Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method, and an information processing program, which enable more appropriate delivery of content to users.SOLUTION: An information processing device disclosed herein comprises an identification unit and a determination unit. The identification unit identifies an appearance target indicated by a delivery content to be delivered. The determination unit determines the level of priority in delivering the delivery content to a user on the basis of a result of comparison between interest information of the user to be delivered with the delivery content and interest information of the appearance target.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] 2. Description of the Related Art Conventionally, there is a technique for distributing content such as videos and news articles to users via a network (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6048977 Summary of the Invention [Problem to be solved by the invention]

[0004] However, conventional techniques leave room for further improvement in terms of more appropriately delivering content to users.

[0005] The present application has been made in consideration of the above, and has an object to provide an information processing device, an information processing method, and an information processing program that can more appropriately deliver content to users. [Means for solving the problem]

[0006] The information processing device according to the present application includes an identification unit and a determination unit. The identification unit identifies a subject indicated by a content to be distributed. The determination unit determines a priority for distributing the content to the user based on a comparison result between interest information of the user who is a destination of the content and interest information of the subject. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to provide an effect that content can be more appropriately delivered to users. [Brief description of the drawings]

[0008] [Figure 1A] FIG. 1A is a diagram showing a first process executed by an information processing device according to an embodiment. [Figure 1B] FIG. 1B is a diagram showing a second process executed by the information processing device according to the embodiment. [Figure 1C] FIG. 1C is a diagram showing a third process executed by the information processing device according to the embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of user information. [Diagram 5] FIG. 5 is a diagram showing an example of content information. [Figure 6] FIG. 6 is a flowchart showing the processing procedure of the first information process executed by the information processing device according to the embodiment. [Figure 7] FIG. 7 is a flowchart showing the processing procedure of the second information process executed by the information processing device according to the embodiment. [Figure 8] FIG. 8 is a flowchart showing the processing procedure of the third information process executed by the information processing device according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the information processing device, the information processing method, and the information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to the embodiments. In addition, the same parts in the following embodiments are given the same reference numerals, and duplicated descriptions are omitted.

[0010] (Embodiment) First, the process executed by the information processing device according to the embodiment will be described with reference to Figs. 1A to 1C. Figs. 1A to 1C are diagrams showing processes 1 to 3 executed by the information processing device according to the embodiment. Figs. 1A to 1C show an operation example of an information processing system S including an information processing device 1 according to the embodiment.

[0011] First, information processing part 1 in Fig. 1A will be described. As shown in Fig. 1A, an information processing system S according to an embodiment includes an information processing device 1, a user terminal 100, and a requesting terminal 200. The user terminal 100 is a terminal device carried by a user who browses the delivery content delivered from the information processing device 1. The requesting terminal 200 is a terminal device carried by a requesting user who requests the delivery of content.

[0012] In information processing 1, the information processing system S of the embodiment determines the priority of the distribution content based on the results of a comparison between the interest information (in tag cloud format) of the characters (an example of a target) shown in the distribution content such as a news article and the interest information of the user.

[0013] Specifically, first, the information processing device 1 accepts a registration request for distribution content from a requesting user via the request source terminal 200 (step S1). The distribution content is content to be distributed to a user, such as news articles and video images. The distribution content may also be a product or service offered in an offering service such as a shopping service or an auction service.

[0014] Next, the information processing device 1 identifies the objects appearing in the distributed content (step S2). Specifically, the objects appearing in the news article are people, objects, regions, etc. that appear in the news article. For example, the information processing device 1 identifies the objects appearing by extracting keywords related to the objects appearing from the text in the news article. For example, the information processing device 1 identifies athletes, politicians, entertainers, etc. that appear in the news article as the objects appearing. For example, the information processing device 1 identifies buildings, land, cities, towns, villages, etc. that appear in the news article as the objects appearing. Note that the information processing device 1 may identify multiple objects appearing from one news article.

