System

Abstract

A system is provided.SOLUTION: A system, comprising: means for obtaining a reading level and an interest from a user; means for customizing a news article based on the reading level and the interest; and means for displaying the customized news article on a user terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Currently, most news media only provide general information and are not sufficiently personalized to suit individual users' reading levels and interests. In particular, in the field of educational content aimed at children, the lack of news articles tailored to an appropriate reading level is a challenge. In addition, there is a lack of intuitive support for understanding using visual information. Therefore, there is a need for a system that provides opportunities for each user, including children, to understand and learn from news articles while engaging them. [Means for solving the problem]

[0005] The present invention provides a system including a means for acquiring a user's reading level and interests, a means for customizing news articles based on the reading level and interests, and a means for displaying the customized news articles on a user terminal. The present invention further includes a means for acquiring the latest news articles from a news source and storing them in a database, and a means for simplifying the text of the news articles or adding visual information according to the user's reading level, thereby enabling news articles to be presented at an appropriate level while still attracting the user's interest. This system allows news articles to be presented as educational content that is easy to understand, particularly for children.

[0006] "Reading level" refers to the user's level of ability to understand text and content.

[0007] "Interests" refers to the range of interest or concern a user has in a particular topic or theme.

[0008] A "news article" is a document or report written to convey a particular event or piece of information.

[0009] "User terminal" means a device used by a user, including a computer, tablet, smartphone, etc.

[0010] A "system" refers to a comprehensive mechanism in which multiple elements and functions work together.

[0011] A "database" refers to a collection of information for managing and storing various data, including news articles.

[0012] "Visual information" refers to visual content other than text, such as diagrams, illustrations, and photographs, that aids users in understanding.

[0013] "API" stands for "Application Programming Interface" and refers to an interface for exchanging data and functions between different software systems.

[0014] "Customization" refers to the adjustment of content or format to a user's specific requirements or preferences. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] System Overview

[0037] This invention provides a system for personalizing news content based on a user's reading level and interests. It mainly involves three elements: a server, a terminal, and a user. The system uses profile information entered by the user to customize news articles and provide them in a format appropriate for the user.

[0038] Server Roles

[0039] The server performs the following functions:

[0040] 1. Update the news database:

[0041] The server periodically retrieves the latest news articles from news sources and stores them in a database, ensuring that fresh content is always available.

[0042] 2. Analysis of User Information:

[0043] The server selects and customizes relevant news articles based on the user's reading level and interests, which may include simplifying the text and adding visual information.

[0044] 3. Generate customized news articles:

[0045] The server condenses the text of news articles and adds relevant visual information based on the user's reading level, using natural language processing and image recognition techniques in the process.

[0046] Device Role

[0047] The terminal performs the following functions:

[0048] 1. Providing a user interface:

[0049] The device provides an interface that allows users to set their reading level and interests, and allows users to easily access news articles.

[0050] 2. Getting and sending user input:

[0051] The device automatically sends the user's input about their reading level and interests to the server.

[0052] 3. Displaying customized news articles:

[0053] The device displays customized news articles retrieved from the server to the user, allowing the user to view news content in a format that best suits them.

[0054] User Roles

[0055] The user does the following:

[0056] 1. Profile Settings:

[0057] Users input their reading level and interests through the device, and these settings personalize the news articles they receive.

[0058] 2. Viewing news articles:

[0059] Users view customized news articles displayed on their devices, which are presented in a format that is easy for users to understand and therefore engaging to read.

[0060] Specific examples

[0061] Specific usage examples are shown below.

[0062] 1. Update the news database:

[0063] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0064] 2. Analysis of User Information:

[0065] If User A is interested in "science" and sets his reading level to "intermediate," the server will select science-related news articles that are appropriate for User A.

[0066] 3. Generate customized news articles:

[0067] The server converts the selected news article into concise text appropriate for User A's reading level, and also adds relevant charts and illustrations.

[0068] 4. Displaying customized news articles:

[0069] The terminal displays the customized news article sent from the server to User A. This allows User A to view the article in an easy-to-understand format.

[0070] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide educational content that is both engaging and easy to understand for the user.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The server retrieves the latest news articles from news sources, for example, by using RSS feeds or news APIs to aggregate data from multiple news sources.

[0074] Step 2:

[0075] The server stores the retrieved news articles in a database, which is then periodically updated with the latest news articles.

[0076] Step 3:

[0077] Users use the device's user interface to input their reading level and interests, using drop-down menus and checkboxes to make selections.

[0078] Step 4:

[0079] The device sends the user-entered reading level and interest information to the server, which is then sent as an HTTP request.

[0080] Step 5:

[0081] The server analyzes the received user information and stores it as a user profile, allowing for customization for each user.

[0082] Step 6:

[0083] The server selects news articles based on the user's profile, searching the database for articles that match the user's interests and reading level.

[0084] Step 7:

[0085] The server customizes the selected news articles by simplifying the text and adding visual information (e.g., illustrations and charts) to suit the user's reading level.

[0086] Step 8:

[0087] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[0088] Step 9:

[0089] The device receives customized news articles from the server and displays them to the user, who can then view them in a format that suits their reading level and interests.

[0090] Step 10:

[0091] After a user finishes viewing a news article, their device sends their browsing history to a server, which can then track changes in the user's interests and reading level and use this information to customize the next news article.

[0092] Example 1

[0093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0094] In today's information-saturated society, users face the challenge of finding information that matches their reading level and interests. Furthermore, many news articles are written in technical terms and long sentences, making them difficult for average users to understand. This creates a challenge for users, making it difficult to quickly and easily obtain information that is relevant to them.

[0095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0096] In this invention, the server includes means for obtaining a reading level and interests from a user, means for customizing news articles based on the reading level and interests, means for displaying the customized news articles on a user terminal, and means for using a generative AI model to simplify text and add visual information to the news articles, thereby enabling users to easily access news articles that match their reading level and interests and obtain information in an easy-to-understand format.

[0097] "User" means a person who uses the System to view news articles.

[0098] "Reading level" is an indicator of the level of difficulty of a text that makes it easy for users to understand the information.

[0099] "Interests" refers to areas or topics that a user is particularly interested in.

[0100] A "news article" is information in text form obtained from a news source and provided to a user.

[0101] "Customization" refers to the act of individually adjusting or changing information based on a user's reading level and interests.

[0102] "User device" means the electronic device (e.g., smartphone, PC, tablet, etc.) that a user uses to view news articles.

[0103] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate and process text.

[0104] "Visual information" refers to visual information such as charts and illustrations added to news articles.

[0105] A "news source" is a media outlet or data provider that provides information for a news article.

[0106] A "database" is a system for managing and storing data such as acquired news articles and user profiles.

[0107] MODE FOR CARRYING OUT THE INVENTION

[0108] The present invention provides a system for personalizing news articles based on a user's reading level and interests, the detailed embodiments of which are described below.

[0109] System Overview

[0110] The system mainly consists of three elements: a server, a terminal, and a user. The server collects, analyzes, and customizes news articles, while the terminal provides the user interface and transmits and displays user input. Users set their own reading level and interests to view customized news articles.

[0111] Server Roles

[0112] 1. Update the news database:

[0113] The server periodically retrieves the latest articles from news sources (e.g., APIs or RSS feeds) and updates the database. This process is performed using Python and the requests library, for example. The retrieved article data is stored in MySQL or MongoDB.

[0114] 2. Analysis of User Information:

[0115] The server receives user profile information (reading level, interests, etc.) sent from the device, and then uses natural language processing and data analysis techniques (e.g., the "scikit-learn" library) to select relevant news articles.

[0116] 3. Generate customized news articles:

[0117] The server then condenses the selected news articles to fit the user's reading level and uses a generative AI model (e.g., GPT-4) to add visual information, using the OpenCV library, for example.

[0118] Device Role

[0119] 1. Providing a user interface:

[0120] The device provides an interface for users to enter their profile information, which is built using React and HTML / CSS.

[0121] 2. Getting and sending user input:

[0122] The device takes the information entered by the user (reading level and interests) and sends it to the server using an HTTP POST request, using JavaScript and the axios library.

[0123] 3. Displaying customized news articles:

[0124] The device receives customized news articles sent from the server and displays them in an appropriate format, using React components.

[0125] User Roles

[0126] 1. Profile Settings:

[0127] Users input and set their reading level and interests through their devices, which then becomes the basis for personalizing news articles.

[0128] 2. Viewing news articles:

[0129] Users can view customized news articles displayed on their device and get information in an easy-to-understand format.

[0130] Specific examples

[0131] 1. Update the news database:

[0132] Every morning, the server retrieves the latest news from news sources and updates the database, for example by collecting and storing data from science-related RSS feeds.

[0133] 2. Analysis of User Information:

[0134] If User A selects "Science" as his or her area of ​​interest and his or her reading level as "Intermediate," the server will select science-related news articles appropriate for that user, such as "AI in Biomedical Research."

[0135] 3. Generate customized news articles:

[0136] The server then uses the GPT-4 model to simplify the selected articles and add relevant charts and illustrations, for example summarizing scientific articles and adding charts and illustrations of relevant experimental results.

[0137] 4. Displaying customized news articles:

[0138] The device displays the received customized news article to the user, who then scrolls through the article in a React-based application.

[0139] Example input to a generative AI model

[0140] Example prompt sentence:

[0141] Please adapt the original article "AI in Biomedical Research" into concise text appropriate for User A's intermediate reading level, and add relevant figures and tables. User A is interested in science. Please also simplify the terminology and emphasize the key points.

[0142] The above is a specific embodiment of the present invention. This system allows users to easily browse news articles that match their reading level and interests, enabling them to obtain information efficiently.

[0143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0144] System program processing flow

[0145] Server Processing Steps

[0146] Step 1:

[0147] Get articles from news sources

[0148] The server periodically retrieves the latest articles from the news source.

[0149] Input: API endpoint or RSS feed URL.

[0150] Data processing: Send an HTTP request using Python's requests library and obtain article data as a response.

[0151] Output: News article data in JSON format.

[0152] What it does: Every morning at 8am the server runs a scheduled task that retrieves data from news sources.

[0153] Step 2:

[0154] Saving to a database

[0155] The server analyzes the acquired article data and stores it in a news database.

[0156] Input: News article data in JSON format.

[0157] Data processing: Parse the acquired article data and extract necessary fields (e.g., title, body text, publication date, category, etc.).

[0158] Output: Store the formatted data in a database.

[0159] Specific behavior: Insert data into the database using SQL queries or MongoDB APIs.

[0160] Step 3:

[0161] Receiving user data

[0162] The server receives the user profile information sent from the terminal.

[0163] Input: User reading level and interest data sent in an HTTP POST request.

[0164] Data processing: Parse the request body and extract user data.

[0165] Output: A user profile object.

[0166] What it does: The server uses the Flask framework to parse the received data and store it in memory.

[0167] Step 4:

[0168] User profile analysis

[0169] The server selects relevant news articles based on the user's profile.

[0170] Input: User profile object, news database.

[0171] Data processing: Using the scikit-learn library, we cluster the user's interest fields and filter out relevant news articles.

[0172] Output: A list of selected news articles.

[0173] What it does: Generates queries to extract relevant articles from the database and selects articles that match the user's profile.

[0174] Step 5:

[0175] Simplifying the article and adding visual information

[0176] The server uses a generative AI model to simplify articles and add visual information.

[0177] Input: List of selected news articles, user profile.

[0178] Data processing: Calls OpenAI API to generate article summaries and adds relevant visual information using OpenCV library.

[0179] Output: A customized news article that has been abbreviated and enhanced with visual information.

[0180] What it does: It uses GPT-4 to generate prompts and perform summarization and visual information addition tasks.

[0181] Terminal processing steps

[0182] Step 6:

[0183] Viewing the Settings Interface

[0184] The device displays an interface that allows the user to enter profile information.

[0185] Input: User Access.

[0186] Data processing: None.

[0187] Output: Display of the configuration interface.

[0188] Specific behavior: Generate a form using React and HTML / CSS and display it to the user.

[0189] Step 7:

[0190] Retrieving Profile Information

[0191] The device collects information about the user's reading level and interests.

[0192] Input: User-entered data.

[0193] Data processing: Form data collection.

[0194] Output: A profile information object.

[0195] Specific operation: Store the form input contents in a variable using JavaScript.

[0196] Step 8:

[0197] Sending profile information

[0198] The terminal transmits the acquired profile information to the server.

[0199] Input: Profile information object.

[0200] Data processing: Convert the data into an HTTP POST request format.

[0201] Output: HTTP POST request to the server.

[0202] Specific behavior: Sends data to the server using the axios library.

[0203] Step 9:

[0204] Receiving news articles

[0205] The terminal receives customized news article data from the server.

[0206] Input: The HTTP response from the server.

[0207] Data processing: Analyze JSON format data.

[0208] Output: A customized news article object.

[0209] Specific operation: Analyze and store the data returned from the server using React.

[0210] Step 10:

[0211] View news articles

[0212] The terminal displays the received customized news article.

[0213] Input: A customized news article object.

[0214] Data processing: None.

[0215] Output: Display of news article.

[0216] What it does: Display an article to the user using a React component.

[0217] User processing steps

[0218] Step 11:

[0219] Enter your profile information

[0220] Users input their reading level and interests through the device.

[0221] Input: Your profile information.

[0222] Data processing: None.

[0223] Output: The profile information entered into the form.

[0224] What happens: A user fills out a form and clicks the "Submit" button.

[0225] Step 12:

[0226] Viewing news articles

[0227] Users view customized news articles displayed on their devices.

[0228] Input: A customized news article.

[0229] Data processing: None.

[0230] Output: View article.

[0231] What happens: The user scrolls through the article on the screen and reads the content.

[0232] The above is a concrete explanation of each processing step in the program of this system.

[0233] (Application example 1)

[0234] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0235] In modern content distribution services, it is difficult to efficiently provide users with news articles that are both interesting and appropriate for their reading level. Conventional news distribution systems provide uniform content without fully considering users' interests or reading level, which is likely to result in low user satisfaction. Furthermore, they do not allow for customization of news articles that include visual information, and lack functionality to further improve the user experience. There is a need to solve this problem and provide users with the most appropriate news articles.

[0236] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0237] In this invention, the server includes means for acquiring a user's reading level and interests, means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies, and means for delivering the customized news articles to a device in real time, thereby enabling the user to be provided with articles tailored to the user's interests that are simplified to fit the user's reading level and include related visual content.

[0238] "Means for obtaining reading level and interests from users" means a method for providing an interface that allows users to input or select their reading ability and interests.

[0239] The "means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies" refers to a method that uses natural language processing and image recognition technologies to simplify sentences according to the user's reading level and add visual information that matches the user's interests.

[0240] "Means for delivering the customized news articles to a device in real time" refers to a method for instantly transmitting individually customized news articles from a server to a user's device (such as a smartphone or head-mounted display).

[0241] "Means for obtaining the latest news articles from news sources and storing them in an information aggregation" refers to a method for periodically collecting the latest news articles from reliable news sources via the Internet and storing them in a database.

[0242] "Means of simplifying the content of news articles or adding visual content to them based on the user's reading level" refers to translating the content into language appropriate to the user's reading ability and inserting relevant charts and pictures into the article.

[0243] System Overview

[0244] This invention provides a system that personalizes news content to match a user's reading level and interests. The system mainly consists of three elements: a server, a terminal, and a user. Based on the profile information entered by the user, the system customizes news articles and provides them in a format appropriate for the user.

[0245] Server Roles

[0246] News database updates

[0247] The server periodically retrieves the latest news articles from news sources (such as news APIs) via the Internet and stores them in an information collection (database). This operation ensures that new content is always available.

[0248] Analyzing user information and customizing articles

[0249] The server analyzes the user's reading level and interests, and then customizes the news article based on this using natural language processing and image recognition technologies. Specifically, it simplifies the content of the article according to the user's reading level and adds visual information appropriate to their interests. This allows the server to provide users with news content that is both easy to understand and interesting.

[0250] Generate customized news articles

[0251] The server uses a generative AI model to generate a customized news article based on a prompt, such as the following:

[0252] "User A has an intermediate reading level and is interested in science and technology. Please translate the latest science news articles into simple sentences and add relevant figures and tables."

[0253] Device Role

[0254] Providing a user interface

[0255] The device provides an interface where users can set their reading level and interests, and through this interface, they can easily enter their profile and access news articles.

[0256] Getting and sending user input

[0257] The device sends the information the user enters to a server, which does this in real time and helps generate a customized news article for the user to view.

[0258] Customized news article display

[0259] The device displays customized news articles sent from the server to the user, allowing the user to view news content in a format that is optimized for them.

[0260] User Roles

[0261] Profile Settings

[0262] Users input their reading level and interests through the device, which personalizes the news articles they receive.

[0263] Viewing news articles

[0264] Users view customized news articles displayed on their devices, providing information in an easy-to-understand format.

