JP7009256B2 - Information processing equipment, information processing methods, and information processing programs - Google Patents

Description

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

Services using the network are actively performed. In recent years, on EC (Electronic Commerce) sites and portal sites, it is possible for users to post comments on predetermined targets (for example, products, articles, etc.).

Japanese Unexamined Patent Publication No. 2013-205875

In order for the service to be actively used, it is desirable to have many users post comments. However, in recent years, since there are many contents (for example, articles) in which comments can be posted, it is not easy to encounter contents that users want to comment on.

The present application has been made in view of the above, and an object of the present application is to provide an information processing device, an information processing method, and an information processing program capable of promoting the posting of comments by a user.

The information processing apparatus according to the present application includes an acquisition unit, a specific unit, and a generation unit. The acquisition unit acquires the comment history of each of the plurality of users for the plurality of contents and the comment attribute of each of the plurality of comments specified in the comment history. The specific unit is a comment pattern specified based on the comment history and the comment attribute, and identifies a user having a comment pattern similar to the comment pattern of a predetermined user. The generation unit generates recommended information for a predetermined user regarding posting of comments based on the comment history of the user specified by the specific unit.

According to one aspect of the embodiment, it is possible to provide an information processing device, an information processing method, and an information processing program capable of promoting the posting of comments by a user.

FIG. 1 is a diagram showing the operation of the information processing system according to the embodiment. FIG. 2 is a diagram showing how the content is displayed on the terminal device according to the embodiment. FIG. 3 is a diagram showing how the information processing server analyzes comments. FIG. 4 is a diagram showing an example of comment attribute information. FIG. 5 is a diagram showing an example of the determination result of the comment pattern. FIG. 6 is a diagram showing another example of the determination result of the comment pattern. FIG. 7 is a diagram showing how the content including the recommended information is displayed on the terminal device. FIG. 8 is a diagram showing a configuration example of the information processing server according to the embodiment. FIG. 9 is a diagram showing a configuration example of the terminal device according to the embodiment. FIG. 10 is a flowchart showing an example of information transmission processing. FIG. 11 is a diagram showing an example of a comment history stored in the comment history database. FIG. 12 is a diagram showing an example of the determination result of the comment pattern. FIG. 13 is a diagram showing another example of the determination result of the comment pattern. FIG. 14 is a diagram showing another example of the determination result of the comment pattern. FIG. 15 is a hardware configuration diagram showing an example of a computer that realizes the function of the information processing device server.

Hereinafter, the information processing apparatus, the information processing method, and the embodiment for implementing the information processing program (hereinafter referred to as “the embodiment”) according to the present application will be described in detail with reference to the drawings. The following embodiments do not limit the information processing apparatus, information processing method, and information processing program according to the present application. Further, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicate explanations are omitted.

[1. Operation of information processing device]
First, the operation of the information processing apparatus will be described by taking an information processing system 1 including an information processing server 10, which is an example of the information processing apparatus, as an example.

[1-1. Information processing system]
FIG. 1 is a diagram showing the operation of the information processing system 1 according to the embodiment. The information processing system 1 includes an information processing server 10 and terminal devices 100 ₁ to 100 ₂ . The terminal device 100 ₁ is a terminal device operated by the user U1, and the terminal device 100 ₂ is a terminal device operated by the user U4. In the example of FIG. 1, only two terminal devices are shown, but the number of terminal devices may be less than two or more than two. In the following description, the terminal devices 100 ₁ to 100 ₂ and the like may be collectively referred to as the terminal device 100.

The information processing server 10 is a server host computer that provides various services to client terminals. The information processing server 10 distributes the content to the terminal device 100. For example, the information processing server 10 is a portal site, a game information distribution site, a news site, an auction site, a weather forecast site, a shopping site, a finance (stock price) site, a route search site, a map providing site, a travel site, and a restaurant introduction site. , The content in which information related to the bulletin board site, the web blog, etc. is arranged in a tile shape is distributed to the terminal device 100.

The terminal device 100 is a smart device such as a smartphone or tablet, and is a mobile terminal device capable of communicating with an arbitrary server device via a wireless communication network such as 3G (3rd Generation) or LTE (Long Term Evolution). be. The terminal device 100 may be not only a smart device but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

[1-2. Information processing system operation]
Hereinafter, the operation of the information processing system 1 will be described.

First, the information processing server 10 receives a content distribution request from the terminal device 100 (terminal device 100 ₁ in the example of FIG. 1). After receiving the content distribution request, the information processing server 10 distributes the content to the terminal device 100 that has made the content distribution request.

FIG. 2 is a diagram showing how the content is displayed on the terminal device 100 according to the embodiment. In the example of the state D11 of FIG. 2, the content C11 (first content) in which a plurality of contents are arranged is displayed on the display surface (hereinafter, also referred to as a screen) included in the terminal device 100. The content C11 is information on an arrangement surface in which a plurality of contents such as images (for example, still images and moving images) and text information (for example, news articles) are arranged in a tile shape. For example, the content C11 is screen information to be displayed on an application (hereinafter referred to as an application) installed in the terminal device 100. The content C11 may be generated based on data (for example, content data such as map data) pre-installed in the storage device included in the terminal device 100. Further, the content C11 may be page information (for example, web page information).

In the present embodiment, the content C11 is a page of an EC site or a portal site, and includes the content C21 (predetermined content) including information to be transmitted by the page. The content C21 is, for example, product information or an article. In the example of the state D11 in FIG. 2, the content C21 is a news article. Further, a comment can be posted to the content C21, and a plurality of comments are posted. A predetermined number of comments selected from a plurality of comments are displayed in the content C11. In the example of the state D11 of FIG. 2, the content C11 displays three comments T11, T31, and T41 with respect to the content C21.

The tile that displays each comment is accompanied by information on the number of replies to the comment and the rating of the comment. For example, the reply information R11 and the evaluation information E11 are attached to the tile displaying the comment T11. The reply information R11 indicates the number of replies to the comment T11. In the example of the state D11 of FIG. 2, "Reply: 51" is displayed as the reply information R11. This example shows that 51 replies were made to the comment T11. Further, in the example of the state D11 of FIG. 2, as the evaluation information E11, an image showing a positive evaluation (an image of a hand with the thumb up) and an image showing a negative evaluation (an image of the hand with the thumb up). ), "100", and "10" are displayed. This example shows that comment T11 was given 100 positive and 10 negative ratings.

Further, the reply information R31 and the evaluation information E31 are attached to the tile displaying the comment T31. The reply information R31 indicates the number of replies to the comment T31. In the example of the state D11 of FIG. 2, "Reply: 23" is displayed as the reply information R31. This example shows that 23 replies were made to the comment T31. Further, in the example of the state D11 in FIG. 2, as the evaluation information E31, an image showing a positive evaluation, an image showing a negative evaluation, “93”, and “12” are displayed. This example shows that comment T31 was given 93 positive and 12 negative ratings.