[0015] Next, the information processing device 1 estimates the interest information of the specified subject (step S3). Specifically, the information processing device 1 analyzes the contents of the news article to extract keywords related to the subject, and estimates a tag cloud (see FIG. 1A) that aggregates the keywords as interest information. The news article is not limited to the news article that was the source of the specification of the subject, but may be a past news article related to the subject. In addition, the information processing device 1 may extract keywords from, for example, the contents posted by the subject on SNS other than the news article. In addition, the information processing device 1 may extract keywords from the behavior information of the subject (search behavior, purchase behavior, etc.) only when permission is obtained from the specified subject. In addition, when the specified subject is real estate (building or land) or a region, the information processing device 1 may generate a tag cloud that aggregates tag clouds of people who have visited the real estate or region or people who live there. In addition, the information processing device 1 may generate a tag cloud that aggregates tag clouds of a group of users who have viewed the news article as the subject. Furthermore, when estimating the interest information, the information processing device 1 may use a learning model by a generation AI. For example, the information processing device 1 may estimate the interest information using a Large Language Model (LLM) that receives information on news articles and subjects as input (prompts) and outputs (generates) the interest information of the subjects.

[0016] In the example of Fig. 1A, the information processing device 1 generates a tag cloud that aggregates keywords displayed in a display mode according to the extraction status of the keyword. For example, in Fig. 1A, the more frequently a keyword is extracted, the larger the display size of the keyword becomes. In addition, the information processing device 1 may express related keywords by using the same color (or similar colors).

[0017] The display mode is not limited to the display size, but may be a display color, a line type (solid line, dashed line, etc.), etc. Furthermore, the information processing device 1 may change the display mode according to the attribute of the keyword (positive word or negative word), not limited to the frequency of extraction of the keyword.

[0018] Next, the information processing device 1 acquires user information of the user to whom the distribution content is to be distributed via the user terminal 100 (step S4). The user information includes user attribute information and information on behavior in various services (search behavior, purchasing behavior, posting behavior, etc.).

[0019] Next, the information processing device 1 estimates the user's interest information based on the acquired user information (step S5). Specifically, the information processing device 1 analyzes the contents of the user information to extract keywords in the user information, and estimates a tag cloud that aggregates the keywords as the interest information.

[0020] Next, the information processing device 1 compares the interest information of the user with that of the featured object (step S6). For example, the information processing device 1 compares the tag cloud of the user with that of the featured object. Specifically, the information processing device 1 calculates the degree of agreement between the tag cloud of the user and the tag cloud of the featured object. The degree of agreement may be limited to those tag clouds with the same keywords, or may include those with the same (or similar) meaning of keywords. Note that when there are multiple featured objects identified from the distributed content, the information processing device 1 calculates an absolute score indicating the degree of agreement, and calculates the sum of the scores of each featured object as the comparison result.

[0021] Next, the information processing device 1 determines the priority of the content to be distributed to the user based on the comparison result (step S7). For example, the information processing device 1 increases the priority of the content to be distributed that is linked to the subject that appears with a high degree of match (a large number of the same keywords). The information processing device 1 may also increase the priority of the content to be distributed when the specific keywords in the tag cloud are the same.

[0022] Next, the information processing device 1 distributes the distribution content to the user based on the determined priority (step S8). For example, when distributing a plurality of news articles in a list of headlines, the information processing device 1 displays and provides distribution content with a higher priority at the top of the list. The information processing device 1 also provides the news article with the highest priority as a recommended news article by emphasizing it. When the information processing device 1 displays the text of a news article, if the user hovers the mouse over the text of a featured subject, the information processing device 1 may display a tag cloud of the featured subject in a speech bubble or the like. At this time, the information processing device 1 may highlight keywords similar to keywords in the user's tag cloud.

[0023] In this way, the information processing device 1 of the embodiment can deliver distribution content to users more appropriately by preferentially displaying distribution content featuring subjects whose interests are similar to the user's interests.

[0024] Although the above describes an example of a news article displayed as text, the present invention can also be applied to a news video. In this case, the information processing device 1 can perform image analysis and audio analysis of the news video to identify subjects who appear in the video.

[0025] In addition to news, for example, manga content, anime content, drama content, movie content, television content, etc. may be used. In this case, the information processing device 1 specifies characters (including fictional characters) that appear in manga, anime, drama, movie, and television as featured targets. In addition, in dramas and movies, a tag cloud may be generated based on the roles of the characters that appear.