[0265] Hardware and Software

[0266] The main hardware used to realize this system is cloud-based servers (e.g., AWS EC2) and devices such as smartphones and head-mounted displays. The software used includes an API for retrieving news articles (e.g., NewsAPI), natural language processing technology, image recognition technology, and generative AI models.

[0267] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide content that is both interesting and easy to understand for the user.

[0268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0269] Step 1:

[0270] The user (device) enters their reading level and interests.

[0271] Input: Reading level and interest categories (e.g., science, technology, sports) set by the user through their device.

[0272] Output: Information about the user's reading level and interests is stored on the device and sent to the server.

[0273] Specific behavior: The user uses drop-down menus and checkboxes on the device app's settings screen to select a reading level (e.g., beginner, intermediate, advanced) and interest categories, then presses the Settings button.

[0274] Step 2:

[0275] The server receives the user profile information and stores it in a database.

[0276] Input: User's reading level and interest information obtained in step 1.

[0277] Output: User profile information stored in a database.

[0278] Specific operation: The server receives the reading level and interest category information sent from the device, first validates the input values, and then stores them in the database.

[0279] Step 3:

[0280] The server retrieves the latest news articles from the news sources and updates the database.

[0281] Input: News API endpoint.

[0282] Output: The latest news articles stored in the database.

[0283] Specific operation: The server periodically calls the news API to retrieve the latest articles provided, receives them in XML or JSON format, and then converts them into a database format and saves them.

[0284] Step 4:

[0285] The server customizes news articles based on the user's reading level and interests.

[0286] Input: User profile information and news articles in the database.

[0287] Output: A customized news article.

[0288] How it works: Based on user profile information, the server selects news articles, simplifies the text, and adds relevant visual information. Natural language processing technology is used to simplify the text, and image recognition technology is used to extract and generate relevant visual elements (such as charts) and add them to the article.

[0289] Step 5:

[0290] Customized news articles are optimized using generative AI models and further personalized for each user based on prompt text.

[0291] Input: Customized news articles and per-user prompts.

[0292] Output: Optimized news articles.

[0293] How it works: The server inputs a prompt into the generative AI model, which then generates a news article in a format appropriate for the user's reading level and interests. For example, a prompt like "User A has an intermediate reading level and is interested in science and technology. Please convert the latest science news article into simple sentences and add relevant figures and tables" is input into the generative AI model.

[0294] Step 6:

[0295] The server delivers optimized news articles to the device in real time.

[0296] Input: Optimized news articles.

[0297] Output: The news article displayed on the user's device.

[0298] How it works: The server sends optimized news articles to the device via push notification or API, and the device receives them. The device app displays the received articles in its user interface.

[0299] Step 7:

[0300] The user views customized news articles through their device.

[0301] Input: A news article displayed on a user's device.

[0302] Output: Improved user satisfaction.

[0303] What it does: The user opens their device, browses to a news article delivered in real time, and reads along with the provided visual information.

[0304] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0305] System Overview

[0306] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It includes three elements: a server, a device, and a user, as well as an emotion engine. The system uses input information and emotional data from the user to customize news articles and present them in a format appropriate for the user.

[0307] Server Roles

[0308] The server performs the following functions:

[0309] 1. Update the news database:

[0310] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing the latest content.

[0311] 2. Analysis of User Information:

[0312] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[0313] 3. How the Emotion Engine works:

[0314] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[0315] 4. Generate customized news articles:

[0316] The server then performs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, thereby providing the news article in the most appropriate format for the user.

[0317] Device Role

[0318] The terminal performs the following functions:

[0319] 1. Providing a user interface:

[0320] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[0321] 2. Getting and sending user input:

[0322] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[0323] 3. Displaying customized news articles:

[0324] The device displays customized news articles retrieved from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[0325] User Roles

[0326] The user does the following:

[0327] 1. Profile Settings:

[0328] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[0329] 2. Viewing news articles:

[0330] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[0331] Specific examples

[0332] Specific usage examples are shown below.

[0333] 1. Update the news database:

[0334] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0335] 2. Analysis of User Information:

[0336] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[0337] 3. Generate customized news articles:

[0338] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[0339] 4. Displaying customized news articles:

[0340] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[0341] The above is a specific embodiment of the present invention. By personalizing news articles based on a user's reading level, interests, and even emotional state, it is possible to provide educational content that is engaging, easy to understand, and appropriate for the user's psychological state.

[0342] The processing flow will be explained below.

[0343] Step 1:

[0344] The server retrieves the latest news articles from news sources. Specifically, it collects data from multiple news sources using RSS feeds and news APIs. The collected data is obtained in JSON or XML format.

[0345] Step 2:

[0346] The server stores the retrieved news articles in a database. When storing them in the database, a duplicate check is performed and articles that already exist are excluded. This process ensures that the latest news articles are always updated in the database.

[0347] Step 3:

[0348] Users use the device's user interface to input their reading level, interests, and emotional state, which can be selected using drop-down menus and checkboxes, or which can be automatically obtained using facial recognition or voice analysis.

[0349] Step 4:

[0350] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information in JSON format as an HTTP request.

[0351] Step 5:

[0352] The server analyzes the received user information and stores it as a user profile, which includes information on reading level, interests, and emotional state, allowing for customization for each user.

[0353] Step 6:

[0354] The server selects news articles based on the user's profile. In particular, it searches the database for articles that match the user's interests, reading level, and emotional state. For example, if the user is interested in "science," has an "intermediate" reading level, and is emotionally "excited," the server will select the corresponding article.

[0355] Step 7:

[0356] The server customizes the selected news articles, shortening the sentences to match the user's reading level and adjusting the tone to suit the user's emotional state. It also adds visual information (e.g., illustrations and diagrams) and selects visual information appropriate to the user's emotional state. For example, a user in an excited state might be shown visually stimulating images.

[0357] Step 8:

[0358] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[0359] Step 9:

[0360] The device receives customized news articles from the server and displays them to the user, allowing the user to view the news articles in a format that suits their reading level, interests, and emotional state.

[0361] Step 10:

[0362] After a user finishes viewing a news article, their browsing history and new emotional data are sent from the device to the server, allowing the server to track changes in the user's interests and emotional state and use this information to customize the next news article. This process allows for even more accurate article delivery.

[0363] Example 2

[0364] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0365] In today's world, the amount of information available via the Internet is enormous, and users need to access information that is appropriate for their individual reading level, interests, and emotional state. However, conventional news delivery systems are unable to meet the individual needs of users, preventing them from effectively understanding the information or achieving psychological satisfaction. In particular, the provision of content tailored to emotional states has not been fully realized. This limits the user experience and reduces the efficiency of information reception and comprehension.

[0366] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's reading level, interests, and emotional state, means for customizing a news article based on the user's reading level, interests, and emotional state, means for displaying the customized news article on the user terminal, means for analyzing the user's emotional data using an emotion engine, and means for adjusting the text of the news article using a generative AI model. This makes it possible to provide news articles optimized for the user's reading level, interests, and emotional state, thereby enabling effective understanding of information and improving psychological satisfaction.

[0367] "User" refers to an individual who uses the System to view news articles.

[0368] "Reading level" is a standard that indicates the level of difficulty of a news article that a user can understand.

[0369] "Interests" refers to the themes or topics that a user is particularly interested in.

[0370] "Emotional state" refers to the user's state of mind or psychological state.

[0371] "News Article" refers to information content obtained from a news source.

[0372] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0373] An "emotion engine" is software or algorithm that analyzes a user's emotional data and determines their emotional state.

[0374] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate or adjust the content of a news article.

[0375] MODE FOR CARRYING OUT THE INVENTION

[0376] The present invention is a system for personalizing news content according to a user's reading level, interests, and emotional state. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0377] Server Roles

[0378] The server performs the following functions:

[0379] 1. Update the news database

[0380] The server retrieves the latest news articles from news sources and automatically updates the database. Specifically, it collects article information using RSS feeds and APIs. This task is set to run periodically. For example, the server can collect the latest technology-related articles every morning at 5:00 and store them in the database.

[0381] 2. Analysis of User Information

[0382] The server analyzes the information submitted by the user regarding reading level, interests, and emotional state, and then uses an emotional engine to further analyze the user's emotional state and select relevant news articles based on the results.

[0383] 3. Generate customized news articles

[0384] The server uses a generative AI model to tailor the content of news articles based on the user's reading level and emotional state. Specifically, it condenses the article, adds relevant visual information, and adjusts the tone to suit the emotion. An example of a prompt for the generative AI model is, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate science-related news articles appropriate for this user."

[0385] Device Role

[0386] The terminal performs the following functions:

[0387] 1. Providing a user interface

[0388] The device provides an interface that allows the user to set reading level, interests, and emotional state. Specific interface elements include drop-down menus and fields for selecting emotional states.

[0389] 2. Getting and Sending User Input

[0390] The device takes the information entered by the user and sends it to the server as an HTTP request. For example, if the user sets their interest as "science," their reading level as "intermediate," and their emotional state as "excited," this information is sent.

[0391] 3. Customized news article display

[0392] The device displays customized news articles sent from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[0393] User Roles

[0394] The user does the following:

[0395] 1. Profile Settings

[0396] The user inputs their reading level, interests, and emotional state through the terminal. For example, the user may set that they are interested in "science," their reading level is "intermediate," and they are currently "excited."

[0397] 2. Reading news articles

[0398] Users view personalized news articles displayed on their devices, optimized based on their preferences to make them easier to understand and more satisfying to the user.

[0399] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level, interests, and even emotional state, it is possible to provide optimal information to the user. Through this system, users can receive news articles in a more understandable format, which is psychologically satisfying.

[0400] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0401] Step 1:

[0402] The server retrieves the latest news articles from news sources. The input is the URL or RSS feed of the news source, and the output is the latest news article. Specifically, the server reads the RSS feed from the specified news source, extracts the content of the latest article, and stores it in a database.

[0403] Step 2:

[0404] Users input their reading level, interests, and emotional state through their devices. The input is the information the user sets on the device, and the output is the information sent to the server as an HTTP request. Specifically, users use drop-down menus and selection fields to set the required settings.

[0405] Step 3:

[0406] The server analyzes the information obtained from the user regarding reading level, interests, and emotional state. The input is the information sent by the user, and the output is the analysis result, which is instructions for selecting and customizing appropriate news articles. Specifically, the server uses an emotion engine to analyze the user's emotional state and selects relevant news articles based on the results.

[0407] Step 4:

[0408] The server inputs relevant news articles into the generative AI model and adjusts the text to suit the user's reading level and emotional state. The input is the selected news article and user information, and the output is a customized news article. Specifically, the server generates a prompt sentence and inputs it into the generative AI model to regenerate the article text. For example, the prompt sentence could be, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate a science-related news article that is appropriate for this user."

[0409] Step 5:

[0410] The server sends the generated customized news article to the user's device. The input is the customized news article, and the output is the news article data as an HTTP response. Specifically, the server formats the article data appropriately and sends it to the device.

[0411] Step 6:

[0412] The terminal displays the received customized news article to the user. The input is the news article data sent from the server, and the output is the news article displayed on the user interface. In concrete terms, the terminal analyzes the received data and displays the article on the screen. The user then views the displayed customized news article.

[0413] (Application example 2)

[0414] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0415] Conventional news delivery systems customize news articles based solely on a user's reading level and interests. This means that they do not provide information appropriate to the user's emotional state, making it difficult to continuously capture the user's interest. Furthermore, the lack of a function to analyze the user's emotional state in real time and adjust the tone of the news article accordingly limits the user experience.

[0416] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the reading level and interests from the user, means for customizing news articles based on the reading level and interests, means for analyzing the user's emotional state, means for customizing news articles based on the emotional state, and means for displaying the customized news articles on the user terminal. This makes it possible to provide news articles that are appropriate for the user's emotional state as well as their reading level and interests.

[0417] "Means of obtaining reading level and interests from users" refers to input interfaces and sensor devices that are used to understand users' reading ability and areas of interest.

[0418] "Means for customizing news articles based on said reading level and interests" refers to algorithms or software processes that adjust news content based on the acquired user's reading level and interests.

[0419] "Means for analyzing the user's emotional state" refers to an emotion engine, biometric sensor, or AI-based analysis module that recognizes and analyzes the user's emotions in real time.

[0420] "Means for customizing news articles based on said emotional state" refers to an algorithm or software that has the ability to adjust the content and tone of a news article depending on the analyzed emotional state of the user.

[0421] "Means for displaying the customized news article on a user terminal" refers to an output device such as a smartphone application or a web interface for displaying the news article optimized for the user.

[0422] "Means of obtaining the latest news articles from news sources and storing them in a database" refers to the process of collecting the latest news data via the Internet or RSS feeds and storing it in a storage device such as a server.

[0423] "Means of simplifying text or adding visual information to news articles based on the user's reading level" refers to algorithms or software that simplify text to adapt to the user's reading ability, or add charts or images to aid comprehension.

[0424] "Means for adjusting the tone of news articles based on the user's emotional state" refers to an algorithm or machine learning model that adjusts the tone and wording of an article to match the user's psychological state.

[0425] "Means of using generative AI models to generate news articles based on a user's reading level, interests, and emotional state" refers to the process of using AI or machine learning models to automatically generate news articles that match the characteristics of a user.

[0426] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It is possible to customize news articles using user input and emotional data, and provide them in a format appropriate for the user. The system includes three elements: a server, a terminal, and a user, as well as an emotional engine.

[0427] Server Roles

[0428] The server performs the following functions:

[0429] 1. Update the news database:

[0430] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing users with the latest content.

[0431] 2. Analysis of User Information:

[0432] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[0433] 3. How the Emotion Engine works:

[0434] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[0435] 4. Generate customized news articles:

[0436] The server then runs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, allowing the news article to be presented to the user in the most appropriate format.

[0437] Device Role

[0438] The terminal performs the following functions:

[0439] 1. Providing a user interface:

[0440] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[0441] 2. Getting and sending user input:

[0442] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[0443] 3. Displaying customized news articles:

[0444] The device displays customized news articles retrieved from the server to the user, allowing the user to view news articles in a format appropriate to their reading level and emotional state.

[0445] User Roles

[0446] The user does the following:

[0447] 1. Profile Settings:

[0448] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[0449] 2. Viewing news articles:

[0450] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[0451] Specific examples

[0452] Here are some specific usage examples:

[0453] 1. Update the news database:

[0454] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0455] 2. Analysis of User Information:

[0456] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[0457] 3. Generate customized news articles:

[0458] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[0459] 4. Displaying customized news articles:

[0460] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[0461] Prompt Sentence Examples

[0462] Here are some example input prompts for a generative AI model:

[0463] "Generate a news article suitable for users with an intermediate reading level, an interest in science, and current excitement. The original article reads: 'New research published today suggests that...'"

[0464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0465] Step 1:

[0466] The device receives input from the user regarding reading level, interests, and emotional state. This input includes the user's selected reading level (beginner, intermediate, advanced, etc.), areas of interest (science, sports, economics, etc.), and current emotional state (excited, calm, etc.). Once this information is entered into the device, it is sent to the server as an HTTP request.

[0467] Input: User's reading level, interests, and emotional state

[0468] Output: User information sent to the server as an HTTP request

[0469] Step 2:

[0470] The server analyzes the user's reading level, interests, and emotional state information obtained from the device. Based on the analysis, it selects news articles from the database that are appropriate for the user. This selection process involves filtering articles in categories that match the user's interests.

[0471] Input: User information received by the server as an HTTP request

[0472] Output: News articles filtered based on the user's reading level and interests

[0473] Step 3:

[0474] The server then simplifies the selected news articles based on the user's reading level. In this step, the server uses a library or algorithm to simplify the text, converting it into a form that is easy for the user to understand.

[0475] Input: filtered news articles, user reading level

[0476] Output: A simplified news article

[0477] Step 4:

[0478] The server uses an emotion engine to analyze the user's emotional data and adjust the tone of the news article based on the results: if the user is "excited," the emotion engine adjusts the article to an energetic tone, and if the user is "calm," it adjusts the tone to a calmer tone.

[0479] Input: Simplified news article, sentiment engine analysis results

[0480] Output: Tone-adjusted news article

[0481] Step 5:

[0482] The server uses the generative AI model to further customize the news article based on all the user information, specifically by inputting prompts to the generative AI model to generate and adjust the article.

[0483] Input: Tone-adjusted news articles, prompts based on user information

[0484] Output: A news article further customized by AI

[0485] Step 6:

[0486] The server then sends the customized news article to the device as an HTTP response.

[0487] Input: Customized news article

[0488] Output: News article sent to the terminal as an HTTP response

[0489] Step 7:

[0490] The device displays customized news articles sent from the server to the user, allowing the user to view news articles that are appropriate for their reading level, interests, and emotional state.

[0491] Input: News article received as an HTTP response

[0492] Output: A customized news article displayed on the terminal screen.

[0493] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0494] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0495] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0496] [Second embodiment]

[0497] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0498] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0499] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0500] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0501] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0502] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0503] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0504] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0505] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0506] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0507] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0508] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0509] System Overview

[0510] This invention provides a system for personalizing news content based on a user's reading level and interests. It mainly involves three elements: a server, a terminal, and a user. The system uses profile information entered by the user to customize news articles and provide them in a format appropriate for the user.

