System

Abstract

A system is provided.SOLUTION: The system includes a means for receiving the selection of a news display mode from a user, a means for acquiring news data, a means for analyzing the acquired news data and classifying them into positive news and negative news, a means for filtering the news on the basis of the mode selected by the user, and a means for displaying the filtered news on the terminal of the user.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] In modern society, there is a lot of anxiety-inducing news and pessimistic information, which has a negative impact on users' mental health. Users who consume news on a daily basis often feel a mental strain, especially. Conventional news services randomly display positive and negative news, requiring users to sort through the information, which requires time and effort. Furthermore, dark news tends to stand out at certain times, increasing the mental strain on users. Addressing these issues and providing an environment where users can consume news with peace of mind is essential. [Means for solving the problem]

[0005] The present invention provides a system including means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, and means for displaying the filtered news on the user's terminal. Specifically, when a user selects the "Display only positive news" mode, only positive news is displayed, and when a user selects the "Reduce and reduce negative news" mode, negative news is reduced in redundancy and displayed less prominently, and the headlines and content are also converted to softer language. This allows the user to efficiently obtain information while maintaining their mental health.

[0006] "User" means any individual or end user of the News Service.

[0007] "News display mode" refers to an option that allows a user to select how news is displayed.

[0008] "Means for accepting a selection" refers to a system component for receiving and processing a user selection.

[0009] "News Data" refers to news articles and their metadata obtained from data sources such as news APIs.

[0010] "Means of Acquisition" refers to the system's capabilities for collecting news data from external data sources.

[0011] "Means of analysis" refers to the system function of analyzing acquired news data using technologies such as natural language processing and classifying it into positive news and negative news.

[0012] "Positive news" refers to news stories that are primarily positive, hopeful, or celebratory in content.

[0013] "Negative news" refers to news articles that are primarily negative, pessimistic, or alarming in content.

[0014] "Filtering means" refers to a system function that sorts news data based on a selected news display mode to extract relevant news items.

[0015] "Means for displaying" refers to a system function for visually presenting filtered news data on a user's terminal.

[0016] "Terminal" refers to the electronic device used by a User to access and view information from a news service. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention provides a system that reduces the mental burden on users when viewing news and allows them to obtain information more comfortably. This system performs a series of processes: news display mode selection, news data acquisition, analysis, filtering, and display.

[0039] A specific embodiment of this system is shown below.

[0040] 1. Accept the user's selection

[0041] When a user accesses a news site, the device presents a choice of news display modes: "Display only positive news" or "Reduce negative news and display only negative news."

[0042] 2. Data processing according to the selected mode

[0043] The server receives the user's selections and begins the process of generating a news feed based on the selections.

[0044] 3. Acquiring news data

[0045] The server sends a request to the news API to retrieve the latest news data, including metadata such as the title, content, and tags of the news article.

[0046] 4. News Data Analysis

[0047] The device analyzes the acquired news data using AI (natural language processing models, etc.), and the analysis categorizes the news data into positive and negative news.

[0048] 5. News filtering

[0049] The server filters the news based on the news display mode selected by the user.

[0050] When "Show only good news" mode is selected:

[0051] The server extracts only positive news and filters out negative news.

[0052] When "Reduce Bad News" mode is selected:

[0053] The server reduces the duplication of negative news and places it in a less important position.

[0054] Implement wording changes to soften headlines and content.

[0055] 6. Generate and send the news feed to be displayed

[0056] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the terminal.

[0057] 7. Viewing News Feeds

[0058] The device displays the received news feed to the user, who can then browse the news according to the selected mode and efficiently obtain the information they need.

[0059] Specific examples

[0060] Example 1: When the user selects the "Show only good news" mode

[0061] A user visits a news site and selects "Show only positive news."

[0062] The server receives this selection and retrieves the data from the news API.

[0063] The device analyzes news data and categorizes it into positive and negative news.

[0064] The server extracts only positive news and generates a filtered feed.

[0065] The server sends the generated feed to the device.

[0066] The device displays only positive news, allowing users to obtain information without mental stress.

[0067] Example 2: When the user selects the "Reduce Negative News" mode

[0068] A user accesses a news site and selects "Reduce and minimize negative news."

[0069] The server receives this selection and retrieves the data from the news API.

[0070] The device analyzes news data and categorizes it into positive and negative news.

[0071] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[0072] The server generates a filtered feed and sends it to the device.

