JP6421146B2 - Information processing system, information processing apparatus, program - Google Patents

Description

  The present invention relates to an information processing system, an information processing apparatus, and a program.

  In recent years, enormous amounts of information and data have been provided from the Internet and broadcast networks, and the information provided has also been diversified. In addition, an increasing number of users are trying to acquire information from the Internet or broadcast networks. Under such circumstances, a provider that provides content using the Internet or a broadcast network collects user access history to the Internet, etc., and analyzes the preference for each user based on the collected access history. There are already known systems for recommending content that matches the analyzed preferences.

  A technique related to the content recommendation system as described above is disclosed in Patent Document 1, for example. In Patent Document 1, a table in which history information and user-specific information are associated with each other so as to be able to follow the user's preference change, and the user's history information is reflected in the table, which is beneficial to the user. A technique for providing information is disclosed.

JP 2009-087155 A

  However, for example, in the conventional technique disclosed in Patent Document 1, the recommended content is searched based on a predetermined keyword, and the searched recommended content is acquired. If the degree of interest is only high, the user-specific degree of interest is not reflected. Also, if there are a plurality of devices that perform search processing, and search is performed on the search engines all at the same time, the performance deteriorates due to concentration of access. In other words, the construction of a recommendation system that reflects the degree of interest unique to the user and does not degrade the performance of the apparatus is an issue.

  The present invention has been made in view of such a situation, and an object of the present invention is to provide an information processing system that can share keywords for searching content together with content between devices.

  An information processing system according to the present invention is an information processing system having an information processing apparatus and a server connected via a network, and the server associates a general interest level with a term that is a word included in a document. A first database to be stored; a first keyword selecting means for selecting a first keyword related to a browse document to be browsed by a user based on a general public interest; and a related to the selected first keyword An information processing apparatus comprising: a first content acquisition unit configured to acquire the first content to be performed; and a keyword content transmission unit configured to transmit the selected first keyword and the acquired first content to the information processing apparatus. A second database that stores the user's interest level in association with a term that is a word included in the document; Second keyword selection means for selecting a second keyword related to the browsing document based on the degree of interest of the user, and the second keyword are transmitted, and the second content related to the second keyword is received. Content receiving means; and display means for displaying the received first content and second content together with the browsing document.

  An information processing apparatus according to the present invention includes a keyword content receiving unit that receives a first keyword and a first content related to a browse document that a user browses, and a term that is a word included in the document. A database that stores the degree of interest in association with each other, a keyword selection unit that selects a second keyword related to the viewing document based on the degree of interest of the user, and a second keyword that is transmitted and related to the second keyword Content receiving means for receiving the second content, and display means for displaying the received first content and the second content together with the browsing document.

  A program for causing a computer to execute a process according to the present invention includes a process of receiving a first keyword related to a browse document browsed by a user and a first content, and a term that is a word included in the document. Generating a database that stores the degree of interest in association with each other, a step of selecting a second keyword related to the viewing document based on the degree of interest of the user, and transmitting the second keyword, Receiving the second content related to the keyword; and displaying the received first content and the second content together with the browsing document.

  According to the present invention, it is possible to share a keyword for specifying content together with content between devices.

It is a hardware block diagram of the server 1 and the information processing apparatus 2 which comprise the information processing system concerning embodiment of this invention. It is a functional block diagram of the information processing system concerning the embodiment of the present invention. It is an example of the document clustering concerning embodiment of this invention. It is an example of the browsing document concerning embodiment of this invention. It is an example of the general interest level display concerning embodiment of this invention. It is an example of the personal interest degree display concerning embodiment of this invention. It is an example of the extraction of the general keyword and personal keyword relevant to the browsing document concerning embodiment of this invention. It is an example of the content display concerning embodiment of this invention. It is an example of keyword ranking according to the embodiment of the present invention. It is an example of keyword ranking according to the embodiment of the present invention. It is an example of the content display concerning embodiment of this invention. It is a flowchart of the content display concerning embodiment of this invention. It is a flowchart of keyword ranking according to the embodiment of the present invention.

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

  First, the hardware configuration of the server 1 and the information processing apparatus 2 according to the information processing system of this embodiment will be described with reference to FIG. Here, the server 1 refers to a host computer that makes a processing request to a plurality of computers through the network 30. The information processing device 2 refers to an information terminal that can be connected to the network 30 such as a personal computer, a tablet terminal, or a smartphone. Note that the configurations of the server 1 and the information processing apparatus 2 are not necessarily the same as those shown in FIG. 1, and it is sufficient if hardware capable of realizing the present embodiment is provided.

