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

What is AI technical title?
AI technical title is built by Patsnap AI team. It summarizes the technical point description of the patent document.
The information processing device analyzes user behavior to determine why content is highlighted, enhancing content distribution by understanding user motivations.

JP2025187376APending Publication Date: 2025-12-25LY CORP

View PDF 1 Cites 0 Cited by

Patent Information

Application Number: JP2024096118
Authority / Receiving Office: JP · JP
Patent Type: Applications
Current Assignee / Owner
Filing Date: 2024-06-13
Publication Date: 2025-12-25

AI Technical Summary

Technical Problem

Conventional techniques fail to grasp the reasons why users highlight content, as they only estimate user search query trends without understanding the underlying factors.

Method used

An information processing device that receives user designations to highlight content, acquires behavioral information, and estimates the factors causing the highlighting based on a rule base and natural language processing models like GPT.

Benefits of technology

Enables understanding the reasons for user highlighting, facilitating targeted content distribution to increase user engagement and motivation to view the content.

✦ Generated by Eureka AI based on patent content.

Smart Images

Figure 2025187376000001_ABST

Patent Text Reader

Abstract

To grasp a cause that a user has designated highlighting of a content.SOLUTION: An information processing device includes: a receiving unit that receives, from a user, designation of highlighting of a part of a content displayed on a screen of a terminal device used by the user; an acquisition unit that acquires action information indicating an action of the user; and an estimation unit that estimates a cause that the user has designated highlighting of a portion that is the part of the content based on the action information acquired by the acquisition unit.SELECTED DRAWING: Figure 5

Need to check novelty before this filing date? Find Prior Art

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] Conventionally, techniques for estimating various pieces of information about a user have been proposed. One example of such a technique is a technique for estimating a user's characteristic search query trends based on the difference between the trends of search queries entered by the user and the trends of search queries entered by other users. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2018-60469 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned techniques cannot be said to be able to grasp the reason why a user specified highlighting of content.

[0005] For example, the above-mentioned conventional technology merely estimates the tendency of characteristic search queries entered by users, and cannot be said to be able to grasp the factors that led users to specify highlighting of content.

[0006] The present invention has been made in view of the above, and aims to understand the factors that caused a user to specify highlighting of content. [Means for solving the problem]

[0007] The information processing device of the present application is characterized by having a reception unit that receives from a user a designation to highlight a portion of content displayed on the screen of a terminal device used by the user, an acquisition unit that acquires behavioral information indicating the user's behavior, and an estimation unit that estimates the factor that caused the user to designate the highlighting for a portion of the content based on the behavioral information acquired by the acquisition unit. [Effects of the Invention]

[0008] According to one aspect of the embodiment, it is possible to obtain an effect that the reason why the user specified highlighting for the content can be grasped. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of behavior information according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of behavior information according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of behavior information according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of the user information database 31. As shown in FIG. [Figure 7] FIG. 7 is a diagram showing an example of the content information database 32. As shown in FIG. [Figure 8] FIG. 8 is a diagram showing an example of the rule database 33. As shown in FIG. [Figure 9] FIG. 9 is a flowchart illustrating an example of a procedure for information processing according to the embodiment. [Figure 10] FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an information processing device, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") 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 these embodiments. Furthermore, the same components in the following embodiments will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0011] 1. Embodiment Information processing implemented by an information processing device or the like according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment. Note that in Fig. 1, it is assumed that the information processing according to the embodiment is implemented by an information processing device 10, which is an example of the information processing device according to the present application.

[0012] As shown in Fig. 1, an information processing system 1 according to an embodiment includes an information processing device 10 and a user terminal 100. The information processing device 10 and the user terminal 100 are connected to each other via a network N (see Fig. 5, for example) so as to be able to communicate with each other via a wired or wireless connection. The network N is, for example, a wide area network (WAN) such as the Internet. Note that the information processing system 1 shown in Fig. 1 may include a plurality of information processing devices 10 and a plurality of user terminals 100.

[0013] 1 is an information processing device that performs information processing, and is realized by, for example, a server device, a cloud system, etc. In the example of Fig. 1, the information processing device 10 is, for example, an information processing device that provides a news service that provides content related to news articles to users.