[0511] Server Roles

[0512] The server performs the following functions:

[0513] 1. Update the news database:

[0514] The server periodically retrieves the latest news articles from news sources and stores them in a database, ensuring that fresh content is always available.

[0515] 2. Analysis of User Information:

[0516] The server selects and customizes relevant news articles based on the user's reading level and interests, which may include simplifying the text and adding visual information.

[0517] 3. Generate customized news articles:

[0518] The server condenses the text of news articles and adds relevant visual information based on the user's reading level, using natural language processing and image recognition techniques in the process.

[0519] Device Role

[0520] The terminal performs the following functions:

[0521] 1. Providing a user interface:

[0522] The device provides an interface that allows users to set their reading level and interests, and allows users to easily access news articles.

[0523] 2. Getting and sending user input:

[0524] The device automatically sends the user's input about their reading level and interests to the server.

[0525] 3. Displaying customized news articles:

[0526] The device displays customized news articles retrieved from the server to the user, allowing the user to view news content in a format that best suits them.

[0527] User Roles

[0528] The user does the following:

[0529] 1. Profile Settings:

[0530] Users input their reading level and interests through the device, and these settings personalize the news articles they receive.

[0531] 2. Viewing news articles:

[0532] Users view customized news articles displayed on their devices, which are presented in a format that is easy for users to understand and therefore engaging to read.

[0533] Specific examples

[0534] Specific usage examples are shown below.

[0535] 1. Update the news database:

[0536] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0537] 2. Analysis of User Information:

[0538] If User A is interested in "science" and sets his reading level to "intermediate," the server will select science-related news articles that are appropriate for User A.

[0539] 3. Generate customized news articles:

[0540] The server converts the selected news article into concise text appropriate for User A's reading level, and also adds relevant charts and illustrations.

[0541] 4. Displaying customized news articles:

[0542] The terminal displays the customized news article sent from the server to User A. This allows User A to view the article in an easy-to-understand format.

[0543] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide educational content that is both engaging and easy to understand for the user.

[0544] The processing flow will be explained below.

[0545] Step 1:

[0546] The server retrieves the latest news articles from news sources, for example, by using RSS feeds or news APIs to aggregate data from multiple news sources.

[0547] Step 2:

[0548] The server stores the retrieved news articles in a database, which is then periodically updated with the latest news articles.

[0549] Step 3:

[0550] Users use the device's user interface to input their reading level and interests, using drop-down menus and checkboxes to make selections.

[0551] Step 4:

[0552] The device sends the user-entered reading level and interest information to the server, which is then sent as an HTTP request.

[0553] Step 5:

[0554] The server analyzes the received user information and stores it as a user profile, allowing for customization for each user.

[0555] Step 6:

[0556] The server selects news articles based on the user's profile, searching the database for articles that match the user's interests and reading level.

[0557] Step 7:

[0558] The server customizes the selected news articles by simplifying the text and adding visual information (e.g., illustrations and charts) to suit the user's reading level.

[0559] Step 8:

[0560] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[0561] Step 9:

[0562] The device receives customized news articles from the server and displays them to the user, who can then view them in a format that suits their reading level and interests.

[0563] Step 10:

[0564] After a user finishes viewing a news article, their device sends their browsing history to a server, which can then track changes in the user's interests and reading level and use this information to customize the next news article.

[0565] Example 1

[0566] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0567] In today's information-saturated society, users face the challenge of finding information that matches their reading level and interests. Furthermore, many news articles are written in technical terms and long sentences, making them difficult for average users to understand. This creates a challenge for users, making it difficult to quickly and easily obtain information that is relevant to them.

[0568] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0569] In this invention, the server includes means for obtaining a reading level and interests from a user, means for customizing news articles based on the reading level and interests, means for displaying the customized news articles on a user terminal, and means for using a generative AI model to simplify text and add visual information to the news articles, thereby enabling users to easily access news articles that match their reading level and interests and obtain information in an easy-to-understand format.

[0570] "User" means a person who uses the System to view news articles.

[0571] "Reading level" is an indicator of the level of difficulty of a text that makes it easy for users to understand the information.

[0572] "Interests" refers to areas or topics that a user is particularly interested in.

[0573] A "news article" is information in text form obtained from a news source and provided to a user.

[0574] "Customization" refers to the act of individually adjusting or changing information based on a user's reading level and interests.

[0575] "User device" means the electronic device (e.g., smartphone, PC, tablet, etc.) that a user uses to view news articles.

[0576] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate and process text.

[0577] "Visual information" refers to visual information such as charts and illustrations added to news articles.

[0578] A "news source" is a media outlet or data provider that provides information for a news article.

[0579] A "database" is a system for managing and storing data such as acquired news articles and user profiles.

[0580] MODE FOR CARRYING OUT THE INVENTION

[0581] The present invention provides a system for personalizing news articles based on a user's reading level and interests, the detailed embodiments of which are described below.

[0582] System Overview

[0583] The system mainly consists of three elements: a server, a terminal, and a user. The server collects, analyzes, and customizes news articles, while the terminal provides the user interface and transmits and displays user input. Users set their own reading level and interests to view customized news articles.

[0584] Server Roles

[0585] 1. Update the news database:

[0586] The server periodically retrieves the latest articles from news sources (e.g., APIs or RSS feeds) and updates the database. This process is performed using Python and the requests library, for example. The retrieved article data is stored in MySQL or MongoDB.

[0587] 2. Analysis of User Information:

[0588] The server receives user profile information (reading level, interests, etc.) sent from the device, and then uses natural language processing and data analysis techniques (e.g., the "scikit-learn" library) to select relevant news articles.

[0589] 3. Generate customized news articles:

[0590] The server then condenses the selected news articles to fit the user's reading level and uses a generative AI model (e.g., GPT-4) to add visual information, using the OpenCV library, for example.

[0591] Device Role

[0592] 1. Providing a user interface:

[0593] The device provides an interface for users to enter their profile information, which is built using React and HTML / CSS.

[0594] 2. Getting and sending user input:

[0595] The device takes the information entered by the user (reading level and interests) and sends it to the server using an HTTP POST request, using JavaScript and the axios library.

[0596] 3. Displaying customized news articles:

[0597] The device receives customized news articles sent from the server and displays them in an appropriate format, using React components.

[0598] User Roles

[0599] 1. Profile Settings:

[0600] Users input and set their reading level and interests through their devices, which then becomes the basis for personalizing news articles.

[0601] 2. Viewing news articles:

[0602] Users can view customized news articles displayed on their device and get information in an easy-to-understand format.

[0603] Specific examples

[0604] 1. Update the news database:

[0605] Every morning, the server retrieves the latest news from news sources and updates the database, for example by collecting and storing data from science-related RSS feeds.

[0606] 2. Analysis of User Information:

[0607] If User A selects "Science" as his or her area of ​​interest and his or her reading level as "Intermediate," the server will select science-related news articles appropriate for that user, such as "AI in Biomedical Research."

[0608] 3. Generate customized news articles:

[0609] The server then uses the GPT-4 model to simplify the selected articles and add relevant charts and illustrations, for example summarizing scientific articles and adding charts and illustrations of relevant experimental results.

[0610] 4. Displaying customized news articles:

[0611] The device displays the received customized news article to the user, who then scrolls through the article in a React-based application.

[0612] Example input to a generative AI model

[0613] Example prompt sentence:

[0614] Please adapt the original article "AI in Biomedical Research" into concise text appropriate for User A's intermediate reading level, and add relevant figures and tables. User A is interested in science. Please also simplify the terminology and emphasize the key points.

[0615] The above is a specific embodiment of the present invention. This system allows users to easily browse news articles that match their reading level and interests, enabling them to obtain information efficiently.

[0616] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0617] System program processing flow

[0618] Server Processing Steps

[0619] Step 1:

[0620] Get articles from news sources

[0621] The server periodically retrieves the latest articles from the news source.

[0622] Input: API endpoint or RSS feed URL.

[0623] Data processing: Send an HTTP request using Python's requests library and obtain article data as a response.

[0624] Output: News article data in JSON format.

[0625] What it does: Every morning at 8am the server runs a scheduled task that retrieves data from news sources.

[0626] Step 2:

[0627] Saving to a database

[0628] The server analyzes the acquired article data and stores it in a news database.

[0629] Input: News article data in JSON format.

[0630] Data processing: Parse the acquired article data and extract necessary fields (e.g., title, body text, publication date, category, etc.).

[0631] Output: Store the formatted data in a database.

[0632] Specific behavior: Insert data into the database using SQL queries or MongoDB APIs.

[0633] Step 3:

[0634] Receiving user data

[0635] The server receives the user profile information sent from the terminal.

[0636] Input: User reading level and interest data sent in an HTTP POST request.

[0637] Data processing: Parse the request body and extract user data.

[0638] Output: A user profile object.

[0639] What it does: The server uses the Flask framework to parse the received data and store it in memory.

[0640] Step 4:

[0641] User profile analysis

[0642] The server selects relevant news articles based on the user's profile.

[0643] Input: User profile object, news database.

[0644] Data processing: Using the scikit-learn library, we cluster the user's interest fields and filter out relevant news articles.

[0645] Output: A list of selected news articles.

[0646] What it does: Generates queries to extract relevant articles from the database and selects articles that match the user's profile.

[0647] Step 5:

[0648] Simplifying the article and adding visual information

[0649] The server uses a generative AI model to simplify articles and add visual information.

[0650] Input: List of selected news articles, user profile.

[0651] Data processing: Calls OpenAI API to generate article summaries and adds relevant visual information using OpenCV library.

[0652] Output: A customized news article that has been abbreviated and enhanced with visual information.

[0653] What it does: It uses GPT-4 to generate prompts and perform summarization and visual information addition tasks.

[0654] Terminal processing steps

[0655] Step 6:

[0656] Viewing the Settings Interface

[0657] The device displays an interface that allows the user to enter profile information.

[0658] Input: User Access.

[0659] Data processing: None.

[0660] Output: Display of the configuration interface.

[0661] Specific behavior: Generate a form using React and HTML / CSS and display it to the user.

[0662] Step 7:

[0663] Retrieving Profile Information

[0664] The device collects information about the user's reading level and interests.

[0665] Input: User-entered data.

[0666] Data processing: Form data collection.

[0667] Output: A profile information object.

[0668] Specific operation: Store the form input contents in a variable using JavaScript.

[0669] Step 8:

[0670] Sending profile information

[0671] The terminal transmits the acquired profile information to the server.

[0672] Input: Profile information object.

[0673] Data processing: Convert the data into an HTTP POST request format.

[0674] Output: HTTP POST request to the server.

[0675] Specific behavior: Sends data to the server using the axios library.

[0676] Step 9:

[0677] Receiving news articles

[0678] The terminal receives customized news article data from the server.

[0679] Input: The HTTP response from the server.

[0680] Data processing: Analyze JSON format data.

[0681] Output: A customized news article object.

[0682] Specific operation: Analyze and store the data returned from the server using React.

[0683] Step 10:

[0684] View news articles

[0685] The terminal displays the received customized news article.

[0686] Input: A customized news article object.

[0687] Data processing: None.

[0688] Output: Display of news article.

[0689] What it does: Display an article to the user using a React component.

[0690] User processing steps

[0691] Step 11:

[0692] Enter your profile information

[0693] Users input their reading level and interests through the device.

[0694] Input: Your profile information.

[0695] Data processing: None.

[0696] Output: The profile information entered into the form.

[0697] What happens: A user fills out a form and clicks the "Submit" button.

[0698] Step 12:

[0699] Viewing news articles

[0700] Users view customized news articles displayed on their devices.

[0701] Input: A customized news article.

[0702] Data processing: None.

[0703] Output: View article.

[0704] What happens: The user scrolls through the article on the screen and reads the content.

[0705] The above is a concrete explanation of each processing step in the program of this system.

[0706] (Application example 1)

[0707] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0708] In modern content distribution services, it is difficult to efficiently provide users with news articles that are both interesting and appropriate for their reading level. Conventional news distribution systems provide uniform content without fully considering users' interests or reading level, which is likely to result in low user satisfaction. Furthermore, they do not allow for customization of news articles that include visual information, and lack functionality to further improve the user experience. There is a need to solve this problem and provide users with the most appropriate news articles.

[0709] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0710] In this invention, the server includes means for acquiring a user's reading level and interests, means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies, and means for delivering the customized news articles to a device in real time, thereby enabling the user to be provided with articles tailored to the user's interests that are simplified to fit the user's reading level and include related visual content.

[0711] "Means for obtaining reading level and interests from users" means a method for providing an interface that allows users to input or select their reading ability and interests.

[0712] The "means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies" refers to a method that uses natural language processing and image recognition technologies to simplify sentences according to the user's reading level and add visual information that matches the user's interests.

[0713] "Means for delivering the customized news articles to a device in real time" refers to a method for instantly transmitting individually customized news articles from a server to a user's device (such as a smartphone or head-mounted display).

[0714] "Means for obtaining the latest news articles from news sources and storing them in an information aggregation" refers to a method for periodically collecting the latest news articles from reliable news sources via the Internet and storing them in a database.

[0715] "Means of simplifying the content of news articles or adding visual content to them based on the user's reading level" refers to translating the content into language appropriate to the user's reading ability and inserting relevant charts and pictures into the article.

[0716] System Overview

[0717] This invention provides a system that personalizes news content to match a user's reading level and interests. The system mainly consists of three elements: a server, a terminal, and a user. Based on the profile information entered by the user, the system customizes news articles and provides them in a format appropriate for the user.

[0718] Server Roles

[0719] News database updates

[0720] The server periodically retrieves the latest news articles from news sources (such as news APIs) via the Internet and stores them in an information collection (database). This operation ensures that new content is always available.

[0721] Analyzing user information and customizing articles

[0722] The server analyzes the user's reading level and interests, and then customizes the news article based on this using natural language processing and image recognition technologies. Specifically, it simplifies the content of the article according to the user's reading level and adds visual information appropriate to their interests. This allows the server to provide users with news content that is both easy to understand and interesting.

[0723] Generate customized news articles

[0724] The server uses a generative AI model to generate a customized news article based on a prompt, such as the following:

[0725] "User A has an intermediate reading level and is interested in science and technology. Please translate the latest science news articles into simple sentences and add relevant figures and tables."

[0726] Device Role

[0727] Providing a user interface

[0728] The device provides an interface where users can set their reading level and interests, and through this interface, they can easily enter their profile and access news articles.

[0729] Getting and sending user input

[0730] The device sends the information the user enters to a server, which does this in real time and helps generate a customized news article for the user to view.

[0731] Customized news article display

[0732] The device displays customized news articles sent from the server to the user, allowing the user to view news content in a format that is optimized for them.

[0733] User Roles

[0734] Profile Settings

[0735] Users input their reading level and interests through the device, which personalizes the news articles they receive.

[0736] Viewing news articles

[0737] Users view customized news articles displayed on their devices, providing information in an easy-to-understand format.

[0738] Hardware and Software

[0739] The main hardware used to realize this system is cloud-based servers (e.g., AWS EC2) and devices such as smartphones and head-mounted displays. The software used includes an API for retrieving news articles (e.g., NewsAPI), natural language processing technology, image recognition technology, and generative AI models.

[0740] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide content that is both interesting and easy to understand for the user.

[0741] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0742] Step 1:

[0743] The user (device) enters their reading level and interests.

[0744] Input: Reading level and interest categories (e.g., science, technology, sports) set by the user through their device.

[0745] Output: Information about the user's reading level and interests is stored on the device and sent to the server.

[0746] Specific behavior: The user uses drop-down menus and checkboxes on the device app's settings screen to select a reading level (e.g., beginner, intermediate, advanced) and interest categories, then presses the Settings button.

[0747] Step 2:

[0748] The server receives the user profile information and stores it in a database.

[0749] Input: User's reading level and interest information obtained in step 1.

[0750] Output: User profile information stored in a database.

[0751] Specific operation: The server receives the reading level and interest category information sent from the device, first validates the input values, and then stores them in the database.

[0752] Step 3:

[0753] The server retrieves the latest news articles from the news sources and updates the database.

[0754] Input: News API endpoint.

[0755] Output: The latest news articles stored in the database.

[0756] Specific operation: The server periodically calls the news API to retrieve the latest articles provided, receives them in XML or JSON format, and then converts them into a database format and saves them.

[0757] Step 4:

[0758] The server customizes news articles based on the user's reading level and interests.

[0759] Input: User profile information and news articles in the database.

[0760] Output: A customized news article.

[0761] How it works: Based on user profile information, the server selects news articles, simplifies the text, and adds relevant visual information. Natural language processing technology is used to simplify the text, and image recognition technology is used to extract and generate relevant visual elements (such as charts) and add them to the article.

[0762] Step 5:

[0763] Customized news articles are optimized using generative AI models and further personalized for each user based on prompt text.

[0764] Input: Customized news articles and per-user prompts.