Further, the reply information R41 and the evaluation information E41 are attached to the tile displaying the comment T41. The reply information R41 indicates the number of replies to the comment T41. In the example of the state D11 of FIG. 2, "Reply: 16" is displayed as the reply information R41. This example shows that 16 replies were made to the comment T41. Further, in the example of the state D11 in FIG. 2, as the evaluation information E41, an image showing a positive evaluation, an image showing a negative evaluation, “121”, and “8” are displayed. This example shows that the comment T41 was given 121 positive and 8 negative evaluations.

Further, the content C11 includes a button B22 for displaying all comments on the content C21. When the user presses the button B22, the terminal device 100 requests the information processing server 10 to deliver all the comments to the content C21. When the information processing server 10 receives the distribution request, the information processing server 10 distributes the content including all the comments for the content C21.

Further, on the content C11, a button B21 for displaying the content for posting a comment on the content C21 (predetermined content) is displayed. When the user presses the button B21, the terminal device 100 requests the information processing server 10 to deliver the content for posting a comment on the content C21. In the following description, the content (for example, the screen or page of the application) for posting a comment for a predetermined content (for example, an article) is referred to as a comment posting content. Upon receiving the distribution request, the information processing server 10 distributes the content C12, which is the comment posting content for the content C21. Upon receiving the distribution of the content C12, the terminal device 100 displays the content C12 on the screen as shown in the state D12 of FIG.

The content C12 includes a text box TB1 for inputting a comment. Further, the content C12 includes a button B1 for posting a comment input in the text box TB1 to a predetermined site. When the user presses the button B1, the terminal device 100 transmits the comment input to the text box TB1 to the information processing server 10 (step S1 in FIG. 1). At this time, the terminal device 100 may transmit the comment to the information processing server 10 together with the identification information of the content to be commented (content C21 in the example of FIG. 1). When the information processing server 10 receives a comment, the information processing server 10 registers the received comment in the comment history database.

The comment history database stores the history of comments made by each of a plurality of users on a plurality of contents. In the example of FIG. 1, the comment history database stores the history of comments of users U1 to U4 with respect to the contents C21 to C25.

In the case of the comment history shown in FIG. 1, the user U1 makes a comment T11 to the content C21, makes a comment T13 to the content C23, and makes a comment T14 to the content C24. Comment T15 is given to C25. User U1 has not commented on the content C22. Further, the user U2 makes a comment T22 to the content C22. User U2 has not commented on the contents C21, C23, C24, and C25. Further, the user U3 makes a comment T31 for the content C21, makes a comment T33 for the content C23, makes a comment T34 for the content C24, and makes a comment T35 for the content C25. Is going. User U3 has not commented on the content C22. Further, the user U4 makes a comment T41 to the content C21, makes a comment T43 to the content C23, and makes a comment T44 to the content C24. User U4 has not commented on the content C22 and the content C25.

In the example shown in FIG. 1, the comment history database stores conceptual information such as "T11" to "T44", but comment data itself such as text data, image data, and voice data is stored. May be. The comment history database may store the URL where the data of each comment is located, the file path name indicating the storage location thereof, and the like. In the comment history database shown in FIG. 1, "-" indicates that no comment has been posted. Therefore, the comment history stored in the comment history database can be regarded as information indicating the presence or absence of comments. Note that the comment history database may not store comment information, but may simply store information indicating the presence or absence of comments.

Further, the information processing server 10 receives a distribution request for content (for example, content including content C21) from the terminal device 100 (step S2). In the following description, it is assumed that the distribution request is received from the terminal device 100 operated by the user U4 (predetermined user). When the information processing server 10 receives the content distribution request, the information processing server 10 acquires the comment history of each of the plurality of users from the comment history database.

Then, the information processing server 10 analyzes each of the plurality of comments specified in the comment history, and acquires the analysis result as a comment attribute. The comment attribute is information (data) indicating the property or characteristic of the comment or the property or characteristic of the comment. For example, the comment attribute is information indicating whether the comment is positive or negative. Of course, the comment attribute is not limited to information indicating whether it is positive or negative. For example, the comment attribute may be the subject to be commented on in the corresponding comment. The information of the subject who is the target of the comment is also one of the information that characterizes the comment.

Further, the comment attribute may be the number of replies to the corresponding comment. The number of replies is also information indicating the nature and characteristics of the comment. For example, a comment with a large number of replies shows the property or characteristic that "it is easy to get a reply".

Further, the comment attribute may be evaluation information for the corresponding comment. Evaluation is also information that shows the nature and characteristics of comments. For example, a comment with a high evaluation (for example, a comment with a high positive evaluation value) exhibits, for example, a property or characteristic of "easily attracting people". A comment can be accompanied by multiple evaluations consisting of either a positive evaluation or a negative evaluation. As mentioned above, a positive rating is, for example, "Good" or "Like", and a negative rating is, for example, "Bad". The information processing server 10 sets a value calculated based on the number of positive evaluations (for example, the number of “Good”) and the number of negative evaluations (for example, the number of “Bad”) attached to the comment. Get as a comment attribute of. For example, the information processing server 10 may acquire a value indicating the ratio of positive evaluation to the total evaluation (for example, positive evaluation / (positive evaluation + negative evaluation)) as a comment attribute.

In the present embodiment, the information processing server 10 determines the subject to be commented on for each of the plurality of comments. Further, the information processing server 10 determines whether the comment is positive or negative (for example, whether the comment is positive or negative with respect to the subject to be commented) for each of the plurality of comments. FIG. 3 is a diagram showing how the information processing server 10 analyzes comments. FIG. 3 shows how the information processing server 10 analyzes the comment T11 and the comment T15.

Comment T11 is a comment with the content that "XX Association is very terrible". The information processing server 10 identifies the subject to be commented on in the comment T11. For example, the information processing server 10 performs a syntactic analysis (for example, morphological analysis) of the comment T11. Then, the information processing server 10 determines the subject "XX Association" as the subject (subject A) to be commented in the comment T11. Further, the information processing server 10 determines whether the comment T11 has a positive content or a negative content. For example, the information processing server 10 holds in advance a positive dictionary in which words with positive contents are registered and a negative dictionary in which words with negative contents are registered. Then, the information processing server 10 determines the predicate portion of the comment T11 by parsing the comment T11. In the example of FIG. 3, "terrible" is the predicate part of the comment T11. Then, the information processing server 10 collates the predicate portion of the comment T11 with the positive dictionary and the negative dictionary to determine whether the predicate portion of the comment T11 has positive content or negative content. The information processing server 10 determines that the comment T11 is positive when the predicate portion of the comment T11 is positive, and determines that the comment T11 is negative when the predicate portion of the comment T11 is negative. do. In the example of FIG. 3, since the predicate part of the comment T11, "terrible", has a negative content, it is determined that the comment T11 is negative. “N” shown in FIG. 3 indicates that the comment T11 is negative.