[0073] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[0074] In this way, the system provides an environment in which the user can efficiently and mentally read the news in accordance with the display mode selected by the user.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[0078] Step 2:

[0079] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[0080] Step 3:

[0081] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0082] Step 4:

[0083] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[0084] Step 5:

[0085] The server filters the news based on the display mode selected by the user.

[0086] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0087] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[0088] Step 6:

[0089] The server generates a news feed based on the filtered news data, and the feed content depends on the mode selected by the user.

[0090] Step 7:

[0091] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[0092] Step 8:

[0093] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[0094] Example 1

[0095] 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."

[0096] In conventional news viewing systems, users may feel a mental burden depending on the content of the news they view. In particular, when a lot of negative news is displayed, users may feel anxious or stressed. In response to this, there is a need for a means to adjust the news content according to the user's desired display mode and reduce the mental burden.

[0097] 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.

[0098] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for acquiring data from a news API, means for analyzing the news data using a natural language processing model, means for generating a news feed and transmitting it to the user's terminal, and means for displaying the filtered news. This allows the user to view news filtered based on the desired news display mode, thereby reducing mental strain.

[0099] A "user" is an entity that uses the system to view news.

[0100] "News display mode" is an option that allows the user to select the type of news to view and the display method.

[0101] "News data" is a collection of information about news, such as the title, content, tags, and publication date of a news article.

[0102] "Positive news" is news that has been classified as positive or optimistic through sentiment analysis of news data.

[0103] "Negative news" is news that has been classified as negative or pessimistic through sentiment analysis of news data.

[0104] "Filtering" is the process of selecting and organizing news data based on the news display mode selected by the user.

[0105] A "News API" is an interface for accessing external news data providers and obtaining news data.

[0106] A "natural language processing model" is an algorithm or software that uses artificial intelligence techniques to analyze and classify text.

[0107] A "news feed" is a filtered list of news articles displayed to a user.

[0108] A "terminal" is a hardware device (e.g., a smartphone, tablet, or PC) that a user uses to access a news site and view a news feed.

[0109] The present invention provides a news viewing system that aims to reduce the mental burden on users when viewing news by presenting them with a choice of news display modes, acquiring, analyzing, and filtering news data according to the selected mode, and ultimately displaying a news feed appropriate for the user.

[0110] composition

[0111] This system operates using a server, terminals, news APIs, and natural language processing (NLP) models. The specific hardware and software configuration is shown below.

[0112] 1. Server:

[0113] The server receives the user's selected display mode, retrieves, analyzes, filters, and generates a feed of news data.

[0114] Technologies used include web frameworks (e.g., Spring Boot, Django) and database systems (e.g., MySQL, PostgreSQL).

[0115] 2. Terminal:

[0116] The terminal accepts the user's selection, presents display mode options, and displays the filtered news feed.

[0117] The devices used include various user devices such as PCs, tablets, and smartphones.

[0118] 3. News API:

[0119] This is an interface for external services used to obtain news data. For example, it uses services that provide news data (e.g., Google News API, NewsAPI.org).

[0120] 4. Natural Language Processing Models (NLP Models):

[0121] It is an AI technology used to analyze news data and analyze the sentiment of text. Specific examples include models such as BERT and GPT-4.

[0122] This technology runs on machine learning frameworks such as TensorFlow and PyTorch.

[0123] Processing flow

[0124] When a user accesses a news site, the device presents a choice of news display modes. After the user selects a display mode, the device sends that information to the server. The server then sends a request to the news API to retrieve the latest news data. The retrieved news data is then analyzed on the device using an NLP model to classify it into positive and negative news.

[0125] The server filters the news based on the user's selection, generates a news feed, and sends it to the device. The device displays the filtered news feed to the user, allowing the user to view news according to the selected mode. This series of processes allows the user to efficiently obtain the information they need while reducing their mental burden.

[0126] Specific examples

[0127] Example 1: "Show only good news" mode

[0128] 1. A user visits a news site and selects "Show only positive news."

[0129] 2. The device sends the user's selection to the server.

[0130] 3. The server receives this selection and retrieves the news data from the news API.

[0131] 4. The device analyzes the news data and classifies it into positive and negative news.

[0132] 5. The server extracts only positive news and generates a news feed.

[0133] 6. The server sends the generated feed to the device, which displays only positive news.

[0134] Example 2: "Reduce negative news and display" mode

[0135] 1. A user visits a news site and selects "Reduce and minimize negative news."

[0136] 2. The device sends the user's selection to the server.