[0765] Output: Optimized news articles.

[0766] How it works: The server inputs a prompt into the generative AI model, which then generates a news article in a format appropriate for the user's reading level and interests. For example, a prompt like "User A has an intermediate reading level and is interested in science and technology. Please convert the latest science news article into simple sentences and add relevant figures and tables" is input into the generative AI model.

[0767] Step 6:

[0768] The server delivers optimized news articles to the device in real time.

[0769] Input: Optimized news articles.

[0770] Output: The news article displayed on the user's device.

[0771] How it works: The server sends optimized news articles to the device via push notification or API, and the device receives them. The device app displays the received articles in its user interface.

[0772] Step 7:

[0773] The user views customized news articles through their device.

[0774] Input: A news article displayed on a user's device.

[0775] Output: Improved user satisfaction.

[0776] What it does: The user opens their device, browses to a news article delivered in real time, and reads along with the provided visual information.

[0777] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0778] System Overview

[0779] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It includes three elements: a server, a device, and a user, as well as an emotion engine. The system uses input information and emotional data from the user to customize news articles and present them in a format appropriate for the user.

[0780] Server Roles

[0781] The server performs the following functions:

[0782] 1. Update the news database:

[0783] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing the latest content.

[0784] 2. Analysis of User Information:

[0785] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[0786] 3. How the Emotion Engine works:

[0787] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[0788] 4. Generate customized news articles:

[0789] The server then performs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, thereby providing the news article in the most appropriate format for the user.

[0790] Device Role

[0791] The terminal performs the following functions:

[0792] 1. Providing a user interface:

[0793] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[0794] 2. Getting and sending user input:

[0795] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[0796] 3. Displaying customized news articles:

[0797] The device displays customized news articles retrieved from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[0798] User Roles

[0799] The user does the following:

[0800] 1. Profile Settings:

[0801] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[0802] 2. Viewing news articles:

[0803] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[0804] Specific examples

[0805] Specific usage examples are shown below.

[0806] 1. Update the news database:

[0807] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0808] 2. Analysis of User Information:

[0809] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[0810] 3. Generate customized news articles:

[0811] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[0812] 4. Displaying customized news articles:

[0813] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[0814] The above is a specific embodiment of the present invention. By personalizing news articles based on a user's reading level, interests, and even emotional state, it is possible to provide educational content that is engaging, easy to understand, and appropriate for the user's psychological state.

[0815] The processing flow will be explained below.

[0816] Step 1:

[0817] The server retrieves the latest news articles from news sources. Specifically, it collects data from multiple news sources using RSS feeds and news APIs. The collected data is obtained in JSON or XML format.

[0818] Step 2:

[0819] The server stores the retrieved news articles in a database. When storing them in the database, a duplicate check is performed and articles that already exist are excluded. This process ensures that the latest news articles are always updated in the database.

[0820] Step 3:

[0821] Users use the device's user interface to input their reading level, interests, and emotional state, which can be selected using drop-down menus and checkboxes, or which can be automatically obtained using facial recognition or voice analysis.

[0822] Step 4:

[0823] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information in JSON format as an HTTP request.

[0824] Step 5:

[0825] The server analyzes the received user information and stores it as a user profile, which includes information on reading level, interests, and emotional state, allowing for customization for each user.

[0826] Step 6:

[0827] The server selects news articles based on the user's profile. In particular, it searches the database for articles that match the user's interests, reading level, and emotional state. For example, if the user is interested in "science," has an "intermediate" reading level, and is emotionally "excited," the server will select the corresponding article.

[0828] Step 7:

[0829] The server customizes the selected news articles, shortening the sentences to match the user's reading level and adjusting the tone to suit the user's emotional state. It also adds visual information (e.g., illustrations and diagrams) and selects visual information appropriate to the user's emotional state. For example, a user in an excited state might be shown visually stimulating images.

[0830] Step 8:

[0831] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[0832] Step 9:

[0833] The device receives customized news articles from the server and displays them to the user, allowing the user to view the news articles in a format that suits their reading level, interests, and emotional state.

[0834] Step 10:

[0835] After a user finishes viewing a news article, their browsing history and new emotional data are sent from the device to the server, allowing the server to track changes in the user's interests and emotional state and use this information to customize the next news article. This process allows for even more accurate article delivery.

[0836] Example 2

[0837] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0838] In today's world, the amount of information available via the Internet is enormous, and users need to access information that is appropriate for their individual reading level, interests, and emotional state. However, conventional news delivery systems are unable to meet the individual needs of users, preventing them from effectively understanding the information or achieving psychological satisfaction. In particular, the provision of content tailored to emotional states has not been fully realized. This limits the user experience and reduces the efficiency of information reception and comprehension.

[0839] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's reading level, interests, and emotional state, means for customizing a news article based on the user's reading level, interests, and emotional state, means for displaying the customized news article on the user terminal, means for analyzing the user's emotional data using an emotion engine, and means for adjusting the text of the news article using a generative AI model. This makes it possible to provide news articles optimized for the user's reading level, interests, and emotional state, thereby enabling effective understanding of information and improving psychological satisfaction.

[0840] "User" refers to an individual who uses the System to view news articles.

[0841] "Reading level" is a standard that indicates the level of difficulty of a news article that a user can understand.

[0842] "Interests" refers to the themes or topics that a user is particularly interested in.

[0843] "Emotional state" refers to the user's state of mind or psychological state.

[0844] "News Article" refers to information content obtained from a news source.

[0845] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0846] An "emotion engine" is software or algorithm that analyzes a user's emotional data and determines their emotional state.

[0847] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate or adjust the content of a news article.

[0848] MODE FOR CARRYING OUT THE INVENTION

[0849] The present invention is a system for personalizing news content according to a user's reading level, interests, and emotional state. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0850] Server Roles

[0851] The server performs the following functions:

[0852] 1. Update the news database

[0853] The server retrieves the latest news articles from news sources and automatically updates the database. Specifically, it collects article information using RSS feeds and APIs. This task is set to run periodically. For example, the server can collect the latest technology-related articles every morning at 5:00 and store them in the database.

[0854] 2. Analysis of User Information

[0855] The server analyzes the information submitted by the user regarding reading level, interests, and emotional state, and then uses an emotional engine to further analyze the user's emotional state and select relevant news articles based on the results.

[0856] 3. Generate customized news articles

[0857] The server uses a generative AI model to tailor the content of news articles based on the user's reading level and emotional state. Specifically, it condenses the article, adds relevant visual information, and adjusts the tone to suit the emotion. An example of a prompt for the generative AI model is, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate science-related news articles appropriate for this user."

[0858] Device Role

[0859] The terminal performs the following functions:

[0860] 1. Providing a user interface

[0861] The device provides an interface that allows the user to set reading level, interests, and emotional state. Specific interface elements include drop-down menus and fields for selecting emotional states.

[0862] 2. Getting and Sending User Input

[0863] The device takes the information entered by the user and sends it to the server as an HTTP request. For example, if the user sets their interest as "science," their reading level as "intermediate," and their emotional state as "excited," this information is sent.

[0864] 3. Customized news article display

[0865] The device displays customized news articles sent from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[0866] User Roles

[0867] The user does the following:

[0868] 1. Profile Settings

[0869] The user inputs their reading level, interests, and emotional state through the terminal. For example, the user may set that they are interested in "science," their reading level is "intermediate," and they are currently "excited."

[0870] 2. Reading news articles

[0871] Users view personalized news articles displayed on their devices, optimized based on their preferences to make them easier to understand and more satisfying to the user.

[0872] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level, interests, and even emotional state, it is possible to provide optimal information to the user. Through this system, users can receive news articles in a more understandable format, which is psychologically satisfying.

[0873] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0874] Step 1:

[0875] The server retrieves the latest news articles from news sources. The input is the URL or RSS feed of the news source, and the output is the latest news article. Specifically, the server reads the RSS feed from the specified news source, extracts the content of the latest article, and stores it in a database.

[0876] Step 2:

[0877] Users input their reading level, interests, and emotional state through their devices. The input is the information the user sets on the device, and the output is the information sent to the server as an HTTP request. Specifically, users use drop-down menus and selection fields to set the required settings.

[0878] Step 3:

[0879] The server analyzes the information obtained from the user regarding reading level, interests, and emotional state. The input is the information sent by the user, and the output is the analysis result, which is instructions for selecting and customizing appropriate news articles. Specifically, the server uses an emotion engine to analyze the user's emotional state and selects relevant news articles based on the results.

[0880] Step 4:

[0881] The server inputs relevant news articles into the generative AI model and adjusts the text to suit the user's reading level and emotional state. The input is the selected news article and user information, and the output is a customized news article. Specifically, the server generates a prompt sentence and inputs it into the generative AI model to regenerate the article text. For example, the prompt sentence could be, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate a science-related news article that is appropriate for this user."

[0882] Step 5:

[0883] The server sends the generated customized news article to the user's device. The input is the customized news article, and the output is the news article data as an HTTP response. Specifically, the server formats the article data appropriately and sends it to the device.

[0884] Step 6:

[0885] The terminal displays the received customized news article to the user. The input is the news article data sent from the server, and the output is the news article displayed on the user interface. In concrete terms, the terminal analyzes the received data and displays the article on the screen. The user then views the displayed customized news article.

[0886] (Application example 2)

[0887] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0888] Conventional news delivery systems customize news articles based solely on a user's reading level and interests. This means that they do not provide information appropriate to the user's emotional state, making it difficult to continuously capture the user's interest. Furthermore, the lack of a function to analyze the user's emotional state in real time and adjust the tone of the news article accordingly limits the user experience.

[0889] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the reading level and interests from the user, means for customizing news articles based on the reading level and interests, means for analyzing the user's emotional state, means for customizing news articles based on the emotional state, and means for displaying the customized news articles on the user terminal. This makes it possible to provide news articles that are appropriate for the user's emotional state as well as their reading level and interests.

[0890] "Means of obtaining reading level and interests from users" refers to input interfaces and sensor devices that are used to understand users' reading ability and areas of interest.

[0891] "Means for customizing news articles based on said reading level and interests" refers to algorithms or software processes that adjust news content based on the acquired user's reading level and interests.

[0892] "Means for analyzing the user's emotional state" refers to an emotion engine, biometric sensor, or AI-based analysis module that recognizes and analyzes the user's emotions in real time.

[0893] "Means for customizing news articles based on said emotional state" refers to an algorithm or software that has the ability to adjust the content and tone of a news article depending on the analyzed emotional state of the user.

[0894] "Means for displaying the customized news article on a user terminal" refers to an output device such as a smartphone application or a web interface for displaying the news article optimized for the user.

[0895] "Means of obtaining the latest news articles from news sources and storing them in a database" refers to the process of collecting the latest news data via the Internet or RSS feeds and storing it in a storage device such as a server.

[0896] "Means of simplifying text or adding visual information to news articles based on the user's reading level" refers to algorithms or software that simplify text to adapt to the user's reading ability, or add charts or images to aid comprehension.

[0897] "Means for adjusting the tone of news articles based on the user's emotional state" refers to an algorithm or machine learning model that adjusts the tone and wording of an article to match the user's psychological state.

[0898] "Means of using generative AI models to generate news articles based on a user's reading level, interests, and emotional state" refers to the process of using AI or machine learning models to automatically generate news articles that match the characteristics of a user.

[0899] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It is possible to customize news articles using user input and emotional data, and provide them in a format appropriate for the user. The system includes three elements: a server, a terminal, and a user, as well as an emotional engine.

[0900] Server Roles

[0901] The server performs the following functions:

[0902] 1. Update the news database:

[0903] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing users with the latest content.

[0904] 2. Analysis of User Information:

[0905] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[0906] 3. How the Emotion Engine works:

[0907] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[0908] 4. Generate customized news articles:

[0909] The server then runs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, allowing the news article to be presented to the user in the most appropriate format.

[0910] Device Role

[0911] The terminal performs the following functions:

[0912] 1. Providing a user interface:

[0913] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[0914] 2. Getting and sending user input:

[0915] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[0916] 3. Displaying customized news articles:

[0917] The device displays customized news articles retrieved from the server to the user, allowing the user to view news articles in a format appropriate to their reading level and emotional state.

[0918] User Roles

[0919] The user does the following:

[0920] 1. Profile Settings:

[0921] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[0922] 2. Viewing news articles:

[0923] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[0924] Specific examples

[0925] Here are some specific usage examples:

[0926] 1. Update the news database:

[0927] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[0928] 2. Analysis of User Information:

[0929] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[0930] 3. Generate customized news articles:

[0931] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[0932] 4. Displaying customized news articles:

[0933] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[0934] Prompt Sentence Examples

[0935] Here are some example input prompts for a generative AI model:

[0936] "Generate a news article suitable for users with an intermediate reading level, an interest in science, and current excitement. The original article reads: 'New research published today suggests that...'"

[0937] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0938] Step 1:

[0939] The device receives input from the user regarding reading level, interests, and emotional state. This input includes the user's selected reading level (beginner, intermediate, advanced, etc.), areas of interest (science, sports, economics, etc.), and current emotional state (excited, calm, etc.). Once this information is entered into the device, it is sent to the server as an HTTP request.

[0940] Input: User's reading level, interests, and emotional state

[0941] Output: User information sent to the server as an HTTP request

[0942] Step 2:

[0943] The server analyzes the user's reading level, interests, and emotional state information obtained from the device. Based on the analysis, it selects news articles from the database that are appropriate for the user. This selection process involves filtering articles in categories that match the user's interests.

[0944] Input: User information received by the server as an HTTP request

[0945] Output: News articles filtered based on the user's reading level and interests

[0946] Step 3:

[0947] The server then simplifies the selected news articles based on the user's reading level. In this step, the server uses a library or algorithm to simplify the text, converting it into a form that is easy for the user to understand.

[0948] Input: filtered news articles, user reading level

[0949] Output: A simplified news article

[0950] Step 4:

[0951] The server uses an emotion engine to analyze the user's emotional data and adjust the tone of the news article based on the results: if the user is "excited," the emotion engine adjusts the article to an energetic tone, and if the user is "calm," it adjusts the tone to a calmer tone.

[0952] Input: Simplified news article, sentiment engine analysis results

[0953] Output: Tone-adjusted news article

[0954] Step 5:

[0955] The server uses the generative AI model to further customize the news article based on all the user information, specifically by inputting prompts to the generative AI model to generate and adjust the article.

[0956] Input: Tone-adjusted news articles, prompts based on user information

[0957] Output: A news article further customized by AI

[0958] Step 6:

[0959] The server then sends the customized news article to the device as an HTTP response.

[0960] Input: Customized news article

[0961] Output: News article sent to the terminal as an HTTP response

[0962] Step 7:

[0963] The device displays customized news articles sent from the server to the user, allowing the user to view news articles that are appropriate for their reading level, interests, and emotional state.

[0964] Input: News article received as an HTTP response

[0965] Output: A customized news article displayed on the terminal screen.

[0966] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0967] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0968] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0969] [Third embodiment]

[0970] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0971] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0972] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0973] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0974] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0975] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0976] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0977] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0978] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0979] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0980] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0981] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0982] System Overview

[0983] This invention provides a system for personalizing news content based on a user's reading level and interests. It mainly involves three elements: a server, a terminal, and a user. The system uses profile information entered by the user to customize news articles and provide them in a format appropriate for the user.

[0984] Server Roles

[0985] The server performs the following functions:

[0986] 1. Update the news database:

[0987] The server periodically retrieves the latest news articles from news sources and stores them in a database, ensuring that fresh content is always available.

[0988] 2. Analysis of User Information:

[0989] The server selects and customizes relevant news articles based on the user's reading level and interests, which may include simplifying the text and adding visual information.

[0990] 3. Generate customized news articles:

[0991] The server condenses the text of news articles and adds relevant visual information based on the user's reading level, using natural language processing and image recognition techniques in the process.

[0992] Device Role

[0993] The terminal performs the following functions:

[0994] 1. Providing a user interface:

[0995] The device provides an interface that allows users to set their reading level and interests, and allows users to easily access news articles.

[0996] 2. Getting and sending user input:

[0997] The device automatically sends the user's input about their reading level and interests to the server.

[0998] 3. Displaying customized news articles:

[0999] The device displays customized news articles retrieved from the server to the user, allowing the user to view news content in a format that best suits them.

[1000] User Roles

[1001] The user does the following:

[1002] 1. Profile Settings:

[1003] Users input their reading level and interests through the device, and these settings personalize the news articles they receive.

[1004] 2. Viewing news articles:

[1005] Users view customized news articles displayed on their devices, which are presented in a format that is easy for users to understand and therefore engaging to read.

[1006] Specific examples

[1007] Specific usage examples are shown below.

[1008] 1. Update the news database:

[1009] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1010] 2. Analysis of User Information:

[1011] If User A is interested in "science" and sets his reading level to "intermediate," the server will select science-related news articles that are appropriate for User A.

[1012] 3. Generate customized news articles:

[1013] The server converts the selected news article into concise text appropriate for User A's reading level, and also adds relevant charts and illustrations.

