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

Abstract

We will deliver a cover article based on the original article. [Solution] The information processing device according to the present invention is characterized by comprising: an acquisition unit that acquires an original article to be used as the source article; an article content analysis unit that analyzes the content of the original article; a cover matching processing unit that matches cover posters based on the analysis results of the content of the original article; an submission acceptance unit that accepts submissions of cover articles based on the original article from cover posters; and a distribution unit that distributes the submitted cover articles.

Description

Technical Field

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

Background Art

[0002] A technology for distributing image information related to the content of an electronic article to a user terminal has been disclosed (see Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the above conventional technology only creates a summary sentence consisting of multiple lines that summarizes the content of the article from the main text of the article included in the electronic article. Therefore, for example, it is not possible to distribute a cover article based on the original article. There is room for improvement in this regard.

[0005] The present application has been made in view of the above, and an object thereof is to distribute a cover article based on the original article.

Means for Solving the Problems

[0006] The information processing apparatus according to the present application includes an acquisition unit that acquires an original article that is a source article, an article content analysis unit that analyzes the content of the original article, a cover matching processing unit that performs matching of a cover contributor based on the analysis result of the content of the original article, a submission reception unit that accepts a submission of a cover article based on the original article from the cover contributor, and a distribution unit that distributes the submitted cover article, and is characterized by including these components.

Effects of the Invention

[0007] According to one embodiment of the system, a cover article based on the original article can be distributed. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is an explanatory diagram showing an overview of the information processing system according to the embodiment. [Figure 2] Figure 2 is an explanatory diagram illustrating the overview of the articles that should be read now. [Figure 3] Figure 3 is an explanatory diagram illustrating the overview of providing cover articles based on original articles. [Figure 4] Figure 4 is an explanatory diagram illustrating the overview of content generation related to "What Day Is It Today?" for your favorite idol. [Figure 5] Figure 5 shows an example of the configuration of a terminal device according to this embodiment. [Figure 6] Figure 6 shows an example of the configuration of a server device according to the embodiment. [Figure 7] Figure 7 shows the details of the configuration of the server device according to this embodiment. [Figure 8] Figure 8 is a flowchart showing the process for generating a summary of trending words. [Figure 9] Figure 9 is a flowchart showing the process for providing articles that you should read now. [Figure 10] Figure 10 is a flowchart showing the procedure for providing a cover article based on the original article. [Figure 11] Figure 11 is a flowchart showing the content generation process for "What Day Is It Today?" related to your favorite idol. [Figure 12] Figure 12 shows an example of a hardware configuration. [Modes for carrying out the invention]

[0009] The following describes in detail, with reference to the drawings, embodiments for implementing the information processing device, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments"). Note that these embodiments do not limit the information processing device, information processing method, and information processing program according to the present application. Furthermore, the same parts are denoted by the same reference numerals in the following embodiments, and redundant descriptions are omitted.

[0010] [1. Overview of the Information Processing System] First, with reference to Figure 1, an overview of the information processing system according to the embodiment will be described. Figure 1 is an explanatory diagram showing an overview of the information processing system according to the embodiment. As shown in Figure 1, the information processing system 1 according to the embodiment includes a terminal device 10 and a server device 100. The terminal device 10 and the server device 100 are connected to each other via a network N, either by wired or wireless means, enabling communication between them. This allows the terminal device 10 to cooperate with the server device 100. The network N is, for example, a LAN (Local Area Network), a WAN (Wide Area Network), or the Internet.

[0011] Terminal device 10 is an information processing device used by user U. For example, terminal device 10 may be a smart device such as a smartphone or tablet, or a PC (Personal Computer) such as a desktop or notebook (laptop). Alternatively, terminal device 10 may be a mobile phone such as a feature phone, a PDA (Personal Digital Assistant), a game console or AV equipment with communication functions, an information appliance or digital appliance, a car navigation system, a smartwatch or head-mounted display (HDD), a wearable device such as smart glasses, or an IoT (Internet of Things) compatible house or building, car, home appliance, electronic device, etc.

[0012] In this embodiment, the terminal device 10 is a smart device such as a smartphone or a tablet terminal used by the user U, and is a portable terminal device that can communicate with an arbitrary server device via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: the 5th generation mobile communication system), Bluetooth (registered trademark), or a wireless LAN. Further, the terminal device 10 has a screen such as a liquid crystal display and has a screen having a touch panel function, and accepts various operations on display data such as content, such as a tap operation, a slide operation, and a scroll operation, by a finger, a stylus, or the like from the user U. Note that an operation performed on the area of the screen where the content is displayed may be regarded as an operation on the content. Also, the terminal device 10 may be not only a smart device but also an information processing device such as a desktop PC or a notebook PC.

[0013] The server device 100 is, for example, a computer such as a PC or a blade server, or a mainframe or a workstation. Note that the server device 100 may be realized by cloud computing.

[0014] In this embodiment, the server device 100 is an information processing device that cooperates with the terminal device 10 of each user U and provides various API (Application Programming Interface) services and various data for the terminal device 10 of each user U with respect to various applications (hereinafter referred to as apps), and is realized by a computer, a cloud system, or the like.

[0015] Further, the server device 100 may be an information processing device that provides some online service to the terminal device 10 of each user U. For example, as an online service, the server device 100 provides services such as Internet connection, search service, advertisement distribution service, chat service, interactive service by voice, image, video, etc., SNS (Social Networking Service), electronic commerce (EC: Electronic Commerce), electronic payment, online game, online banking, online trading, accommodation and ticket reservation, video and music distribution, news, map, route search, route guidance, route information, operation information, weather forecast, etc. In fact, the server device 100 may cooperate with various servers that provide the above online services to mediate the online service or be responsible for the processing of the online service.

[0016] In addition, the server device 100 can acquire user information regarding the user U. For example, as user information, the server device 100 acquires information (attribute information) regarding the attributes of the user U, such as the gender, age, and residential area of the user U. Further, the server device 100 can acquire information regarding attributes such as the demographics (demographic attributes), psychographics (psychological attributes), geographics (geographical attributes), and behavioral (behavioral attributes) of the user U. Also, the server device 100 may acquire, as user information, the segment or persona (persona) to which the user U belongs in the field of marketing. Then, the server device 100 stores and manages information (attribute information) regarding the attributes of the user U together with the identification information (user ID, etc.) indicating the user U.

[0017] Furthermore, the server device 100 acquires various historical information (log data) indicating user U's actions from user U's terminal device 10, or from various servers based on the user ID, etc. For example, the server device 100 acquires location history, which is the history of user U's location and date and time, from the terminal device 10. The server device 100 also acquires search history, which is the history of search queries entered by user U, from the search server (search engine). The server device 100 also acquires browsing history, which is the history of content viewed by user U, from the content server. The server device 100 also acquires purchase history (payment history), which is the history of user U's product purchases and payment processing, from the e-commerce server or payment processing server. The server device 100 may also acquire listing history and sales history, which are the history of user U's listings on the marketplace, from the e-commerce server or payment processing server. The server device 100 also acquires posting history, which is the history of user U's posts, from posting servers that provide word-of-mouth posting services or SNS servers. The various servers mentioned above may also be the server device 100 itself. In other words, the server device 100 may function as the various servers mentioned above.

[0018] Furthermore, the number of devices included in the information processing system 1 shown in Figure 1 is not limited to those illustrated. For example, in Figure 1, only one terminal device 10 is shown for the sake of illustration, but this is merely an example and not limiting; there may be two or more.