Comment T15 is a comment with the content that "Director YY is amazing". The information processing server 10 identifies the subject to be commented on in the comment T15. For example, the information processing server 10 performs a syntactic analysis (for example, morphological analysis) of the comment T15. Then, the information processing server 10 determines that the subject portion "YY director" is the subject (subject B) to be commented in the comment T15. Further, the information processing server 10 determines whether the comment T15 has a positive content or a negative content. For example, the information processing server 10 holds in advance a positive dictionary in which words with positive contents are registered and a negative dictionary in which words with negative contents are registered. Then, the information processing server 10 determines the predicate portion of the comment T15 by parsing the comment T15. In the example of FIG. 3, "wow" is the predicate part of the comment T15. Then, the information processing server 10 collates the predicate portion of the comment T15 with the positive dictionary and the negative dictionary to determine whether the predicate portion of the comment T15 has positive content or negative content. The information processing server 10 determines that the comment T15 is positive when the predicate portion of the comment T15 is positive, and determines that the comment T15 is negative when the predicate portion of the comment T15 is negative. do. In the example of FIG. 3, since the predicate part of the comment T15, "wow", has a positive content, it is determined that the comment T15 is affirmative. “P” shown in FIG. 3 indicates that the comment T15 is positive.

The information processing server 10 analyzes each of a plurality of comments and generates comment attribute information based on the analysis result. FIG. 4 is a diagram showing an example of comment attribute information. The comment attribute information shown in FIG. 4 has items such as "comment" and "comment attribute".

"Comment" indicates each user's comment on the content. In the example shown in FIG. 4, the "comment" stores conceptual information such as "T11" to "T33", but the comment data itself such as text data may be stored.

"Comment attribute" indicates the comment attribute of the comment indicated by "comment". The "comment attribute" item has items such as "subject", "polarity", "number of replies", and "evaluation". "Subject" indicates the subject to be commented in the comment indicated by "comment". The "polarity" indicates whether the comment indicated by the "comment" is positive or negative (for example, whether the comment is positive or negative with respect to the subject to be commented). In the example of FIG. 4, it can be seen that the comment T11 is a negative comment to the subject A. Further, it can be seen that the comment T13 is a negative comment for the subject B. It can be seen that the comment T14 is a positive comment for the subject A. Further, it can be seen that the comment T15 is a positive comment for the subject B.

Further, the "number of replies" indicates the number of replies to the comment indicated by the "comment". In the example of FIG. 4, it can be seen that 51 replies were made to the comment T11. In addition, "evaluation" indicates an evaluation for a comment. The "evaluation" may be a positive evaluation or a negative evaluation. Of course, the evaluation for the comment may be both a positive evaluation and a negative evaluation, or may be a value calculated based on the value of the positive evaluation and the value of the negative evaluation. In the example of FIG. 4, it can be seen that 90.9% of the evaluations for the comment T11 were positive evaluations (for example, "Good", "Like", etc.).

In the following explanation, the subject to be commented in the comment may be simply referred to as "subject". In addition, information indicating whether a comment is positive or negative (for example, whether the comment is positive or negative with respect to the subject to be commented) may be referred to as "polarity". Subject, polarity, number of replies, and rating are all types of comment attributes.

The information processing server 10 determines the comment pattern of each of the plurality of users based on the comment history stored in the comment history database and the comment attribute stored in the comment attribute information.

FIG. 5 is a diagram showing an example of the determination result of the comment pattern. The comment pattern shown in FIG. 5 is a comment pattern based on the presence / absence of a comment, the subject of the comment target, and the polarity of the comment. In the figure, "AN" indicates a negative comment with the subject as A. In addition, "BN" indicates a negative comment with the subject as B. In addition, "AP" indicates a positive comment with the subject as A. In addition, "BP" indicates a positive comment with the subject as B. In addition, "CP" indicates a positive comment with the subject as C.

In the following description, the AN comment means a negative comment with the subject as A, and the AP comment means a positive comment with the subject as A. Further, the BN comment means a negative comment with the subject as B, and the BP comment means a positive comment with the subject as B. A CP comment means a positive comment with the subject as C.

In the example of FIG. 5, the comment pattern of the user U1 has an AN comment for the content C21, no comment for the content C22, a BN comment for the content C23, an AP comment for the content C24, and the content C25. There is a BP comment for. Further, the comment pattern of the user U2 is that there is a CP comment for the content C22 and no comment for the content C21, C23, C24, and C25. The comment pattern of the user U3 is that there is an AP comment for the content C21, there is no comment for the content C22, there is a BP comment for the content C23, there is a BP comment for the content C24, and there is a BN comment for the content C25. It has become. Further, the comment pattern of the user U4 is as follows: there is an AN comment for the content C21, there is no comment for the content C22, there is a BN comment for the content C23, there is an AP comment for the content C24, and there is a comment for the content C25. It is none.

The information processing server 10 can determine the comment pattern of each user by using a comment attribute other than the subject and the polarity. FIG. 6 is a diagram showing another example of the determination result of the comment pattern. The comment pattern 2 shown in FIG. 6 is a comment pattern based on the presence / absence of a comment and the evaluation of the comment. In the example shown in FIG. 6, if the ratio of positive evaluation is 60% or more, it is marked with a circle, if the ratio of positive evaluation is lower than 60%, it is marked with a cross, and if there is no comment, it is marked with “-”. It has become. In the example of FIG. 6, the combination of the circle mark, the cross mark, and “−” is the comment pattern of each user.

The comment patterns shown in FIGS. 5 and 6 are merely examples. The comment pattern is not limited to the examples shown in FIGS. 5 and 6. For example, the comment pattern may be a comment pattern based on the presence or absence of a comment and the number of replies to the comment. Further, the expression format of the comment pattern is not limited to the examples shown in FIGS. 5 and 6. For example, the comment pattern may be a vector representation (for example, a real number vector having 10 or more dimensions). The expression format of the comment pattern is arbitrary.

After the determination of the comment pattern is completed, the information processing server 10 identifies a user having a comment pattern similar to the comment pattern of the user U4 (predetermined user). For example, it is assumed that the information processing server 10 has acquired the comment pattern shown in FIG. In this case, the information processing server 10 identifies users whose comment patterns match, for example, based on the number of matches of the comment analysis results (AN, BN, AP, BP, CP, no comment, etc.) for each content. For example, the information processing server 10 determines the user having the largest number of matches in the comment analysis results as a user having a similar comment pattern. As described above, in the example of FIG. 5, the comment pattern of the user U4 has an AN comment for the content C21, no comment for the content C22, a BN comment for the content C23, and an AP for the content C24. There is a comment, and there is no comment for the content C25. In the example shown in FIG. 5, the analysis result of the four comments other than the content C25 of the user U1 matches the comment analysis result of the user U4. Each of the users U2 and U3 has only one comment analysis result that matches the comment analysis result of the user U4. Therefore, the information processing server 10 identifies that the user having a comment pattern similar to the comment pattern of the user U4 (predetermined user) is the user U1 (another user).