  The server 1 executes a predetermined program so as to realize the overall control of the server 1, and a read-only nonvolatile memory that stores a program read by the CPU 10 when the server 1 is powered on A mask ROM, EPROM, SSD, or the like, a memory 11 composed of SRAM, DRAM, or the like, which is a volatile memory for work in which the CPU 10 reads a program and temporarily writes data generated by arithmetic processing, etc., and a server And an HDD 12 capable of holding various data records when the power of one of the devices is turned off.

  The server 1 further includes a communication I / F 13. The server 1 is connected to the network 30 via the communication I / F 13. The communication I / F 13 accesses various types of information that can be accessed via the network 30 based on user operations on a plurality of information processing apparatuses 2 connected to the communication I / F 13. Specific examples of the communication I / F 13 include a USB port and a LAN. There are a port, a wireless LAN port, etc. Anything can be used as long as data can be transmitted / received to / from an external device.

  The information processing apparatus 2 executes a predetermined program to store a CPU 20 for realizing overall control of the information processing apparatus 2 and a program read by the CPU 20 when the information processing apparatus 2 is turned on. It consists of mask ROM, EPROM, SSD, etc., which are read-only non-volatile memories, and SRAM, DRAM, etc., which are volatile memories for work in which the CPU 20 reads programs and temporarily writes data generated by arithmetic processing, etc. Memory 21, HDD 22 capable of holding various data records when the information processing device 2 is turned off, an input device 23 composed of a mouse and input keys, a liquid crystal display, and an organic EL display And a display device 24 including a display using a panel such as the above.

  The information processing apparatus 2 further includes a communication I / F 25. The information processing apparatus 2 is connected to the network 30 via the communication I / F 25. The communication I / F 25 accesses various types of information that can be accessed via the network 30 based on the operation of the user of the information processing apparatus 2. Specific examples of the communication I / F include a USB port, a LAN port, and a wireless LAN port. Anything can be used as long as data can be transmitted / received to / from an external device.

  FIG. 2 is a functional block diagram of the information processing system according to the embodiment of the present invention. As shown in FIG. 2, the server 1 constituting the information processing system according to the present invention includes a first database 100, a first keyword selection unit 101, a first content acquisition unit 102, and a keyword content transmission unit. 103 and keyword ranking means 104. Further, the information processing apparatus 2 constituting the information processing system according to the present invention includes a second database 200, a second keyword selection unit 201, a content reception unit 202, and a display unit 203.

  The first database 100 of the server 1 is information that stores various data in a nonvolatile manner. In the present embodiment, it means information that is periodically acquired from the outside via the network 30 and stored in a database by a predetermined method. What is handled as a database in this embodiment may be provided with a nonvolatile storage device such as a dedicated HDD for storing information, or may be stored in the HDD 12. Details of the first database 100 will be described later.

  The first database 100 provided in the server 1 is a social database for a database generated by a so-called clustering method in which documents accessible via the network 30 are grouped for each category included in the document and for each term included in the document. A general “degree of general interest” is stored in association with each other. In this embodiment, “document” means, for example, a wide variety of information that can be browsed by an unspecified number of people. For example, information on sites that distribute social articles such as political economy, sports articles, etc. The information of the site that distributes. In this embodiment, “term” refers to a word that appears in a document. Hereinafter, the words appearing in the browsing document browsed by the user and the words constituting various databases and the like are collectively referred to as terms. Details of general interest will be described later.

  There are various methods for document clustering. For example, there is a two-dimensional database method in which documents are morphologically analyzed, and groups of terms having similar appearance tendencies of terms appearing and categories of the documents themselves are grouped. For example, there is a one-dimensional database system in which documents are grouped only by category for each term in which the appearance tendency of appearing terms is similar by performing morphological analysis. By performing clustering in this way, even a huge amount of documents can be grouped according to the appearance tendency of terms appearing in the documents. The first database 100 and the second database 200 used in this embodiment will be described as being clustered by the above-described one-dimensional database method.