[1014] 4. Displaying customized news articles:

[1015] The terminal displays the customized news article sent from the server to User A. This allows User A to view the article in an easy-to-understand format.

[1016] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide educational content that is both engaging and easy to understand for the user.

[1017] The processing flow will be explained below.

[1018] Step 1:

[1019] The server retrieves the latest news articles from news sources, for example, by using RSS feeds or news APIs to aggregate data from multiple news sources.

[1020] Step 2:

[1021] The server stores the retrieved news articles in a database, which is then periodically updated with the latest news articles.

[1022] Step 3:

[1023] Users use the device's user interface to input their reading level and interests, using drop-down menus and checkboxes to make selections.

[1024] Step 4:

[1025] The device sends the user-entered reading level and interest information to the server, which is then sent as an HTTP request.

[1026] Step 5:

[1027] The server analyzes the received user information and stores it as a user profile, allowing for customization for each user.

[1028] Step 6:

[1029] The server selects news articles based on the user's profile, searching the database for articles that match the user's interests and reading level.

[1030] Step 7:

[1031] The server customizes the selected news articles by simplifying the text and adding visual information (e.g., illustrations and charts) to suit the user's reading level.

[1032] Step 8:

[1033] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[1034] Step 9:

[1035] The device receives customized news articles from the server and displays them to the user, who can then view them in a format that suits their reading level and interests.

[1036] Step 10:

[1037] After a user finishes viewing a news article, their device sends their browsing history to a server, which can then track changes in the user's interests and reading level and use this information to customize the next news article.

[1038] Example 1

[1039] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1040] In today's information-saturated society, users face the challenge of finding information that matches their reading level and interests. Furthermore, many news articles are written in technical terms and long sentences, making them difficult for average users to understand. This creates a challenge for users, making it difficult to quickly and easily obtain information that is relevant to them.

[1041] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1042] In this invention, the server includes means for obtaining a reading level and interests from a user, means for customizing news articles based on the reading level and interests, means for displaying the customized news articles on a user terminal, and means for using a generative AI model to simplify text and add visual information to the news articles, thereby enabling users to easily access news articles that match their reading level and interests and obtain information in an easy-to-understand format.

[1043] "User" means a person who uses the System to view news articles.

[1044] "Reading level" is an indicator of the level of difficulty of a text that makes it easy for users to understand the information.

[1045] "Interests" refers to areas or topics that a user is particularly interested in.

[1046] A "news article" is information in text form obtained from a news source and provided to a user.

[1047] "Customization" refers to the act of individually adjusting or changing information based on a user's reading level and interests.

[1048] "User device" means the electronic device (e.g., smartphone, PC, tablet, etc.) that a user uses to view news articles.

[1049] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate and process text.

[1050] "Visual information" refers to visual information such as charts and illustrations added to news articles.

[1051] A "news source" is a media outlet or data provider that provides information for a news article.

[1052] A "database" is a system for managing and storing data such as acquired news articles and user profiles.

[1053] MODE FOR CARRYING OUT THE INVENTION

[1054] The present invention provides a system for personalizing news articles based on a user's reading level and interests, the detailed embodiments of which are described below.

[1055] System Overview

[1056] The system mainly consists of three elements: a server, a terminal, and a user. The server collects, analyzes, and customizes news articles, while the terminal provides the user interface and transmits and displays user input. Users set their own reading level and interests to view customized news articles.

[1057] Server Roles

[1058] 1. Update the news database:

[1059] The server periodically retrieves the latest articles from news sources (e.g., APIs or RSS feeds) and updates the database. This process is performed using Python and the requests library, for example. The retrieved article data is stored in MySQL or MongoDB.

[1060] 2. Analysis of User Information:

[1061] The server receives user profile information (reading level, interests, etc.) sent from the device, and then uses natural language processing and data analysis techniques (e.g., the "scikit-learn" library) to select relevant news articles.

[1062] 3. Generate customized news articles:

[1063] The server then condenses the selected news articles to fit the user's reading level and uses a generative AI model (e.g., GPT-4) to add visual information, using the OpenCV library, for example.

[1064] Device Role

[1065] 1. Providing a user interface:

[1066] The device provides an interface for users to enter their profile information, which is built using React and HTML / CSS.

[1067] 2. Getting and sending user input:

[1068] The device takes the information entered by the user (reading level and interests) and sends it to the server using an HTTP POST request, using JavaScript and the axios library.

[1069] 3. Displaying customized news articles:

[1070] The device receives customized news articles sent from the server and displays them in an appropriate format, using React components.

[1071] User Roles

[1072] 1. Profile Settings:

[1073] Users input and set their reading level and interests through their devices, which then becomes the basis for personalizing news articles.

[1074] 2. Viewing news articles:

[1075] Users can view customized news articles displayed on their device and get information in an easy-to-understand format.

[1076] Specific examples

[1077] 1. Update the news database:

[1078] Every morning, the server retrieves the latest news from news sources and updates the database, for example by collecting and storing data from science-related RSS feeds.

[1079] 2. Analysis of User Information:

[1080] If User A selects "Science" as his or her area of ​​interest and his or her reading level as "Intermediate," the server will select science-related news articles appropriate for that user, such as "AI in Biomedical Research."

[1081] 3. Generate customized news articles:

[1082] The server then uses the GPT-4 model to simplify the selected articles and add relevant charts and illustrations, for example summarizing scientific articles and adding charts and illustrations of relevant experimental results.

[1083] 4. Displaying customized news articles:

[1084] The device displays the received customized news article to the user, who then scrolls through the article in a React-based application.

[1085] Example input to a generative AI model

[1086] Example prompt sentence:

[1087] Please adapt the original article "AI in Biomedical Research" into concise text appropriate for User A's intermediate reading level, and add relevant figures and tables. User A is interested in science. Please also simplify the terminology and emphasize the key points.

[1088] The above is a specific embodiment of the present invention. This system allows users to easily browse news articles that match their reading level and interests, enabling them to obtain information efficiently.

[1089] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1090] System program processing flow

[1091] Server Processing Steps

[1092] Step 1:

[1093] Get articles from news sources

[1094] The server periodically retrieves the latest articles from the news source.

[1095] Input: API endpoint or RSS feed URL.

[1096] Data processing: Send an HTTP request using Python's requests library and obtain article data as a response.

[1097] Output: News article data in JSON format.

[1098] What it does: Every morning at 8am the server runs a scheduled task that retrieves data from news sources.

[1099] Step 2:

[1100] Saving to a database

[1101] The server analyzes the acquired article data and stores it in a news database.

[1102] Input: News article data in JSON format.

[1103] Data processing: Parse the acquired article data and extract necessary fields (e.g., title, body text, publication date, category, etc.).

[1104] Output: Store the formatted data in a database.

[1105] Specific behavior: Insert data into the database using SQL queries or MongoDB APIs.

[1106] Step 3:

[1107] Receiving user data

[1108] The server receives the user profile information sent from the terminal.

[1109] Input: User reading level and interest data sent in an HTTP POST request.

[1110] Data processing: Parse the request body and extract user data.

[1111] Output: A user profile object.

[1112] What it does: The server uses the Flask framework to parse the received data and store it in memory.

[1113] Step 4:

[1114] User profile analysis

[1115] The server selects relevant news articles based on the user's profile.

[1116] Input: User profile object, news database.

[1117] Data processing: Using the scikit-learn library, we cluster the user's interest fields and filter out relevant news articles.

[1118] Output: A list of selected news articles.

[1119] What it does: Generates queries to extract relevant articles from the database and selects articles that match the user's profile.

[1120] Step 5:

[1121] Simplifying the article and adding visual information

[1122] The server uses a generative AI model to simplify articles and add visual information.

[1123] Input: List of selected news articles, user profile.

[1124] Data processing: Calls OpenAI API to generate article summaries and adds relevant visual information using OpenCV library.

[1125] Output: A customized news article that has been abbreviated and enhanced with visual information.

[1126] What it does: It uses GPT-4 to generate prompts and perform summarization and visual information addition tasks.

[1127] Terminal processing steps

[1128] Step 6:

[1129] Viewing the Settings Interface

[1130] The device displays an interface that allows the user to enter profile information.

[1131] Input: User Access.

[1132] Data processing: None.

[1133] Output: Display of the configuration interface.

[1134] Specific behavior: Generate a form using React and HTML / CSS and display it to the user.

[1135] Step 7:

[1136] Retrieving Profile Information

[1137] The device collects information about the user's reading level and interests.

[1138] Input: User-entered data.

[1139] Data processing: Form data collection.

[1140] Output: A profile information object.

[1141] Specific operation: Store the form input contents in a variable using JavaScript.

[1142] Step 8:

[1143] Sending profile information

[1144] The terminal transmits the acquired profile information to the server.

[1145] Input: Profile information object.

[1146] Data processing: Convert the data into an HTTP POST request format.

[1147] Output: HTTP POST request to the server.

[1148] Specific behavior: Sends data to the server using the axios library.

[1149] Step 9:

[1150] Receiving news articles

[1151] The terminal receives customized news article data from the server.

[1152] Input: The HTTP response from the server.

[1153] Data processing: Analyze JSON format data.

[1154] Output: A customized news article object.

[1155] Specific operation: Analyze and store the data returned from the server using React.

[1156] Step 10:

[1157] View news articles

[1158] The terminal displays the received customized news article.

[1159] Input: A customized news article object.

[1160] Data processing: None.

[1161] Output: Display of news article.

[1162] What it does: Display an article to the user using a React component.

[1163] User processing steps

[1164] Step 11:

[1165] Enter your profile information

[1166] Users input their reading level and interests through the device.

[1167] Input: Your profile information.

[1168] Data processing: None.

[1169] Output: The profile information entered into the form.

[1170] What happens: A user fills out a form and clicks the "Submit" button.

[1171] Step 12:

[1172] Viewing news articles

[1173] Users view customized news articles displayed on their devices.

[1174] Input: A customized news article.

[1175] Data processing: None.

[1176] Output: View article.

[1177] What happens: The user scrolls through the article on the screen and reads the content.

[1178] The above is a concrete explanation of each processing step in the program of this system.

[1179] (Application example 1)

[1180] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1181] In modern content distribution services, it is difficult to efficiently provide users with news articles that are both interesting and appropriate for their reading level. Conventional news distribution systems provide uniform content without fully considering users' interests or reading level, which is likely to result in low user satisfaction. Furthermore, they do not allow for customization of news articles that include visual information, and lack functionality to further improve the user experience. There is a need to solve this problem and provide users with the most appropriate news articles.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1183] In this invention, the server includes means for acquiring a user's reading level and interests, means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies, and means for delivering the customized news articles to a device in real time, thereby enabling the user to be provided with articles tailored to the user's interests that are simplified to fit the user's reading level and include related visual content.

[1184] "Means for obtaining reading level and interests from users" means a method for providing an interface that allows users to input or select their reading ability and interests.

[1185] The "means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies" refers to a method that uses natural language processing and image recognition technologies to simplify sentences according to the user's reading level and add visual information that matches the user's interests.

[1186] "Means for delivering the customized news articles to a device in real time" refers to a method for instantly transmitting individually customized news articles from a server to a user's device (such as a smartphone or head-mounted display).

[1187] "Means for obtaining the latest news articles from news sources and storing them in an information aggregation" refers to a method for periodically collecting the latest news articles from reliable news sources via the Internet and storing them in a database.

[1188] "Means of simplifying the content of news articles or adding visual content to them based on the user's reading level" refers to translating the content into language appropriate to the user's reading ability and inserting relevant charts and pictures into the article.

[1189] System Overview

[1190] This invention provides a system that personalizes news content to match a user's reading level and interests. The system mainly consists of three elements: a server, a terminal, and a user. Based on the profile information entered by the user, the system customizes news articles and provides them in a format appropriate for the user.

[1191] Server Roles

[1192] News database updates

[1193] The server periodically retrieves the latest news articles from news sources (such as news APIs) via the Internet and stores them in an information collection (database). This operation ensures that new content is always available.

[1194] Analyzing user information and customizing articles

[1195] The server analyzes the user's reading level and interests, and then customizes the news article based on this using natural language processing and image recognition technologies. Specifically, it simplifies the content of the article according to the user's reading level and adds visual information appropriate to their interests. This allows the server to provide users with news content that is both easy to understand and interesting.

[1196] Generate customized news articles

[1197] The server uses a generative AI model to generate a customized news article based on a prompt, such as the following:

[1198] "User A has an intermediate reading level and is interested in science and technology. Please translate the latest science news articles into simple sentences and add relevant figures and tables."

[1199] Device Role

[1200] Providing a user interface

[1201] The device provides an interface where users can set their reading level and interests, and through this interface, they can easily enter their profile and access news articles.

[1202] Getting and sending user input

[1203] The device sends the information the user enters to a server, which does this in real time and helps generate a customized news article for the user to view.

[1204] Customized news article display

[1205] The device displays customized news articles sent from the server to the user, allowing the user to view news content in a format that is optimized for them.

[1206] User Roles

[1207] Profile Settings

[1208] Users input their reading level and interests through the device, which personalizes the news articles they receive.

[1209] Viewing news articles

[1210] Users view customized news articles displayed on their devices, providing information in an easy-to-understand format.

[1211] Hardware and Software

[1212] The main hardware used to realize this system is cloud-based servers (e.g., AWS EC2) and devices such as smartphones and head-mounted displays. The software used includes an API for retrieving news articles (e.g., NewsAPI), natural language processing technology, image recognition technology, and generative AI models.

[1213] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide content that is both interesting and easy to understand for the user.

[1214] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1215] Step 1:

[1216] The user (device) enters their reading level and interests.

[1217] Input: Reading level and interest categories (e.g., science, technology, sports) set by the user through their device.

[1218] Output: Information about the user's reading level and interests is stored on the device and sent to the server.

[1219] Specific behavior: The user uses drop-down menus and checkboxes on the device app's settings screen to select a reading level (e.g., beginner, intermediate, advanced) and interest categories, then presses the Settings button.

[1220] Step 2:

[1221] The server receives the user profile information and stores it in a database.

[1222] Input: User's reading level and interest information obtained in step 1.

[1223] Output: User profile information stored in a database.

[1224] Specific operation: The server receives the reading level and interest category information sent from the device, first validates the input values, and then stores them in the database.

[1225] Step 3:

[1226] The server retrieves the latest news articles from the news sources and updates the database.

[1227] Input: News API endpoint.

[1228] Output: The latest news articles stored in the database.

[1229] Specific operation: The server periodically calls the news API to retrieve the latest articles provided, receives them in XML or JSON format, and then converts them into a database format and saves them.

[1230] Step 4:

[1231] The server customizes news articles based on the user's reading level and interests.

[1232] Input: User profile information and news articles in the database.

[1233] Output: A customized news article.

[1234] How it works: Based on user profile information, the server selects news articles, simplifies the text, and adds relevant visual information. Natural language processing technology is used to simplify the text, and image recognition technology is used to extract and generate relevant visual elements (such as charts) and add them to the article.

[1235] Step 5:

[1236] Customized news articles are optimized using generative AI models and further personalized for each user based on prompt text.

[1237] Input: Customized news articles and per-user prompts.

[1238] Output: Optimized news articles.

[1239] How it works: The server inputs a prompt into the generative AI model, which then generates a news article in a format appropriate for the user's reading level and interests. For example, a prompt like "User A has an intermediate reading level and is interested in science and technology. Please convert the latest science news article into simple sentences and add relevant figures and tables" is input into the generative AI model.

[1240] Step 6:

[1241] The server delivers optimized news articles to the device in real time.

[1242] Input: Optimized news articles.

[1243] Output: The news article displayed on the user's device.

[1244] How it works: The server sends optimized news articles to the device via push notification or API, and the device receives them. The device app displays the received articles in its user interface.

[1245] Step 7:

[1246] The user views customized news articles through their device.

[1247] Input: A news article displayed on a user's device.

[1248] Output: Improved user satisfaction.

[1249] What it does: The user opens their device, browses to a news article delivered in real time, and reads along with the provided visual information.

[1250] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1251] System Overview

[1252] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It includes three elements: a server, a device, and a user, as well as an emotion engine. The system uses input information and emotional data from the user to customize news articles and present them in a format appropriate for the user.

[1253] Server Roles

[1254] The server performs the following functions:

[1255] 1. Update the news database:

[1256] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing the latest content.

[1257] 2. Analysis of User Information:

[1258] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[1259] 3. How the Emotion Engine works:

[1260] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[1261] 4. Generate customized news articles:

[1262] The server then performs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, thereby providing the news article in the most appropriate format for the user.

[1263] Device Role

[1264] The terminal performs the following functions:

[1265] 1. Providing a user interface:

[1266] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[1267] 2. Getting and sending user input:

[1268] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[1269] 3. Displaying customized news articles:

[1270] The device displays customized news articles retrieved from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[1271] User Roles

[1272] The user does the following:

[1273] 1. Profile Settings:

[1274] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[1275] 2. Viewing news articles:

[1276] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[1277] Specific examples

[1278] Specific usage examples are shown below.