Further, it is assumed that the information processing server 10 has acquired the comment pattern 2 shown in FIG. In this case, the information processing server 10 identifies other users whose comment patterns match, for example, based on the number of matches of the comment analysis results (circle mark, cross mark, no comment, etc.) for each content. For example, the information processing server 10 determines the user having the largest number of matches in the comment analysis results as a user having a similar comment pattern. In the example shown in FIG. 6, the analysis result of the four comments other than the content C25 of the user U1 matches the comment analysis result of the user U4. The user U2 and U3 each have only one or two comment analysis results that match the comment analysis result of the user U4. Therefore, the information processing server 10 identifies that another user having a comment pattern similar to the comment pattern of the user U4 (predetermined user) is the user U1.

Then, the information processing server 10 generates recommended information for the user U4 (predetermined user) regarding the posting of the comment based on the comment history of the specified user (other user) (step S4). For example, the information processing server 10 generates information on the content not commented by the user U4 as the recommended information H1 among the contents commented by the specified user. For example, assume that the specified user is user U1. In this case, in the comment history shown in FIG. 1, the content that the user U1 has commented on and that the user U4 has not commented on is the content C25. Therefore, the information processing server 10 generates the information of the content C25 as the recommended information H1. The information processing server 10 may include information on a plurality of contents in the recommended information H1.

When the generation of the display information is completed, the information processing server 10 transmits the content including the recommended information to the terminal device 100 (step S5). FIG. 7 is a diagram showing how the content C14 including the recommended information H1 is displayed on the terminal device 100. For example, it is assumed that the content C13 in which the headlines of the articles are listed is displayed on the screen of the terminal device 100 as shown in the state D21 of FIG. Each headline listed in the content C13 has a link to the article. When the user taps the heading M1, the terminal device 100 transmits the distribution of the content corresponding to the heading M1 to the information processing server 10. Upon receiving the distribution request, the information processing server 10 transmits the content C14 including the recommended information H1 to the terminal device 100 as shown in the state D22 of FIG. In the example of the state D22 of FIG. 7, the information processing server 10 transmits information indicating that the recommended article is the content C25 as the recommended information H1.

In the example of the state D22 in FIG. 7, a button B3 for posting a comment to the recommended information H1 is arranged. When the user presses the button B3, the terminal device 100 requests the information processing server 10 to deliver the content for posting the comment. When the information processing server 10 receives the distribution request, the information processing server 10 transmits the content for posting a comment to the terminal device 100, for example, as shown in the state D12 of FIG.

According to the present embodiment, the information processing server 10 generates recommended information for a predetermined user based on the comment history of users having similar comment patterns. Content that is commented by another user with a similar comment pattern is likely to be content that the user wants to comment on. Therefore, the information processing server 10 can allow many users to post comments.

[2. Information processing system configuration example]
The operation of the information processing system 1 of the present embodiment has been described above, but the configuration of the information processing system 1 including the information processing server 10 which is an example of the information processing apparatus of the present embodiment will be described below. As described above, the information processing system 1 includes a terminal device 100 and an information processing server 10.

[2-1. Information processing server configuration example]
The information processing server 10 is a server host computer (hereinafter, simply referred to as “server”) that processes a request from a client computer such as a terminal device 100. The information processing server 10 may be a PC server, a midrange server, or a mainframe server. Further, the information processing server 10 may be configured by one server or may be configured by a plurality of servers that perform processing in cooperation with each other. When the information processing server 10 is composed of a plurality of servers, the installation locations of these servers may be separated. Even if the installation locations are far apart, these servers can be regarded as one information processing device (information processing server) if the processes are executed in cooperation with each other.

As described above, the information processing server 10 is connected to the terminal device 100 via a network. The network is a communication network such as LAN (Local Area Network), WAN (Wide Area Network), telephone network (mobile telephone network, fixed telephone network, etc.), regional IP (Internet Protocol) network, and the Internet. The network may include a wired network or may include a wireless network.

FIG. 8 is a diagram showing a configuration example of the information processing server 10 according to the embodiment. The information processing server 10 includes a communication unit 11, a storage unit 12, and a control unit 13. The configuration shown in FIG. 8 is a functional configuration, and the hardware configuration may be different from this.

The communication unit 11 is a communication interface that communicates with an external device. The communication unit 11 may be a network interface or a device connection interface. For example, the communication unit 11 may be a LAN interface such as a NIC (Network Interface Card), or may be a USB interface composed of a USB (Universal Serial Bus) host controller, a USB port, or the like. Further, the communication unit 11 may be a wired interface or a wireless interface. The communication unit 11 functions as a communication means of the information processing server 10. The communication unit 11 communicates with the terminal device 100 according to the control of the control unit 13.

The storage unit 12 is a storage device capable of reading and writing data such as a DRAM (Dynamic Random Access Memory), a SRAM (Static Random Access Memory), a flash memory, and a hard disk. The storage unit 12 functions as a storage means for the information processing server 10. The storage unit 12 stores the comment history database 121, the comment attribute information database 122, and the comment pattern database 123.

The comment history of each of the plurality of users for the plurality of contents is registered in the comment history database 121. The comment history database 121 is the same as the comment history database shown in FIG.

The attribute information of each comment is registered in the comment attribute information database 122. The information stored in the comment attribute information database 122 is the same as the comment history shown in FIG.

The comment pattern determination result of each of the plurality of users is registered in the comment pattern database 123. The information stored in the comment pattern database 123 is the same as the comment pattern shown in FIG. 5 or FIG.

Returning to FIG. 8, the control unit 13 is a controller, and is stored in a storage device inside the information processing server 10 by a processor such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). It is realized by executing various programs with the RAM or the like as a work area. Further, the control unit 13 is a controller, and may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 8, the control unit 13 includes an acquisition unit 131, a discrimination unit 132, a specific unit 133, a generation unit 134, and a transmission unit 135. The blocks (acquisition unit 131 to transmission unit 135) constituting the control unit 13 are functional blocks indicating the functions of the control unit 13, respectively. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be one software module realized by software (including a microprogram), or may be one circuit block on a semiconductor chip (die). Of course, each functional block may be one processor or one integrated circuit. The method of configuring the functional block is arbitrary. The control unit 13 may be configured in a functional unit different from the above-mentioned functional block.

The acquisition unit 131 acquires the comment history of each of the plurality of users for the plurality of contents. For example, the acquisition unit 131 acquires information indicating the presence or absence of comments for each content of the user as the comment history of the user. Note that a plurality of contents may be classified into a plurality of clusters. At this time, the acquisition unit 131 may acquire information indicating the presence or absence of comments for each cluster of the user as the comment history of the user.

Further, the acquisition unit 131 acquires information indicating whether the content of the comment is positive or negative as the comment attribute of the comment.

Further, the acquisition unit 131 acquires information indicating the number of replies to the comment as the comment attribute of the comment.

Further, the acquisition unit 131 acquires the evaluation information for the comment as the comment attribute of the comment.