[0137] 3. The server receives this selection and retrieves the news data from the news API.

[0138] 4. The device analyzes the news data and classifies it into positive and negative news.

[0139] 5. The server reduces duplicate negative news and transforms it to soften the headline and content.

[0140] 6. The server generates a news feed and sends it to the device.

[0141] 7. The device will display negative news in a reduced volume, helping users reduce their mental burden.

[0142] In this way, the system provides an environment in which the user can efficiently and mentally read the news according to the display mode selected by the user.

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

[0144] Step 1: User visits a news site and selects a viewing mode

[0145] A user accesses a news site using a web browser or a dedicated app. The input is the user's access behavior.

[0146] The device presents a news display mode option ("Show only positive news" or "Show less negative news"), which is displayed as HTML or in the app's UI, allowing the user to click on the option.

[0147] Step 2: Receive the user's choice and send it to the server

[0148] The user selects one of the display modes. The selected mode (input) is either "display only positive news" or "reduced display with less negative news."

[0149] The device sends the user's selection to the server as a POST request (output). Data is sent in JSON format.

[0150] Step 3: Save the user's selections to the database

[0151] The server receives the user's selection (input).

[0152] The server saves the selection in a database (e.g. MySQL or PostgreSQL), making the user's selection persistent.

[0153] Step 4: Get news data from the News API

[0154] The server sends an HTTP request to the News API (output), which includes parameters (e.g., category, region) in JSON format.

[0155] The server receives response data from the API (input), which includes the news article title, content, tags, publication date, etc.

[0156] Step 5: Send news data to your device

[0157] The server sends the received news data to the terminal. Here, news data in JSON format is used (input).

[0158] The terminal temporarily stores the received data.

[0159] Step 6: Analyze the news data and categorize it into positive and negative news

[0160] The device analyzes (inputs) the stored news data using natural language processing (NLP) models, such as BERT and GPT-4, to perform sentiment analysis of the text.

[0161] The device classifies news articles into positive and negative news (output). Each news item is assigned a sentiment score and the classification results are saved in JSON format.

[0162] Step 7: Filter the news data

[0163] The server filters (inputs) news data based on the display mode selected by the user. Filtering is performed based on the analysis results.

[0164] If the "Show only positive news" mode is selected, the server extracts only positive news and excludes negative news (output).

[0165] When the "Reduce Negative News and Display" mode is selected, the server reduces the duplication of negative news and performs representation transformations to soften the headlines and content (output).

[0166] Step 8: Generate a filtered news feed

[0167] The server generates a news feed to display to the user based on the filtered news data (input). The feed is generated using HTML or JSON format.

[0168] The generated news feed is sent to the terminal (output).

[0169] Step 9: View your filtered news feed

[0170] The terminal displays the received news feed to the user (input).

[0171] Users get information by looking at the news feed, which displays news appropriately based on the selected display mode, reducing mental strain (output).

[0172] (Application example 1)

[0173] 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."

[0174] In modern society, reading the news is a part of everyday life, but the mental burden caused by negative news has become a problem. While there is a demand for systems that allow users to comfortably view specific information, there is a lack of means to provide users with appropriately personalized information amid the advancement of information provision in virtual spaces and smart devices. The present invention aims to solve these problems and provide a system that allows users to obtain information without feeling any mental burden.

[0175] 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.

[0176] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for displaying the filtered news on the user's terminal, and means for displaying a news feed on a device that provides information to the user in a virtual space. This reduces the mental burden on the user when viewing news and enables the user to receive optimal information in a personalized form even within the virtual space.

[0177] "News display mode" is a setting option that allows the user to select the format in which news is displayed.

[0178] "News data" refers to information including the title, content, and metadata of a news article.

[0179] "Analysis" is the process of classifying acquired news data into positive and negative news using natural language processing models, etc.

[0180] "Positive news" is a news article that is judged to have positive content and to have a positive impact on users.

[0181] "Negative news" refers to news articles that are deemed to have negative content and have a negative impact on users.

[0182] "Filtering" is the process of selecting and adjusting news data based on the news display mode selected by the user.

[0183] A "user terminal" is a user's information device used to display a news feed.

[0184] A "virtual space" is a virtual area in which users can carry out various activities within a digital environment.

[0185] A "smart device" is an electronic device equipped with internet connectivity that can display and operate information in a virtual space.

[0186] A "news feed" is an information list that organizes filtered news data and displays it to the user.