[0014] The information processing device 10 may have a function as a web server that provides a website related to a news service. The information processing device 10 may also be a device that distributes information to the user terminal 100 to be displayed on an application related to a news service (hereinafter, may be referred to as a "news app") installed in the user terminal 100. The information processing device 10 may also be a server that distributes the data of the news app itself. The information processing device 10 may also function as a distribution device that distributes control information to the user terminal 100. Here, the control information is written in, for example, a script language such as JavaScript (registered trademark) or a style sheet language such as CSS (Cascading Style Sheets). The news app itself distributed from the information processing device 10 may also be considered as control information.

[0015] In addition, the information processing device 10 may distribute to the user terminal 100 information to be displayed on websites related to portal services, auction services, weather forecast services, shopping services, finance (stock prices) services, route search services, map provision services, travel services, restaurant introduction services, etc., and various apps installed on the user terminal 100 (for example, portal apps, auction sites, weather forecast apps, shopping apps, finance (stock prices) apps, route search apps, map provision apps, travel apps, restaurant introduction apps, etc.).

[0016] The user terminal 100 shown in Fig. 1 is an information processing device used by a user. The user terminal 100 is realized, for example, by a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. In the example shown in Fig. 1, the user terminal 100 is a smartphone used by a user.

[0017] Furthermore, the user terminal 100 displays information provided by the information processing device 10 using a web browser or an application. When the user terminal 100 receives control information for realizing information display processing from the information processing device 10 or the like, the user terminal 100 realizes the display processing in accordance with the control information.

[0018] The information processing performed by information processing device 10 will be described below with reference to FIG. 1. In the following description, user terminals 100-1 to 100-N (N is any natural number) will be described according to the user using user terminal 100. For example, user terminal 100-1 is the user terminal 100 used by a user (user U1) identified by user ID "UID#1". In the following description, user terminals 100-1 to 100-N will be referred to as user terminal 100 when there is no particular distinction between them. In the following description, user terminal 100 may be considered to be the same as the user. In other words, in the following description, user can also be read as user terminal 100.

[0019] In the following description, it is assumed that a news application is pre-installed on the user terminal 100.

[0020] First, the information processing device 10 provides content related to a news article to the user terminal 100-1 (step S1). For example, the information processing device 10 provides content C1 related to a news article to the user terminal 100-1 via a news app, and causes it to be displayed on the screen.

[0021] As a specific example, the information processing device 10 provides content C1 including an area AR1 that displays the title of a news article and an image related to the news article, an area AR2 that displays text information indicating the content of the news article, an area AR3 that displays a button (rating button) indicating a rating for the content C1, and a button (share button) B1 for performing an operation related to sharing the content C1 with other users on a predetermined service (for example, a social networking service (SNS)).

[0022] In the example of FIG. 1, the information processing device 10 displays three types of evaluation buttons in the area AR3: "Instructive," "Easy to understand," and "New perspective." Here, "Instructive" evaluates the information contained in the content C1, such as whether it provides a point of view or new insights. "Easy to understand" evaluates the structure of the content C1, such as how the main points are summarized and easy to understand. "New perspective" evaluates the information contained in the content C1, such as the novelty of the phenomenon itself conveyed by the content C1 and the originality of the poster's interpretation of the phenomenon.

[0023] Next, the information processing device 10 receives from the user terminal 100-1 a designation to highlight a part of the content C1 (step S2). For example, the user U1 performs an operation (e.g., a drag operation) on the user terminal 100-1 to designate highlighting of text information displayed in areas AR1 and AR2 of the content C1 displayed on the user terminal 100-1. The information processing device 10 then receives from the user terminal 100-1 the text information designated for highlighting by the user U1.

[0024] Then, the information processing device 10 provides the content C1, in which a part of the content C1 is highlighted, to other users. For example, the information processing device 10 provides the content C1, in which the text information specified by the user U1 is highlighted, to user terminals 100 used by users (followers) who follow the user U1 in a news service or similar users similar to the user (for example, users who share attributes or behavioral histories in various services). Furthermore, when the user U1 presses the share button B1, the information processing device 10 provides the content C1, in which the text information specified by the user U1 is highlighted, via an SNS.

[0025] Note that the information processing device 10 may also receive a designation to highlight an image included in the content C1 (for example, an image displayed in the area AR1) in addition to the text information.