In addition, it is possible to attach multiple evaluations consisting of either positive evaluations or negative evaluations to comments. Then, the acquisition unit 131 acquires a value calculated based on the number of positive evaluations and the number of negative evaluations attached to the comment as the comment attribute of the comment.

The acquisition unit 131 acquires the content attributes of each of the plurality of contents. For example, suppose the content is an article. At this time, the acquisition unit 131 may acquire information indicating whether the content of the article is positive or negative as the content attribute of the article.

In addition, the content may be an article. At this time, the acquisition unit 131 may acquire information indicating whether the content of the comment is positive or negative as the comment attribute of the comment, and also acquire information indicating whether the content of the article is positive or negative. good.

The determination unit 132 determines the comment pattern of each of the plurality of users based on the comment history and the comment attributes of the plurality of comments specified in the comment history. The determination unit 132 determines the comment pattern of each of the plurality of users based on the comment history and the information indicating whether the content of the comment is positive or negative.

In addition, the content may be an article. At this time, the determination unit 132 has the first case in which each of the plurality of comments is either a positive content comment for an article with negative content or a negative content comment for an article with positive content. And the second case, which is either a negative content comment for an article with negative content or a positive content comment for an article with positive content. The comment pattern may be discriminated based on the discriminant result and the comment history.

The specific unit 133 identifies another user who has a comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and which has a comment pattern similar to the comment pattern of a predetermined user. ..

Further, the specifying unit 133 identifies another user having a comment pattern similar to the comment pattern of a predetermined user specified based on the comment history, the comment attribute, and the content attribute.

The generation unit 134 generates information on the content not commented by the predetermined user among the contents commented by the other user specified by the specific unit 133 as recommended information.

The transmission unit 135 transmits predetermined content including recommended information to the terminal device 100.

[2-2. Configuration example of terminal device]
Next, the configuration of the terminal device 100 will be described. The terminal device 100 is an information display device used by the user to browse the contents. The terminal device 100 is, for example, a communication terminal such as a smartphone, a tablet, or a mobile phone. As long as it has a communication function, the terminal device 100 may be an information processing terminal such as a personal computer (notebook PC, desktop PC) or a PDA (Personal Digital Assistant). In this case, the information processing terminal is also a kind of communication terminal. The terminal device 100 connects to the information processing server 10 via a network.

FIG. 9 is a diagram showing a configuration example of the terminal device 100 according to the embodiment. The terminal device 100 includes a communication unit 110, an input unit 120, a storage unit 130, an output unit 140, and a control unit 150. The configuration shown in FIG. 9 is a functional configuration, and the hardware configuration may be different from this.

The communication unit 110 is a communication interface that communicates with an external device. The communication unit 110 may be a network interface or a device connection interface. For example, the communication unit 110 may be a LAN interface such as a NIC, or may be a USB interface composed of a USB host controller, a USB port, or the like. Further, the communication unit 110 may be a wired interface or a wireless interface. The communication unit 110 functions as a communication means of the terminal device 100. The communication unit 110 communicates with the information processing server 10 according to the control of the control unit 150.

The input unit 120 is an input device that receives various inputs from the outside. For example, the input unit 120 is an operation device for the user to perform various operations such as a keyboard, a mouse, and operation keys. The input unit 120 functions as an input means of the terminal device 100. When a touch panel is adopted for the terminal device 100, the touch panel is also included in the input unit 120. In this case, the user performs various operations by touching the screen with a finger or a stylus.

The storage unit 130 is a data-readable / writable storage device such as a DRAM (Dynamic Random Access Memory), a SRAM (Static Random Access Memory), a flash memory, and a hard disk. The storage unit 130 functions as a storage means for the terminal device 100. The storage unit 130 stores application data. The application data may be web browser data.

The output unit 140 is a device that outputs various outputs such as sound, light, vibration, and an image to the outside. The output unit 140 functions as an output means of the terminal device 100. The output unit 140 includes a display device that displays various types of information. The display device is, for example, a liquid crystal display or an organic EL (Electro Luminescence) display. When a touch panel is adopted for the terminal device 100, the display device (hereinafter referred to as a screen) may be integrated with the input unit 120. The output unit 140 displays an image on the screen according to the control of the control unit 150.

The control unit 150 is a controller, and is realized by, for example, using a processor such as a CPU or MPU to execute various programs stored in a storage device inside the terminal device 100 using RAM or the like as a work area. Further, the control unit 150 is a controller, and may be realized by an integrated circuit such as an ASIC or FPGA.

As shown in FIG. 9, the control unit 150 includes a display unit 151 and a display control unit 152. The blocks (display unit 151 and display control unit 152) constituting the control unit 150 are functional blocks indicating the functions of the control unit 150, respectively. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be one software module realized by software (including a microprogram), or may be one circuit block on a semiconductor chip (die). Of course, each functional block may be one processor or one integrated circuit. The method of configuring the functional block is arbitrary. The control unit 150 may be configured in a functional unit different from the above-mentioned functional block.

The display unit 151 displays a predetermined content (for example, the content C14 shown in FIG. 7) transmitted from the information processing server 10 on the screen.

The display control unit 152 changes the display mode of the predetermined content displayed on the screen according to the control information transmitted from the information processing server 10.

[3. Information processing server processing flow]
Next, the procedure of the process executed by the information processing server 10 will be described. FIG. 10 is a flowchart showing an example of information transmission processing.

First, the information processing server 10 determines whether or not a distribution request for content (for example, predetermined content including content C21) has been received from the terminal device 100 operated by the user (step S11). If the delivery request has not been received (step S11: No), the information processing server 10 repeats step S11 until the delivery request is received.

When the distribution request is received (step S11: Yes), the information processing server 10 acquires the comment history of a plurality of users including the comment history of the user who made the distribution request from the comment history database 121 (step S12). Then, the information processing server 10 acquires the comment attribute of each of the plurality of comments specified in the comment history (step S13). For example, the information processing server 10 acquires information indicating whether the content of the comment is positive or negative as the comment attribute of the comment.

Subsequently, the information processing server 10 determines the comment pattern of each of the plurality of users based on the comment history and the comment attribute (step S14). Then, the information processing server 10 identifies another user having a comment pattern similar to the comment pattern of the user who made the delivery request (step S15).

Then, the information processing server 10 generates recommended information for the user who made the delivery request based on the comment history of the other user specified in step S15 (step S16). The recommended information is information regarding posting of comments, and is, for example, recommended information H1 shown in FIG. 7.

Subsequently, the information processing server 10 generates predetermined content (for example, the content C14 shown in FIG. 9) including the recommended information acquired in step S16 (step S17). Then, the information processing server 10 transmits the generated content to the terminal device 100 (step S18).

When the transmission is completed, the information processing server 10 returns to step S11 and waits until the content distribution request is received from the terminal device 100.

[4. Modification example]
The above embodiment shows an example, and various modifications and applications are possible.