[0019] [2. AI-powered article generation and provision] In this embodiment, the server device 100 generates and provides articles (content) using AI (Artificial Intelligence) such as GPT (Generative Pre-trained Transformer). GPT is a text generation AI and a language model capable of generating text using natural language processing. Note that GPT is just one example. Other models, such as Large Language Models (LLM), may also be used.

[0020] [2-1. Generating a summary of trending words] First, please refer to Figure 1 to explain the generation of trend word summaries.

[0021] For example, as shown in Figure 1, the server device 100 selects trending words based on comments (posted information) submitted to an article (step S1). For example, the server device 100 selects keywords that are being discussed in the comments section as trending words.

[0022] In this case, the server device 100 selects keywords that appear in the top 10 comments as trending words. Alternatively, the server device 100 refers to the comment sections of 2 to 5 articles and selects keywords that appear in each comment (within 24 hours) above a threshold as trending words. Alternatively, the server device 100 selects keywords that appear in the comment timeline (timeline: TL) as trending words. The server device 100 may also segment the submitted comments by keyword and select keywords whose increase rate exceeds a predetermined threshold as trending words.

[0023] The server device 100 may accept keyword input from user U. The server device 100 may also obtain keywords from comments posted by each poster using the comment API.

[0024] Next, the server device 100 collects (collects) the selected trend words and corresponding comments (step S2). For example, the server device 100 collects comments that contain the selected trend words. At this time, the server device 100 may collect comments in the order of the comment timeline or in the order of recommendations for article details.

[0025] The server device 100 may periodically collect comments corresponding to predetermined keywords, rather than selected trending words. Alternatively, the server device 100 may collect comments associated with keywords using a comment API.

[0026] Next, the server device 100 performs filtering to exclude comments with specific content from the collected comments (step S3). For example, the server device 100 filters out comments from the collected comments that contain offensive or inappropriate words or expressions. At this time, the server device 100 may calculate an offensiveness index indicating the degree of offensiveness of the content of the collected comments or keywords contained in the comments, and exclude comments whose offensiveness index is above a threshold.

[0027] Next, the server device 100 generates a prompt based on the remaining comments after filtering (step S4). For example, the server device 100 generates a prompt indicating that it will generate a summary article about the topic in the comments section, including the theme (title), summary, frequency of keywords, public reaction, the starting comment timeline, and disclaimers.

[0028] Next, the server device 100 inputs the generated prompts into the AI ​​to generate a summary article about the trending words (step S5). At this time, the server device 100 uses the AI ​​to automatically generate a description (summary) of the trending words and the events corresponding to them from the collected comments and the generated prompts. At this time, the server device 100 may also generate a summary of the comments as a representation of everyone's reactions. The server device 100 may also generate the summary article by combining the AI ​​with a summary article generation patch.

[0029] Next, the server device 100 displays the summary article related to the generated trend word on the screen for human review by an operator (checker) (step S6). At this time, the server device 100 may output the generated summary article to the operator's terminal device 10. The operator visually checks whether the generated summary article meets the distribution conditions. For example, the operator checks whether the generated summary article is a specific scoop that does not meet the conditions. The operator also checks whether the content of the generated summary article is consistent with the content of the user comments in the input data. Furthermore, the operator checks whether the content of the generated summary article does not fall under any specific NG conditions. The operator may be a specific user, such as a pre-selected expert. The server device 100 may also perform the check of the generated summary article using a model or AI that has been trained on the operator's content check.

[0030] Next, the server device 100 submits the generated summary article to the submission tool in response to the operator's submission operation (step S7). At this time, if the generated summary article meets the distribution conditions, the operator submits it to the submission tool. Conversely, if the generated summary article does not meet the distribution conditions, the operator does not submit it to the submission tool and discards (discards) the generated summary article.

[0031] Next, the server device 100 distributes the generated summary article (step S8). For example, the server device 100 provides the generated summary article to those who wish to view it. The server device 100 may also make the generated summary article publicly available to an unspecified number of people.

[0032] [2-2. Providing articles you should read now] Next, we will explain how to provide articles that you should read now, referring to Figure 2. Figure 2 is an explanatory diagram that shows an overview of how to provide articles that you should read now.

[0033] For example, as shown in Figure 2, the server device 100 accepts the submission (entry) of an article from the poster to the user U (step S11). At this time, the server device 100 may also receive news articles from the news article distributor.

[0034] Next, the server device 100 acquires a history of user U's actions (step S12). For example, the server device 100 acquires various historical information indicating user U's actions. At this time, the server device 100 may also acquire attribute information of user U.

[0035] Next, the server device 100 determines, based on the user U's behavior history, which of the multiple articles provided to user U should read now (immediately recommended articles) (step S13). At this time, the server device 100 may calculate a score (or index) for each article indicating the degree to which it should be read now, compare the scores of each article, and determine that articles within a predetermined ranking (for example, within the top 10) should be read now. Alternatively, the server device 100 may compare the score of each article with a threshold, determine whether the score of each article is above the threshold, and determine that articles whose scores are above the threshold should be read now.

[0036] Furthermore, the server device 100 may determine whether an article is worth reading based on its recency. For example, the server device 100 may determine that an article is worth reading if it is recent. The recency of an article may be determined by the number of days elapsed since the article's publication date (or posting date), or by the date of the latest comment.

[0037] Alternatively, the server device 100 may determine that an article should be read as its lifespan approaches its end. The lifespan of an article may be the last day of the article's publication period, or a predetermined number of days elapsed since the article's publication date (or posting date). In this case, the server device 100 may calculate or change a score indicating how much the article should be read now, according to the number of days remaining until the article's lifespan ends.

[0038] Furthermore, the server device 100 may estimate user U's interests from user U's behavior history and determine whether an article is worth reading now by combining the recency of the news with the interests of user U. For example, the server device 100 may determine that an article that matches user U's interests and is nearing the end of its lifespan is worth reading now. Alternatively, the server device 100 may determine that a new article, even if it is of little interest to user U, is worth reading now.

[0039] Furthermore, the server device 100 may also determine articles that do not need to be read immediately or that can be read later (articles recommended to postpone reading, articles recommended to be read later), not just articles that should be read now. For example, the server device 100 may determine that articles that are desirable for user U to read but have low priority, or articles with plenty of time left in their lifespan, do not need to be read immediately.

[0040] Next, the server device 100 highlights the thumbnails of articles that it has determined to be articles that should be read now, from among the thumbnails of multiple articles provided to user U in the comment timeline (step S14). At this time, the server device 100 may change the display method for each article according to a score indicating the degree to which it should be read now. That is, the server device 100 may use different display methods for highlighting the thumbnails of articles that should be read now, depending on the score. The highlighting may be in the form of a speech bubble or an icon. In addition, the server device 100 may also highlight articles that do not need to be read immediately in a different display method that is distinguishable from the articles that should be read now.

[0041] Furthermore, the server device 100 generates and displays reasons for reading the article using an AI such as GPT (step S15). In practice, the generation of reasons for reading the article may be performed simultaneously with the determination of which article should be read now. That is, the server device 100 may perform the process in step S15 together with or in parallel with the process in step S13. In this case, the server device 100 may display the reasons for reading the article together with the article to be read now. The display format is arbitrary. For example, the server device 100 may display the reasons for reading the article in a speech bubble for the article to be read now, or it may display the reasons for reading the article in a modal / popup / dialog format when the article or speech bubble to be read now is selected or the mouse hovers over it.

[0042] Next, the server device 100 provides user U with the article to read that corresponds to the highlighted thumbnail selected by user U (step S16).

[0043] Next, the server device 100 highlights a portion of the content of the article that user U has opened and is currently reading (step S17). For example, the server device 100 highlights the content that explains why the article should be read and the key points that should be read. The server device 100 may also indicate "where the most interesting points are located" when user U opens the article.