[0026] In such a case, when searching manga content, anime content, drama content, movie content, television content, etc., the information processing device 1 provides search results based on the degree of coincidence of the tag cloud. Also, the information processing device 1 can provide as search results manga that feature characters similar to fictional characters that appear in the manga, based on the tag cloud of the featured object. Also, when the featured object is an accommodation facility, the information processing device 1 may generate a tag cloud of people who have stayed at the accommodation facility, provide the tag cloud as the guest characteristics of the accommodation facility, or suggest accommodation facilities to users similar to the tag cloud.

[0027] Next, the second information processing will be described with reference to FIG. 1B.

[0028] In the second information processing, the information processing system S identifies related parties having a relationship with the distribution content, and determines the priority of the distribution content based on the results of comparing the related parties' interest information with the user's interest information.

[0029] Specifically, first, the information processing device 1 accepts a registration request for distribution content from a requesting user via the request source terminal 200 (step S1). The distribution content is content to be distributed to a user, such as news articles and video images. The distribution content may also be a product or service offered in an offering service such as a shopping service or an auction service.

[0030] Next, the information processing device 1 identifies related parties having a relationship with the distribution content (step S2). Specifically, the related parties are posters of comments on news articles, sellers on shopping sites or auction sites, reviewers, etc.

[0031] Next, the information processing device 1 estimates the interest information of the identified related person (step S3). Specifically, the information processing device 1 analyzes the posted contents of the related person and the contents of the listing information to extract keywords, and estimates a tag cloud (see FIG. 1A) that aggregates such keywords as the interest information.

[0032] Next, the information processing device 1 acquires user information of the user to whom the distribution content is to be distributed via the user terminal 100 (step S4). The user information includes user attribute information and information on behavior in various services (search behavior, purchasing behavior, posting behavior, etc.).

[0033] Next, the information processing device 1 estimates the user's interest information based on the acquired user information (step S5). Specifically, the information processing device 1 analyzes the contents of the user information to extract keywords in the user information, and estimates a tag cloud that aggregates the keywords as the interest information.

[0034] For example, the information processing device 1 may estimate the user's interest information for each domain accessed by the user. Specifically, the information processing device 1 estimates the user's interest information in a search service based on the search behavior performed by the user in the domain of the search service. The information processing device 1 also estimates the user's interest information in a shopping service or an auction service based on the behavior (search behavior, purchasing behavior, posting behavior, etc.) performed by the user in the domain of the shopping service or the auction service.

[0035] Next, the information processing device 1 compares the interest information of the user with that of the related party (step S6). For example, the information processing device 1 compares the tag cloud of the user with that of the related party. For example, the information processing device 1 compares the tag cloud of the user in a specific domain with the tag cloud of the related party of the distributed content in that domain. More specifically, the information processing device 1 compares the tag cloud of a seller who is a related party in the shopping service with the tag cloud of the user in the shopping service.

[0036] Next, the information processing device 1 determines the priority of the content to be distributed to the user based on the comparison result (step S7). For example, the information processing device 1 increases the priority of the content to be distributed associated with a person in a tag cloud that has many keywords similar to those shown in the user's tag cloud. The information processing device 1 also determines the priority of the content to be distributed in a specific domain based on the user's interest information in the specific domain.

[0037] Next, the information processing device 1 distributes the distribution content to the user based on the determined priority (step S8). For example, when distributing a plurality of news articles in a list of headlines, the information processing device 1 displays and provides the distribution content with a higher priority at the top of the list. The information processing device 1 also provides the news article with the highest priority as a recommended news article by emphasizing it. The information processing device 1 also preferentially distributes items of a seller in a shopping service or an auction service to a user whose tag cloud is similar to that of the seller. The information processing device 1 may also display only the ratings and comments of related parties (including commentators who made explanatory comments) who have rated or commented on purchased products or news articles in a shopping service, an auction service, or a news article to a user whose tag cloud is similar to that of the related party, or display them preferentially.

[0038] In this way, the information processing device 1 of the embodiment can deliver distribution content to users more appropriately by preferentially displaying distribution content related to people whose interests are similar to those of the user.

[0039] Next, the third information processing will be described with reference to FIG. 1C.

[0040] In the third information processing, the information processing system S determines interest information to be provided to the user from among interest information of related persons, based on context information based on sensor information of the user.

[0041] Specifically, first, the information processing device 1 accepts a registration request for distribution content from a requesting user via the request source terminal 200 (step S1). The distribution content is content to be distributed to a user, such as news articles and video images. The distribution content may also be a product or service offered in an offering service such as a shopping service or an auction service.