For example, in the above-described embodiment, the information processing server 10 has acquired information indicating the presence or absence of comments for each content as the comment history of the user. However, the comment history is not limited to the comment history for each content. For example, a plurality of contents may be classified into a plurality of clusters (for example, a plurality of categories such as automobiles, home appliances, fashion, etc.). Then, the information processing server 10 may acquire information indicating the presence or absence of comments for each cluster of users as the comment history of the user. The cluster is not limited to the category. For example, if the content is an article, the information processing server 10 identifies the subject (for example, a celebrity) targeted by the article for each of the plurality of articles, and classifies the plurality of articles into clusters for each subject. May be good. Further, the information processing server 10 may specify an event (for example, a parliamentary election) targeted by an article for each of the plurality of articles, and classify the plurality of articles into clusters for each event. Further, the information processing server 10 may specify an article distribution subject (for example, a newspaper company) for each of the plurality of articles, and classify the plurality of articles into clusters for each distribution subject.

FIG. 11 is a diagram showing an example of a comment history stored in the comment history database. The comment history 2 shown in FIG. 11 is a history of comments made by users U1 to U4 with respect to the clusters G1 to G5. Each cluster has multiple contents associated with it. In the example shown in FIG. 11, when the corresponding user makes a comment on a predetermined number of contents among a plurality of contents associated with a predetermined cluster, the item of the predetermined cluster of the corresponding user is marked with a circle. Attached. For example, in the case of the comment history 2 shown in FIG. 11, the user U1 makes a comment on a predetermined number of contents among a plurality of contents associated with each of the clusters G1, G3, G4, and G5. However, the user U1 has commented less than a predetermined number on the cluster G2.

The information processing server 10 determines the comment pattern of each user based on the information indicating the presence or absence of comments for each cluster and the comment attributes of each of the plurality of comments belonging to each cluster. FIG. 12 is a diagram showing an example of the determination result of the comment pattern. The comment pattern 3 shown in FIG. 12 is a comment pattern based on the presence / absence of comments for each cluster and the polarity of comments for each cluster. In the figure, "N" indicates that a plurality of comments belonging to the cluster are negative. Further, "P" indicates that a plurality of comments belonging to the cluster are positive. The information processing server 10 determines, for example, the polarity of each of the plurality of comments belonging to the cluster, and if there are many negative comments, the information processing server 10 determines that the plurality of comments belonging to the cluster are negative, and positive comments. If there are many comments, it is determined that multiple comments belonging to the corresponding cluster are positive.

Then, the information processing server 10 identifies another user having a comment pattern similar to the comment pattern of the predetermined user based on the determined comment pattern. In the example shown in FIG. 12, the analysis result of the user U1 is the same as the analysis result of the user U4 in four clusters other than the cluster G5. The analysis results of the users U2 and U3 are only one or two clusters, respectively, and the analysis results match the analysis results of the user U4. Therefore, the information processing server 10 identifies that another user having a comment pattern similar to the comment pattern of the user U4 (predetermined user) is the user U1.

Further, in the above-described embodiment, the information processing server 10 acquires the comment attribute of each of the plurality of comments, but the information processing server 10 may acquire the content attribute of each of the plurality of contents. For example, assuming that the content is an article, the information processing server 10 acquires, for example, information indicating whether the content of the article is positive or negative as the content attribute of the article. Then, the information processing server 10 determines the comment pattern of each of the plurality of users based on the comment history, the comment attribute, and the content attribute. As a result, the information processing server 10 has, for example, a user with a first comment pattern that tends to make a negative comment on the content with a positive content and a positive comment on the content with a positive content. For users with a second comment pattern that tends to make comments, users with a third comment pattern that tends to make negative comments for content with negative content, and content with negative content It is possible to distinguish from the user of the fourth comment pattern, which tends to make a positive comment.

The comment pattern is not limited to the above four patterns. The information processing server 10 determines a more detailed comment pattern by adding elements other than the comment history and comment attributes, such as the subject targeted by the article, the event targeted by the article, and the distribution subject of the article. May be good. FIG. 13 is a diagram showing another example of the determination result of the comment pattern. The information processing server 10 determines the comment pattern as follows, for example.

For example, assuming that the content is an article, first, the information processing server 10 classifies a plurality of comments into a plurality of clusters. At this time, the cluster may be classified based on the subject targeted by the article, the event targeted by the article, the distribution subject of the article, and the like. Then, the information processing server 10 determines which of the cases K1 to K4 corresponds to each of the plurality of users for each cluster. For example, the information processing server 10 determines which of the cases K1 to K4 corresponds to each of the plurality of comments belonging to the cluster, and determines which of the cases K1 to K4 is the most common as the case in the corresponding cluster.

In addition, case K1 shows a negative comment for an article with positive content, case K2 shows a positive comment for content with positive content, and case K3 shows a positive comment for content with negative content. Negative comments are shown, and Case K4 shows positive comments for content with negative content. In the comment pattern 4 shown in FIG. 13, it can be seen that the user U1 corresponds to the case K1 in the cluster G1. Assuming that the cluster G1 is a cluster of articles related to the subject A, in this example, it can be seen that the user U1 tends to make a negative comment for an article that is positive to the subject A.

Then, the information processing server 10 determines the combinations of cases K1 to K4 and no comment for each cluster as the comment pattern of each user. Then, the information processing server 10 identifies another user having a comment pattern similar to the comment pattern of the predetermined user based on the determined comment pattern. In the example shown in FIG. 13, the user U1 has four clusters other than the cluster G5, and the case matches the case of the user U4. Users U2 and U3 only match the case of user U4 in one or two clusters, respectively. Therefore, the information processing server 10 identifies that another user having a comment pattern similar to the comment pattern of the user U4 (predetermined user) is the user U1.

It can be said that a user who makes a positive comment on an article with negative content and a user who makes a negative comment on an article with positive content tend to have the same comment tendency. For example, a user who makes a positive comment on an article with negative content to subject A and a user who makes a negative comment on an article with positive content to subject A , Both are negative to the subject A. In addition, it can be said that a user who makes a positive comment on an article with a positive content and a user who makes a negative comment on an article with a negative content tend to have the same comment tendency. For example, a user who makes a positive comment on an article with a positive content to the subject A and a user who makes a negative comment on an article with a negative content to the subject A , Both are positive for the subject A.

Therefore, in the information processing server 10, the first case, in which each of the plurality of comments is either a positive content comment for an article with negative content or a negative content comment for an article with positive content. Either (Case L1) or the second case (Case L2), which is either a negative content comment for an article with negative content or a positive content comment for an article with positive content. It may be determined whether it corresponds to. Then, the information processing server 10 may discriminate the comment pattern of each of the plurality of users based on the discrimination result and the comment history. FIG. 14 is a diagram showing another example of the determination result of the comment pattern. In the comment pattern 5 shown in FIG. 14, the case K1 and the case K4 shown in FIG. 13 are replaced by the case L1, and the case K2 and the case K3 shown in FIG. 13 are replaced by the case L2.