[1279] 1. Update the news database:

[1280] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1281] 2. Analysis of User Information:

[1282] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[1283] 3. Generate customized news articles:

[1284] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[1285] 4. Displaying customized news articles:

[1286] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[1287] The above is a specific embodiment of the present invention. By personalizing news articles based on a user's reading level, interests, and even emotional state, it is possible to provide educational content that is engaging, easy to understand, and appropriate for the user's psychological state.

[1288] The processing flow will be explained below.

[1289] Step 1:

[1290] The server retrieves the latest news articles from news sources. Specifically, it collects data from multiple news sources using RSS feeds and news APIs. The collected data is obtained in JSON or XML format.

[1291] Step 2:

[1292] The server stores the retrieved news articles in a database. When storing them in the database, a duplicate check is performed and articles that already exist are excluded. This process ensures that the latest news articles are always updated in the database.

[1293] Step 3:

[1294] Users use the device's user interface to input their reading level, interests, and emotional state, which can be selected using drop-down menus and checkboxes, or which can be automatically obtained using facial recognition or voice analysis.

[1295] Step 4:

[1296] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information in JSON format as an HTTP request.

[1297] Step 5:

[1298] The server analyzes the received user information and stores it as a user profile, which includes information on reading level, interests, and emotional state, allowing for customization for each user.

[1299] Step 6:

[1300] The server selects news articles based on the user's profile. In particular, it searches the database for articles that match the user's interests, reading level, and emotional state. For example, if the user is interested in "science," has an "intermediate" reading level, and is emotionally "excited," the server will select the corresponding article.

[1301] Step 7:

[1302] The server customizes the selected news articles, shortening the sentences to match the user's reading level and adjusting the tone to suit the user's emotional state. It also adds visual information (e.g., illustrations and diagrams) and selects visual information appropriate to the user's emotional state. For example, a user in an excited state might be shown visually stimulating images.

[1303] Step 8:

[1304] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[1305] Step 9:

[1306] The device receives customized news articles from the server and displays them to the user, allowing the user to view the news articles in a format that suits their reading level, interests, and emotional state.

[1307] Step 10:

[1308] After a user finishes viewing a news article, their browsing history and new emotional data are sent from the device to the server, allowing the server to track changes in the user's interests and emotional state and use this information to customize the next news article. This process allows for even more accurate article delivery.

[1309] Example 2

[1310] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1311] In today's world, the amount of information available via the Internet is enormous, and users need to access information that is appropriate for their individual reading level, interests, and emotional state. However, conventional news delivery systems are unable to meet the individual needs of users, preventing them from effectively understanding the information or achieving psychological satisfaction. In particular, the provision of content tailored to emotional states has not been fully realized. This limits the user experience and reduces the efficiency of information reception and comprehension.

[1312] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's reading level, interests, and emotional state, means for customizing a news article based on the user's reading level, interests, and emotional state, means for displaying the customized news article on the user terminal, means for analyzing the user's emotional data using an emotion engine, and means for adjusting the text of the news article using a generative AI model. This makes it possible to provide news articles optimized for the user's reading level, interests, and emotional state, thereby enabling effective understanding of information and improving psychological satisfaction.

[1313] "User" refers to an individual who uses the System to view news articles.

[1314] "Reading level" is a standard that indicates the level of difficulty of a news article that a user can understand.

[1315] "Interests" refers to the themes or topics that a user is particularly interested in.

[1316] "Emotional state" refers to the user's state of mind or psychological state.

[1317] "News Article" refers to information content obtained from a news source.

[1318] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1319] An "emotion engine" is software or algorithm that analyzes a user's emotional data and determines their emotional state.

[1320] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate or adjust the content of a news article.

[1321] MODE FOR CARRYING OUT THE INVENTION

[1322] The present invention is a system for personalizing news content according to a user's reading level, interests, and emotional state. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1323] Server Roles

[1324] The server performs the following functions:

[1325] 1. Update the news database

[1326] The server retrieves the latest news articles from news sources and automatically updates the database. Specifically, it collects article information using RSS feeds and APIs. This task is set to run periodically. For example, the server can collect the latest technology-related articles every morning at 5:00 and store them in the database.

[1327] 2. Analysis of User Information

[1328] The server analyzes the information submitted by the user regarding reading level, interests, and emotional state, and then uses an emotional engine to further analyze the user's emotional state and select relevant news articles based on the results.

[1329] 3. Generate customized news articles

[1330] The server uses a generative AI model to tailor the content of news articles based on the user's reading level and emotional state. Specifically, it condenses the article, adds relevant visual information, and adjusts the tone to suit the emotion. An example of a prompt for the generative AI model is, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate science-related news articles appropriate for this user."

[1331] Device Role

[1332] The terminal performs the following functions:

[1333] 1. Providing a user interface

[1334] The device provides an interface that allows the user to set reading level, interests, and emotional state. Specific interface elements include drop-down menus and fields for selecting emotional states.

[1335] 2. Getting and Sending User Input

[1336] The device takes the information entered by the user and sends it to the server as an HTTP request. For example, if the user sets their interest as "science," their reading level as "intermediate," and their emotional state as "excited," this information is sent.

[1337] 3. Customized news article display

[1338] The device displays customized news articles sent from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[1339] User Roles

[1340] The user does the following:

[1341] 1. Profile Settings

[1342] The user inputs their reading level, interests, and emotional state through the terminal. For example, the user may set that they are interested in "science," their reading level is "intermediate," and they are currently "excited."

[1343] 2. Reading news articles

[1344] Users view personalized news articles displayed on their devices, optimized based on their preferences to make them easier to understand and more satisfying to the user.

[1345] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level, interests, and even emotional state, it is possible to provide optimal information to the user. Through this system, users can receive news articles in a more understandable format, which is psychologically satisfying.

[1346] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1347] Step 1:

[1348] The server retrieves the latest news articles from news sources. The input is the URL or RSS feed of the news source, and the output is the latest news article. Specifically, the server reads the RSS feed from the specified news source, extracts the content of the latest article, and stores it in a database.

[1349] Step 2:

[1350] Users input their reading level, interests, and emotional state through their devices. The input is the information the user sets on the device, and the output is the information sent to the server as an HTTP request. Specifically, users use drop-down menus and selection fields to set the required settings.

[1351] Step 3:

[1352] The server analyzes the information obtained from the user regarding reading level, interests, and emotional state. The input is the information sent by the user, and the output is the analysis result, which is instructions for selecting and customizing appropriate news articles. Specifically, the server uses an emotion engine to analyze the user's emotional state and selects relevant news articles based on the results.

[1353] Step 4:

[1354] The server inputs relevant news articles into the generative AI model and adjusts the text to suit the user's reading level and emotional state. The input is the selected news article and user information, and the output is a customized news article. Specifically, the server generates a prompt sentence and inputs it into the generative AI model to regenerate the article text. For example, the prompt sentence could be, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate a science-related news article that is appropriate for this user."

[1355] Step 5:

[1356] The server sends the generated customized news article to the user's device. The input is the customized news article, and the output is the news article data as an HTTP response. Specifically, the server formats the article data appropriately and sends it to the device.

[1357] Step 6:

[1358] The terminal displays the received customized news article to the user. The input is the news article data sent from the server, and the output is the news article displayed on the user interface. In concrete terms, the terminal analyzes the received data and displays the article on the screen. The user then views the displayed customized news article.

[1359] (Application example 2)

[1360] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1361] Conventional news delivery systems customize news articles based solely on a user's reading level and interests. This means that they do not provide information appropriate to the user's emotional state, making it difficult to continuously capture the user's interest. Furthermore, the lack of a function to analyze the user's emotional state in real time and adjust the tone of the news article accordingly limits the user experience.

[1362] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the reading level and interests from the user, means for customizing news articles based on the reading level and interests, means for analyzing the user's emotional state, means for customizing news articles based on the emotional state, and means for displaying the customized news articles on the user terminal. This makes it possible to provide news articles that are appropriate for the user's emotional state as well as their reading level and interests.

[1363] "Means of obtaining reading level and interests from users" refers to input interfaces and sensor devices that are used to understand users' reading ability and areas of interest.

[1364] "Means for customizing news articles based on said reading level and interests" refers to algorithms or software processes that adjust news content based on the acquired user's reading level and interests.

[1365] "Means for analyzing the user's emotional state" refers to an emotion engine, biometric sensor, or AI-based analysis module that recognizes and analyzes the user's emotions in real time.

[1366] "Means for customizing news articles based on said emotional state" refers to an algorithm or software that has the ability to adjust the content and tone of a news article depending on the analyzed emotional state of the user.

[1367] "Means for displaying the customized news article on a user terminal" refers to an output device such as a smartphone application or a web interface for displaying the news article optimized for the user.

[1368] "Means of obtaining the latest news articles from news sources and storing them in a database" refers to the process of collecting the latest news data via the Internet or RSS feeds and storing it in a storage device such as a server.

[1369] "Means of simplifying text or adding visual information to news articles based on the user's reading level" refers to algorithms or software that simplify text to adapt to the user's reading ability, or add charts or images to aid comprehension.

[1370] "Means for adjusting the tone of news articles based on the user's emotional state" refers to an algorithm or machine learning model that adjusts the tone and wording of an article to match the user's psychological state.

[1371] "Means of using generative AI models to generate news articles based on a user's reading level, interests, and emotional state" refers to the process of using AI or machine learning models to automatically generate news articles that match the characteristics of a user.

[1372] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It is possible to customize news articles using user input and emotional data, and provide them in a format appropriate for the user. The system includes three elements: a server, a terminal, and a user, as well as an emotional engine.

[1373] Server Roles

[1374] The server performs the following functions:

[1375] 1. Update the news database:

[1376] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing users with the latest content.

[1377] 2. Analysis of User Information:

[1378] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[1379] 3. How the Emotion Engine works:

[1380] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[1381] 4. Generate customized news articles:

[1382] The server then runs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, allowing the news article to be presented to the user in the most appropriate format.

[1383] Device Role

[1384] The terminal performs the following functions:

[1385] 1. Providing a user interface:

[1386] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[1387] 2. Getting and sending user input:

[1388] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[1389] 3. Displaying customized news articles:

[1390] The device displays customized news articles retrieved from the server to the user, allowing the user to view news articles in a format appropriate to their reading level and emotional state.

[1391] User Roles

[1392] The user does the following:

[1393] 1. Profile Settings:

[1394] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[1395] 2. Viewing news articles:

[1396] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[1397] Specific examples

[1398] Here are some specific usage examples:

[1399] 1. Update the news database:

[1400] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1401] 2. Analysis of User Information:

[1402] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[1403] 3. Generate customized news articles:

[1404] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[1405] 4. Displaying customized news articles:

[1406] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[1407] Prompt Sentence Examples

[1408] Here are some example input prompts for a generative AI model:

[1409] "Generate a news article suitable for users with an intermediate reading level, an interest in science, and current excitement. The original article reads: 'New research published today suggests that...'"

[1410] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1411] Step 1:

[1412] The device receives input from the user regarding reading level, interests, and emotional state. This input includes the user's selected reading level (beginner, intermediate, advanced, etc.), areas of interest (science, sports, economics, etc.), and current emotional state (excited, calm, etc.). Once this information is entered into the device, it is sent to the server as an HTTP request.

[1413] Input: User's reading level, interests, and emotional state

[1414] Output: User information sent to the server as an HTTP request

[1415] Step 2:

[1416] The server analyzes the user's reading level, interests, and emotional state information obtained from the device. Based on the analysis, it selects news articles from the database that are appropriate for the user. This selection process involves filtering articles in categories that match the user's interests.

[1417] Input: User information received by the server as an HTTP request

[1418] Output: News articles filtered based on the user's reading level and interests

[1419] Step 3:

[1420] The server then simplifies the selected news articles based on the user's reading level. In this step, the server uses a library or algorithm to simplify the text, converting it into a form that is easy for the user to understand.

[1421] Input: filtered news articles, user reading level

[1422] Output: A simplified news article

[1423] Step 4:

[1424] The server uses an emotion engine to analyze the user's emotional data and adjust the tone of the news article based on the results: if the user is "excited," the emotion engine adjusts the article to an energetic tone, and if the user is "calm," it adjusts the tone to a calmer tone.

[1425] Input: Simplified news article, sentiment engine analysis results

[1426] Output: Tone-adjusted news article

[1427] Step 5:

[1428] The server uses the generative AI model to further customize the news article based on all the user information, specifically by inputting prompts to the generative AI model to generate and adjust the article.

[1429] Input: Tone-adjusted news articles, prompts based on user information

[1430] Output: A news article further customized by AI

[1431] Step 6:

[1432] The server then sends the customized news article to the device as an HTTP response.

[1433] Input: Customized news article

[1434] Output: News article sent to the terminal as an HTTP response

[1435] Step 7:

[1436] The device displays customized news articles sent from the server to the user, allowing the user to view news articles that are appropriate for their reading level, interests, and emotional state.

[1437] Input: News article received as an HTTP response

[1438] Output: A customized news article displayed on the terminal screen.

[1439] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1440] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1441] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1442] [Fourth embodiment]

[1443] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1444] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1445] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1446] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1447] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1448] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1449] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1450] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1451] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1452] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1453] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1454] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1455] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1456] System Overview

[1457] This invention provides a system for personalizing news content based on a user's reading level and interests. It mainly involves three elements: a server, a terminal, and a user. The system uses profile information entered by the user to customize news articles and provide them in a format appropriate for the user.

[1458] Server Roles

[1459] The server performs the following functions:

[1460] 1. Update the news database:

[1461] The server periodically retrieves the latest news articles from news sources and stores them in a database, ensuring that fresh content is always available.

[1462] 2. Analysis of User Information:

[1463] The server selects and customizes relevant news articles based on the user's reading level and interests, which may include simplifying the text and adding visual information.

[1464] 3. Generate customized news articles:

[1465] The server condenses the text of news articles and adds relevant visual information based on the user's reading level, using natural language processing and image recognition techniques in the process.

[1466] Device Role

[1467] The terminal performs the following functions:

[1468] 1. Providing a user interface:

[1469] The device provides an interface that allows users to set their reading level and interests, and allows users to easily access news articles.

[1470] 2. Getting and sending user input:

[1471] The device automatically sends the user's input about their reading level and interests to the server.

[1472] 3. Displaying customized news articles:

[1473] The device displays customized news articles retrieved from the server to the user, allowing the user to view news content in a format that best suits them.

[1474] User Roles

[1475] The user does the following:

[1476] 1. Profile Settings:

[1477] Users input their reading level and interests through the device, and these settings personalize the news articles they receive.

[1478] 2. Viewing news articles:

[1479] Users view customized news articles displayed on their devices, which are presented in a format that is easy for users to understand and therefore engaging to read.

[1480] Specific examples

[1481] Specific usage examples are shown below.

[1482] 1. Update the news database:

[1483] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1484] 2. Analysis of User Information:

[1485] If User A is interested in "science" and sets his reading level to "intermediate," the server will select science-related news articles that are appropriate for User A.

[1486] 3. Generate customized news articles:

[1487] The server converts the selected news article into concise text appropriate for User A's reading level, and also adds relevant charts and illustrations.

[1488] 4. Displaying customized news articles:

[1489] The terminal displays the customized news article sent from the server to User A. This allows User A to view the article in an easy-to-understand format.

[1490] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide educational content that is both engaging and easy to understand for the user.

[1491] The processing flow will be explained below.

[1492] Step 1:

[1493] The server retrieves the latest news articles from news sources, for example, by using RSS feeds or news APIs to aggregate data from multiple news sources.

[1494] Step 2:

[1495] The server stores the retrieved news articles in a database, which is then periodically updated with the latest news articles.

[1496] Step 3:

[1497] Users use the device's user interface to input their reading level and interests, using drop-down menus and checkboxes to make selections.

[1498] Step 4:

[1499] The device sends the user-entered reading level and interest information to the server, which is then sent as an HTTP request.

[1500] Step 5:

[1501] The server analyzes the received user information and stores it as a user profile, allowing for customization for each user.

[1502] Step 6:

[1503] The server selects news articles based on the user's profile, searching the database for articles that match the user's interests and reading level.

[1504] Step 7:

[1505] The server customizes the selected news articles by simplifying the text and adding visual information (e.g., illustrations and charts) to suit the user's reading level.

[1506] Step 8:

[1507] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[1508] Step 9:

[1509] The device receives customized news articles from the server and displays them to the user, who can then view them in a format that suits their reading level and interests.

[1510] Step 10:

[1511] After a user finishes viewing a news article, their device sends their browsing history to a server, which can then track changes in the user's interests and reading level and use this information to customize the next news article.

[1512] Example 1

[1513] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1514] In today's information-saturated society, users face the challenge of finding information that matches their reading level and interests. Furthermore, many news articles are written in technical terms and long sentences, making them difficult for average users to understand. This creates a challenge for users, making it difficult to quickly and easily obtain information that is relevant to them.