[0042] Next, the information processing device 1 identifies related parties having a relationship with the distribution content (step S2). Specifically, the related parties are posters of comments on news articles, sellers on shopping sites or auction sites, reviewers, etc.

[0043] Next, the information processing device 1 estimates the interest information of the identified related person (step S3). Specifically, the information processing device 1 analyzes the posted contents of the related person and the contents of the listing information to extract keywords, and estimates a tag cloud (see FIG. 1A) that aggregates such keywords as the interest information.

[0044] Next, the information processing device 1 acquires sensor information of the user to whom the distribution content is to be distributed via the user terminal 100 (step S4). The sensor information is, for example, location information acquired by a location sensor, motion information of the user (user terminal 100) acquired by a gyro sensor, etc. The sensor information may also be sensor information acquired by a sensor (such as a sleep sensor or a heart rate sensor) of a terminal device (such as a smart watch) linked to the user terminal 100.

[0045] Next, the information processing device 1 estimates the context information of the user based on the acquired sensor information (step S5). Specifically, the information processing device 1 estimates the context information indicating the current situation of the user. The current situation is a situation related to the user's current behavior or state, such as on the way to work (commuting), at work, traveling, exercising, sleeping, etc.

[0046] Next, the information processing device 1 determines interest information to be provided to the user from among the interest information of related persons based on the context information of the user (step S6). For example, the information processing device 1 extracts keywords to be provided from among keywords included in the tag cloud of related persons. For example, when the context information of the user is exercising, the information processing device 1 extracts keywords related to exercise from the tag cloud of related persons. In addition, the information processing device 1 may link each keyword related to exercise in the tag cloud of related persons with a time, and extract keywords related to the exercise when the context information indicates that the user is exercising at that time.

[0047] Next, the information processing device 1 provides the user with content indicating the determined interest information (step S7). For example, when displaying the tag cloud of related parties, the information processing device 1 provides content (tag cloud) in which the extracted keywords are highlighted. When displaying the tag cloud of a user, the information processing device 1 provides content (tag cloud) in which the extracted keywords are highlighted. In addition, in a matching app that introduces users (related parties) to users, the information processing device 1 may introduce related parties whose tag clouds match the user's (having many extracted keywords) to the user. In addition, when displaying the tag clouds of related parties and users, the information processing device 1 may change (update) the contents of the tag cloud (keywords to be highlighted and contents of keywords included in the tag cloud) in real time based on the current context information described above. In addition, the information processing device 1 may generate and provide a tag cloud in which tag clouds of a group of users who have viewed a news article or used a service are aggregated as related parties. At this time, the information processing device 1 may extract and provide keywords related to the content of the service used by the user. For example, when a news article about real estate is being viewed, the information processing device 1 may extract and provide only keywords related to real estate from the tag cloud of related parties.

[0048] In this way, the information processing device 1 according to the embodiment can provide the interests of the related parties determined based on the context information of the user, which makes it easier for the user to empathize with the related parties. In other words, it is possible to provide the user with a service that provides a higher level of satisfaction.

[0049] Next, a configuration example of an information processing system S according to an embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing a configuration example of an information processing system S according to an embodiment. As shown in Fig. 2, in the information processing system S according to the embodiment, an information processing device 1 and a plurality of user terminals 100 are connected to a network N by wire or wirelessly. The network N is, for example, a network such as the Internet, a Wide Area Network (WAN), or a Local Area Network (LAN).

[0050] The information processing device 1 is a server device that executes an information processing method according to an embodiment. The information processing device 1 determines the priority of the distribution content based on a comparison result between interest information (in tag cloud format) of a character (an example of a subject) shown in the distribution content such as a news article and interest information of a user.

[0051] Furthermore, the information processing device 1 identifies related parties having a relationship with the distribution content, and determines the priority of the distribution content based on the result of comparing the interest information of the related parties with the interest information of the user.

[0052] Furthermore, the information processing device 1 determines interest information to be provided to the user from among the interest information of related persons, based on context information based on the sensor information of the user.

[0053] In addition, the information processing device 1 is an information processing device that cooperates with multiple user terminals 100 and provides each user terminal 100 with API (Application Programming Interface) services for various applications (hereinafter, apps), etc., as well as various data, and is realized by a server device, a cloud system, etc.