[0026] Next, the information processing device 10 acquires behavioral information related to the behavior of the user U1 in various services from the user terminal 100-1 (step S3). For example, the information processing device 10 acquires behavioral information related to the behavior of the user U1 before specifying highlighting for the content C1 and behavioral information related to the behavior of the user U1 after specifying highlighting for the content C1. As a specific example, the information processing device 10 acquires, as behavioral information, information such as a search query entered by the user U1 in a news service, a portal service, or the like, and operations on content provided by the news service (for example, whether or not the share button was pressed, an evaluation of the content, etc.). Note that the information processing device 10 may acquire behavioral information related to the behavior of the user U1 stored in a storage unit of the information processing device 10 itself.

[0027] Next, the information processing device 10 estimates the reason why the user U1 specified highlighting for a part of the content C1 based on the behavioral information of the user U1 (step S4). For example, the information processing device 10 estimates the reason why the user U1 specified highlighting based on a rule base in which behavioral information and factors associated with the behavioral information are set.

[0028] Here, the rule is a table that shows, for each combination of the type of user action (e.g., entering a search query, pressing the share button, etc.) and whether the action is before or after the action that specifies highlighting (hereinafter sometimes referred to as "specified action"), what factor the highlighted portion contributes to that action. For example, such a table may register a record indicating that "entering a search query: before performing the specified action: the information the user wanted to know through the search query was the highlighted portion."

[0029] Such a rule base is generated by a model (language model) that performs natural language processing, such as a Generative Pre-trained Transformer (GPT). For example, the information processing device 10 identifies a specified action for content from a user's action log (action history) in various services, and extracts actions before and after the identified specified action (i.e., actions within the same session). Then, the information processing device 10 identifies actions that are highly related to the specified action using a relationship score between the specified action and the actions before and after it. The relationship score may be calculated using any known technology. Here, the information processing device 10 generates a prompt that includes the specified action indicating the content for which emphasis has been specified or the part for which emphasis has been specified, the identified action, and an instruction sentence that differs depending on whether the identified action occurs before or after the specified action, and inputs the prompt to the GPT.

[0030] For example, if the identified behavior occurs before the specified behavior, the information processing device 10 inputs an instruction sentence such as "The user who performed the specified behavior performed the behavior to be presented (the identified behavior) before the specified behavior. Please infer the factors that led to the user's specified behavior based on the content of such behavior" into the GTP, and outputs an answer sentence (factors). Also, if the identified behavior occurs after the specified behavior, the information processing device 10 inputs an instruction sentence such as "The user who performed the specified behavior performed the behavior to be presented after the specified behavior. Please infer the factors that led to the user's specified behavior based on the content of such behavior" into the GTP, and outputs an answer sentence. By repeating this process, it is possible to generate rules indicating factors associated with the specified behavior for behaviors before and after the user's specified behavior.

[0031] The GPT is stored in the information processing device 10 and was created independently by the business operator that manages the information processing device 10. It is desirable to keep input information, such as personal information, confidential by learning it so that it will not be used as a new answer.

[0032] Here, the factor estimation process will be described with reference to Figures 2 to 4. Figures 2 to 4 are diagrams showing examples of behavior information according to the embodiment.

[0033] 2, assume that user U1 inputs a search query "AA region end of rainy season" and, after content C1 is provided as a search result, specifies that text information T1 in content C1 be highlighted. In this case, the information processing device 10 infers that the information that user U1 wanted to search for using the search query "AA region end of rainy season" (i.e., the information that user U1 wanted to know) is the text information T1.

[0034] 3, it is assumed that user U1 presses the share button B1 after specifying highlighting for text information T2 of content C1. In such a case, the information processing device 10 presumes that the reason is that user U1 wishes to share text information T2 with other users.

[0035] 4, it is assumed that user U1 specifies highlighting of text information T3 of content C1 and then presses the rating button "educational" (i.e., rates content C1 as "educational"). In such a case, the information processing device 10 infers that the reason is that user U1 rated text information T3 as "educational" (e.g., that new knowledge was gained).

[0036] In the example shown in Figure 4, the information processing device 10 may also infer that the reason for this is that user U1 evaluated text information T3 as "educational" even if the user U1 pressed the rating button "educational" before specifying highlighting for text information T3 of content C1.

