on a two-dimensional space in which the competency is the X axis and the job type is the Y axis. The target area indicates, for example, an area that is a target to be reached (or is required) according to the job type, work history, class, and the like of the user.

(5) Next, the recommended region (see FIG. 13) is filtered by the target region (see FIG. 14) to create a filtered recommended region. FIG. 15 shows a recommendation region obtained by filtering the recommendation region shown in FIG. 13 with the target region shown in FIG.

(6) Next, the weighting of the recommendation obtained by applying the following rule 2 to the competency diagnosis table (see FIG. 12) is mapped on the two-dimensional space. FIG. 16 shows recommendation weights obtained by applying rule 2 to the competency diagnosis table shown in FIG.

Rule 2:
Weights are given in the following order within an area having competency.
1. 1. In order of ability level 2. Match with user level 3. Close to user level Competency X coordinate in ascending order

(7) The content map that is mapped in the recommended region after filtering is recommended according to the weight of the recommendation. In the example shown in FIGS. 3 and 16, recommendations are made in the order of A → B → F → C.

  Then, the search engine 14 extracts the content number 10a and the content information 10b for the content for which job type information and capability information matching the input user profile are set.

  For example, the search engine 14 searches the content database 10 using the input hierarchical information and job type information of the user profile as keys, and sets the hierarchical information 10c and job type information 10d that match the information input by the employee user. The content number 10a and the content information 10b are extracted. Further, when there are a plurality of extracted contents, the search engine 14 compares each item set in the behavior characteristic information 10e with each item of the analysis result 74, and analyzes the extracted content information as an analysis result. As in order of weak behavior characteristics. Here, if “observation ability”, “reading ability”, and “planning ability” are weak as the behavior characteristic analysis result 74, these three items “observation ability”, “reading ability”, The order is set such that “planning power” is set, two items are set, and one item is set. Therefore, it is possible to analyze the employee user, find a weak part as a behavior characteristic, and prioritize the content useful for enhancing the weak part, and recommend it to the employee user.

  Then, the service server 1 creates a list page by arranging the content information 10b obtained as a search result by the search engine 14 according to the priority order. The list page includes an anchor including each content number or a URL for extracting the content. The list page is transmitted to the user terminal 2 and displayed as a recommended content list on the browser screen. FIG. 9 shows a configuration example of a presentation screen for content recommendation information including a recommended content list. In the recommended content list, items 81 of each searched content are displayed according to the priority order including the content name 82 and the content content outline 83. Each content item 81 is provided with a check box 85. When the employee user checks in the check box 85 of the content that the user wants to use, and presses the "apply" button 86, the check box 85 is selected. The content number is transmitted to the service server 1.

  The presentation of the content recommendation information according to the present embodiment is characterized in that the content is displayed in a strong and weak manner according to the recommendation level given according to the suitability between the searched content and the job type information and capability information of the target user. Is a point. That is, highlighting is performed on content with a higher recommendation level.

  In the example shown in FIG. 9, on the recommended content list page, as indicated by reference numeral 87, the ones adapted to the ability, the ones that improve the strength, the ones that reinforce the weak points, the ones recommended by the boss, etc. are highlighted. These are displayed in combination. Also, the recommendation level corresponding to the recommendation level is also displayed as an index value.

  For example, when the user's ability related to competency A is level 0, content that complies with level 1 regarding competency A is displayed as “weak point reinforcement content”. Further, when the ability related to the competency B of the user is level 1, the content that matches level 2 with respect to competency B is displayed as “capability compatible content”. Further, when the ability related to the competency C of the user is level 2, content that complies with level 3 with respect to competency C is displayed as “strength-up content”. In addition, on the list page screen, it can be sorted in order of recommendation or displayed by filtering.

  In the recommended content list, the items of each searched content include the content name and the outline of the content, and are displayed in the priority order. Each content item is provided with a “detail” button 84, and by pressing this detail button, a more detailed outline of the corresponding content can be displayed on the screen.

  Each content item is provided with a check box. When a user inputs a check into the check box of the content that the employee user wants to use and presses the “apply” button 86, the content number selected by the check input is displayed. Sent to the service server 1.

  When the service server 1 receives the application in this manner, these contents are added to a screen displaying a list of learning contents for each individual not shown in the figure (hereinafter referred to as learning my page) and transmitted to the user terminal 2. . The learning my page not shown in the figure has a list of contents selected as learning targets and a learning start button corresponding to each content. When the learning start button is pressed, the service server 1 sends a request for transmission of actual data including the content number. Is sent.