[0044] In this way, the server device 100 provides a function that displays a message indicating that the user should read an article with a high degree of matching, along with the reasons why. This effectively recommends articles that match the user's interests and improves engagement.

[0045] [2-3. Providing cover articles based on original articles] Next, we will explain the provision of cover articles based on the original article, referring to Figure 3. Figure 3 is an explanatory diagram showing an overview of the provision of cover articles based on the original article. A cover article is an article that adds supplementary information, counterarguments, or new information to the original article, and is created as a result of the original article.

[0046] For example, as shown in Figure 3, the server device 100 retrieves the original article (source article) (step S21). For example, the server device 100 accepts submissions of original articles from contributors. Alternatively, the server device 100 may select original articles from among the published and distributed articles. For example, the server device 100 may select articles with a large number of views or comments, or articles that are rapidly increasing in popularity, as original articles.

[0047] Next, the server device 100 analyzes the content of the original article (step S22). For example, the server device 100 analyzes the title, body text, images, or videos of the original article. At this time, the server device 100 analyzes the theme, genre, style, tone, etc. of the original article. The server device 100 may also analyze the author, characters, source (publisher, etc.), etc. of the original article.

[0048] Next, the server device 100 matches cover contributors based on the analysis results of the original article's content (step S23). At this time, the server device 100 identifies accounts that can create new value that is not present in the original article. For example, the server device 100 identifies accounts that have a track record of posting and distributing articles in the same or similar genre as the original article, based on the content and content evaluation. The server device 100 also identifies accounts that have different subject attributes (expertise, information, perspective, etc.) from the original article's contributor. The server device 100 then decides on the identified accounts as candidates for cover contributors.

[0049] Next, the server device 100 requests the candidate cover posters obtained as a result of the matching process to post cover articles based on the original article (step S24). There may be multiple candidate cover posters.

[0050] Next, if a candidate for cover poster accepts the request, the server device 100 officially approves them as a cover poster and sets them as such (step S25). At this time, the server device 100 may register or list the approved cover posters in a database. The server device 100 may then extract and select cover poster candidates from the database or list during the matching process. In other words, the server device 100 may extract and select cover poster candidates from past cover posters. Note that there may be multiple people contributing to the cover art.

[0051] Next, the server device 100 accepts the submission (input) of the created cover article from the cover contributor (step S26). Only cover contributors are allowed to create cover articles based on the original article. In other words, not just anyone can create a cover article. At this time, the server device 100 may make the cover article content identifiable as a cover article and accept only cover article submissions (inputs) from approved cover contributors.

[0052] Furthermore, the server device 100 may set (restrict) the scope of cover articles that can be created for each cover contributor. For example, the server device 100 may set the scope of cover articles that can be created for a cover contributor according to the subject attributes of that cover contributor (expertise, information, perspective, etc.).

[0053] Next, the server device 100 distributes the submitted cover article (step S27). For example, the server device 100 provides the summary article to those who wish to view the cover article. The server device 100 may also make the cover article publicly available to an unspecified number of people.

[0054] Next, the server device 100 performs a linking (association) between the original article and the cover article (step S28). At this time, the server device 100 may link the original article and the cover article to each other. Alternatively, the server device 100 may create a tree structure in which the original article and the cover article have a hierarchical parent-child relationship. Or, the server device 100 may simply link the original article and the cover article. In practice, the server device 100 may perform the process in step S28 before the process in step S27.

[0055] In this way, server device 100 accepts submissions (contributions) of original content from the first contributor. Server device 100 also accepts submissions of cover content from the second contributor, based on the first contributor's original content. Finally, server device 100 publishes the cover content.

[0056] [2-4. Creating content related to "What Day Is It Today?" for your favorite idol / celebrity] Next, please refer to Figure 4 to explain how to generate content related to "What Day Is It Today?" for your favorite idol. Figure 4 is an explanatory diagram that shows an overview of how to generate content related to "What Day Is It Today?" for your favorite idol.

[0057] For example, as shown in Figure 4, the server device 100 accepts article submissions (inputs) from contributors (step S31). At this time, the server device 100 may also receive news articles from news article distributors.

[0058] Next, the server device 100 extracts and lists information from the body of the posted article that indicates the "target" (who, to whom), "date" (when), and "event" (what happened, what occurred) (step S32). At this time, the server device 100 may also train the AI ​​with the listed information (listed information). Note that the date may be a day and time. That is, if the time of day in which the event occurred is also known, the time may be included in addition to the date. Furthermore, it is not limited to a date, but may also be a specific public holiday (holiday) whose date differs from year to year, or the day of a specific event (Christmas, Halloween, Valentine's Day, etc.), or a specific day of the week in a specific month (for example, the second Saturday of June).

[0059] Next, the server device 100 determines the reliability of the information about the subject based on the content of the posted articles and the trends of the distribution accounts (step S33). At this time, the server device 100 may determine the reliability by comparing the list information with list information of multiple other articles about the same subject. The server device 100 may also calculate the reliability of the information about the subject.

[0060] Next, if the reliability level is above a threshold, the server device 100 requests specific users to verify the facts of the listed information (step S34). For example, the server device 100 selects users with high expertise in the subject, users who have a relationship with the subject, users who are compatible with the subject, and users who have a strong fan attribute to the subject, and requests the selected users to verify the facts of the listed information. At this time, the server device 100 may score (quantify) the expertise in the subject, the relationship (relevance) to the subject, the compatibility with the subject, and the fan attribute to the subject, and select users whose scores are above a threshold. Note that there may be multiple specific users (selected users). In practice, the process in step S33 (determining reliability) and the process in step S34 (requesting fact verification) may be performed in parallel, consecutively, or in any order.

[0061] Next, if the server device 100 receives a response from the user to the request for fact-checking and determines that there is no problem, it determines that the listed information is a past event relating to the official subject (step S35). At this time, the server device 100 may add information regarding reliability to the listed information. Also, if the user's response contains supplements or corrections to the listed information, the server device 100 may reflect the supplements or corrections in the listed information.

[0062] In practice, after step S33, the server device 100 may determine that the listed information is a past event relating to a formal subject if the confidence level is above a threshold. In this case, the processing in steps S34 and S35 is unnecessary. That is, the server device 100 may perform only a confidence level determination without performing fact-checking by a specific user.

[0063] Alternatively, the server device 100 may skip the processing in step S33 and immediately after step S32 request a specific user to verify the facts of the listed information in step S34. In other words, the server device 100 may skip the confidence level determination and only perform fact-checking by a specific user.

[0064] Next, the server device 100 acquires a history of user U's actions (step S36). For example, the server device 100 acquires various historical information indicating user U's actions. At this time, the server device 100 may also acquire attribute information of user U.

[0065] Next, the server device 100 estimates user U's interests (favorites) from user U's behavior history (step S37). User U's interests (favorites) are objects that user U is interested in or concerned with. For example, user U's interests (favorites) are not limited to people or groups such as idols or actors, or teams such as baseball or soccer, but may also be works such as manga, anime, novels, dramas, or movies, objects of hobbies and preferences such as cars or trains, specific genres such as music or fashion, specific events held on a fixed day each year, or any other items or events. In practice, the processes in steps S36 and S37 may be performed in parallel with the processes in steps S31 to S35, or they may be performed before the processes in steps S31 to S35.

[0066] Next, the server device 100 matches the "target" in the list information with the user U's interests (favorites), and if a match is found, it delivers information about past events related to the target at the same time as the "date" in the list information (step S38). For example, the server device 100 may deliver information about past events related to the target every year on the same date (time) as the "date" in the list information. Also, if the server device 100 knows not only the date but also the time when the past event occurred, it may deliver information about past events related to the target at the time when the past event occurred. In this case, the server device 100 may have the AI, which has been trained on the list information, generate text about past events related to the target. The delivered past events may be displayed on the user U's terminal device 10 in the form of a modal / popup / dialog, etc.