[0054] The information processing device 1 may also be an information processing device that provides some kind of Web service online to each user terminal 100. For example, the information processing device 1 may provide services such as Internet connection, search service, SNS (Social Networking Service), Electronic Commerce (EC), electronic payment, online games, online banking, online trading, hotel and ticket reservations, video and music distribution, news, maps, route search, route guidance, line information, operation information, and weather forecasts as Web services. In practice, the information processing device 1 may cooperate with various servers that provide the above-mentioned Web services and mediate the Web services or be responsible for processing the Web services.

[0055] The user terminal 100 is a terminal device owned by a user who browses distributed content and posts comments on the distributed content. The user terminal 100 may be any type of terminal device, such as a smartphone, a desktop PC, a notebook PC, or a tablet PC. The user terminal 100 transmits various types of information to the information processing device 1 or the like, and receives information provided by the information processing device 1 or the like.

[0056] The requester terminal 200 is a terminal device owned by a requester who requests distribution of distribution content. The requester terminal 200 may be any type of terminal device, such as a smartphone, a desktop PC, a notebook PC, or a tablet PC. The requester terminal 200 transmits various information to the information processing device 1 or the like, and receives information provided by the information processing device 1 or the like.

[0057] Next, a configuration example of the information processing device 1 will be described with reference to FIG.

[0058] Fig. 3 is a diagram showing an example of the configuration of an information processing device 1 according to an embodiment. As shown in Fig. 3, the information processing device 1 has a communication unit 2, a control unit 3, and a storage unit 4. The control unit 3 includes a reception unit 31, an acquisition unit 32, an identification unit 33, an estimation unit 34, a comparison unit 35, a determination unit 36, a distribution unit 37, and a provision unit 38. The storage unit 4 stores user information 41 and content information 42.

[0059] The communication unit 2 is realized by, for example, a network interface card (NIC) etc. The communication unit 2 is connected to a network by wire or wirelessly.

[0060] The control unit 3 is a controller, and is realized by, for example, a processor such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the information processing device 1 using a RAM or the like as a working area. The control unit 3 is also a controller, and may be realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a GPGPU (General Purpose Graphic Processing Unit).

[0061] The storage unit 4 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk.

[0062] The user information 41 is information about a user. Fig. 4 is a diagram showing an example of the user information 41. As shown in Fig. 4, the user information 41 includes items such as "user ID", "user information", and "interest information".

[0063] "User ID" is identification information that identifies a user. "User information" is information about a user, including, for example, attribute information and user behavior information. "Interest information" is information about a user's interests, such as the tag cloud information shown in FIG. 1A.

[0064] The content information 42 is information related to the distribution content. Fig. 5 is a diagram showing an example of the content information 42. As shown in Fig. 5, the content information 42 includes items such as "content ID", "details information", and "interests information".

[0065] "Content ID" is identification information that identifies the content. "Content information" is information about the content, including video and image data, information about news articles (text information and image information), and comments and ratings posted by each user. "Interest information" is information about the interests of the people involved and subjects appearing in the distributed content, such as the tag cloud information shown in Figure 1A.

[0066] Next, each function of the control unit 3 of the information processing device 1 (receiving unit 31, acquiring unit 32, identifying unit 33, estimating unit 34, comparing unit 35, deciding unit 36, distributing unit 37 and providing unit 38) will be described.

[0067] The reception unit 31 receives a request to register a distribution content from a requesting user via the request source terminal 200. The distribution content is, for example, a news article, a video, a comic, an animation, or the like, which is distributed to a user. The distribution content may also be a product or service sold in a shopping service.

[0068] The acquisition unit 32 acquires user information of users to whom distribution content is to be distributed via the user terminal 100. The user information includes user attribute information and information on behavior in various services (search behavior, purchasing behavior, posting behavior, etc.). The acquisition unit 32 also acquires sensor information of users to whom distribution content is to be distributed via the user terminal 100. The sensor information is, for example, location information acquired by a location sensor, and motion information of the user (user terminal 100) acquired by a gyro sensor. The sensor information may also be sensor information acquired by a sensor (sleep sensor, heart rate sensor, etc.) of a terminal device (smart watch, etc.) linked to the user terminal 100.