[0037] Returning to Figure 1, the explanation will be continued. Next, the information processing device 10 provides content indicating the portion designated for highlighting by user U1 and information related to the reason for the designation of highlighting to the user terminal 100-2 used by another user U2 who has a predetermined relationship with user U1 (step S5). For example, when user U2 inputs a search query corresponding to the search query "AA region end of rainy season," the information processing device 10 provides content indicating information based on the reason why user U1 highlighted text information T1 (for example, text information such as "The desired information is here"), together with text information T1 and a URL (Uniform Resource Locator) of content C1.

[0038] In addition, when user U2 follows user U1 in a news service, the information processing device 10 provides content that shows information based on the reason why user U1 highlighted the text information T2 (for example, text information such as "User U1 is sharing this information"), along with text information T2 and the URL of content C1.

[0039] Furthermore, if the attributes (e.g., interests) estimated based on the behavioral history in various services are common between user U1 and user U2, the information processing device 10 provides content indicating information based on the factor that caused user U1 to highlight the text information T3 (e.g., text information such as "You will gain new knowledge"), along with the text information T3 and the URL of content C1.

[0040] As described above, the information processing device 10 according to the embodiment receives a designation for highlighting a part of content from a user, and estimates the reason why the user designated the highlighting based on the behavioral information of the user. This allows the information processing device 10 according to the embodiment to understand the reason why the user designated the highlighting of content.

[0041] Furthermore, by estimating the factors that caused the highlighting to be specified, the information processing device 10 according to the embodiment can extract points from the content that will lead to new discoveries, new knowledge, or information that the user wants to know, and provide these to other users who have not yet viewed the content, thereby increasing the motivation to view the content and creating an opportunity for them to visit the content.

[0042] [2. Other processing examples] The above-described process is merely an example, and the information processing device 10 may perform various processes using various information. In this regard, examples are listed below.

[0043] [2-1. About saving content] 1, it is assumed that user U1 specifies highlighting of text information T4 of content C1 and then performs an operation to save content C1 (for example, a screenshot). In such a case, the information processing device 10 infers that the reason for this is that user U1 wanted to save text information T4 (in other words, the reason is that user U1 gained new knowledge or wanted to save the content and share it with other users).

[0044] When user U2 is following user U1 in a news service, the information processing device 10 provides content indicating information based on the reason why user U1 highlighted the text information T4 (for example, text information such as "User U1 has saved this information") together with the text information T4 and the URL of the content C1. Furthermore, when the attributes are common between user U1 and user U2, the information processing device 10 provides content indicating information based on the reason why user U1 highlighted the text information T4 (for example, text information such as "You will gain new knowledge") together with the text information T4 and the URL of the content C1.

[0045] [2-2. Viewing multiple contents] 1, it is assumed that user U1 browses a plurality of contents, including content C1, related to the same event (e.g., the onset of the rainy season) as that indicated by content C1, and then specifies highlighting of text information T5 of content C1. In such a case, the information processing device 10 infers that the information that interested user U1 in the event "the onset of the rainy season" was text information T5.

[0046] Then, when user U2 is viewing content related to the event "the rainy season begins" in the news service, the information processing device 10 provides content showing information based on the reason why user U1 highlighted the text information T5 (for example, text information such as "useful information related to the event "the rainy season begins"), along with text information T5, the URL of content C1, etc.

[0047] [2-3. Content Evaluation] 1, it is assumed that user U1 gives a positive evaluation of content C1 (for example, by pressing a reaction button such as "Like") after specifying highlighting for text information T6 of content C1, or gives a positive evaluation of content C1 before specifying highlighting for text information T6 of content C1. In such a case, the information processing device 10 infers that the reason is that user U1 feels sympathy for text information T6.

[0048] If the attributes estimated based on the behavioral history in various services are common between user U1 and user U2, the information processing device 10 provides content that shows information based on the factor that caused user U1 to highlight the text information T6 (for example, text information such as "Recommended for you"), along with the text information T6 and the URL of content C1.

[0049] The information processing device 10 may receive from user U1 a designation to highlight a portion of a comment posted by another user on content C1. Here, it is assumed that user U1 gave a positive evaluation to the comment after designating highlighting of text information T7 of the comment, or gave a positive evaluation to the comment before designating highlighting of text information T7 of the comment. In such a case, the information processing device 10 infers that the reason for this is that user U1 felt sympathy for the text information T7.