  An example of a one-dimensional database that has been clustered as described above is shown in FIG. Grouping by terms appearing in a vast number of documents will produce an infinite number of categories, but in FIG. 3 there are three categories: “baseball”, “soccer”, and “politics” for simplicity of explanation. Limited to. For easy understanding, the category names are described as “baseball”, “soccer”, and “politics”, but when a database is actually generated in a computer, it is managed by category ID, category number, etc. It is common. If the category is “baseball”, the appearance tendency of terms related to “baseball” is similar, and “Giants”, “Hideki Matsui” and the like are grouped as terms belonging to the category “baseball”. “Soccer” and “Politics” are grouped in the same way.

  The appearance frequency in FIG. 3 means an appearance rate of a predetermined term with respect to the number of appearances of all terms constituting the one-dimensional database.

  The first keyword selection unit 101 of the server 1 selects the first keyword related to the browsing document browsed by the user based on the general public interest level in the first database 100. A browsing document is a document accessible via the network 30 as shown in FIG. 4, for example. Here, consider the case of selecting a keyword related to the document of FIG.

  First, a method for specifying a category to which the document of FIG. 4 belongs among a plurality of categories existing in the one-dimensional database will be described. The category to which the user belongs can be determined, for example, by paying attention to the terms that are extracted by morphological analysis of the sentences constituting the document in FIG. Specifically, the similarity between the document of FIG. 4 and each category of FIG. 3 is evaluated based on the appearance frequency in the one-dimensional database of terms extracted by the morphological analysis of the sentences constituting the document of FIG. . Similarity can be evaluated based on the correlation between the total appearance frequency of terms appearing in a browsing document in a one-dimensional database and the total appearance frequency of browsing documents. The evaluation method is not limited to this method. For example, it is also possible to evaluate that the value of the appearance frequency of the term appearing in the browsing document in the one-dimensional database is simply large as having high similarity. Furthermore, the similarity can be evaluated by applying the Euclidean distance or the cosine similarity.

  From the similarity determination result, it is assumed that the category of FIG. 3 similar to the document of FIG. 4 is “baseball”. That is, the first keyword is selected from terms in the category “baseball”. FIG. 5 is an example in which the general interest level is calculated from the appearance frequency of terms appearing in the category “baseball”. The general interest level is defined as a feature amount of a term appearing in the one-dimensional database in FIG. As information acquired by the server 1, in addition to the various categories of documents that can be accessed via the network 30 described above, a so-called Twitter that allows an unspecified number of users to speak freely or attach a WEB link ( There are social network services such as registered trademark and SNS. Such a social network service has a feature that it is easy to reflect the current trend and attention from the writing of an unspecified user and the number of accesses to a topic, for example. In other words, what is popular and popular in society is likely to be noticeable. Although not shown, the server 1 includes a “social database” in which terms extracted from a morphological analysis of sentences constituting a document acquired by such a social network service are associated with the appearance frequency.

  The general interest level can be calculated based on the correlation between the appearance frequency of terms appearing in a database generated from a document acquired by a social network service and the appearance frequency of the terms appearing in the database of FIG. As an example, the general interest degree can be calculated by LOG (B / A), where A is the appearance frequency in the one-dimensional database of FIG. 5 and B is the appearance frequency in the social database. In the present embodiment, the bottom of the LOG is calculated as 10, but the bottom is not limited to 10. The calculated value indicates the degree of interest in society in general. This is because the lower the appearance frequency in the one-dimensional database and the higher the appearance frequency in the social database, the larger the value, and it can be said that the term has a stronger preference. In FIG. 5, the terms with high general interest in the category “baseball” are “Giants”, “Hideki Matsui”, and “Hanshin”. In this way, a one-dimensional database is stored in association with a social database, that is, a general interest level as a feature quantity of a term constituting the one-dimensional database from information on a site that is attracting attention in general society. It is defined as the first database 100.

  Based on the calculated general interest level, “Giants”, “Hideki Matsui”, and “Hanshin” are selected from the category “baseball”. Note that only keywords with the highest general interest may be selected, or a plurality of keywords may be selected based on a predetermined rule. In this embodiment, the top three terms “Giants”, “Hideki Matsui”, and “Hanshin” with the highest degree of interest are selected as keywords.

  The first keyword selection means 101 of the server 1 reads and executes a database or the like stored in the HDD 12 based on a predetermined keyword selection program stored in the memory 11 by the CPU 10, and executes the arithmetic processing data. This can be realized by temporarily storing it in the memory 11 or storing it in the HDD 12 or the like.