[0187] "Representation transformation" is the process of softening the headline and content of a news article to reduce the mental burden on the user.

[0188] The present invention provides a system that reduces the mental burden placed on users when viewing news and allows them to obtain information in a comfortable manner. The system is configured as follows.

[0189] Select news display mode

[0190] When a user accesses a news site through a device, the server presents a choice of news display modes. A screen is displayed asking the user to select either "Display only positive news" or "Reduce negative news and display." When the user makes a selection, the selection information is sent to the server.

[0191] Acquiring news data

[0192] The server sends a request to the news API to retrieve the latest news data. This data includes metadata such as the title, content, and tags of the news article. For example, the server retrieves the data using NewsAPI (https: / / newsapi.org / ).

[0193] News data analysis

[0194] The server analyzes the acquired news data using a natural language processing model (e.g., Hugging Face's Transformers library). Based on the analysis results, the news articles are classified into positive news and negative news.

[0195] For example, a news headline such as "A new clothing line has been launched" would be classified as positive news, while a headline such as "Some products need improvement" would be classified as negative news.

[0196] News filtering

[0197] The server filters the news based on the news display mode selected by the user.

[0198] When "Show only good news" mode is selected:

[0199] The server extracts only positive news and filters out negative news.

[0200] When "Reduce Bad News" mode is selected:

[0201] The server reduces the duplication of negative news and performs wording transformation to soften headlines and content. Wording transformation is expected to have the effect of softening negative expressions.

[0202] Generate and display a filtered news feed

[0203] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the device. The user can view news according to the selected mode, allowing for convenient information acquisition.

[0204] Providing information in virtual space

[0205] This system has the ability to provide users with the most appropriate information even in virtual spaces. For example, it can display news, the latest information, product notifications, and more within a virtual store via a smart device. The information displayed is personalized based on the selected news display mode, reducing the user's mental burden.

[0206] Prompt Sentence Examples

[0207] "Classify your news data into positive and negative news. Analyze the following news headlines: 'A new clothing line has been launched', 'Some products need improvement'."

[0208] In this way, the system allows users to browse the news without feeling any mental strain, and also provides an optimal user experience, including information provision in a virtual space.

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] A user visits a news site and selects a viewing mode.

[0212] Input: A user visits a news site and is presented with a choice screen.

[0213] Behavior: The device presents the user with the option to "display only positive news" or "reduce negative news." The user selects one of these display modes.

[0214] Output: The user's selection is sent to the server.

[0215] Step 2:

[0216] The server retrieves news data

[0217] Input: User selections and request to News API.

[0218] How it works: The server uses a news API (e.g., NewsAPI) to retrieve the latest news data, including metadata such as title, content, and tags.

[0219] Output: The retrieved news data is stored on the server.

[0220] Step 3:

[0221] News data analysis

[0222] Input: Retrieved news data.

[0223] How it works: The server analyzes news data using Hugging Face's Transformers library. A natural language processing model classifies the news data into positive and negative news.

[0224] Output: Categorized news data. A list of positive and negative news is generated.

[0225] Step 4:

[0226] News filtering

[0227] Input: Categorized news data and user-selected news display mode.

[0228] How it works: The server filters based on the mode selected by the user.

[0229] In the positive news only display mode: Only positive news is extracted and negative news is removed.

[0230] In the "Reduce and lighten dark news" display mode: Reduces the duplication of negative news and performs wording transformations to soften headlines and content.

[0231] Output: Filtered news data.

[0232] Step 5:

[0233] Newsfeed generation and submission

[0234] Input: Filtered news data.

[0235] How it works: The server generates a news feed based on the filtered news data, and the generated feed is sent to the user's device.

[0236] Output: The news feed sent to the user's device.

[0237] Step 6:

[0238] Displaying news feeds on users' devices

[0239] Input: The news feed sent from the server.

[0240] How it works: The device displays the news feed to the user, who then browses the news according to the mode selected.

[0241] Output: The news feed displayed on the user's device.

[0242] Step 7:

[0243] Providing information in virtual space

[0244] Input: Filtered news data sent from the server.

[0245] How it works: Smart devices (e.g. smart glasses) display personalized news and notifications in a virtual space.

[0246] Output: Personalized news feed and notifications displayed on your smart device.

[0247] The above is the flow of processing steps from selecting the news display mode to providing information in the virtual space.

[0248] 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.

[0249] This invention provides a system that allows users to browse the news while maintaining their mental health. It combines a conventional news display system with an emotion engine that recognizes the user's emotions. This system realizes a series of steps from selecting the news display mode to emotion recognition, filtering the news, and displaying it.