[0069] The identification unit 33 identifies the featured object indicated by the distribution content. Specifically, the featured object is a person, object, region, etc. that appears in a news article. For example, the identification unit 33 identifies the featured object by extracting keywords related to the featured object from the text in the news article. For example, the identification unit 33 identifies an athlete, politician, entertainer, etc. that appears in the news article as the featured object. For example, the identification unit 33 identifies a building, land, city, ward, town, village, etc. that appears in the news article as the featured object. Note that the identification unit 33 may identify multiple featured objects from one news article. In addition, the identification unit 33 identifies a related person having a relationship with the distribution content. Specifically, the related person is a person who posted a comment on the news article, a seller on a shopping site or an auction site, a review poster, etc.

[0070] The estimation unit 34 estimates the interest information of the specified subject. Specifically, the estimation unit 34 analyzes the contents of the news article to extract keywords related to the subject, and estimates a tag cloud (see FIG. 1A) that aggregates the keywords as interest information. The news article is not limited to the news article that was the source of the specification of the subject, but may be a past news article related to the subject. In addition, the estimation unit 34 may extract keywords from, for example, the content posted by the subject on SNS other than the news article. In addition, the estimation unit 34 may extract keywords from the behavior information of the subject (search behavior, purchase behavior, etc.) only when permission is obtained from the specified subject. In addition, when the specified subject is real estate (building or land) or a region, the estimation unit 34 may generate a tag cloud that aggregates tag clouds of people who have visited the real estate or region or people who live there. In addition, the estimation unit 34 estimates the interest information of the user based on the acquired user information. Specifically, the estimation unit 34 analyzes the contents of the user information to extract keywords in the user information, and estimates a tag cloud that aggregates the keywords as interest information. The estimation unit 34 also estimates the interest information of the specified related party. Specifically, the estimation unit 34 analyzes the contents of the related party's posts and the contents of the listing information to extract keywords, and estimates a tag cloud that aggregates the keywords as interest information. The estimation unit 34 also estimates the user's context information based on the acquired sensor information. Specifically, the estimation unit 34 estimates context information that indicates the user's current situation. The current situation is a situation related to the user's current behavior or state, such as going to work (commuting), working, traveling, exercising, sleeping, etc.

[0071] The comparison unit 35 compares the interest information of the user with the interest information of the featured subject. For example, the comparison unit 35 compares the tag cloud of the user with the tag cloud of the featured subject. Specifically, the comparison unit 35 calculates the degree of agreement between the tag cloud of the user and the tag cloud of the featured subject. The degree of agreement may be limited to the tag clouds having the same keywords, and may include the tag clouds having the same (or similar) meanings. In addition, when there are multiple featured subjects identified from the delivery content, the comparison unit 35 calculates an absolute score indicating the degree of agreement, and calculates the score of each featured subject as the comparison result. In addition, the comparison unit 35 compares the interest information of the user with the interest information of the related person. For example, the comparison unit 35 compares the tag cloud of the user with the tag cloud of the related person. For example, the comparison unit 35 compares the tag cloud of the user in a specific domain with the tag cloud of the related person of the delivery content in the domain. More specifically, the comparison unit 35 compares the tag cloud of the seller who is a related party in the shopping service with the tag cloud of the user in the shopping service.

[0072] The determination unit 36 ​​determines the priority of the content to be delivered to the user based on the comparison result. For example, the determination unit 36 ​​increases the priority of the content to be delivered that is linked to the subject that appears with a high degree of match (a large number of the same keywords). The determination unit 36 ​​may also increase the priority of the content to be delivered when the specific keywords in the tag cloud are the same. The determination unit 36 ​​increases the priority of the content to be delivered that is linked to the person in the tag cloud that has a large number of keywords similar to the keywords indicated by the tag cloud of the user. The determination unit 36 ​​determines the priority of the content to be delivered in a specific domain based on the interest information of the user in the specific domain. The determination unit 36 ​​determines the interest information to be provided to the user from the interest information of the person in question based on the context information of the user. For example, the determination unit 36 ​​extracts the keyword to be provided from the keywords included in the tag cloud of the person in question. For example, when the context information of the user is exercising, the determination unit 36 ​​extracts a keyword related to exercise from the tag cloud of the person in question. In addition, the determination unit 36 ​​may link each keyword related to exercise in the tag cloud of the person concerned with a time, and extract a keyword related to the exercise when the context information indicates that the user is exercising at that time.