  The first content acquisition unit 102 of the server 1 acquires the first content related to the selected first keyword. Note that “content” in the present embodiment is a person that is recorded or transmitted by a medium such as video, music, text, or a combination thereof and is viewed by a human being in addition to the ordinary meaning of the word “content” itself. This refers to a group of information. For example, it refers to applications distributed on the Internet, downloadable video content, music content, and the like.

  The acquired contents may all be handled as valid information, but the sentences constituting the document included in the contents may be subjected to morphological analysis again, and the contents may be narrowed down based on the general interest level of the appearing terms. By re-evaluating the acquired content, it becomes possible to narrow down and provide content that matches general social preferences.

  The first content acquisition unit 102 of the server 1 reads and executes a database or the like stored in the HDD 12 based on a predetermined content acquisition program stored in the memory 11 by the CPU 10, and the network 30 through the communication I / F 13. This can be realized by accessing a predetermined website via the URL and acquiring content.

  The keyword content transmission unit 103 of the server 1 transmits the selected first keyword and the acquired first content to the information processing apparatus 2. When there are a plurality of acquired contents, all the contents may be transmitted, or only the contents evaluated as having a high general interest level by the first content acquiring unit 102 may be transmitted. Similarly, the first keyword may be associated with the second content, and only the first keyword related to the first content to be transmitted may be transmitted.

  The keyword content transmitting means 103 of the server 1 reads and executes a database or the like stored in the HDD 12 based on a predetermined keyword content transmission program stored in the memory 11 by the CPU 10, and connects the network 30 through the communication I / F 13. This can be realized by transmitting the first keyword and the first content to the information processing apparatus 2 via the network.

  The second database 200 included in the information processing apparatus 2 is a database generated by a so-called clustering method in which documents accessible via the network 30 are grouped for each category including the document and for each term included in the document. The “user interest” is stored in association with each other. As a database generation method, as in the first database 100 generation method, for example, sentences constituting a document are analyzed by morphological analysis, and groups of terms having similar appearance tendencies of appearing terms and categories of the document itself are grouped. There is also a two-dimensional database method, or a one-dimensional database method in which sentences constituting a document are morphologically analyzed and grouped only by terms having similar appearance tendencies. As described above, the database serving as the basis of the second database 200 is a one-dimensional database similar to the first database 100. Details of the user interest level will be described later.

  The one-dimensional database uses FIG. 3 similarly to the first database 100. As in the first database 100, the general interest level is defined as the feature amount, the second database 200 included in the information processing device 2 defines the user interest level of the user who owns the information processing device 2 as the feature amount. . Information acquired by the information processing apparatus 2 includes documents acquired via the network 30 based on the user's own preferences, in addition to the various categories of documents accessible via the network 30 described above. For example, a user who likes “baseball” inevitably browses documents related to “baseball”, and a document acquired via the network 30 based on the user's own operation is stored. Thus, a “user database” generated by the same clustering method as the one-dimensional database of FIG. 3 based on the browsing history of the document acquired via the network 30 based on the user's own preference is also provided.

  The user interest level is calculated based on the correlation between the appearance frequency of the terms appearing in the user database generated from the document acquired based on the user's own preference and the appearance frequency of the terms appearing in the one-dimensional database of FIG. It is possible. As an example of the calculation method, the calculation can be performed by the same calculation method as the general interest degree in FIG. The calculation result is as shown in FIG. 6. Here, assuming that the two information processing apparatuses 2 are connected to the server 1 via the network 30, the user interests of “Mr. A” and “Mr. B” respectively. Degrees are listed. Even if the user interests of “Mr. A” and “Mr. B” are in the same category “baseball”, for example, “Mr. A” has a higher interest degree of the term “Softbank”, and “Mr. B” has “Ichiro” The interest level within the category varies from user to user. Thus, the user interest degree as the feature quantity of the term constituting the one-dimensional database from the history information of the user database, that is, the document viewed in the past by the user holding the information processing apparatus 2 is compared with the one-dimensional database. What is stored in association with each other is defined as the second database 200.

  As described above, each user who has the information processing apparatus 2 has the unique second database 200.