[0067] Furthermore, the server device 100 may present users U with highlights and points of interest regarding past events related to the subject. For example, the server device 100 may present users U with past "highlights of matches" or "memorable scenes from movies" related to the subject. This will allow users to enjoy the subject more deeply.

[0068] For example, if user U's area of ​​interest (favorite) is "Baseball Team A," the server device 100 will notify U with the title "What Day Is It for Baseball Team A Today?" and include information such as "Three years ago on September 18th, they played against another team B and won 4-1" and "Highlights: Starting pitcher XX held the opponent scoreless for 6 innings, and in the 8th inning, XX hit a walk-off home run."

[0069] Next, the server device 100 receives a setting from user U regarding the distribution of information about past events related to the target (step S39). In the initial state (default), the distribution of information about user U's interests (favorites) and past events related to those interests is set, and user U does not need to do anything if they wish to continue receiving the distribution. Conversely, if user U wishes to stop receiving the distribution, the server device 100 accepts a setting to stop the distribution. The server device 100 may also accept a setting (change) from user U regarding the time period during which they wish to receive the distribution.

[0070] At this time, the server device 100 may accept settings regarding user U's interests (favorites). For example, the server device 100 may accept settings regarding other objects (favorites) that user U is interested in. The server device 100 may also accept settings for changing user U's interests (favorites). Furthermore, the server device 100 may classify objects (favorites) by genre or category, and allow user U to set objects (favorites) for each genre or category.

[0071] Furthermore, the server device 100 may collect news information on specific dates related to user U's interests. Based on the collected news information on specific dates, the server device 100 may generate content related to user U's interests on specific dates.

[0072] This allows the server device 100 to provide a function that notifies users at predetermined times (on specific dates or days of the week, or daily) of "what happened in their area of ​​interest on this day several years ago," specializing in their favorite genres or categories, thus providing users with the enjoyment of looking back on past events related to their favorite genres or categories. Users can customize the settings based on their own interests.

[0073] [3. Example of terminal device configuration] Next, the configuration of the terminal device 10 will be described using Figure 5. Figure 5 is a diagram showing an example of the configuration of the terminal device 10 according to this embodiment. As shown in Figure 5, the terminal device 10 comprises a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40.

[0074] (Communications Section 11) The communication unit 11 is connected to the network N by wire or wireless connection and transmits and receives information to and from the server device 100 via the network N. For example, the communication unit 11 can be implemented using a NIC (Network Interface Card) or an antenna.

[0075] (Display section 12) The display unit 12 is a display device that displays various information such as location information. For example, the display unit 12 may be a liquid crystal display (LCD) or an organic electro-luminescent display (OLED). The display unit 12 may also be a touch panel display, but is not limited to this.

[0076] (Input section 13) The input unit 13 is an input device that receives various operations from the user U. For example, the input unit 13 has buttons for inputting characters, numbers, etc. The input unit 13 may also be an input / output port (I / O port) or a USB (Universal Serial Bus) port. If the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13. The input unit 13 may also be a microphone that receives voice input from the user U. The microphone may be wireless.

[0077] (Positioning unit 14) The positioning unit 14 receives signals (radio waves) transmitted from GPS (Global Positioning System) satellites and, based on the received signals, acquires position information (e.g., latitude and longitude) indicating the current position of the terminal device 10. In other words, the positioning unit 14 determines the position of the terminal device 10. Note that GPS is just one example of a GNSS (Global Navigation Satellite System).

[0078] Furthermore, the positioning unit 14 can determine its position using various methods other than GPS. For example, the positioning unit 14 may use various communication functions of the terminal device 10 to determine its position as an auxiliary positioning means for position correction, etc., as described below.

[0079] (Wi-Fi positioning) For example, the positioning unit 14 determines the location of the terminal device 10 by utilizing the Wi-Fi® communication function of the terminal device 10 and the communication network provided by each telecommunications company. Specifically, the positioning unit 14 determines the location of the terminal device 10 by performing Wi-Fi communication, etc., and determining the distance to nearby base stations and access points.

[0080] (Beacon positioning) Furthermore, the positioning unit 14 may determine the location using the Bluetooth® function of the terminal device 10. For example, the positioning unit 14 determines the location of the terminal device 10 by connecting to a beacon transmitter connected via the Bluetooth® function.

[0081] (Geomagnetic positioning) Furthermore, the positioning unit 14 determines the position of the terminal device 10 based on the geomagnetic pattern of the structure, which has been measured in advance, and the geomagnetic sensor provided by the terminal device 10.

[0082] (RFID positioning) Furthermore, if, for example, the terminal device 10 is equipped with an RFID (Radio Frequency Identification) tag function equivalent to that of a contactless IC card used at a train station ticket gate or in a store, or if it is equipped with a function to read RFID tags, the location where it was used will be recorded along with the information on the payment or other transactions made by the terminal device 10. The positioning unit 14 may determine the location of the terminal device 10 by acquiring such information. Alternatively, the location may be determined by an optical sensor or infrared sensor equipped in the terminal device 10.

[0083] The positioning unit 14 may, if necessary, determine the position of the terminal device 10 using one or a combination of the positioning means described above.

[0084] (Sensor unit 20) The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. The connection can be wired or wireless. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices or wireless devices. In the example shown in Figure 5, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, a barometric pressure sensor 23, a temperature sensor 24, a sound sensor 25, a light sensor 26, a magnetic sensor 27, and an image sensor (camera) 28.

[0085] The sensors 21-28 described above are merely examples and not limiting. In other words, the sensor unit 20 may be configured to include some of the sensors 21-28, or it may include other sensors such as humidity sensors in addition to or instead of the sensors 21-28.

[0086] The acceleration sensor 21 is, for example, a 3-axis acceleration sensor and detects the physical movement of the terminal device 10, such as its direction of movement, velocity, and acceleration. The gyro sensor 22 detects the physical movement of the terminal device 10, such as its tilt in the three axes, based on its angular velocity. The barometric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

[0087] Since the terminal device 10 is equipped with the acceleration sensor 21, gyroscope 22, barometric pressure sensor 23, etc., it becomes possible to determine the position of the terminal device 10 using technologies such as pedestrian dead-reckoning (PDR) that utilize these sensors 21 to 23. This makes it possible to obtain indoor location information that is difficult to obtain with positioning systems such as GPS.

[0088] For example, a pedometer using an accelerometer 21 can calculate the number of steps, walking speed, and distance walked. Additionally, a gyroscope 22 can be used to determine the user U's direction of movement, gaze direction, and body tilt. Furthermore, the barometric pressure detected by the barometric pressure sensor 23 can be used to determine the altitude and floor number of the user U's terminal device 10.

[0089] The temperature sensor 24 detects, for example, the ambient temperature around the terminal device 10. The sound sensor 25 detects, for example, the ambient sound around the terminal device 10. The light sensor 26 detects the ambient illumination around the terminal device 10. The magnetic sensor 27 detects, for example, the Earth's magnetic field around the terminal device 10. The image sensor 28 captures an image of the area around the terminal device 10.

[0090] The aforementioned pressure sensor 23, temperature sensor 24, sound sensor 25, light sensor 26, and image sensor 28 can detect the surrounding environment and conditions of the terminal device 10 by detecting atmospheric pressure, temperature, sound, and illuminance, respectively, and by capturing images of the surroundings. Furthermore, it becomes possible to improve the accuracy of the location information of the terminal device 10 based on the surrounding environment and conditions.