[0050] Then, in the news service, when user U2 is viewing content C1 or viewing content related to content C1 (for example, content related to the event "the rainy season begins"), the information processing device 10 provides content that shows information based on the reason why user U1 highlighted text information T7 (for example, text information such as "This is a recommended comment"), along with text information T7 and the URL of the comment.

[0051] [2-4. User location] 1, it is assumed that user U1 was in a location where an event indicated by content C1 occurred (for example, "AA region" where the event "start of the rainy season" occurred) before specifying highlighting for text information T8 of content C1. In such a case, the information processing device 10 presumes that the reason is that user U1 judged that text information T8 was accurate information.

[0052] Then, when user U2 is located in the "AA region," the information processing device 10 provides content that shows information based on the reason why user U1 highlighted the text information T8 (for example, text information such as "This is accurate information about the AA region"), along with text information T8 and the URL of content C1.

[0053] The location of user U1 may be estimated based on the behavioral history of various services (e.g., route search services, map provision services, travel services, etc.), or may be detected by a GPS (Global Positioning System) or the like possessed by user terminal 100-1, etc.

[0054] 3. Configuration of Information Processing Device Next, the configuration of the information processing device 10 will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. As shown in Fig. 5, the information processing device 10 has a communication unit 20, a storage unit 30, and a control unit 40.

[0055] (Regarding the communication unit 20) The communication unit 20 is realized by, for example, a network interface card (NIC), etc. The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the user terminal 100, etc.

[0056] (Regarding the storage unit 30) The storage unit 30 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 5, the storage unit 30 has a user information database 31, a content information database 32, a rule database 33, and a model database 34.

[0057] (Regarding User Information Database 31) The user information database 31 stores various types of information related to users. An example of the information stored in the user information database 31 will now be described with reference to FIG. 6. FIG. 6 is a diagram showing an example of the user information database 31. In the example of FIG. 6, the user information database 31 has items such as "user ID," "attribute information," "behavioral history," and "follower information."

[0058] "User ID" indicates identification information for identifying a user. "Attribute information" indicates the user's attributes (for example, demographic attributes and psychographic attributes). Note that "Attribute information" may store information entered by the user in various services, information estimated based on "Behavioral History," and the like.

[0059] "Action history" indicates the user's action history in various services. "Follower information" indicates information about other users who follow the user in news services, and stores, for example, user IDs.

[0060] That is, FIG. 6 shows an example in which the attribute information of a user identified by a user ID "UID#1" is "attribute information #1", the action history is "action history #1", and the follower information is "following information #1".

[0061] (About Content Information Database 32) The content information database 32 stores various types of information related to content provided by the news service. An example of the information stored in the content information database 32 will now be described with reference to FIG. 7. FIG. 7 is a diagram showing an example of the content information database 32. In the example of FIG. 7, the content information database 32 has items such as "content ID," "text information," "image information," and "posted comments."

[0062] "Content ID" indicates identification information for identifying the content. "Text information" indicates text information that shows the content of the news article. "Image information" indicates images related to the news article. "Posted comments" indicates comments posted by users in response to the content.

[0063] That is, FIG. 7 shows an example in which the text information of the content identified by the content ID "NID#1" is "Text Information #1", the image information is "Image Information #1", and the posted comment is "Posted Comment #1".

[0064] (About Rule Database 33) The rule database 33 stores various information (rule base) related to rules used to estimate the factor that caused the user to specify highlighting. An example of information stored in the rule database 33 will now be described with reference to FIG. 8. FIG. 8 is a diagram showing an example of the rule database 33. In the example of FIG. 8, the rule database 33 has items such as "rule ID," "action," "time of action," and "factor."

[0065] "Rule ID" indicates identification information for identifying a rule. "Action" indicates an action that is highly relevant to the specified action. "Time of action" indicates whether the "action" occurred before the specified action or after the specified action. "Factor" indicates the factor that caused the user to specify highlighting.

[0066] That is, Figure 8 shows that the rule identified by rule ID "RID#1" specifies that when "action #1" is performed at "action time #1," the factor for which the user specified highlighting is "factor #1."

[0067] (About Model Database 34) The model database 34 stores models (e.g., GPT) that have been trained to generate answers to input questions.