  The second keyword selection unit 201 of the information processing device 2 selects the second keyword related to the browse document based on the user's interest level in the second database 200. Consider a case where the second keyword is selected from the information processing apparatus 2 owned by “Mr. A” based on the user interest level defined above. As shown in FIG. 7, when attention is focused on the user interest level, “soft bank”, “carp”, and “giants” are selected from the category “baseball” as candidate keywords. It is assumed that the category having a high similarity to the browsed document is “baseball” in the same manner as when the first keyword is selected. As the second keyword to be selected, only the keyword having the highest degree of user interest may be selected, or a plurality of second keywords may be selected based on a predetermined rule. Further, a keyword that overlaps with the keyword selected by the first keyword selection unit 101 may not be selected. In the present embodiment, the top three terms “Softbank”, “Carp”, and “Giants” with the highest user interest are selected as keywords.

  When the user interest degree of the selected second keyword is compared with the general interest degree, the keyword “Giants” overlaps with the first keyword, but “soft bank” and “carp” have low general interest degree. This is a user-specific keyword with a high degree of user interest. As described above, it is possible to select a keyword having high preference for both the general interest level and the user interest level.

  In the second keyword selection unit 201 of the information processing apparatus 2, the CPU 20 reads and executes a database or the like stored in the HDD 22 based on a predetermined keyword selection program stored in the memory 21, and performs arithmetic processing or the like. This can be realized by temporarily storing the data in the memory 21 or by storing it in the HDD 22 or the like.

  The content receiving unit 202 of the information processing device 2 transmits the second keyword and receives the second content related to the second keyword. The second keyword selected by the second keyword selection means 201 described above is transmitted to the server 1 capable of acquiring the second content. The second keyword transmission destination server may be the first keyword and the server 1 that is the transmission source of the first content, or may be another server or a host computer. Good. There is no particular limitation as long as the computer has a function capable of acquiring content related to the second keyword received from the information processing device 2. The second keyword is “Softbank”, “Carp”, and “Giants” selected from the information processing apparatus 2 owned by “Mr. A”. When receiving the second content, for example, the content related to the duplicate keyword “Giants” selected from the general interest level may not be acquired.

  In the content receiving unit 202 of the information processing apparatus 2, the CPU 20 transmits the second keyword from the communication I / F 25 via the network 30 based on a predetermined content receiving program stored in the memory 21. This can be realized by receiving the second content related to.

  The display unit 203 of the information processing apparatus 2 displays the received first content and second content together with the browse document. FIG. 8 shows an example of content display. The received first content and the second content acquired based on the user interest level are output to the display device 24, for example. Not only content related to user-specific keywords “Softbank” and “Carp”, but also content related to “Giants” and “Hideki Matsui” with high general interest can be viewed personally. It is possible to browse not only highly-preference content, but also general and high-taste content.

  The display unit 203 of the information processing device 2 displays information on the display device 24 according to a predetermined display format stored in the display device 24 based on a predetermined information display program stored in the memory 21 by the CPU 20. Can be realized.

  The keyword ranking unit 104 further provided in the server 1 performs ranking based on the characteristics of the second keyword received from the information processing apparatus 2. Here, consider a case where the server 1 is connected to a plurality of information processing apparatuses 2 via the network 30. It is assumed that all the information processing apparatuses 2 have the above-described function, and the second keyword selected by the information processing apparatus 2 is transmitted to the server 1. That is, the second keyword is received from the information processing apparatus 2 owned by “Mr. A” and “Mr. B” connected to the server 1.

  A list of keywords received from a plurality of users is shown in FIG. The second keywords received from each user are the top three having the highest user interest. Referring to FIG. 9, there are three keywords “Softbank”, “Carp”, and “Giants” received from the information processing apparatus 2 possessed by “Mr. A”, and the information processing apparatus 2 possessed by “Mr. B”. The keywords received from are “Ichiro”, “Giants”, and “Hideki Matsui”. A term belonging to the category “baseball” and not selected as a keyword is set to “not selected”, and the user interest level is set to 0.

<First embodiment of keyword ranking in this embodiment>
A first embodiment in which the second keyword received from the information processing apparatus 2 owned by the user is ranked based on the information shown in FIG. 9 will be described. In the first embodiment, ranking is performed based on keywords received from the information processing apparatus 2 and information on the degree of user interest in the keywords. First, the user interest levels of a plurality of users are integrated and calculated for each keyword. For example, since the keyword “Giant” is a keyword received from each of the information processing apparatuses 2 of “Mr. A” and “Mr. B”, the user interest level of “Mr. A” is 0.3 and the user interest level of “Mr. B” is Assuming 0.35, the integration result is 0.65. Thus, the user interest level is integrated for each keyword, and ranking is performed in descending order of the integration result.