[1515] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1516] In this invention, the server includes means for obtaining a reading level and interests from a user, means for customizing news articles based on the reading level and interests, means for displaying the customized news articles on a user terminal, and means for using a generative AI model to simplify text and add visual information to the news articles, thereby enabling users to easily access news articles that match their reading level and interests and obtain information in an easy-to-understand format.

[1517] "User" means a person who uses the System to view news articles.

[1518] "Reading level" is an indicator of the level of difficulty of a text that makes it easy for users to understand the information.

[1519] "Interests" refers to areas or topics that a user is particularly interested in.

[1520] A "news article" is information in text form obtained from a news source and provided to a user.

[1521] "Customization" refers to the act of individually adjusting or changing information based on a user's reading level and interests.

[1522] "User device" means the electronic device (e.g., smartphone, PC, tablet, etc.) that a user uses to view news articles.

[1523] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate and process text.

[1524] "Visual information" refers to visual information such as charts and illustrations added to news articles.

[1525] A "news source" is a media outlet or data provider that provides information for a news article.

[1526] A "database" is a system for managing and storing data such as acquired news articles and user profiles.

[1527] MODE FOR CARRYING OUT THE INVENTION

[1528] The present invention provides a system for personalizing news articles based on a user's reading level and interests, the detailed embodiments of which are described below.

[1529] System Overview

[1530] The system mainly consists of three elements: a server, a terminal, and a user. The server collects, analyzes, and customizes news articles, while the terminal provides the user interface and transmits and displays user input. Users set their own reading level and interests to view customized news articles.

[1531] Server Roles

[1532] 1. Update the news database:

[1533] The server periodically retrieves the latest articles from news sources (e.g., APIs or RSS feeds) and updates the database. This process is performed using Python and the requests library, for example. The retrieved article data is stored in MySQL or MongoDB.

[1534] 2. Analysis of User Information:

[1535] The server receives user profile information (reading level, interests, etc.) sent from the device, and then uses natural language processing and data analysis techniques (e.g., the "scikit-learn" library) to select relevant news articles.

[1536] 3. Generate customized news articles:

[1537] The server then condenses the selected news articles to fit the user's reading level and uses a generative AI model (e.g., GPT-4) to add visual information, using the OpenCV library, for example.

[1538] Device Role

[1539] 1. Providing a user interface:

[1540] The device provides an interface for users to enter their profile information, which is built using React and HTML / CSS.

[1541] 2. Getting and sending user input:

[1542] The device takes the information entered by the user (reading level and interests) and sends it to the server using an HTTP POST request, using JavaScript and the axios library.

[1543] 3. Displaying customized news articles:

[1544] The device receives customized news articles sent from the server and displays them in an appropriate format, using React components.

[1545] User Roles

[1546] 1. Profile Settings:

[1547] Users input and set their reading level and interests through their devices, which then becomes the basis for personalizing news articles.

[1548] 2. Viewing news articles:

[1549] Users can view customized news articles displayed on their device and get information in an easy-to-understand format.

[1550] Specific examples

[1551] 1. Update the news database:

[1552] Every morning, the server retrieves the latest news from news sources and updates the database, for example by collecting and storing data from science-related RSS feeds.

[1553] 2. Analysis of User Information:

[1554] If User A selects "Science" as his or her area of ​​interest and his or her reading level as "Intermediate," the server will select science-related news articles appropriate for that user, such as "AI in Biomedical Research."

[1555] 3. Generate customized news articles:

[1556] The server then uses the GPT-4 model to simplify the selected articles and add relevant charts and illustrations, for example summarizing scientific articles and adding charts and illustrations of relevant experimental results.

[1557] 4. Displaying customized news articles:

[1558] The device displays the received customized news article to the user, who then scrolls through the article in a React-based application.

[1559] Example input to a generative AI model

[1560] Example prompt sentence:

[1561] Please adapt the original article "AI in Biomedical Research" into concise text appropriate for User A's intermediate reading level, and add relevant figures and tables. User A is interested in science. Please also simplify the terminology and emphasize the key points.

[1562] The above is a specific embodiment of the present invention. This system allows users to easily browse news articles that match their reading level and interests, enabling them to obtain information efficiently.

[1563] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1564] System program processing flow

[1565] Server Processing Steps

[1566] Step 1:

[1567] Get articles from news sources

[1568] The server periodically retrieves the latest articles from the news source.

[1569] Input: API endpoint or RSS feed URL.

[1570] Data processing: Send an HTTP request using Python's requests library and obtain article data as a response.

[1571] Output: News article data in JSON format.

[1572] What it does: Every morning at 8am the server runs a scheduled task that retrieves data from news sources.

[1573] Step 2:

[1574] Saving to a database

[1575] The server analyzes the acquired article data and stores it in a news database.

[1576] Input: News article data in JSON format.

[1577] Data processing: Parse the acquired article data and extract necessary fields (e.g., title, body text, publication date, category, etc.).

[1578] Output: Store the formatted data in a database.

[1579] Specific behavior: Insert data into the database using SQL queries or MongoDB APIs.

[1580] Step 3:

[1581] Receiving user data

[1582] The server receives the user profile information sent from the terminal.

[1583] Input: User reading level and interest data sent in an HTTP POST request.

[1584] Data processing: Parse the request body and extract user data.

[1585] Output: A user profile object.

[1586] What it does: The server uses the Flask framework to parse the received data and store it in memory.

[1587] Step 4:

[1588] User profile analysis

[1589] The server selects relevant news articles based on the user's profile.

[1590] Input: User profile object, news database.

[1591] Data processing: Using the scikit-learn library, we cluster the user's interest fields and filter out relevant news articles.

[1592] Output: A list of selected news articles.

[1593] What it does: Generates queries to extract relevant articles from the database and selects articles that match the user's profile.

[1594] Step 5:

[1595] Simplifying the article and adding visual information

[1596] The server uses a generative AI model to simplify articles and add visual information.

[1597] Input: List of selected news articles, user profile.

[1598] Data processing: Calls OpenAI API to generate article summaries and adds relevant visual information using OpenCV library.

[1599] Output: A customized news article that has been abbreviated and enhanced with visual information.

[1600] What it does: It uses GPT-4 to generate prompts and perform summarization and visual information addition tasks.

[1601] Terminal processing steps

[1602] Step 6:

[1603] Viewing the Settings Interface

[1604] The device displays an interface that allows the user to enter profile information.

[1605] Input: User Access.

[1606] Data processing: None.

[1607] Output: Display of the configuration interface.

[1608] Specific behavior: Generate a form using React and HTML / CSS and display it to the user.

[1609] Step 7:

[1610] Retrieving Profile Information

[1611] The device collects information about the user's reading level and interests.

[1612] Input: User-entered data.

[1613] Data processing: Form data collection.

[1614] Output: A profile information object.

[1615] Specific operation: Store the form input contents in a variable using JavaScript.

[1616] Step 8:

[1617] Sending profile information

[1618] The terminal transmits the acquired profile information to the server.

[1619] Input: Profile information object.

[1620] Data processing: Convert the data into an HTTP POST request format.

[1621] Output: HTTP POST request to the server.

[1622] Specific behavior: Sends data to the server using the axios library.

[1623] Step 9:

[1624] Receiving news articles

[1625] The terminal receives customized news article data from the server.

[1626] Input: The HTTP response from the server.

[1627] Data processing: Analyze JSON format data.

[1628] Output: A customized news article object.

[1629] Specific operation: Analyze and store the data returned from the server using React.

[1630] Step 10:

[1631] View news articles

[1632] The terminal displays the received customized news article.

[1633] Input: A customized news article object.

[1634] Data processing: None.

[1635] Output: Display of news article.

[1636] What it does: Display an article to the user using a React component.

[1637] User processing steps

[1638] Step 11:

[1639] Enter your profile information

[1640] Users input their reading level and interests through the device.

[1641] Input: Your profile information.

[1642] Data processing: None.

[1643] Output: The profile information entered into the form.

[1644] What happens: A user fills out a form and clicks the "Submit" button.

[1645] Step 12:

[1646] Viewing news articles

[1647] Users view customized news articles displayed on their devices.

[1648] Input: A customized news article.

[1649] Data processing: None.

[1650] Output: View article.

[1651] What happens: The user scrolls through the article on the screen and reads the content.

[1652] The above is a concrete explanation of each processing step in the program of this system.

[1653] (Application example 1)

[1654] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1655] In modern content distribution services, it is difficult to efficiently provide users with news articles that are both interesting and appropriate for their reading level. Conventional news distribution systems provide uniform content without fully considering users' interests or reading level, which is likely to result in low user satisfaction. Furthermore, they do not allow for customization of news articles that include visual information, and lack functionality to further improve the user experience. There is a need to solve this problem and provide users with the most appropriate news articles.

[1656] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1657] In this invention, the server includes means for acquiring a user's reading level and interests, means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies, and means for delivering the customized news articles to a device in real time, thereby enabling the user to be provided with articles tailored to the user's interests that are simplified to fit the user's reading level and include related visual content.

[1658] "Means for obtaining reading level and interests from users" means a method for providing an interface that allows users to input or select their reading ability and interests.

[1659] The "means for customizing news articles based on the user's reading level and interests using natural language processing and image recognition technologies" refers to a method that uses natural language processing and image recognition technologies to simplify sentences according to the user's reading level and add visual information that matches the user's interests.

[1660] "Means for delivering the customized news articles to a device in real time" refers to a method for instantly transmitting individually customized news articles from a server to a user's device (such as a smartphone or head-mounted display).

[1661] "Means for obtaining the latest news articles from news sources and storing them in an information aggregation" refers to a method for periodically collecting the latest news articles from reliable news sources via the Internet and storing them in a database.

[1662] "Means of simplifying the content of news articles or adding visual content to them based on the user's reading level" refers to translating the content into language appropriate to the user's reading ability and inserting relevant charts and pictures into the article.

[1663] System Overview

[1664] This invention provides a system that personalizes news content to match a user's reading level and interests. The system mainly consists of three elements: a server, a terminal, and a user. Based on the profile information entered by the user, the system customizes news articles and provides them in a format appropriate for the user.

[1665] Server Roles

[1666] News database updates

[1667] The server periodically retrieves the latest news articles from news sources (such as news APIs) via the Internet and stores them in an information collection (database). This operation ensures that new content is always available.

[1668] Analyzing user information and customizing articles

[1669] The server analyzes the user's reading level and interests, and then customizes the news article based on this using natural language processing and image recognition technologies. Specifically, it simplifies the content of the article according to the user's reading level and adds visual information appropriate to their interests. This allows the server to provide users with news content that is both easy to understand and interesting.

[1670] Generate customized news articles

[1671] The server uses a generative AI model to generate a customized news article based on a prompt, such as the following:

[1672] "User A has an intermediate reading level and is interested in science and technology. Please translate the latest science news articles into simple sentences and add relevant figures and tables."

[1673] Device Role

[1674] Providing a user interface

[1675] The device provides an interface where users can set their reading level and interests, and through this interface, they can easily enter their profile and access news articles.

[1676] Getting and sending user input

[1677] The device sends the information the user enters to a server, which does this in real time and helps generate a customized news article for the user to view.

[1678] Customized news article display

[1679] The device displays customized news articles sent from the server to the user, allowing the user to view news content in a format that is optimized for them.

[1680] User Roles

[1681] Profile Settings

[1682] Users input their reading level and interests through the device, which personalizes the news articles they receive.

[1683] Viewing news articles

[1684] Users view customized news articles displayed on their devices, providing information in an easy-to-understand format.

[1685] Hardware and Software

[1686] The main hardware used to realize this system is cloud-based servers (e.g., AWS EC2) and devices such as smartphones and head-mounted displays. The software used includes an API for retrieving news articles (e.g., NewsAPI), natural language processing technology, image recognition technology, and generative AI models.

[1687] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level and interests, it is possible to provide content that is both interesting and easy to understand for the user.

[1688] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1689] Step 1:

[1690] The user (device) enters their reading level and interests.

[1691] Input: Reading level and interest categories (e.g., science, technology, sports) set by the user through their device.

[1692] Output: Information about the user's reading level and interests is stored on the device and sent to the server.

[1693] Specific behavior: The user uses drop-down menus and checkboxes on the device app's settings screen to select a reading level (e.g., beginner, intermediate, advanced) and interest categories, then presses the Settings button.

[1694] Step 2:

[1695] The server receives the user profile information and stores it in a database.

[1696] Input: User's reading level and interest information obtained in step 1.

[1697] Output: User profile information stored in a database.

[1698] Specific operation: The server receives the reading level and interest category information sent from the device, first validates the input values, and then stores them in the database.

[1699] Step 3:

[1700] The server retrieves the latest news articles from the news sources and updates the database.

[1701] Input: News API endpoint.

[1702] Output: The latest news articles stored in the database.

[1703] Specific operation: The server periodically calls the news API to retrieve the latest articles provided, receives them in XML or JSON format, and then converts them into a database format and saves them.

[1704] Step 4:

[1705] The server customizes news articles based on the user's reading level and interests.

[1706] Input: User profile information and news articles in the database.

[1707] Output: A customized news article.

[1708] How it works: Based on user profile information, the server selects news articles, simplifies the text, and adds relevant visual information. Natural language processing technology is used to simplify the text, and image recognition technology is used to extract and generate relevant visual elements (such as charts) and add them to the article.

[1709] Step 5:

[1710] Customized news articles are optimized using generative AI models and further personalized for each user based on prompt text.

[1711] Input: Customized news articles and per-user prompts.

[1712] Output: Optimized news articles.

[1713] How it works: The server inputs a prompt into the generative AI model, which then generates a news article in a format appropriate for the user's reading level and interests. For example, a prompt like "User A has an intermediate reading level and is interested in science and technology. Please convert the latest science news article into simple sentences and add relevant figures and tables" is input into the generative AI model.

[1714] Step 6:

[1715] The server delivers optimized news articles to the device in real time.

[1716] Input: Optimized news articles.

[1717] Output: The news article displayed on the user's device.

[1718] How it works: The server sends optimized news articles to the device via push notification or API, and the device receives them. The device app displays the received articles in its user interface.

[1719] Step 7:

[1720] The user views customized news articles through their device.

[1721] Input: A news article displayed on a user's device.

[1722] Output: Improved user satisfaction.

[1723] What it does: The user opens their device, browses to a news article delivered in real time, and reads along with the provided visual information.

[1724] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1725] System Overview

[1726] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It includes three elements: a server, a device, and a user, as well as an emotion engine. The system uses input information and emotional data from the user to customize news articles and present them in a format appropriate for the user.

[1727] Server Roles

[1728] The server performs the following functions:

[1729] 1. Update the news database:

[1730] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing the latest content.

[1731] 2. Analysis of User Information:

[1732] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[1733] 3. How the Emotion Engine works:

[1734] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[1735] 4. Generate customized news articles:

[1736] The server then performs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, thereby providing the news article in the most appropriate format for the user.

[1737] Device Role

[1738] The terminal performs the following functions:

[1739] 1. Providing a user interface:

[1740] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[1741] 2. Getting and sending user input:

[1742] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[1743] 3. Displaying customized news articles:

[1744] The device displays customized news articles retrieved from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[1745] User Roles

[1746] The user does the following:

[1747] 1. Profile Settings:

[1748] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[1749] 2. Viewing news articles:

[1750] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[1751] Specific examples

[1752] Specific usage examples are shown below.

[1753] 1. Update the news database:

[1754] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1755] 2. Analysis of User Information:

[1756] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[1757] 3. Generate customized news articles:

[1758] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[1759] 4. Displaying customized news articles:

[1760] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[1761] The above is a specific embodiment of the present invention. By personalizing news articles based on a user's reading level, interests, and even emotional state, it is possible to provide educational content that is engaging, easy to understand, and appropriate for the user's psychological state.

[1762] The processing flow will be explained below.

[1763] Step 1:

[1764] The server retrieves the latest news articles from news sources. Specifically, it collects data from multiple news sources using RSS feeds and news APIs. The collected data is obtained in JSON or XML format.

[1765] Step 2:

[1766] The server stores the retrieved news articles in a database. When storing them in the database, a duplicate check is performed and articles that already exist are excluded. This process ensures that the latest news articles are always updated in the database.

[1767] Step 3:

[1768] Users use the device's user interface to input their reading level, interests, and emotional state, which can be selected using drop-down menus and checkboxes, or which can be automatically obtained using facial recognition or voice analysis.

[1769] Step 4:

[1770] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information in JSON format as an HTTP request.

[1771] Step 5:

[1772] The server analyzes the received user information and stores it as a user profile, which includes information on reading level, interests, and emotional state, allowing for customization for each user.

[1773] Step 6:

[1774] The server selects news articles based on the user's profile. In particular, it searches the database for articles that match the user's interests, reading level, and emotional state. For example, if the user is interested in "science," has an "intermediate" reading level, and is emotionally "excited," the server will select the corresponding article.