[0091] (Control Unit 30) The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit) or MPU (Micro Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), input / output ports, and various circuits. Alternatively, the control unit 30 may be composed of hardware such as an integrated circuit (ASIC) or FPGA (Field Programmable Gate Array). The control unit 30 includes a transmission unit 31, a reception unit 32, and a processing unit 33.

[0092] (Transmitter 31) The transmission unit 31 can transmit various information, such as information input by the user U using the input unit 13, various information detected by sensors 21-28 mounted on or connected to the terminal device 10, and location information of the terminal device 10 determined by the positioning unit 14, to the server device 100 via the communication unit 11.

[0093] (Receiver 32) The receiving unit 32 can receive various information provided by the server device 100, as well as requests for various information from the server device 100, via the communication unit 11.

[0094] (Processing 33) The processing unit 33 controls the entire terminal device 10, including the display unit 12. For example, the processing unit 33 can output and display various information transmitted by the transmission unit 31 and various information received from the server device 100 by the reception unit 32 to the display unit 12.

[0095] (Storage unit 40) The storage unit 40 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or by storage devices such as HDD (Hard Disk Drive), SSD (Solid State Drive), and optical discs. Various programs and various data are stored in this storage unit 40.

[0096] [4. Example of Server Device Configuration] Next, the configuration of the server device 100 according to the embodiment will be described using Figures 6 and 7. Figure 6 is a diagram showing an example of the configuration of the server device 100 according to the embodiment. Figure 7 is a diagram showing the details of the configuration of the server device according to the embodiment. As shown in Figure 6, the server device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

[0097] (Communications Department 110) The communication unit 110 is implemented, for example, by a NIC (Network Interface Card). The communication unit 110 is also connected to the network N by wired or wireless connection.

[0098] (Storage unit 120) The storage unit 120 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or by storage devices such as HDDs, SSDs, and optical discs. The storage unit 120 may store identification information (such as a user ID) indicating user U, as well as attribute information and history information (log data) of user U.

[0099] (Control unit 130) The control unit 130 is a controller, and is realized by various programs (corresponding to an example of an information processing program) stored in the internal storage device of the server device 100, such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), ASIC (Application Specific Integrated Circuit), or FPGA (Field Programmable Gate Array), executing them using a storage area such as RAM as the working area. In the example shown in Figure 6, the control unit 130 includes an acquisition unit 131, a summary article generation processing unit 132, a recommended article presentation unit 133, a cover article creation processing unit 134, a target event notification unit 135, a distribution unit 136, and a setting unit 137.

[0100] (Acquisition part 131) The acquisition unit 131 acquires the search query entered by the user U. For example, when the user U enters a search query into a search engine or the like and performs a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110. In other words, the acquisition unit 131 acquires the keyword entered by the user U into the search box of a search engine, website, or application via the communication unit 110.

[0101] Furthermore, the acquisition unit 131 acquires user information about user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information (such as user ID), location information, and attribute information of user U from user U's terminal device 10. The acquisition unit 131 may also acquire identification information and attribute information of user U when user U is registered. The acquisition unit 131 then stores the user information in the storage unit 120.

[0102] Furthermore, the acquisition unit 131 acquires various historical information (log data) indicating the user U's actions via the communication unit 110. In other words, the acquisition unit 131 acquires a history of the user U's actions. For example, the acquisition unit 131 acquires various historical information indicating the user U's actions from the user U's terminal device 10, or from various servers based on the user ID, etc. The acquisition unit 131 then stores the various historical information in the storage unit 120.

[0103] Furthermore, the acquisition unit 131 acquires articles, comments, etc., via the communication unit 110. As shown in Figure 7, the acquisition unit 131 also functions as a collection unit 131A, a keyword reception unit 131B, and a submission reception unit 131C. That is, the acquisition unit 131 has a collection unit 131A, a keyword reception unit 131B, and a submission reception unit 131C.

[0104] (Collection Unit 131A) The collection unit 131A collects comments that contain the selected trend words.

[0105] (Keyword reception section 131B) The keyword reception unit 131B receives keyword input from user U.

[0106] (Submission Reception Section 131C) The submission reception unit 131C accepts article submissions (article submissions) via the communication unit 110. For example, the submission reception unit 131C accepts submissions of original articles that will serve as source articles. The submission reception unit 131C also accepts submissions of cover articles based on the original article from cover contributors. For example, the submission reception unit 131C accepts submissions of cover articles created by cover contributors who have accepted the request. In this case, the submission reception unit 131C may also accept submissions of cover articles created by officially approved cover contributors.

[0107] (Summary article generation processing unit 132) The summary article generation processing unit 132 includes a selection unit 132A, a filter processing unit 132B, a summary generation unit 132C, and a check processing unit 132D.

[0108] (Selection section 132A) The selection unit 132A selects trending words based on keywords contained in comments posted in the comment section. For example, the selection unit 132A selects trending words based on keywords that appear in the comment timeline.

[0109] (Filter processing unit 132B) The filter processing unit 132B performs filtering to exclude comments containing specific content from the collected comments.

[0110] (Summary generation unit 132C) The summary generation unit 132C generates summary articles related to trending words from the collected comments. Alternatively, instead of generating summary articles related to trending words, the summary generation unit 132C generates summary articles related to keywords entered by user U or predefined keywords collected periodically, from the collected comments.

[0111] Furthermore, the summary generation unit 132C generates prompts from the collected comments and feeds these prompts into the AI ​​to generate summary articles related to trending words.

[0112] Furthermore, the summary generation unit 132C generates summary articles related to trending words based on the remaining comments after filtering.

[0113] (Check processing unit 132D) The checking processing unit 132D displays the generated summary article on the screen and processes it for human review. Then, the submission acceptance unit 131C accepts the summary article after it has undergone content review.

[0114] (Recommended Articles Section 133) The recommended article presentation unit 133 includes an interest estimation unit 133A, a recommended article determination unit 133B, a recommendation reason generation unit 133C, and a display control unit 133D.

[0115] (Interest estimation unit 133A) The interest estimation unit 133A estimates user U's interests from the user U's behavioral history.

[0116] (Recommended article determination unit 133B) The recommended article determination unit 133B determines which articles should be read now (immediately recommended articles) from among the articles offered to user U, based on user U's behavior history. For example, the recommended article determination unit 133B determines which articles should be read now from among the articles offered to user U, based on user U's interests estimated from user U's behavior history.

[0117] Furthermore, the recommended article determination unit 133B determines whether an article should be read now based on its recency. Alternatively, the recommended article determination unit 133B determines whether an article should be read now based on its lifespan. It also determines whether an article should be read now by combining its recency with the user U's interests. Additionally, the recommended article determination unit 133B calculates a score for each article indicating its degree of readability, and determines articles with a score above a threshold as articles that should be read now.

[0118] Furthermore, the recommended article determination unit 133B may also determine which articles provided to user U are suitable for later reading (articles recommended to postpone reading, articles recommended to read later).

[0119] (Recommendation reason generation unit 133C) The recommendation reason generation unit 133C uses AI to generate reasons why an article should be read now, based on its determination as such.

[0120] (Display control unit 133D) The display control unit 133D highlights the thumbnails of articles that it has determined to be articles that should be read now, from among the thumbnails of articles provided to the user U. At this time, the display control unit 133D may also display the generated reason why the article should be read, in addition to highlighting the thumbnail of the article that should be read now. Furthermore, the display control unit 133D may change the display mode of the highlighting of the thumbnail of the article that should be read now according to the score.