[0250] A specific embodiment of this system is shown below.

[0251] 1. Select the news display mode

[0252] When a user accesses a news site, the device displays a news display mode selection screen, allowing the user to choose between "Display only positive news" or "Reduce negative news and display."

[0253] 2. Transmit and record the selected mode

[0254] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[0255] 3. Acquiring news data

[0256] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0257] 4. News Data Analysis

[0258] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[0259] 5. News filtering

[0260] The server filters the news based on the display mode selected by the user.

[0261] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0262] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[0263] 6. Emotional Engine Adjustment

[0264] The present invention further includes an emotion engine that recognizes the user's emotions. The emotion engine includes the following three functions:

[0265] 1. Real-time recognition and assessment of user emotions:

[0266] The server uses an emotion engine to evaluate the user's emotions in real time based on their facial expressions, voice, input, etc. Based on this evaluation, the server adjusts the news display mode and content.

[0267] 2. Emotion history learning:

[0268] By recording the user's emotion history, the server uses a learning algorithm to predict future news display modes based on past data, and provides more relevant news based on this prediction.

[0269] 3. Adjust content based on emotions:

[0270] The emotion engine further adjusts the filtered news content based on the user's current emotions: for example, if the user is feeling stressed, it will increase the proportion of positive news and use more calming language.

[0271] 7. Generate and send the news feed to be displayed

[0272] The server generates a news feed based on the filtered and adjusted news data by the emotion engine, and the generated feed is tailored to the user's selected mode and current emotional state.

[0273] 8. Viewing News Feeds

[0274] The terminal displays the received news feed to the user, who can browse the news feed on the terminal and obtain news according to the selected mode and current emotional state efficiently and mentally at ease.

[0275] Specific examples

[0276] Example 1: When the user selects the "Show only good news" mode

[0277] A user visits a news site and selects "Show only positive news."

[0278] The server receives this selection and retrieves the data from the news API.

[0279] The device analyzes news data and categorizes it into positive and negative news.

[0280] The server extracts only positive news and generates a filtered feed.

[0281] The emotion engine evaluates the user's emotions and enriches news that contains particularly gentle expressions.

[0282] The server sends the generated feed to the device.

[0283] The device displays only positive news, allowing users to obtain information without mental stress.

[0284] Example 2: When the user selects the "Reduce Negative News" mode

[0285] A user accesses a news site and selects "Reduce and minimize negative news."

[0286] The server receives this selection and retrieves the data from the news API.

[0287] The device analyzes news data and categorizes it into positive and negative news.

[0288] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[0289] The emotion engine assesses the user's emotions and further tailors the news content displayed based on that state.

[0290] The server generates a filtered feed and sends it to the device.

[0291] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[0292] In this way, the system takes into account the user's emotional state and provides an efficient and safe environment for browsing news according to the selected display mode.

[0293] The processing flow will be explained below.

[0294] Step 1:

[0295] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[0296] Step 2:

[0297] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode for use in subsequent processing.

[0298] Step 3:

[0299] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0300] Step 4:

[0301] The server analyzes the acquired news data using AI (such as natural language processing models), and the news data is classified into positive news and negative news.

[0302] Step 5:

[0303] The server filters the news based on the display mode selected by the user.

[0304] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0305] When the "Reduce and lighten the display of negative news" mode is selected, the server reduces the duplication of negative news, places it in a less important position, and performs wording transformations to soften the headlines and content.

[0306] Step 6:

[0307] The server uses an emotion engine to recognize the user's current emotional state, collecting data such as the user's facial expressions, voice, and input from the device, and evaluating the user's emotions in real time.

[0308] Step 7:

[0309] The server adjusts the news display mode and content based on the emotional information acquired by the emotion engine. For example, if the user is assessed as feeling stressed, the server increases the proportion of positive news.

[0310] Step 8:

[0311] The emotion engine learns the user's past emotion history, and the server predicts future news display modes based on this and provides news based on the prediction.

[0312] Step 9:

[0313] The server generates a news feed based on the filtered news data, and ensures that the feed is in accordance with the user's selected mode and sentiment rating.

[0314] Step 10:

[0315] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[0316] Step 11:

[0317] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[0318] Example 2

[0319] 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."