[0073] The distribution unit 37 distributes the distribution content to the user based on the determined priority. For example, when the distribution unit 37 distributes a plurality of news articles in a list of headlines, the distribution unit 37 displays and provides the distribution content with a higher priority at the top of the list. The distribution unit 37 also provides the news article with the highest priority as a recommended news article by emphasizing it. The distribution unit 37 may also display a tag cloud of the featured target in a speech bubble or the like when the user hovers the mouse over the text of the featured target when the text of the news article is displayed. At this time, the distribution unit 37 may also highlight keywords similar to the keywords of the tag cloud of the user. The distribution unit 37 also preferentially distributes the items of a seller to a user whose tag cloud is similar to that of a seller in a shopping service or an auction service. The distribution unit 37 may also display only the evaluations and comments of a related person (including a commentator who made an explanatory comment) who has evaluated or commented on a purchased product or a news article in a shopping service, an auction service, or a news article, or may display the evaluations and comments of the related person preferentially to a user whose tag cloud is similar to that of the related person.

[0074] The providing unit 38 provides the user with content indicating the determined interest information to be provided. For example, when displaying the tag cloud of related persons, the providing unit 38 provides content (tag cloud) in which the extracted keywords are highlighted. When displaying the tag cloud of a user, the providing unit 38 provides content (tag cloud) in which the extracted keywords are highlighted. In addition, in a matching app that introduces users (related persons) to users, the providing unit 38 may introduce related persons whose tag clouds match the user's (having many extracted keywords) to the user. In addition, when displaying the tag clouds of related persons and users, the providing unit 38 may change (update) the content of the tag cloud (keywords to be highlighted and content of keywords included in the tag cloud) in real time based on the current context information described above.

[0075] Next, a process procedure of information processing types 1 to 3 executed by the information processing device 1 according to the embodiment will be described with reference to Fig. 6 to Fig. 8. Fig. 6 to Fig. 8 are flowcharts showing the process procedure of information processing types 1 to 3 executed by the information processing device 1 according to the embodiment.

[0076] As shown in FIG. 6, in information processing 1, the control unit 3 identifies an object appearing in the distribution content (step S101).

[0077] Next, the control unit 3 estimates the interest information of the featured subject (step S102).

[0078] Next, the control unit 3 estimates the user's interest information based on the user information (step S103).

[0079] Next, the control unit 3 compares the interest information of the featured subject with the interest information of the user (step S104).

[0080] Next, the control unit 3 determines the priority of the distribution content based on the comparison result (step S105).

[0081] Next, the control unit 3 distributes the distribution content to the user based on the determined priority (step S106), and ends the process.

[0082] Next, as shown in FIG. 7, in information processing part 2, the control unit 3 identifies a person concerned with the distribution content (step S201).

[0083] Next, the control unit 3 estimates the interest information of the related person (step S202).

[0084] Next, the control unit 3 estimates the user's interest information based on the user information (step S203).

[0085] Next, the control unit 3 compares the interest information of the related person with the interest information of the user (step S204).

[0086] Next, the control unit 3 determines the priority of the distribution content based on the comparison result (step S205).

[0087] Next, the control unit 3 distributes the distribution content to the user based on the determined priority (step S206), and ends the process.

[0088] Next, as shown in FIG. 8, in information processing part 3, the control unit 3 identifies a person concerned with the distribution content (step S301).

[0089] Next, the control unit 3 estimates the interest information of the related person (step S302).

[0090] Next, the control unit 3 acquires sensor information of the user (step S303), and determines interest information to be provided to the user from the interest information of related persons based on the sensor information (step S304).

[0091] Next, the control unit 3 provides the user with the content indicating the determined interest information (step S305), and ends the process.

[0092] 〔others〕 In addition, among the processes described in the above embodiments, some of the processes described as being performed automatically can be performed manually. Alternatively, all or some of the processes described as being performed manually can be performed automatically using a known method. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0093] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0094] 3 may be held in a storage server or the like instead of being held by each device. In this case, each device obtains various pieces of information by accessing the storage server.

[0095] [Hardware configuration] The information processing device 1 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in Fig. 9, for example. Fig. 9 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected by a bus 1090.

[0096] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050 and programs read from the input device 1020, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), a HDD (Hard Disk Drive), a flash memory, or the like.