  When the service server 1 receives such a transmission request for actual data, the content server 10 searches the content database 10 for the corresponding content entity 10f based on the content number, and sends the content entity to the requesting user terminal 2, for example. Send in stream format. As a result, the employee user can display the provided content on the user terminal 2 for use in skill-up learning.

  On the content recommendation information presentation screen as shown in FIG. 9, the strength of each content is displayed according to the recommendation level given according to the suitability between the searched content and the job type information and capability information of the target user. . In other words, on the display screen for recommending content, items for presenting (differentiated) items specialized for the user's own profile are arranged in the content attribute display. By differentiating and displaying the content that the user should see and the content that should be viewed, the user can be differentiated in the viewing attitude when viewing the content, and the effect of viewing the content can be enhanced. it can.

  In the present embodiment, content and people profiles are mapped to the same two-dimensional space with competency as the X-axis and job type as the Y-axis, so that both content and people can be targeted for recommendations and searches. . Hereinafter, the use of the search function and the recommendation function using the two-dimensional space to which the profile is mapped will be exemplified.

<Search function>
(1) It is possible to efficiently search for a person (or team) having a close ability from an individual (or team) map. As an example of this utility, it is possible to select an object to be called for when a seminar is held.

(2) A more capable (or lower) person (or team) can be efficiently searched from an individual (or team) map. As an example of this utility, it is possible to select a lecturer when a seminar is held. As another utility example, it is possible to search for a person who can be consulted as a problem solver for work.

(3) A content (or content group) having similar properties can be efficiently searched from a map of content (or content group). As an example of this utility, you can quickly narrow down candidates when you want to strengthen concentrated competencies.

(4) A higher-quality (or lower-quality) content (or content group) can be efficiently searched from the content (or content group) map. As an example of this utility, if the level of the viewed video is low, a higher quality video can be searched. As another utility example, when the viewed content is difficult, it is possible to search for a more easily understood content.

(5) A person (or team) that satisfies the target map can be searched efficiently. As an example of this utility, in order to carry out a project, it is possible to create a goal map that is indispensable for carrying out the project and to form a team.

(6) Content (or content group) satisfying the target map can be searched. As an example of this utility, you can select videos that are required for human resource education in order to make a project successful.

(7) It is possible to efficiently search for a person (or team) who makes up for a lack of competency from an individual (or team) map and a target map. As an example of this utility, it is possible to select insufficient human resources to make a project successful. As another utility example, when educating a new employee, a suitable person for OJT can be selected.

(8) It is possible to efficiently search for a content (or content group) that supplements a lack of competency from an individual (or team) map and a target map. As an example of this utility, it is possible to efficiently search for videos that lead to lack of skills to become a senior consultant.

<Recommend function>
(1) By applying the target map and attaching rules when searching for people, the system can make recommendations. For example, a rule can be attached to a specific user. As an example of this utility, a new team can be organized to carry out a project. Furthermore, by setting company-specific rules, it is possible to select in order of human resources that match the corporate strategy. In addition, as another example of utility, it is possible to introduce a qualified person for solving a problem in work.

(2) By applying the target map and attaching rules when searching for content, the system can make recommendations. For example, a rule can be attached to a specific user. As an example of this utility, it is possible to recommend content to a certain team that reinforces weak points relatively. In addition, as another utility example, it is possible to recommend content to a team that further enhances professional ability. As another example of utility, if a company wants all employees to acquire up to level 1 of time management skills, it can be recommended as mandatory viewing content for employees.

[Supplement]
The present invention has been described in detail above with reference to specific embodiments. However, it is obvious that those skilled in the art can make modifications and substitutions of the embodiment without departing from the gist of the present invention. That is, the present invention has been disclosed in the form of exemplification, and the contents described in the present specification should not be interpreted in a limited manner. In order to determine the gist of the present invention, the claims section described at the beginning should be considered.

FIG. 1 is a diagram schematically showing a configuration of a content recommendation system according to an embodiment of the present invention. FIG. 2 is a diagram schematically showing the configuration of the content database. FIG. 3 is a diagram schematically showing the structure of the content map. FIG. 4 is a diagram schematically showing the configuration of the profile database. FIG. 5 is a diagram schematically showing the configuration of the access database. FIG. 6 is a diagram schematically showing a screen configuration of a personal data registration page for inputting user information. FIG. 7 is a diagram schematically showing a screen configuration of the behavior / thought characteristic check sheet / page presenting the user's question answer information. FIG. 8 is a diagram schematically showing a screen configuration of analysis result information by the profile engine. FIG. 9 is a diagram showing a configuration example of a presentation screen for content recommendation information including a recommended content list. FIG. 10 is a diagram showing an example of job classification. FIG. 11 is a diagram showing capability elements. FIG. 12 is a diagram illustrating a configuration example of a competency diagnosis table. FIG. 13 is a diagram showing a recommendation region created based on the competency diagnosis result shown in FIG. FIG. 14 is a diagram showing a state in which the target area is mapped on a two-dimensional space with the competency as the X axis and the job type as the Y axis. FIG. 15 is a diagram showing a recommendation region obtained by filtering the recommendation region shown in FIG. 13 with the target region shown in FIG. FIG. 16 is a diagram showing the weighting of recommendations obtained by applying rule 2 to the competency diagnosis table shown in FIG.