Then, the information processing server 10 determines the combinations of cases L1 and L2 for each cluster and no comment as the comment pattern of each user. Then, the information processing server 10 identifies another user having a comment pattern similar to the comment pattern of the predetermined user based on the determined comment pattern. In the example shown in FIG. 14, the user U1 has four clusters other than the cluster G5, and the case matches the case of the user U4. Users U2 and U3 only match the case of user U4 in one or two clusters, respectively. Therefore, the information processing server 10 identifies that another user having a comment pattern similar to the comment pattern of the user U4 (predetermined user) is the user U1.

The control device for controlling the information processing server 10 of the present embodiment may be realized by a dedicated computer system or a normal computer system. For example, a program or data (for example, model M) for performing the above operation is stored and distributed in a computer-readable recording medium such as an optical disk, a semiconductor memory, a magnetic tape, or a flexible disk, and the program or data is distributed. May be configured in the control device by installing on a computer and performing the above-mentioned processing. The control device may be an external device (for example, a personal computer) of the information processing server 10 or an internal device (for example, a control unit 13). Further, the above program may be stored in a disk device provided in a server device on a network such as the Internet so that it can be downloaded to a computer or the like. Further, the above-mentioned functions may be realized by the collaboration between the OS (Operating System) and the application software. In this case, the part other than the OS may be stored in a medium and distributed, or the part other than the OS may be stored in the server device so that it can be downloaded to a computer or the like.

Further, among the processes described in each of the above embodiments, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed. It is also possible to automatically perform all or part of the above by a known method. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown in the figure.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in any unit according to various loads and usage conditions. Can be integrated and configured.

In addition, the above-described embodiments can be appropriately combined as long as the processing contents do not contradict each other.

[5. Hardware configuration]
The information processing server 10 according to the embodiment and the modification can also be realized by, for example, a computer 1000 having a configuration as shown in FIG. FIG. 15 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing server 10. The computer 1000 includes a CPU (Central Processing Unit) 1100, a RAM 1200, a ROM 1300, an HDD (Hard Disk Drive) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F). ) Has 1700.

The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, a program depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 receives data from another device via the network N and sends it to the CPU 1100, and transmits the data generated by the CPU 1100 to the other device via the network N.

The CPU 1100 controls an output device such as a display or a printer, and an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

For example, when the computer 1000 functions as the information processing server 10 according to the embodiment, the CPU 1100 of the computer 1000 is controlled by executing a process based on a program or data (for example, model M) loaded on the RAM 1200. The unit 13 is realized. The CPU 1100 of the computer 1000 reads and executes these programs or data (eg, model M) from the recording medium 1800, but as another example, these programs or data (eg, from another device) via network N. Model M) may be acquired.

Although some of the embodiments of the present application have been described in detail with reference to the drawings, these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure line of the invention. It is possible to carry out the present invention in other modified forms.

[6. effect〕
According to the present embodiment, the information processing server 10 acquires the comment history of each of the plurality of users for the plurality of contents. Then, the information processing server 10 uses a comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and has a comment pattern similar to the comment pattern of a predetermined user. Identify. Then, the information processing server 10 generates recommended information for a predetermined user regarding posting of a comment based on the comment history of the specified user. As a result, the information processing server 10 can generate highly accurate recommended information using the history of similar users, so that it is possible to promote the posting of comments by many users.

The information processing server 10 acquires information indicating whether the content of the comment is positive or negative as the comment attribute of the comment. The polarity of the comments is a good indication of the user's tendency. Therefore, the information processing server 10 can generate more accurate recommended information, and can promote the posting of comments by many users.

The information processing server 10 acquires information indicating the number of replies to a comment as a comment attribute of the comment. Comments made with a light feeling are not often replied to, and comments made seriously are often replied to. Therefore, the number of replies to a comment is a good indication of the quality of the comment, and thus the user's interest in the content being commented on. Therefore, the information processing server 10 can generate more accurate recommended information, and can promote the posting of comments by many users.

The information processing server 10 acquires evaluation information for a comment as a comment attribute of the comment. Comments made with a light feeling are not highly evaluated, and comments made seriously are highly evaluated. Therefore, the rating of a comment is a good indication of the quality of the comment, and thus the user's interest in the content being commented on. Therefore, the information processing server 10 can generate more accurate recommended information, and can promote the posting of comments by many users.

A comment can be accompanied by multiple evaluations consisting of either a positive evaluation or a negative evaluation. Then, the information processing server 10 acquires a value calculated based on the number of positive evaluations and the number of negative evaluations attached to the comment as the comment attribute of the comment. As a result, the information processing server 10 can generate more accurate recommended information, so that it is possible to promote the posting of comments by many users.

The information processing server 10 acquires information indicating the presence or absence of comments for each content of the user as the comment history of the user. As a result, the information processing server 10 can accurately determine the comment pattern, so that it is possible to promote the posting of comments by many users.

Multiple contents are classified into multiple clusters. The information processing server 10 acquires information indicating the presence or absence of comments for each cluster of users as the comment history of the user. As a result, the information processing server 10 can determine the comment pattern more accurately, so that it is possible to promote the posting of comments by many users.

The information processing server 10 acquires the content attributes of each of the plurality of contents. Then, the information processing server 10 identifies a user having a comment pattern similar to the comment pattern of a predetermined user determined based on the comment history, the comment attribute, and the content attribute. As a result, the information processing server 10 can determine the comment pattern more accurately, so that it is possible to promote the posting of comments by many users.

The content is an article. The information processing server 10 acquires information indicating whether the content of the article is positive or negative as the content attribute of the article. As a result, the information processing server 10 can determine the comment pattern more accurately, so that it is possible to promote the posting of comments by many users.

The information processing server 10 determines the comment pattern of each of the plurality of users based on the comment history and the comment attributes of the plurality of comments specified in the comment history. Then, the content is an article, and the information processing server 10 acquires information indicating whether the content of the comment is positive or negative as a comment attribute of the comment, and indicates whether the content of the article is positive or negative. Get information. The information processing server 10 has a first case in which each of the plurality of comments is either a positive content comment for an article with negative content or a negative content comment for an article with positive content. And the second case, which is either a negative content comment for an article with negative content or a positive content comment for an article with positive content. The comment pattern is discriminated based on the discrimination result and the comment history. As a result, the information processing server 10 can determine the comment pattern more accurately, so that it is possible to promote the posting of comments by many users.

The information processing server 10 generates information on the content not commented by the predetermined user among the contents commented by the specified user as recommended information. As a result, the information processing server 10 can generate highly accurate recommended information, so that it is possible to promote the posting of comments by many users.

Although some of the embodiments of the present application have been described in detail with reference to the drawings, these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure column of the invention. It is possible to carry out the present invention in other modified forms.

Further, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the specific unit can be read as a specific means or a specific circuit.