[0320] Conventional news display systems simply display news as is and do not consider the user's emotional state, which can cause mental strain. Displaying a large amount of negative news, in particular, can have a negative impact on the user's mental health. Furthermore, systems that adjust news display based on the user's emotions have not yet been fully implemented. The present invention aims to provide an environment in which users can browse the news with peace of mind.

[0321] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0322] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results, means for generating a news feed based on the filtering and emotion recognition, means for transmitting the generated news feed to the user's terminal, means for readjusting the news feed based on the feedback, and means for displaying the filtered news on the user's terminal, thereby enabling the user to browse the news with peace of mind without feeling any mental burden.

[0323] The "means for accepting selection of a news display mode" is a means having a function of providing an interface that allows a user to select a news display mode and transmitting the selection to a server.

[0324] "Means for acquiring news data" refers to a means by which the server has the function of acquiring the latest news article data from an external news API.

[0325] "Means for analyzing news data and classifying it into positive and negative news" refers to a means that uses AI technology such as natural language processing models to analyze acquired news article data and classify it into positive and negative content.

[0326] The "means for filtering news" is a means having a function for selecting news to be displayed based on the news display mode selected by the user and the analysis results.

[0327] "Means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results" refers to a means that uses an emotion engine to analyze the user's facial expressions, voice, input content, etc. in real time, and adjusts the content and display method of the news based on the results.

[0328] The "means for generating a news feed based on filtering and emotion recognition" is a means having a function for generating an optimal news feed for a user based on filtered news and the user's emotion evaluation results.

[0329] The "means for transmitting the generated news feed to the user's terminal" refers to a means having a function for transmitting the news feed generated by the server to the user's terminal using a communication means.

[0330] The "means for readjusting a news feed based on feedback" refers to a means having a function for readjusting the content and display method of a news feed based on feedback information from a user.

[0331] The "means for displaying filtered news on a user's terminal" refers to a means having a function for displaying the final filtered news feed on a user's terminal so that the user can view it.

[0332] The present invention provides a system for selecting a news display mode, acquiring, analyzing, filtering, and recognizing emotions in news data, and generating and displaying a news feed, all of which are performed to enable users to browse news without feeling any mental strain.

[0333] Hardware and software used

[0334] Hardware

[0335] Terminal: A device operated by a user. Examples include computers, smartphones, and tablets.

[0336] Server: A computer system responsible for processing and storing data.

[0337] Emotion recognition devices: Devices such as cameras and microphones that capture the user's facial expressions and voice.

[0338] software

[0339] News API: API for obtaining external news data.

[0340] Natural language processing model (NLP model): An AI model for analyzing news data and classifying it into positive and negative news. Examples include BERT and GPT.

[0341] Emotion engine: Software for analyzing the user's emotional state in real time.

[0342] Filtering Algorithm: The algorithm for filtering the news data.

[0343] System Overview

[0344] Select news display mode

[0345] When a user accesses a news site, the device displays a news display mode selection screen, where the user can choose between "Display only positive news" or "Reduce negative news and display."

[0346] Mode transmission and recording

[0347] The terminal transmits information about the mode selected by the user to the server, which records this selection information in a database.

[0348] Acquiring news data

[0349] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news articles.

[0350] News analysis and classification

[0351] The server analyzes the news data using a natural language processing model and classifies articles into positive and negative news.

[0352] News filtering

[0353] The server filters news based on the mode selected by the user: "Show only positive news" mode extracts only positive news, while "Reduce and lighten negative news" mode reduces the overlap of negative news and softens the headlines.

[0354] Emotional engine regulation

[0355] The server uses an emotion engine to recognize the user's emotional state in real time and adjusts the news content displayed based on the evaluation, which may include increasing the proportion of positive news or converting the news content to a more gentle expression.

[0356] Newsfeed generation and submission

[0357] Based on the filtering and emotion recognition, the server generates a news feed and sends the news feed to the user's terminal.

[0358] Viewing the news feed

[0359] The device displays the received news feed to the user, allowing the user to comfortably browse news according to the selected mode and emotional state.

[0360] Specific examples

[0361] Example 1: When the user selects the "Show only good news" mode

[0362] The user selects the "Show only positive news" mode on their device.

[0363] The server receives this information and retrieves the latest news from the news API.

[0364] The server analyzes the news data using a natural language processing model and extracts only positive news.

[0365] The emotion engine assesses the user's emotions and adjusts the news content to be particularly gentle.

[0366] The server generates the final news feed and sends it to the device.

[0367] The device displays positive news, allowing users to obtain information without mental strain.