  From the integration result, the upper keywords are “SoftBank”, “Ichiro”, and “Giants”, and these keywords are candidate keywords for acquiring content to be transmitted to the user. The keyword “Ichiro” is “not selected” from the user interest level of “Mr. A”, but the keyword “Ichiro” is selected from the user interest level of “Mr. B”. That is, even if a keyword has a low degree of user interest, it may be selected as a keyword if the interest of another user is high.

<Second embodiment of keyword ranking in this embodiment>
Next, a second embodiment will be described in which the second keyword received from the information processing apparatus 2 owned by the user is ranked based on the information shown in FIG. In the second embodiment, ranking is performed based on the total number of keywords received. In the present embodiment, it is assumed that there are two information processing apparatuses 2 connected to the server 1 via the network 30. For example, when the information processing apparatuses 2 are connected to 1000 information processing apparatuses 2, the keyword It is assumed that many duplications will occur. As a counting method, if “Ichiro” is included in the keyword received from the information processing apparatus 2 owned by “Mr. A”, the keyword is counted as “1”. Thus, the total amount of keywords received from the information processing devices 2 of all users connected to the server 1 and the network 30 is calculated.

  According to the calculation result, the upper keywords are “ICHIRO”, “GIANTS”, and “SOFTBANK”, and these keywords are candidate keywords for acquiring content transmitted to the information processing apparatus 2 owned by the user.

  As another embodiment of the keyword ranking in this embodiment, for example, a keyword that overlaps with a keyword selected based on the general interest level and a user-specific keyword that is not selected based on the general interest level coexist. In this case, the keywords specific to the user are ranked in a higher ranking, and keywords that overlap with the keywords selected based on the general interest are excluded. Thus, performance can be expected to be reduced by reducing the number of keywords as much as possible. In addition, there is a method in which keywords unique to users are preferentially ranked for each user. For example, “Softbank” and “Ichiro”, which were not selected based on general interest, are “Softbank” is a keyword unique to Mr. A, and “Ichiro” is a keyword unique to Mr. B. “Softbank” is preferentially ranked higher, and “Ichiro” is preferentially ranked higher for “Mr. B”. In this way, the keywords unique to each user are ranked preferentially for each user, so that it is possible to select the keywords with high preference unique to each user without leakage. In addition, for keywords with a high degree of interest in general society, a threshold is set in advance for the user's response to acquired content, that is, the number of accesses, etc., and keywords related to content that has been accessed more than a predetermined number of times are given priority. There are also methods such as ranking in the higher rank.

  When several types of second keywords are received from a plurality of users, the keywords are ranked based on a predetermined ranking method, instead of acquiring content related to all the received second keywords. It is possible to define the superiority or inferiority of keywords, and it is possible to expect the improvement of the performance as a whole because keywords that are not of high interest can be omitted in advance.

  The keyword ranking unit 104 of the server 1 reads and executes a database or the like stored in the HDD 12 based on a predetermined keyword ranking program stored in the memory 11 by the CPU 10, and stores the processed data in the memory 11. This can be realized by temporarily storing it in the HDD 12 or the like.

  FIG. 11 shows a display example of content related to keywords selected based on keyword ranking. FIG. 11 is a display example in which content is displayed on the information processing apparatus 2 owned by “Mr. A”. The keyword ranking method may be based on the above-described degree of user interest or may be based on the total amount, and is not particularly limited as long as it can be selected without leaking keywords specific to the user. In FIG. 11, the first content acquired based on the general interest level and the second content acquired based on the user interest level are displayed together with the designated document as in FIG.

  Although the keyword “ICHIRO” was “not selected” from the characteristics of the keyword received from the information processing apparatus 2 owned by “Mr. A”, the keyword characteristics received from the information processing apparatus 2 owned by other users Since “ICHIRO” is selected, the content related to “ICHIRO” is displayed on the information processing apparatus 2 owned by “Mr. A”. In addition, by displaying the keywords with the content, what kind of phrases the general society is interested in for the specified document and the phrases that the user or an unspecified number of users are interested in? It is possible to recognize that there is.