[0121] Furthermore, when the user U selects a thumbnail of an article that has been determined to be an article to be read, the display control unit 133D highlights a portion of the article's content (points of interest) when the article is presented to the user U.

[0122] Furthermore, the display control unit 133D may also highlight the thumbnails of articles that have been determined to be articles that can be read later, using a different display method than that used for articles that should be read now.

[0123] (Cover article creation processing unit 134) The cover article creation processing unit 134 includes an article content analysis unit 134A, a cover matching processing unit 134B, and a cover request processing unit 134C.

[0124] (Article Content Analysis Department 134A) Article content analysis unit 134A analyzes the content of the original article.

[0125] (Cover matching processing unit 134B) The cover matching processing unit 134B matches cover contributors based on the analysis results of the original article's content. For example, the cover matching processing unit 134B identifies accounts that can create new value not present in the original article as cover contributors. The cover matching processing unit 134B also identifies accounts that have a track record of publishing articles in the same or similar genre as the original article, based on their content and content evaluation. Furthermore, the cover matching processing unit 134B identifies accounts that have different subject attributes than the original article's contributor as cover contributors.

[0126] (Cover request processing unit 134C) The cover request processing unit 134C requests the candidate cover posters obtained as a result of the matching process to submit a cover article based on the original article.

[0127] (Target Event Notification Section 135) The target event notification unit 135 includes a list processing unit 135A, a confirmation request processing unit 135B, a probability determination unit 135C, a target estimation unit 135D, and a target matching processing unit 135E.

[0128] (Listing processing unit 135A) The list creation processing unit 135A extracts information indicating the subject, date, and event from the body of the article submitted by the poster and creates a list.

[0129] (Confirmation request processing unit 135B) The verification request processing unit 135B requests a specific user to verify the facts of the listed information. For example, the verification request processing unit 135B, acting as a specific user, requests a verification of the facts of the listed information from multiple users who are compatible with user U's interests (favorites). Alternatively, the verification request processing unit 135B, acting as a specific user, requests a verification of the facts of the listed information from multiple users who have a high fan attribute for user U's interests.

[0130] (Accuracy determination unit 135C) The accuracy determination unit 135C determines that the listed information is a past event relating to a formal subject if it receives a response from a specific user to a request for fact-checking and determines that there is no problem.

[0131] Furthermore, the accuracy determination unit 135C calculates the reliability of the listed information based on the content of the article posted by the poster and the trends of the distribution account. If the reliability is above a threshold, it determines that the listed information is a past event related to an official subject.

[0132] (Target estimation unit 135D) The target estimation unit 135D estimates the object of user U's interest (favorite) from the history of user U's actions.

[0133] (Target matching processing unit 135E) The target matching processing unit 135E performs matching between the listed information and the user U's interests (favorites).

[0134] (Distribution section 136) The distribution unit 136 distributes the generated or submitted articles. For example, the distribution unit 136 distributes the generated or submitted summary articles. The distribution unit 136 also distributes the submitted cover articles.

[0135] Furthermore, the distribution unit 136 distributes information about past events related to user U's interests (favorites) on the date the events related to user U's interests occurred. For example, if the distribution unit 136 finds a match between the listed information and user U's interests, it distributes information about past events related to user U's interests on the same date as the listed information.

[0136] (Settings section 137) The settings unit 137 officially approves a candidate for cover poster as a cover poster and sets them as such if they accept the request. The settings unit 137 also sets the scope of cover article creation according to the subject attributes of the cover poster.

[0137] Furthermore, the settings unit 137 links (associates) the original article with the cover article. In addition, the settings unit 137 configures and modifies the distribution of information about past events related to user U's interests (favorites) in response to user U's actions.

[0138] [5. Processing Procedure] Next, the processing procedure by the server device 100 according to the embodiment will be described using Figures 8 to 11. Figures 8 to 11 are flowcharts of the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the server device 100.

[0139] [5-1. Trend word summary generation process procedure] The procedure for generating a trend word summary will be explained with reference to Figure 8. Figure 8 is a flowchart showing the procedure for generating a trend word summary.

[0140] For example, as shown in Figure 8, the selection unit 132A of the server device 100 selects trending words based on keywords included in comments posted in the comment section (step S101). In practice, the keyword reception unit 131B of the server device 100 may receive input of keywords corresponding to trending words from the user U.

[0141] Next, the collection unit 131A of the server device 100 collects comments that contain the selected trend words (step S102). In practice, the collection unit 131A of the server device 100 may periodically collect comments that contain predetermined keywords.

[0142] Next, the filter processing unit 132B of the server device 100 performs filtering to exclude comments with specific content from the collected comments (step S103).

[0143] Next, the summary generation unit 132C of the server device 100 generates a prompt from the remaining comments after filtering, and feeds the prompt to the AI ​​to generate a summary article about the trending word (step S104).

[0144] Next, the check processing unit 132D of the server device 100 displays the generated summary article on the screen and presents it to a designated checker, and performs processing to allow the checker to review the content (step S105).

[0145] Next, the submission reception unit 131C of the server device 100 receives the submission of the summary article after it has been checked by the reviewer (step S106).

[0146] Next, the distribution unit 136 of the server device 100 distributes the submitted summary article (step S107).

[0147] [5-2. Procedure for providing articles that should be read now] Refer to Figure 9 to explain the procedure for providing articles that you should read now. Figure 9 is a flowchart showing the procedure for providing articles that you should read now.

[0148] For example, as shown in Figure 9, the acquisition unit 131 of the server device 100 acquires the history of user U's actions (step S201).

[0149] Next, the interest estimation unit 133A of the server device 100 estimates user U's interests from the history of user U's actions (step S202).

[0150] Next, the recommended article determination unit 133B of the server device 100 determines which articles should be read now (immediately recommended articles) from among the articles provided to user U, based on user U's interests estimated from user U's behavior history and the article's recency or lifespan (step S203).

[0151] Furthermore, the recommended article determination unit 133B of the server device 100 also determines which articles provided to user U can be read later (articles recommended to postpone reading, articles recommended to read later) (step S204).

[0152] Next, the recommendation reason generation unit 133C of the server device 100 uses AI to generate reasons why the article that has been determined to be worth reading should be read (step S205).

[0153] Next, the display control unit 133D of the server device 100 highlights the thumbnail of the article that has been determined to be the article that should be read now from among the thumbnails of the articles provided to the user U, and displays the generated reason why it should be read (step S206).

[0154] Next, the display control unit 133D of the server device 100 highlights the thumbnails of articles that have been determined to be articles to be read later, in a different display manner than the articles that should be read now (step S207).

[0155] Next, the display control unit 133D of the server device 100, when the thumbnail of the article that has been determined to be the article to be read is selected by the user U and the article to be read is presented to the user U, highlights a part of the content of the article to be read (points of interest) (step S208).

[0156] [5-3. Procedure for providing cover articles based on original articles] Referring to Figure 10, the procedure for providing a cover article based on the original article will be explained. Figure 10 is a flowchart of the procedure for providing a cover article based on the original article.

[0157] For example, as shown in Figure 10, the acquisition unit 131 of the server device 100 acquires the original article that will become the source article (step S301). For example, the submission acceptance unit 131C of the server device 100 accepts submissions (submissions) of the original article that will become the source article from the contributor. Alternatively, the acquisition unit 131 of the server device 100 may select and acquire the original article that will become the source article from articles provided to user U or articles that have already been distributed, according to predetermined conditions.

[0158] Next, the article content analysis unit 134A of the server device 100 analyzes the content of the original article (step S302).

[0159] Next, the cover matching processing unit 134B of the server device 100 performs cover poster matching based on the analysis results of the original article's content (step S303).