1 ... Information processing system 10 ... Information processing server 11, 110 ... Communication unit 12, 130 ... Storage unit 121 ... Comment history database 122 ... Comment attribute information database 123 ... Comment pattern database 13, 150 ... Control unit 131 ... Acquisition unit 132 ... Discrimination unit 133 ... Specific unit 134 ... Generation unit 135 ... Transmission unit 100 ... Terminal device 120 ... Input unit 140 ... Output unit 151 ... Display unit 152 ... Display control unit C11 to C14, C21, C25 ... Content T11, T31, T41 ... Comment B1, B21, B22, B3 ... Button H1 ... Recommended information

Claims (12)

An acquisition unit that acquires the comment history of each of multiple users for multiple contents,
A comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and a specific unit that identifies a user having a comment pattern similar to the comment pattern of a predetermined user. ,
A generation unit that generates recommended information for the predetermined user regarding posting of comments based on the comment history of the user specified by the specific unit is provided.
The acquisition unit acquires information indicating whether the content of the content is positive or negative as the content attribute of each of the plurality of contents.
The specific unit identifies a user having the comment pattern similar to the comment pattern of the predetermined user determined based on the comment history, the comment attribute, and the content attribute.
The generation unit generates information on the content not commented by the predetermined user among the contents commented by the user specified by the specific unit as the recommended information.
The content is an article,
An information processing device characterized by this. An acquisition unit that acquires the comment history of each of multiple users for multiple contents,
A comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and a specific unit that identifies a user having a comment pattern similar to the comment pattern of a predetermined user. ,
A generation unit that generates recommended information for the predetermined user regarding posting of comments based on the comment history of the user specified by the specific unit, and a generation unit.
A discriminant unit for discriminating a comment pattern for each of the plurality of users based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history is provided.
The acquisition unit acquires information indicating whether the content of the comment is positive or negative as the comment attribute of the comment, and acquires information indicating whether the content of the content is positive or negative.
The discriminating unit includes a first case in which each of the plurality of comments is either a positive content comment for a negative content content or a negative content comment for a positive content content. It is determined whether it corresponds to the second case, which is either a negative content comment for the negative content content or a positive content comment for the positive content content, and the determination is made. The comment pattern is discriminated based on the result and the comment history.
The generation unit generates information on the content not commented by the predetermined user among the contents commented by the user specified by the specific unit as the recommended information.
The content is an article,
An information processing device characterized by this. The acquisition unit acquires information indicating whether the content of the comment is positive or negative as the comment attribute of the comment.
The information processing apparatus according to claim 1. The acquisition unit acquires information indicating the number of replies to the comment as the comment attribute of the comment.
The information processing apparatus according to claim 1. The acquisition unit acquires evaluation information for the comment as the comment attribute of the comment.
The information processing apparatus according to claim 1. It is possible to attach multiple evaluations consisting of either positive evaluations or negative evaluations to the comments.
The acquisition unit acquires a value calculated based on the number of positive evaluations and the number of negative evaluations attached to the comment as the comment attribute of the comment.
The information processing apparatus according to claim 1. The acquisition unit acquires information indicating the presence or absence of comments for each content of the user as the comment history of the user.
The information processing apparatus according to claim 1, 3 , 4 , 5 or 6 . The plurality of contents are classified into a plurality of clusters, and the plurality of contents are classified into a plurality of clusters.
The acquisition unit acquires information indicating the presence or absence of comments for each cluster of the user as the comment history of the user.
The information processing apparatus according to claim 1, 3 , 4 , 5 or 6 . It is an information processing method executed by an information processing device.
The acquisition process to acquire the comment history of each of multiple users for multiple contents,
A specific step of identifying a user having a comment pattern similar to the comment pattern of a predetermined user, which is a comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history. ,
A generation step of generating recommended information to the predetermined user regarding posting of a comment based on the comment history of the user specified in the specific step is included.
In the acquisition step, information indicating whether the content of the content is positive or negative is acquired as the content attribute of each of the plurality of contents.
In the specific step, a user having the comment pattern similar to the comment pattern of the predetermined user determined based on the comment history, the comment attribute, and the content attribute is specified.
In the generation step, among the contents commented by the user specified in the specific step, the information of the content not commented by the predetermined user is generated as the recommended information.
The content is an article,
An information processing method characterized by that. It is an information processing method executed by an information processing device.
The acquisition process to acquire the comment history of each of multiple users for multiple contents,
A specific step of identifying a user having a comment pattern similar to the comment pattern of a predetermined user, which is a comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history. ,
A generation step of generating recommended information to the predetermined user regarding posting of a comment based on the comment history of the user specified in the specific step, and a generation step.
A determination step for determining a comment pattern for each of the plurality of users based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history is included.
In the acquisition step, information indicating whether the content of the comment is positive or negative is acquired as the comment attribute of the comment, and information indicating whether the content of the content is positive or negative is acquired.
In the determination step, the first case in which each of the plurality of comments is either a positive content comment for a negative content content or a negative content comment for a positive content content, and the first case. It is determined whether it corresponds to the second case, which is either a negative content comment for the negative content content or a positive content comment for the positive content content, and the determination is made. The comment pattern is discriminated based on the result and the comment history.
In the generation step, among the contents commented by the user specified in the specific step, the information of the content not commented by the predetermined user is generated as the recommended information.
The content is an article,
An information processing method characterized by that. The acquisition procedure to acquire the comment history of each of multiple users for multiple contents, and
A comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and a specific procedure for identifying a user having a comment pattern similar to the comment pattern of a predetermined user. ,
A computer is made to execute a generation procedure for generating recommended information for the predetermined user regarding posting of a comment based on the comment history of the user specified in the specific procedure.
In the acquisition procedure, information indicating whether the content of the content is positive or negative is acquired as the content attribute of each of the plurality of contents.
In the specific procedure, a user having the comment pattern similar to the comment pattern of the predetermined user determined based on the comment history, the comment attribute, and the content attribute is specified.
In the generation procedure, among the contents commented by the user specified in the specific procedure, the information of the content not commented by the predetermined user is generated as the recommended information.
The content is an article,
An information processing program characterized by this. The acquisition procedure to acquire the comment history of each of multiple users for multiple contents, and
A comment pattern based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history, and a specific procedure for identifying a user having a comment pattern similar to the comment pattern of a predetermined user. ,
A generation procedure for generating recommended information for the predetermined user regarding posting of a comment based on the comment history of the user specified in the specific procedure, and a generation procedure.
A computer is made to execute a determination procedure for determining a comment pattern for each of the plurality of users based on the comment history and the comment attributes of each of the plurality of comments specified in the comment history.
In the acquisition procedure, information indicating whether the content of the comment is positive or negative is acquired as the comment attribute of the comment, and information indicating whether the content of the content is positive or negative is acquired.
In the determination procedure, the first case, in which each of the plurality of comments is either a positive content comment for a negative content content or a negative content comment for a positive content content, and the first case. It is determined whether it corresponds to the second case, which is either a negative content comment for the negative content content or a positive content comment for the positive content content, and the determination is made. The comment pattern is discriminated based on the result and the comment history.
In the generation procedure, among the contents commented by the user specified in the specific procedure, the information of the content not commented by the predetermined user is generated as the recommended information.
The content is an article,
An information processing program characterized by this.

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