[0368] Example 2: When the user selects the "Reduce Negative News" mode

[0369] The user selects the "Reduce negative news and display" mode on the device.

[0370] The server receives this information and retrieves the latest news from the news API.

[0371] The server analyzes the news data using a natural language processing model and extracts negative news.

[0372] The server reduces duplicate negative news and transforms it to soften the headlines.

[0373] The emotion engine evaluates the user's emotions and further adjusts the displayed content.

[0374] The server sends the filtered news feed to the terminal.

[0375] The device displays negative news in a reduced manner, allowing users to obtain important information with peace of mind.

[0376] Example prompt sentence:

[0377] "Show us the latest news and filter it to positive news."

[0378] "Please reduce the negative news and present softened headlines."

[0379] In this way, the system provides a safe news viewing environment based on the user's emotional state and the selected display mode.

[0380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0381] Step 1: Select the news display mode

[0382] Input: The user accesses a news site on their device.

[0383] Processing: The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news and display."

[0384] Output: The news display mode selected by the user.

[0385] Specific operation: Display options on the device screen using radio buttons or a drop-down menu, and allow the user to select one.

[0386] Step 2: Send and record the selected mode

[0387] Input: The news display mode selected by the user.

[0388] Processing: The terminal sends the selected mode to the server, which receives this information and records it in a database.

[0389] Output: Selected mode recorded data.

[0390] Specific operation: The terminal sends an HTTP request to the server, and the server receives the request and stores it in a database.

[0391] Step 3: Getting news data

[0392] Input: The server sends a request to retrieve news data.

[0393] Processing: The server sends a request to an external news API to get the latest news data. The data is received in JSON format.

[0394] Output: The retrieved news data.

[0395] Specific operation: The server sends an HTTP request to the news API and parses the returned JSON data to extract the title, content, tags, etc. of the news article.

[0396] Step 4: News analysis and classification

[0397] Input: Retrieved news data.

[0398] Processing: The server analyzes the news data using natural language processing models (e.g., BERT, GPT) and classifies each article into positive or negative news.

[0399] Output: Data categorized into positive and negative news.

[0400] Specific operation: A news article is input into a natural language processing model, and positive and negative scores are obtained and classified.

[0401] Step 5: Filtering the news

[0402] Input: Categorized news data, user selection mode.

[0403] Processing: The server filters the news based on the selection mode.

[0404] "Show only positive news" mode: Extracts only positive news.

[0405] "Reduce and soften negative news" mode: Reduces overlapping negative news and softens headlines.

[0406] Output: Filtered news data.

[0407] What it does: It uses algorithms to reprocess news and extract or edit the articles you want.

[0408] Step 6: Emotional Engine Alignment

[0409] Input: User's emotional information (facial expression, voice, input content), filtered news data.

[0410] Processing: The server uses an emotion engine to recognize the user's emotions in real time and adjusts the news content displayed based on the evaluation results.

[0411] Output: Adjusted news data.

[0412] Specific operation: Data is collected in real time from cameras and microphones, analyzed using emotion recognition algorithms, and the news data is adjusted based on the evaluation results.

[0413] Step 7: Generate and submit your news feed

[0414] Input: Adjusted news data.

[0415] Processing: The server generates the final news feed and sends it to the device.

[0416] Output: The generated news feed.

[0417] Specific operation: The news feed is packaged in HTML or JSON format and sent to the terminal as an HTTP response.

[0418] Step 8: View your news feed

[0419] Input: Received news feed.

[0420] Processing: The device displays the received news feed.

[0421] Output: The news feed displayed to the user.

[0422] What happens: The device's web browser renders the news feed and displays it on the screen.

[0423] The above are the specific steps of the program processing of this system.

[0424] (Application example 2)

[0425] 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."

[0426] In modern society, people are exposed to an enormous amount of information, often including negative news and stressful information. This has a serious impact on mental health. Furthermore, physical stores are not yet providing services that take into account the emotional state of customers, making improving customer satisfaction a key challenge. Therefore, there is a need for the development of a system that can recognize the emotional state of users and customers in real time and provide appropriate information based on that information.

[0427] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0428] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing and adjusting the user's emotional state in real time, means for further adjusting the news display content based on the felt emotions, means for learning past emotional data and predicting future news display modes, means for adjusting product information and promotions offered in stores according to the customer's emotional state, and means for displaying the filtered and adjusted news and product information on the user's or customer's terminal. This makes it possible to provide appropriate information while maintaining the mental health of the user or customer.