[0097] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (registered trademark) (High Definition Multimedia Interface). The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner, and is realized by a USB, for example.

[0098] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

[0099] The network IF 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0100] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0101] For example, when the computer 1000 functions as the information processing device 1, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 3 by executing a program loaded onto the primary storage device 1040.

[0102] 〔effect〕 As described above, the information processing device 1 according to the embodiment includes the identification unit 33 and the determination unit 36. The identification unit 33 identifies a featured subject indicated by the distribution content to be distributed. The determination unit 36 ​​determines a priority for distributing the distribution content to the user based on a comparison result between the interest information of the user who is the distribution destination of the distribution content and the interest information of the featured subject. With this configuration, it is possible to more appropriately distribute the content to the user.

[0103] Moreover, the information processing device 1 according to the embodiment includes an identification unit 33 and a determination unit 36. The identification unit 33 identifies related parties having a relationship with the distribution content to be distributed. The determination unit 36 ​​determines a priority for distributing the distribution content to the user based on a comparison result between the interest information of the user to whom the distribution content is to be distributed and the interest information of the related parties. With this configuration, it is possible to more appropriately distribute the content to the user.

[0104] Moreover, the information processing device 1 according to the embodiment includes an identification unit 33, an estimation unit 34, and a determination unit 36. The identification unit 33 identifies related parties having a relationship with the distribution content to be distributed. The estimation unit 34 estimates context information of the users to whom the distribution content is to be distributed, based on sensor information about the users. The determination unit 36 ​​determines interest information to be provided to the users from the interest information of the related parties, based on the context information. With this configuration, it is possible to provide services that provide users with a higher level of satisfaction.

[0105] Moreover, the information processing device 1 according to the embodiment includes an estimation unit 34 and a determination unit 36. The estimation unit 34 estimates the user's interest information in each domain accessed by the user based on the user's behavior in the domain. The determination unit 36 ​​determines the priority of the content to be distributed in the domain based on the interest information in the domain. With this configuration, content can be more appropriately distributed to the user.

[0106] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section.

[0107] 〔others〕 In addition, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0108] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0109] Furthermore, the processes described in the above-described embodiments can be appropriately combined as long as the process contents are not contradictory.

[0110] Moreover, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, the control unit 3 can be read as control means or a control circuit. [Explanation of symbols]

[0111] 1. Information processing device 2. Communications Department 3. Control Unit 4 Storage section 31 Reception 32 Acquisition Department 33 Specific part 34 Estimation part 35 Comparison section 36 Decision Section 37 Distribution Department 38 Providing Department 41 User information 42 Content Information 100 user terminals 200 Requesting terminal S Information Processing System

Claims

1. An identification unit that identifies a subject appearing in a distribution content to be distributed; a determination unit that determines a priority level for distributing the content to the user based on a comparison result between interest information of the user who is a destination of the content to be distributed and interest information of the subject; An information processing device comprising:

2. The determination unit is The priority is determined based on the degree of agreement between the interest information of the user and the interest information of the featured subject. The information processing device according to claim 1 .

3. The present invention further includes an estimation unit that estimates the interest information of the featured subject based on the content of the distribution content related to the featured subject. The information processing device according to claim 1 .

4. The estimation unit is The interest information of the subject is estimated based on the content of the distribution content that is the source of the identification of the subject. The information processing device according to claim 3 .

5. The estimation unit is Estimating the interest information of the featured subject based on the content of the past distribution content related to the featured subject The information processing device according to claim 3 .

6. A distribution unit that distributes the distribution content based on the priority. The information processing device according to claim 1 .

7. The distribution unit is A list of the distribution contents arranged in the order based on the priority is distributed to the user. The information processing device according to claim 6.

8. The subject of the appearance is: A person who appears in the distribution content The information processing device according to claim 1 .

9. 1. A computer-implemented information processing method, comprising: A step of identifying a subject appearing in the distribution content to be distributed; a determining step of determining a priority level for distributing the content to the user based on a comparison result between interest information of the user to whom the content is to be distributed and interest information of the subject; An information processing method comprising:

10. A step of identifying a subject represented by the distribution content to be distributed; a determination step of determining a priority level for distributing the content to the user based on a comparison result between interest information of the user who is to receive the content and interest information of the subject; An information processing program characterized by causing a computer to execute the above.

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