[0160] Next, the cover request processing unit 134C of the server device 100 requests the candidate cover posters obtained as a result of the matching to post a cover article based on the original article (step S304).

[0161] Next, the configuration unit 137 of the server device 100 officially approves the candidate for cover poster as the cover poster and sets them as such if the candidate accepts the request (step S305).

[0162] Next, the setting unit 137 of the server device 100 sets the range in which cover articles can be created according to the subject attributes of the cover poster (step S306).

[0163] Next, the submission reception unit 131C of the server device 100 accepts the submission of cover articles created by cover contributors who have accepted the request and been formally approved (step S307).

[0164] Next, the distribution unit 136 of the server device 100 distributes the submitted cover article (step S308).

[0165] Next, the setting unit 137 of the server device 100 performs the linking (association) of the original article and the cover article (step S309).

[0166] [5-4. Content generation process for your favorite idol's "What Day Is It Today?"] Refer to Figure 11 to explain the content generation process for "What Day Is It Today?" related to your favorite idol. Figure 11 is a flowchart showing the content generation process for "What Day Is It Today?" related to your favorite idol.

[0167] For example, as shown in Figure 11, the listing processing unit 135A of the server device 100 extracts information indicating the subject, date, and event from the body of the article posted (or retrieved) by the poster and lists it (step S401).

[0168] Next, the verification request processing unit 135B of the server device 100 requests a specific user to verify the facts of the listed information (step S402). In practice, the verification request processing unit 135B may request a specific user to verify multiple items (a predetermined number of items) of the listed information at once, rather than one item at a time.

[0169] Next, the accuracy determination unit 135C of the server device 100 determines whether a response has been received from a specific user in response to the request for fact-checking and whether it has been determined that there is no problem (step S403).

[0170] Furthermore, the accuracy determination unit 135C of the server device 100 calculates the reliability of the listed information based on the content of the articles posted by the poster and the trends of the distribution accounts, and determines whether the reliability is above a threshold (step S404). Note that the processes in steps S402 and S403 and the process in step S404 may be performed in parallel, consecutively, or in any order.

[0171] At this point, if the accuracy determination unit 135C does not determine that there is no problem (step S403: No), or if the confidence level is above the threshold (step S404: No), it determines that it is not a past event relating to the official subject and discards the listed information (inaccurate information) (step S405). Here, if the accuracy determination unit 135C requests fact-checking for multiple pieces of listed information (a predetermined number of pieces) at once, it discards all of the listed information that it has determined is not a past event relating to the official subject. Then, it terminates the series of processes.

[0172] Furthermore, if the accuracy determination unit 135C of the server device 100 determines that there is no problem (step S403: Yes) and the confidence level is above the threshold (step S404: Yes), it determines that the listed information is a past event relating to a formal subject (step S406).

[0173] Next, the target estimation unit 135D of the server device 100 estimates the user U's interests (favorites) from the user U's behavior history (step S407). At this time, the acquisition unit 131 of the server device 100 may acquire the user U's behavior history.

[0174] Next, the target matching processing unit 135E of the server device 100 performs a match between the targets in the list information and the interests of user U (step S408). If there are no targets in the list information that match the interests of user U, the target matching processing unit 135E terminates the series of processes.

[0175] Next, if the distribution unit 136 of the server device 100 finds a match between the subject of the listed information and the user U's interests, it distributes information about past events related to the user U's interests on the same date as the date of the listed information (step S409).

[0176] Next, the setting unit 137 of the server device 100 configures and modifies the distribution of information about past events related to the user U's interests, in response to the user U's actions after receiving the information (step S410).

[0177] [6. Variant Example] The terminal device 10 and server device 100 described above may be implemented in various other forms besides those of the embodiment described above. Therefore, the following describes modifications of the embodiment.

[0178] In the above embodiment, some or all of the processing performed by the server device 100 may actually be performed by the terminal device 10 (or an application running on the terminal device 10). For example, the terminal device 10 may perform all processing in a standalone manner. In this case, the terminal device 10 is assumed to have the same functions as the server device 100 in the above embodiment. Furthermore, in the above embodiment, since the terminal device 10 is in cooperation with the server device 100, from the perspective of the user U, it appears as if the processing of the server device 100 is also being performed by the terminal device 10. In other words, from another perspective, it can be said that the terminal device 10 is equipped with the server device 100.

[0179] Furthermore, in the above embodiment, the server device 100 performs cover poster matching based on the analysis results of the content of the original article, but in practice, it may also perform original article matching based on the subject attributes of the cover poster. In other words, the server device 100 may perform the reverse matching to select original articles that match the cover poster.

[0180] Furthermore, in the above embodiment, the following are examples of original articles and cover articles.

[0181] (1) Example of an original article • Title: "Japan's GDP growth rate exceeds expectations" Headline 1. Overview of Growth Rates 2. Factors for Growth 3. Future Outlook ...

[0182] (2) Example of a cover article 1 • Title: "Japan's GDP growth rate exceeds expectations" (Automatically retains the title of the original article) • Subtitle: "The Background and Prospects of Growth from an Economist's Perspective" (Entered by the cover poster) Headline 1. Overview of Growth Rates (with added explanations from economists) 2. Factors contributing to growth (additional expert analysis) 3. Future Outlook (Additional predictions and recommendations) • Timestamp (clearly indicating the publication date) • Authentication mark (proof of authenticity for the writer) ...

[0183] (3) Example of a cover article 2 • Title: "Japan's GDP growth rate exceeds expectations" (Automatically retains the title of the original article) • Subtitle: "What is the reality of economic growth as perceived by ordinary citizens?" (Entered by the cover poster) Headline 1. Overview of Growth Rates (with added explanation from the perspective of the general public) 2. Factors contributing to growth (including citizen interviews) 3. Future Outlook (Adding the hopes and concerns of the general public) • Timestamp (clearly indicating the publication date) • Authentication mark (proof of authenticity for the writer) ...

[0184] However, the above is merely one example, and in reality, it is not limited to the above example.

[0185] [7. Effects] As described above, the information processing device (terminal device 10 and server device 100) according to the present application is characterized by comprising: an acquisition unit 131 that acquires the original article to be the source article; an article content analysis unit 134A that analyzes the content of the original article; a cover matching processing unit 134B that matches cover posters based on the analysis results of the content of the original article; an submission acceptance unit 131C that accepts submissions of cover articles based on the original article from cover posters; and a distribution unit 136 that distributes the submitted cover articles.

[0186] This allows for the distribution of cover articles based on original articles. In other words, multiple derivative articles from diverse perspectives can be generated from a single article, broadening perspectives, deepening knowledge, and engaging discussions on the same theme. For example, it can provide readers with articles from new perspectives and styles, promoting information diversity. It can also encourage article reuse and extend the content lifecycle. Furthermore, it provides opportunities for journalists, writers, and other professionals to create new articles. In addition, it allows for matching cover contributors with the original article, taking into account their compatibility and added value. Matching with the right person is crucial precisely because it's a cover article.

[0187] Furthermore, the information processing device according to the present invention further includes a cover request processing unit 134C that requests the candidate cover posters obtained as a result of the matching to submit a cover article based on the original article. The submission acceptance unit 131C accepts the submission of the cover article created by the cover poster who has accepted the request.

[0188] This allows you to request cover article creation only from people who are a good match. Because it's a cover article, choosing the right person to create it is crucial.

[0189] Furthermore, the information processing device according to the present invention further includes a setting unit 137 that, when a candidate for cover author accepts the request, formally approves and sets the candidate as a cover author. The submission acceptance unit 131C accepts the submission of cover articles created by formally approved cover authors.

[0190] This means that not just anyone can create a cover story; only approved individuals can.