  The embodiment of the present invention has been described above. According to the present invention, it is possible to share a keyword for searching content together with content between devices, and recognize not only content with high user's own preference but also content with general society and high preference for third parties. It becomes possible. With the information processing system of the present invention, it is possible to expect an expansion of the recommended information range provided to the user as compared with the conventional system.

  FIG. 12 is a flowchart of content display according to the embodiment of the present invention.

  First, the server 1 selects a first keyword related to the viewed document (step 1). First content related to the selected first keyword is acquired (step 2). The first keyword and the acquired first content are transmitted to the information processing apparatus 2 (step 3). Next, the information processing apparatus 2 selects a second keyword related to the browse document (step 4). Note that the timing at which the information processing device 2 selects the second keyword related to the viewed document may be the timing at which the server 1 selects the first keyword, or the timing at which the first content is received, and is particularly limited. Is not provided.

  The information processing device 2 transmits the selected second keyword to the server 1 (step 5). Next, the server 1 acquires the second content related to the second keyword received from the information processing device 2 (step 6). The second keyword and the second content are transmitted to the information processing device 2 (step 7). Next, the information processing apparatus 2 displays the first content and the second content received from the server 1 together with the browsing document (step 8).

  FIG. 13 is a flowchart of keyword ranking according to the embodiment of the present invention.

  The plurality of information processing devices 2 select a second keyword related to the browsed document (Steps 9 and 11). The selected second keyword is transmitted to the server 1 (steps 10 and 12). The server 1 ranks the second keyword received from the plurality of information processing devices 2 according to a predetermined standard (step 13). The second content related to the keyword having the highest ranking is additionally acquired (step 14).

  As long as the present invention can be realized, the contents of the apparatus used, the number of apparatuses, and the like are not limited to the present embodiment.

DESCRIPTION OF SYMBOLS 100 1st database 101 1st keyword selection means 102 1st content acquisition means 103 Keyword content transmission means 104 Keyword ranking means 200 2nd database 201 2nd keyword selection means 202 Content reception means 203 Display means

Claims (8)

An information processing system having an information processing apparatus and a server connected via a network,
The server
A first database for storing a general interest level in association with a term that is a word included in a document;
A first keyword selecting means for selecting a first keyword related to a viewing document that the user browses based on the degree of interest of the general society;
First content acquisition means for acquiring first content related to the selected first keyword;
Keyword content transmission means for transmitting the selected first keyword and the acquired first content to the information processing apparatus;
With
Information processing device
A second database that stores the user's interest level in association with terms that are words included in the document;
Second keyword selection means for selecting a second keyword related to the browsing document based on the degree of interest of the user;
Content receiving means for transmitting the second keyword and receiving second content related to the second keyword;
Display means for displaying the received first content and second content together with the browse document;
Comprising
An information processing system characterized by this. The second keyword selecting means selects, as the second keyword, a keyword that does not overlap with the received first keyword based on the degree of interest of the user.
The information processing system according to claim 1. The display means displays the second keyword and the received first keyword together with the first content and the second content on the browsing document;
The information processing system according to claim 1 or 2. The content receiving means transmits the second keyword to the server, and receives second content related to the second keyword from the server.
The information processing system according to any one of claims 1 to 3. The server
Keyword ranking means for ranking based on the characteristics of the second keyword received from the information processing device;
Further comprising
The information processing system according to claim 4. The keyword ranking means calculates the aggregate amount of the second keyword, and ranks in order of increasing the aggregate amount.
The information processing system according to claim 5. A keyword content receiving means for receiving a first keyword related to a browsing document browsed by a user and a first content related to the first keyword;
A database that stores the user's interest level in association with terms that are words included in the document;
Keyword selection means for selecting a second keyword related to the browse document based on the degree of interest of the user;
Content receiving means for transmitting the second keyword and receiving second content related to the second keyword;
Display means for displaying the received first content and second content together with the browse document;
Comprising
An information processing apparatus characterized by that. Receiving a first keyword associated with a viewing document viewed by a user and first content associated with the first keyword ;
Generating a database for storing a user's interest level in association with a term that is a word included in the document;
Selecting a second keyword associated with the browsed document based on the user's degree of interest;
Transmitting the second keyword and receiving second content related to the second keyword;
Displaying the received first content and second content together with the browsing document;
To run on a computer,
program.

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