[0068] (Regarding the control unit 40) The control unit 40 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the information processing device 10 using RAM as a work area. The control unit 40 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 5 , the control unit 40 according to the embodiment has a reception unit 41, an acquisition unit 42, an estimation unit 43, and a provision unit 44, and realizes or executes the functions and actions of information processing described below.

[0069] (Regarding Reception Section 41) The reception unit 41 receives, from a user, a designation to highlight a part of content displayed on the screen of a terminal device used by the user. For example, in the example of Fig. 1, the reception unit 41 receives, from the user terminal 100-1, a designation to highlight a part of content C1.

[0070] The receiving unit 41 may also receive a designation to highlight a part of a comment posted by another user. For example, in the example of Fig. 1, the receiving unit 41 receives, from user U1, a designation to highlight a part of a comment posted by another user on content C1.

[0071] (Regarding the acquisition unit 42) The acquiring unit 42 acquires behavioral information indicating user behavior. For example, in the example of Fig. 1, the acquiring unit 42 acquires behavioral information regarding the behavior of the user U1 before specifying highlighting for the content C1 and behavioral information regarding the behavior of the user U1 after specifying highlighting for the content C1, and stores the information in the storage unit 30 (for example, the user information database 31).

[0072] (Regarding the estimation unit 43) The estimation unit 43 estimates the reason why the user specified highlighting for a part of the content, based on the behavioral information acquired by the acquisition unit 42. For example, in the example of Fig. 1, the estimation unit 43 refers to the storage unit 30 (e.g., the user information database 31, the rule database 33, etc.) and estimates the reason why the user U1 specified highlighting, based on a rule base in which behavioral information and factors associated with the behavioral information are set.

[0073] The estimation unit 43 may also estimate the factor based on behavioral information indicating the user's behavior before specifying highlighting. For example, in the example of Fig. 1, the estimation unit 43 estimates the factor that caused the user U1 to specify highlighting based on behavioral information regarding the user U1's behavior before specifying highlighting for the content C1.

[0074] Furthermore, when behavioral information indicating a search query input by a user before viewing content is acquired, the estimation unit 43 may estimate that a factor is that a part indicates information that the user desired to search for using the search query. For example, in the example of Fig. 1, when user U1 inputs the search query "AA region, end of rainy season" and specifies highlighting for text information T1 of content C1 after content C1 is provided as a search result, the estimation unit 43 estimates that a factor is that the information that user U1 desired to search for using the search query "AA region, end of rainy season" is the text information T1.

[0075] Furthermore, when behavioral information indicating that a user was at a location corresponding to an event indicated by content is acquired, the estimation unit 43 may estimate that the cause is that the content indicated by the portion regarding the event is accurate. For example, in the example of Fig. 1, when user U1 was at a location where an event indicated by content C1 occurred before specifying highlighting for text information T8 of content C1, the estimation unit 43 estimates that the cause is that user U1 determined that text information T8 was accurate information.

[0076] Furthermore, the estimation unit 43 may estimate the reason why a user specified highlighting for a portion based on behavioral information indicating the user's behavior after specifying highlighting. For example, in the example of Fig. 1, the estimation unit 43 estimates the reason why user U1 specified highlighting for content C1 based on behavioral information regarding user U1's behavior after specifying highlighting for content C1.

[0077] Furthermore, when behavioral information indicating that a user performed an operation to share content with other users after viewing the content is acquired, the estimation unit 43 may estimate that the cause is that the user desired to share a portion. For example, in the example of Fig. 1, when user U1 specifies highlighting for text information T2 of content C1 and then presses the share button B1, the estimation unit 43 estimates that the cause is that user U1 desired to share text information T2 with other users.

[0078] Furthermore, when behavioral information indicating that a user performed an operation to save content for which emphasis was specified is acquired, the estimation unit 43 may estimate that the cause is that the user desired to save a portion. For example, in the example of Fig. 1, when user U1 specified emphasis on text information T4 of content C1 and then performed an operation to save content C1, the estimation unit 43 estimates that the cause is that user U1 desired to save text information T4.

[0079] Furthermore, when behavioral information indicating a user's evaluation of content is acquired, the estimation unit 43 may estimate that the cause is that the user has evaluated a part in question. For example, in the example of Fig. 1, when the user U1 specifies highlighting for text information T3 of content C1 and then presses the evaluation button "I learned something," the estimation unit 43 estimates that the cause is that the user U1 evaluated the text information T3 as "I learned something."