[0191] Furthermore, the information processing device according to the present invention further includes a setting unit 137 that sets the range of cover articles that can be created in accordance with the subject attributes of the cover poster.

[0192] This allows us to define the scope of cover articles that cover contributors can create.

[0193] Furthermore, the information processing device according to the present invention further includes a setting unit 137 that links the original article with the cover article.

[0194] This allows the original article and the cover article to be linked and presented as a single piece of content.

[0195] The cover matching processing unit 134B identifies accounts that can create new value that is not present in the original article, as cover posters.

[0196] This allows for the creation of cover articles from a different perspective than the original article, thereby creating new added value.

[0197] The cover matching processing unit 134B identifies accounts that have a track record of publishing articles in the same or similar genre as the original article, based on the content of the posts and content evaluation, as cover posters.

[0198] This allows for the creation of cover articles that expand upon or delve deeper into the content of the original article, thereby creating new added value.

[0199] The cover matching processing unit 134B identifies an account that has different subject attributes from the original article's author as the cover poster.

[0200] This allows us to accept cover article submissions from cover contributors who offer a different perspective than the original article's author, thereby creating new added value.

[0201] Through any or a combination of the above-described processes, the information processing device according to this application can distribute cover articles based on the original articles.

[0202] [8. Hardware Configuration] Furthermore, the terminal device 10 and server device 100 according to the above-described embodiment are realized by a computer 1000 having a configuration such as that shown in Figure 12. The following explanation will use the server device 100 as an example. Figure 12 is a diagram showing an example of the hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which an arithmetic unit 1030, a primary storage device 1040, a secondary storage device 1050, an output interface 1060, an input interface 1070, and a network interface 1080 are connected by a bus 1090.

[0203] The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, as well as programs read from the input device 1020, and executes various processes. The arithmetic unit 1030 can be implemented using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array).

[0204] The primary storage device 1040 is a memory device, such as RAM (Random Access Memory), that temporarily stores data used by the arithmetic unit 1030 for various calculations. The secondary storage device 1050 is a storage device where data used by the arithmetic unit 1030 for various calculations and various databases are registered, and can be implemented using ROM (Read Only Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, etc. The secondary storage device 1050 may be internal storage or external storage. The secondary storage device 1050 may also be a removable storage medium such as USB (Universal Serial Bus) memory or SD (Secure Digital) memory card. The secondary storage device 1050 may also be cloud storage (online storage), NAS (Network Attached Storage), file server, etc.

[0205] The output I / F 1060 is an interface for transmitting information to be output to output devices 1010, such as displays, projectors, and printers, and is implemented using connectors of standards such as USB (Universal Serial Bus), DVI (Digital Visual Interface), and HDMI (High Definition Multimedia Interface). The input I / F 1070 is an interface for receiving information from various input devices 1020, such as mice, keyboards, keypads, buttons, and scanners, and is implemented using, for example, USB.

[0206] Furthermore, the output interface 1060 and input interface 1070 may be wirelessly connected to the output device 1010 and input device 1020, respectively. In other words, the output device 1010 and input device 1020 may be wireless devices.

[0207] Furthermore, the output device 1010 and the input device 1020 may be integrated as a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated as an input / output I / F.

[0208] The input device 1020 may also be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), DVD (Digital Versatile Disc), or 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.

[0209] The network interface 1080 receives data from other devices via network N and sends it to the computing unit 1030, and also transmits data generated by the computing unit 1030 to other devices via network N.

[0210] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output interface 1060 and the input interface 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.

[0211] For example, when computer 1000 functions as a server device 100, the arithmetic unit 1030 of computer 1000 realizes the functions of the control unit 130 by executing a program loaded onto the primary storage device 1040. Alternatively, the arithmetic unit 1030 of computer 1000 may load a program obtained from another device via the network interface 1080 onto the primary storage device 1040 and execute the loaded program. Furthermore, the arithmetic unit 1030 of computer 1000 may cooperate with other devices via the network interface 1080 and call and use program functions, data, etc., from other programs on other devices.

[0212] [9. Other] Although embodiments of the present invention have been described above, the present invention is not limited by the content of these embodiments. Furthermore, the aforementioned components include those that can be easily conceived by those skilled in the art, those that are substantially the same, and those that fall within the so-called equivalent range. Moreover, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the gist of the embodiments described above.

[0213] Furthermore, 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 known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0214] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0215] For example, the server device 100 described above may be implemented using multiple server computers, and the configuration can be flexibly changed, such as by calling external platforms via APIs (Application Programming Interfaces) or network computing depending on the function.

[0216] Furthermore, the embodiments and modifications described above can be combined as appropriate, provided that the processing content is not inconsistent.

[0217] Furthermore, the terms "section, module, unit" mentioned above can be replaced with "means" or "circuit," etc. For example, the acquisition unit can be replaced with acquisition means or acquisition circuit. [Explanation of symbols]

[0218] 1. Information Processing System 10 Terminal devices 100 Server Devices 110 Communications Department 120 Storage section 130 Control Unit 131 Acquisition Department 131C Submission Department 132 Summary Article Generation Processing Unit 133 Recommended Articles Section 134 Cover Article Creation Processing Unit 134A Article Content Analysis Department 134B Cover matching processing unit 134C Cover Request Processing Unit 135 Target Event Notification Section 136 Distribution Department 137 Settings Section

Claims

1. The acquisition section retrieves the original article that serves as the source, The article content analysis unit analyzes the content of the aforementioned original article, Based on the analysis results of the content of the original article, a cover matching processing unit performs matching of cover posters, The submission department accepts submissions of cover articles based on the aforementioned original article from the aforementioned cover contributor, The distribution department distributes the submitted cover articles, An information processing device characterized by comprising:

2. The system further includes a cover request processing unit that requests the candidate cover posters obtained as a result of the matching to submit a cover article based on the original article. The aforementioned submission department accepts submissions of cover articles created by cover contributors who have accepted the request. The information processing apparatus according to feature 1.

3. If a candidate for cover poster accepts the request, the system further includes a setting section to officially approve and set them as the cover poster. The aforementioned submission department accepts cover articles created by officially approved cover contributors. The information processing apparatus according to feature 2.

4. A setting section that determines the range of cover articles that can be created, based on the subject attributes of the cover poster. The information processing apparatus according to claim 1, further comprising:

5. A setting unit that links the aforementioned original article with the aforementioned cover article. The information processing apparatus according to claim 1, further comprising:

6. The cover matching processing unit identifies accounts that can create new value not present in the original article, as cover posters. The information processing apparatus according to feature 1.

7. The aforementioned cover matching processing unit identifies accounts that have a track record of publishing articles in the same or similar genre as the original article, based on the content of the posts and content evaluation, as cover posters. The information processing apparatus according to feature 6.

8. The cover matching processing unit identifies an account that has different subject attributes from the original article's author as the cover poster. The information processing apparatus according to feature 6.

9. An information processing method performed by an information processing device, The process of obtaining the original article that serves as the source, The analysis process involves analyzing the content of the aforementioned original article, Based on the analysis results of the content of the aforementioned original article, a matching process is performed to match cover posters, The process of receiving submissions of cover articles based on the original article from the aforementioned cover contributors, The distribution process involves delivering the submitted cover article, An information processing method characterized by including

10. The procedure for obtaining the original article, The analysis procedure for analyzing the content of the aforementioned original article, Based on the analysis results of the content of the aforementioned original article, a matching process is performed to match cover posters, The procedure for accepting submissions of cover articles based on the aforementioned original article from the aforementioned cover contributor, The distribution procedure for delivering submitted cover articles, An information processing program characterized by causing a computer to execute it.

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