Explanation of symbols

1 ... Service server 2 ... User terminal (employee user)
3 ... Content provider 4 ... Corporate education department 10 ... Content database 11 ... Profile database 12 ... Access database 13 ... Communication interface 14 ... Search engine 19 ... Profile engine

Claims (19)

An information providing system for providing content information to a user,
Content storage means for storing content to be provided to users;
User profile management means for managing user profiles;
Content profile management means for managing profiles of contents stored in the content storage means;
Search means for searching for a desired user or content according to a comparison of said user profile and / or content profile;
Information presenting means for presenting information related to the content extracted by the content search means to the user;
An information providing system comprising: The user profile management means manages a profile acquired through analyzing the user based on an answer input from a target user with respect to a predetermined question.
The information providing system according to claim 1. The user profile management means manages at least job type information about a user and capability information including a plurality of capability elements (competencies) about job types as a profile,
The information providing system according to claim 1. The content profile management means manages the compatibility with the job type information possessed by the content and the compatibility with each capability element (competency) for each job type as a content profile.
The information providing system according to claim 3. The user profile management means and the content profile management means use a two-dimensional space in which competencies that are components of capabilities are mapped on the X axis and occupations having a hierarchical structure are mapped on the Y axis. Manage all profiles with the same type of map,
The information providing system according to claim 4, wherein: The search means compares a recommended area and a content profile that are equal to or higher than the ability level of the user within each competency on the job type axis corresponding to the user of the user profile.
The information providing system according to claim 1. The search means includes filtering the recommended area and the content profile obtained by filtering the recommended area with a target area that is a target to be reached (or required) according to a job type, work history, class, or the like of the user. Compare,
The information providing system according to claim 6. The search means performs a predetermined weighting on the recommended region after filtering, and then compares the content profile.
The information providing system according to claim 7. The information presenting means assigns each content with a recommendation level corresponding to the suitability between the searched content and the job type information and capability information of the target user, and generates recommendation information indicating the content according to the recommendation level. To
The information providing system according to claim 1. An information providing method for providing content information to a user,
A user profile management step for managing the user's profile;
A content profile management step for managing a profile of a predetermined content group;
A search step of searching for a desired user or content according to a comparison of said user profile and / or content profile;
An information presentation step of presenting information about the content extracted in the content search step to the user;
An information providing method comprising: In the user profile management step, a profile acquired through analyzing the user based on an answer input from a target user with respect to a predetermined question is managed.
The information providing method according to claim 10. In the user profile management step, at least job type information about the user and capability information consisting of a plurality of capability elements (competencies) about the job type are managed as a profile.
The information providing method according to claim 10. In the content profile management step, the compatibility with the job type information possessed by the content and the compatibility with each capability element (competency) for each job type are managed as a content profile.
The information providing method according to claim 12, wherein: In the user profile management step and the content profile management step, a content profile and a user are created using a two-dimensional space in which competencies that are competencies are mapped on the X axis and occupations having a hierarchical structure are mapped on the Y axis. Manage all profiles with the same type of map,
The information providing method according to claim 13. In the search step, a comparison is made between a recommended area and a content profile that are equal to or higher than the ability level of the user within each competency on the job axis corresponding to the user of the user profile.
The information providing method according to claim 10. In the search step, the recommended region and the content profile after filtering are obtained by filtering the recommended region with a target region that is a target (or required) according to the job type, work history, class, etc. of the user. Compare,
The information providing method according to claim 15. In the search step, after performing a predetermined weighting on the recommended region after filtering, the content profile is compared.
The information providing method according to claim 16. In the information presenting step, a recommendation level corresponding to the suitability between the searched content and the job type information and capability information of the target user is assigned to each content, and recommendation information that displays the content in accordance with the recommendation level is generated. To
The information providing method according to claim 10. A computer program written in a computer-readable format to execute processing for providing content information to a user on a computer system,
A user profile management step for managing the user's profile;
A content profile management step for managing a profile of a predetermined content group;
A search step of searching for a desired user or content according to a comparison of said user profile and / or content profile;
An information presentation step of presenting information about the content extracted in the content search step to the user;
A computer program comprising:

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