[1775] Step 7:

[1776] The server customizes the selected news articles, shortening the sentences to match the user's reading level and adjusting the tone to suit the user's emotional state. It also adds visual information (e.g., illustrations and diagrams) and selects visual information appropriate to the user's emotional state. For example, a user in an excited state might be shown visually stimulating images.

[1777] Step 8:

[1778] The server transmits the customized news article to the terminal, where the customized news article is converted into a data format suitable for display on the user terminal.

[1779] Step 9:

[1780] The device receives customized news articles from the server and displays them to the user, allowing the user to view the news articles in a format that suits their reading level, interests, and emotional state.

[1781] Step 10:

[1782] After a user finishes viewing a news article, their browsing history and new emotional data are sent from the device to the server, allowing the server to track changes in the user's interests and emotional state and use this information to customize the next news article. This process allows for even more accurate article delivery.

[1783] Example 2

[1784] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1785] In today's world, the amount of information available via the Internet is enormous, and users need to access information that is appropriate for their individual reading level, interests, and emotional state. However, conventional news delivery systems are unable to meet the individual needs of users, preventing them from effectively understanding the information or achieving psychological satisfaction. In particular, the provision of content tailored to emotional states has not been fully realized. This limits the user experience and reduces the efficiency of information reception and comprehension.

[1786] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's reading level, interests, and emotional state, means for customizing a news article based on the user's reading level, interests, and emotional state, means for displaying the customized news article on the user terminal, means for analyzing the user's emotional data using an emotion engine, and means for adjusting the text of the news article using a generative AI model. This makes it possible to provide news articles optimized for the user's reading level, interests, and emotional state, thereby enabling effective understanding of information and improving psychological satisfaction.

[1787] "User" refers to an individual who uses the System to view news articles.

[1788] "Reading level" is a standard that indicates the level of difficulty of a news article that a user can understand.

[1789] "Interests" refers to the themes or topics that a user is particularly interested in.

[1790] "Emotional state" refers to the user's state of mind or psychological state.

[1791] "News Article" refers to information content obtained from a news source.

[1792] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1793] An "emotion engine" is software or algorithm that analyzes a user's emotional data and determines their emotional state.

[1794] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate or adjust the content of a news article.

[1795] MODE FOR CARRYING OUT THE INVENTION

[1796] The present invention is a system for personalizing news content according to a user's reading level, interests, and emotional state. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1797] Server Roles

[1798] The server performs the following functions:

[1799] 1. Update the news database

[1800] The server retrieves the latest news articles from news sources and automatically updates the database. Specifically, it collects article information using RSS feeds and APIs. This task is set to run periodically. For example, the server can collect the latest technology-related articles every morning at 5:00 and store them in the database.

[1801] 2. Analysis of User Information

[1802] The server analyzes the information submitted by the user regarding reading level, interests, and emotional state, and then uses an emotional engine to further analyze the user's emotional state and select relevant news articles based on the results.

[1803] 3. Generate customized news articles

[1804] The server uses a generative AI model to tailor the content of news articles based on the user's reading level and emotional state. Specifically, it condenses the article, adds relevant visual information, and adjusts the tone to suit the emotion. An example of a prompt for the generative AI model is, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate science-related news articles appropriate for this user."

[1805] Device Role

[1806] The terminal performs the following functions:

[1807] 1. Providing a user interface

[1808] The device provides an interface that allows the user to set reading level, interests, and emotional state. Specific interface elements include drop-down menus and fields for selecting emotional states.

[1809] 2. Getting and Sending User Input

[1810] The device takes the information entered by the user and sends it to the server as an HTTP request. For example, if the user sets their interest as "science," their reading level as "intermediate," and their emotional state as "excited," this information is sent.

[1811] 3. Customized news article display

[1812] The device displays customized news articles sent from the server to the user, allowing the user to view the news articles in a format appropriate to their reading level and emotional state.

[1813] User Roles

[1814] The user does the following:

[1815] 1. Profile Settings

[1816] The user inputs their reading level, interests, and emotional state through the terminal. For example, the user may set that they are interested in "science," their reading level is "intermediate," and they are currently "excited."

[1817] 2. Reading news articles

[1818] Users view personalized news articles displayed on their devices, optimized based on their preferences to make them easier to understand and more satisfying to the user.

[1819] The above is a specific embodiment of the present invention. By personalizing news articles based on the user's reading level, interests, and even emotional state, it is possible to provide optimal information to the user. Through this system, users can receive news articles in a more understandable format, which is psychologically satisfying.

[1820] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1821] Step 1:

[1822] The server retrieves the latest news articles from news sources. The input is the URL of the news source or an RSS feed, and the output is the latest news article. Specifically, the server reads the RSS feed from the specified news source, extracts the content of the latest article, and stores it in a database.

[1823] Step 2:

[1824] Users input their reading level, interests, and emotional state through their devices. The input is the information the user sets on the device, and the output is the information sent to the server as an HTTP request. Specifically, users use drop-down menus and selection fields to set the required settings.

[1825] Step 3:

[1826] The server analyzes the information obtained from the user regarding reading level, interests, and emotional state. The input is the information sent by the user, and the output is the analysis result, which is instructions for selecting and customizing appropriate news articles. Specifically, the server uses an emotion engine to analyze the user's emotional state and selects relevant news articles based on the results.

[1827] Step 4:

[1828] The server inputs relevant news articles into the generative AI model and adjusts the text to suit the user's reading level and emotional state. The input is the selected news article and user information, and the output is a customized news article. Specifically, the server generates a prompt sentence and inputs it into the generative AI model to regenerate the article text. For example, the prompt sentence could be, "The user is looking for intermediate-level reading material, is interested in science, and is currently excited. Please generate a science-related news article that is appropriate for this user."

[1829] Step 5:

[1830] The server sends the generated customized news article to the user's device. The input is the customized news article, and the output is the news article data as an HTTP response. Specifically, the server formats the article data appropriately and sends it to the device.

[1831] Step 6:

[1832] The terminal displays the received customized news article to the user. The input is the news article data sent from the server, and the output is the news article displayed on the user interface. In concrete terms, the terminal analyzes the received data and displays the article on the screen. The user then views the displayed customized news article.

[1833] (Application example 2)

[1834] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1835] Conventional news delivery systems customize news articles based solely on a user's reading level and interests. This means that they do not provide information appropriate to the user's emotional state, making it difficult to continuously capture the user's interest. Furthermore, the lack of a function to analyze the user's emotional state in real time and adjust the tone of the news article accordingly limits the user experience.

[1836] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the reading level and interests from the user, means for customizing news articles based on the reading level and interests, means for analyzing the user's emotional state, means for customizing news articles based on the emotional state, and means for displaying the customized news articles on the user terminal. This makes it possible to provide news articles that are appropriate for the user's emotional state as well as their reading level and interests.

[1837] "Means of obtaining reading level and interests from users" refers to input interfaces and sensor devices that are used to understand users' reading ability and areas of interest.

[1838] "Means for customizing news articles based on said reading level and interests" refers to algorithms or software processes that adjust news content based on the acquired user's reading level and interests.

[1839] "Means for analyzing the user's emotional state" refers to an emotion engine, biometric sensor, or AI-based analysis module that recognizes and analyzes the user's emotions in real time.

[1840] "Means for customizing news articles based on said emotional state" refers to an algorithm or software that has the ability to adjust the content and tone of a news article depending on the analyzed emotional state of the user.

[1841] "Means for displaying the customized news article on a user terminal" refers to an output device such as a smartphone application or a web interface for displaying the news article optimized for the user.

[1842] "Means of obtaining the latest news articles from news sources and storing them in a database" refers to the process of collecting the latest news data via the Internet or RSS feeds and storing it in a storage device such as a server.

[1843] "Means of simplifying text or adding visual information to news articles based on the user's reading level" refers to algorithms or software that simplify text to adapt to the user's reading ability, or add charts or images to aid comprehension.

[1844] "Means for adjusting the tone of news articles based on the user's emotional state" refers to an algorithm or machine learning model that adjusts the tone and wording of an article to match the user's psychological state.

[1845] "Means of using generative AI models to generate news articles based on a user's reading level, interests, and emotional state" refers to the process of using AI or machine learning models to automatically generate news articles that match the characteristics of a user.

[1846] This invention is a system that personalizes news content based on a user's reading level, interests, and emotional state. It is possible to customize news articles using user input and emotional data, and provide them in a format appropriate for the user. The system includes three elements: a server, a terminal, and a user, as well as an emotional engine.

[1847] Server Roles

[1848] The server performs the following functions:

[1849] 1. Update the news database:

[1850] The server periodically retrieves the latest news articles from news sources and stores them in a database, forming the basis for always providing users with the latest content.

[1851] 2. Analysis of User Information:

[1852] The server selects and customizes relevant news articles based on the user's reading level, interests, and emotional data, including simplifying text and adding visual information.

[1853] 3. How the Emotion Engine works:

[1854] The server uses an emotion engine to analyze the user's emotional data and adjusts the content and visual information of the news article based on the results, thereby providing content that is appropriate for the user's psychological state.

[1855] 4. Generate customized news articles:

[1856] The server then runs a process to simplify the text of the news article and add relevant visual information based on the user's reading level and sentiment data, allowing the news article to be presented to the user in the most appropriate format.

[1857] Device Role

[1858] The terminal performs the following functions:

[1859] 1. Providing a user interface:

[1860] The device provides an interface that allows the user to set reading level, interests, and emotional state, including drop-down menus and fields for selecting emotional states.

[1861] 2. Getting and sending user input:

[1862] The device sends the user's input about their reading level, interests, and emotional state to the server, which sends this information as an HTTP request.

[1863] 3. Displaying customized news articles:

[1864] The device displays customized news articles retrieved from the server to the user, allowing the user to view news articles in a format appropriate to their reading level and emotional state.

[1865] User Roles

[1866] The user does the following:

[1867] 1. Profile Settings:

[1868] Users input their reading level, interests, and emotional state through the device, which then personalizes the news article.

[1869] 2. Viewing news articles:

[1870] Users view customized news articles displayed on their devices, which are easy to understand and tailored to the user's state of mind.

[1871] Specific examples

[1872] Here are some specific usage examples:

[1873] 1. Update the news database:

[1874] The server retrieves the latest articles from news sources every day and updates the database. For example, the server collects science-related articles using RSS feeds and stores them in the database.

[1875] 2. Analysis of User Information:

[1876] If User A is interested in "science" and sets his reading level to "intermediate," and the emotion engine recognizes User A's emotional state as "excited," the server will select science-related news articles that suit User A.

[1877] 3. Generate customized news articles:

[1878] The server converts the selected news articles into concise sentences tailored to User A's reading level and emotional state, while adding relevant charts and illustrations. The sentences are adjusted to an excited tone that matches User A's emotional state.

[1879] 4. Displaying customized news articles:

[1880] The device displays the customized news article sent from the server to User A. This allows User A to view the article in a format that suits his or her own psychological state.

[1881] Prompt Sentence Examples

[1882] Here are some example input prompts for a generative AI model:

[1883] "Generate a news article suitable for users with an intermediate reading level, an interest in science, and current excitement. The original article reads: 'New research published today suggests that...'"

[1884] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1885] Step 1:

[1886] The device receives input from the user regarding reading level, interests, and emotional state. This input includes the user's selected reading level (beginner, intermediate, advanced, etc.), areas of interest (science, sports, economics, etc.), and current emotional state (excited, calm, etc.). Once this information is entered into the device, it is sent to the server as an HTTP request.

[1887] Input: User's reading level, interests, and emotional state

[1888] Output: User information sent to the server as an HTTP request

[1889] Step 2:

[1890] The server analyzes the user's reading level, interests, and emotional state information obtained from the device. Based on the analysis, it selects news articles from the database that are appropriate for the user. This selection process involves filtering articles in categories that match the user's interests.

[1891] Input: User information received by the server as an HTTP request

[1892] Output: News articles filtered based on the user's reading level and interests

[1893] Step 3:

[1894] The server then simplifies the selected news articles based on the user's reading level. In this step, the server uses a library or algorithm to simplify the text, converting it into a form that is easy for the user to understand.

[1895] Input: filtered news articles, user reading level

[1896] Output: A simplified news article

[1897] Step 4:

[1898] The server uses an emotion engine to analyze the user's emotional data and adjust the tone of the news article based on the results: if the user is "excited," the emotion engine adjusts the article to an energetic tone, and if the user is "calm," it adjusts the tone to a calmer tone.

[1899] Input: Simplified news article, sentiment engine analysis results

[1900] Output: Tone-adjusted news article

[1901] Step 5:

[1902] The server uses the generative AI model to further customize the news article based on all the user information, specifically by inputting prompts to the generative AI model to generate and adjust the article.

[1903] Input: Tone-adjusted news articles, prompts based on user information

[1904] Output: A news article further customized by AI

[1905] Step 6:

[1906] The server then sends the customized news article to the device as an HTTP response.

[1907] Input: Customized news article

[1908] Output: News article sent to the terminal as an HTTP response

[1909] Step 7:

[1910] The device displays customized news articles sent from the server to the user, allowing the user to view news articles that are appropriate for their reading level, interests, and emotional state.

[1911] Input: News article received as an HTTP response

[1912] Output: A customized news article displayed on the terminal screen.

[1913] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1914] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1915] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1916] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1917] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1918] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1919] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1920] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1921] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1922] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1923] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1924] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1925] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1926] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1927] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1928] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1929] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1930] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1931] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1932] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1933] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1934] The following is further disclosed regarding the above embodiment.

[1935] (Claim 1)

[1936] a means of obtaining reading level and interests from users;

[1937] means for customizing news articles based on said reading level and interests;

[1938] means for displaying the customized news article on a user terminal;

[1939] A system including:

[1940] (Claim 2)

[1941] 10. The system of claim 1, further comprising means for retrieving current news articles from a news source and storing them in a database.

[1942] (Claim 3)

[1943] 10. The system of claim 1, further comprising means for simplifying text or adding visual information to a news article depending on a user's reading level.

[1944] "Example 1"

[1945] (Claim 1)

[1946] a means of obtaining reading level and interests from users;

[1947] means for customizing news articles based on said reading level and interests;

[1948] means for displaying the customized news article on a user terminal;

[1949] Using generative AI models to simplify text and add visual information to news articles;

[1950] A system including:

[1951] (Claim 2)

[1952] 10. The system of claim 1, further comprising means for retrieving current news articles from a news source and storing them in a database.

[1953] (Claim 3)

[1954] 10. The system of claim 1, further comprising means for simplifying text or adding visual information to a news article depending on a user's reading level.

[1955] "Application Example 1"

[1956] (Claim 1)

[1957] a means of obtaining reading level and interests from users;

[1958] a means for customizing news articles based on the reading level and interests using natural language processing and image recognition techniques;

[1959] means for delivering the customized news articles to a device in real time;

[1960] A system including:

[1961] (Claim 2)

[1962] 10. The system of claim 1, further comprising means for obtaining current news articles from a news source and storing them in an information collection.

[1963] (Claim 3)

[1964] 10. The system of claim 1, further comprising means for abbreviating the content of the news article or adding visual content depending on the user's reading level.

[1965] "Example 2: Combining Emotion Engines"

[1966] (Claim 1)

[1967] a means for obtaining reading level, interests, and emotional state from the user;

[1968] means for customizing news articles based on said reading level, interests, and emotional state;

[1969] means for displaying the customized news article on a user terminal;

[1970] A means for analyzing user emotion data using an emotion engine;

[1971] a means of tailoring the text of news articles using generative AI models; and

[1972] A system including:

[1973] (Claim 2)

[1974] 10. The system of claim 1, further comprising means for retrieving current news articles from a news source and storing them in a database.

[1975] (Claim 3)

[1976] 10. The system of claim 1, further comprising means for simplifying text or adding visual information to a news article depending on a user's reading level.

[1977] "Application example 2 when combining emotion engines"

[1978] (Claim 1)

[1979] a means of obtaining reading level and interests from users;

[1980] means for customizing news articles based on said reading level and interests;

[1981] a means for analyzing the emotional state of a user;

[1982] means for customizing news articles based on said emotional state;

[1983] means for displaying the customized news article on a user terminal;

[1984] A system including:

[1985] (Claim 2)

[1986] 10. The system of claim 1, further comprising means for retrieving current news articles from a news source and storing them in a database.

[1987] (Claim 3)

[1988] 10. The system of claim 1, further comprising means for simplifying text or adding visual information to a news article depending on a user's reading level.

[1989] (Claim 4)

[1990] 10. The system of claim 1, further comprising means for adjusting the tone of the news article based on the emotional state of the user.

[1991] (Claim 5)

[1992] 10. The system of claim 1, further comprising means for generating news articles based on a user's reading level, interests, and emotional state using a generative AI model. [Explanation of symbols]

[1993] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of obtaining reading level and interests from users; means for customizing news articles based on said reading level and interests; means for displaying the customized news article on a user terminal; A system including:

2. 10. The system of claim 1, further comprising means for retrieving current news articles from a news source and storing them in a database.

3. 10. The system of claim 1, further comprising means for simplifying text and adding visual information to news articles depending on the user's reading level.

Images