[0080] Furthermore, when behavioral information indicating that a user has viewed a plurality of pieces of content corresponding to an event indicated by the content is acquired, the estimation unit 43 may infer that a factor is that a portion indicates information in the event that the user was interested in. For example, in the example of Fig. 1, when user U1 views a plurality of pieces of content, including content C1, related to the same event "the start of the rainy season" as that indicated by content C1, and then specifies highlighting for text information T5 of content C1, the estimation unit 43 infers that a factor is that the information in which user U1 was interested in the event "the start of the rainy season" is text information T5.

[0081] Furthermore, when behavioral information indicating that a user has given a positive evaluation to content is acquired, the estimation unit 43 may estimate that the cause is that the user sympathized with a part. For example, in the example of Fig. 1, when the user U1 gave a positive evaluation to content C1 after specifying highlighting for text information T6 of content C1, or when the user U1 gave a positive evaluation to content C1 before specifying highlighting for text information T6 of content C1, the estimation unit 43 estimates that the cause is that the user U1 sympathized with text information T6.

[0082] Furthermore, when behavioral information indicating that a user has given a positive evaluation to a comment is acquired, the estimation unit 43 may estimate that the cause is that the user sympathized with a part of the comment. For example, in the example of Fig. 1, when a positive evaluation is given to a comment after specifying highlighting for text information T7 of the comment, or a positive evaluation is given to a comment before specifying highlighting for the text information T7 of the comment, the estimation unit 43 estimates that the cause is that the user U1 sympathized with the text information T7.

[0083] (About the provider 44) The providing unit 44 provides content indicating the part and information related to the factor to another user who has a predetermined relationship with the user U1. For example, in the example of Fig. 1, the providing unit 44 provides content indicating the part specified for highlighting by user U1 and information related to the factor for which the highlighting was specified to user terminal 100-2 used by another user U2 who has a predetermined relationship with user U1.

[0084] [4. Information processing flow] The procedure of information processing of the information processing device 10 according to the embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing an example of the procedure of information processing according to the embodiment.

[0085] 9, the information processing device 10 determines whether or not a designation for highlighting a part of content has been received from the user (step S101). If a designation for highlighting has not been received (step S101; No), the information processing device 10 waits until a designation for highlighting is received.

[0086] On the other hand, if a designation of highlighting is accepted (step S101; Yes), the information processing device 10 acquires behavioral information indicating the user's behavior (step S102). Next, the information processing device 10 estimates the reason why the user designated a part of the content to be highlighted based on the behavioral information (step S103), and ends the process.

[0087] [5. Modifications] The above-described embodiment is merely an example, and various modifications and applications are possible.

[0088] [5-1. Processing mode] Of the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information, including the processing procedures, specific names, various data, and parameters shown in the above text and drawings, can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0089] Furthermore, the components of each device shown in the figure are conceptual functional components and do 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 depending on various loads, usage conditions, etc.

[0090] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0091] [6. Effects] As described above, the information processing device 10 according to the embodiment includes a receiving unit 41, an acquiring unit 42, an estimating unit 43, and a providing unit 44. The receiving unit 41 receives, from a user, a designation to highlight a portion of content displayed on the screen of a terminal device used by the user. The acquiring unit 42 acquires behavioral information indicating the user's behavior. The estimating unit 43 estimates the reason why the user designated a portion of the content to be highlighted, based on the behavioral information acquired by the acquiring unit 42. The providing unit 44 provides content indicating the portion and information related to the reason to other users who have a predetermined relationship with the user.

[0092] As a result, the information processing device 10 according to the embodiment can receive a designation from a user to highlight a portion of content, and can estimate the reason why the user designated the portion for highlighting based on the designated portion for highlighting and the user's behavioral information, thereby understanding the reason why the user designated the content for highlighting.

[0093] Furthermore, in the information processing device 10 according to the embodiment, for example, the estimation unit 43 estimates a cause based on behavioral information indicating a user's behavior before specifying highlighting. Furthermore, when behavioral information indicating a search query entered by a user before viewing content is acquired, the estimation unit 43 estimates that a cause is that the part indicates information that the user wanted to search for using the search query. Furthermore, when behavioral information indicating that the user was located at a location corresponding to an event indicated by the content is acquired, the estimation unit 43 estimates that a cause is that the content indicated by the part regarding the event is accurate.

[0094] As a result, the information processing device 10 according to the embodiment can ascertain the reason why the user specified highlighting for the content, based on the behavior information of the user before specifying highlighting.

[0095] Furthermore, in the information processing device 10 according to the embodiment, for example, the estimation unit 43 estimates the reason why a user specified highlighting for a portion based on behavioral information indicating behavior after the user specified highlighting. Furthermore, when behavioral information indicating that a user performed an operation to share content with other users after viewing the content is acquired, the estimation unit 43 estimates that the reason is that the user desired to share the portion. Furthermore, when behavioral information indicating that a user performed an operation to save content for which highlighting was specified is acquired, the estimation unit 43 estimates that the reason is that the user desired to save the portion.

[0096] As a result, the information processing device 10 according to the embodiment can ascertain the reason why the user specified highlighting for the content, based on the behavior information of the user after specifying highlighting.

[0097] Furthermore, in the information processing device 10 according to the embodiment, for example, when behavioral information indicating a user's evaluation of content is acquired, the estimation unit 43 estimates that the cause is that the user has evaluated a part. Furthermore, when behavioral information indicating that the user has viewed multiple pieces of content corresponding to an event indicated by the content is acquired, the estimation unit 43 estimates that the cause is that the part indicates information in which the user was interested in the event. Furthermore, when behavioral information indicating that the user has evaluated content positively is acquired, the estimation unit 43 estimates that the cause is that the user sympathized with the part.

[0098] As a result, the information processing device 10 according to the embodiment can estimate the factors that led a user to specify highlighting based on various user behaviors, and can therefore accurately grasp the factors that led a user to specify highlighting for content.

[0099] In the information processing device 10 according to the embodiment, for example, the receiving unit 41 receives a designation to highlight a part of a comment posted by another user. Then, when behavioral information indicating that the user gave a positive evaluation to the comment is acquired, the estimation unit 43 estimates that the reason is that the user sympathized with the part.

[0100] As a result, the information processing device 10 according to the embodiment can estimate the reason why the user specified highlighting for the comment, and can therefore understand the reason why the user specified highlighting for the comment.

[0101] [7. Hardware Configuration] The information processing device 10 according to each of the above-described embodiments is realized, for example, by a computer 1000 configured as shown in Fig. 10. The information processing device 10 will be described below as an example. Fig. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. The computer 1000 has a CPU 1100, a ROM 1200, a RAM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0102] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1200 or the HDD 1400. The ROM 1200 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0103] The HDD 1400 stores programs executed by the CPU 1100, data used by such programs, etc. The communication interface 1500 receives data from other devices via a communication network 500 (corresponding to the network N in the embodiment) and sends the data to the CPU 1100, and also transmits data generated by the CPU 1100 to other devices via the communication network 500.

[0104] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0105] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1300. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1300 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0106] For example, when the computer 1000 functions as the information processing device 10, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1300 to realize the functions of the control unit 40. The HDD 1400 also stores various data in the storage device of the information processing device 10. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0107] [8. Other] 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 implemented in other forms that include the embodiments described in the Disclosure of the Invention section and that have undergone various modifications and improvements based on the knowledge of those skilled in the art.

[0108] Furthermore, the information processing device 10 described above can flexibly change its configuration, for example, by calling an external platform or the like using an API (Application Programming Interface) or network computing, depending on the function.

[0109] Furthermore, the term "unit" in the claims can be read as "means" or "circuit," etc. For example, a reception unit can be read as a reception means or a reception circuit. [Explanation of symbols]

[0110] 10. Information processing equipment 20 Communications Department 30 Storage section 31 User Information Database 32 Content Information Database 33 Rules Database 34 Model Database 40 Control Unit 41 Reception 42 Acquisition Department 43 Estimation part 44 Providing Department 100 user terminals

Claims

1. a receiving unit that receives, from a user, a designation to highlight a part of content displayed on a screen of a terminal device used by the user; an acquisition unit that acquires behavior information indicating the user's behavior; an estimation unit that estimates a factor that caused the user to specify highlighting for a part of the content based on the behavior information acquired by the acquisition unit; An information processing device comprising:

2. The estimation unit The factor is estimated based on the behavior information indicating the behavior of the user before specifying the highlighting.