[0429] "News display mode" refers to a setting that a user selects when viewing news, and is used to tailor the news content to the user's preferences and emotional state.

[0430] "News data" refers to data containing the latest news article information, including titles, contents, tags, and other information.

[0431] "Emotion recognition" is a technology that analyzes a user's facial expressions, voice, input content, etc. to evaluate their current emotional state.

[0432] "Filtering" refers to the process of sorting acquired news data based on the mode selected by the user and adjusting the displayed content.

[0433] "Emotion history learning" is a technology that records and analyzes a user's past emotional data to predict future news display modes and information content.

[0434] "Adjusting the news display content" refers to the process of changing the news headline or content to a more toned-down expression based on the emotion recognition results, thereby changing the content to suit the user's emotional state.

[0435] "Promotion" means a marketing activity designed to inform customers about a particular product or service and encourage their purchase or use.

[0436] "Emotion-based product recommendation" is a technology that assesses a customer's current emotional state and provides them with product information and promotions accordingly.

[0437] This invention is a system that recognizes the emotional state of users and customers in real time and provides appropriate information and promotions based on that. This system can be used on news sites and in brick-and-mortar stores.

[0438] System Program

[0439] This system includes a user terminal, a server, and an emotion recognition engine. Specific examples of hardware and software include the following:

[0440] User devices: Tablet devices and smart employee robots

[0441] Server: Cloud server

[0442] Emotion recognition engine: Emotion API

[0443] News API: API to get the latest news data

[0444] Recommender system: A system that recommends product information and news

[0445] Program processing explanation

[0446] When a user uses a tablet device on a news site or in a physical store, the system works as follows:

[0447] 1. Emotion Recognition: Using the device's built-in camera and microphone, the Emotion API analyzes the user's emotions in real time, evaluating the customer's facial expressions and tone of voice to detect their current emotional state.

[0448] 2. Mode selection: When a user selects a news display mode, the selection and emotional state are sent to the server. News display modes include "display only positive news" and "reduced display of negative news." In physical stores, there are modes for "relaxing products" and "energetic products."

[0449] 3. Data Acquisition and Analysis: The server acquires the latest news data through the news API, analyzes the news data using AI and classifies it into positive news and negative news. Similarly, it uses the recommender system to acquire product information for physical stores.

[0450] 4. Filtering and Adjustment: Filter and adjust news and product information based on the user's selected mode and emotion recognition results. For example, for a user who is feeling stressed, increase positive news or recommend relaxing products.

[0451] 5. Display: Display tailored news and product information on the user's device. Users can browse their news feed and see recommended product information on their device.

[0452] Specific examples

[0453] As an example, the system processing when a customer selects the "Relaxing Products" mode using a tablet device and the Emotion API detects that the customer is feeling "stressed" is shown below.

[0454] 1. The customer's feelings are recognized as stress.

[0455] 2. The server filters information about products that have a relaxing effect based on the settings in the "Relaxing Products" mode.

[0456] 3. The filtered product information is displayed on the customer's tablet device.

[0457] Example prompts for generative AI models

[0458] Prompt: "Suggest relaxing products to customers who are feeling stressed. Generate a list of recommended products based on the following emotional data: Emotion Data: {'Emotion': 'Stress', 'Intensity': 'High'}"

[0459] In this way, it is possible to provide information and promotions tailored to the individual emotional state of the user or customer while maintaining their mental health.

[0460] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0461] Step 1:

[0462] The user selects a news display mode from the terminal. For example, the user may select "display only positive news" or "reduce negative news and display." This selection information is sent to the server. The input is the mode information selected by the user, and the output is the transmission of this information to the server.

[0463] Step 2:

[0464] Emotion recognition is performed in real time via the camera and microphone installed on the user's device. The device uses the Emotion API to analyze the user's facial expressions and voice to evaluate their emotional state. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[0465] Step 3:

[0466] The data of the news display mode selected by the user and the recognized emotional state are sent to the server. The input is the user's selected mode information and emotional state, and the output is the transmission of this information to the server.

[0467] Step 4:

[0468] The server retrieves the latest news data via the news API. The input is a request to the news API, and the output is the retrieved news data. The news data includes information such as title, content, and tags.

[0469] Step 5:

[0470] The server uses AI to analyze the acquired news data and classify it into positive news and negative news. The input is news data, and the output is data classified into positive news and negative news.

[0471] Step 6:

[0472] The server filters news based on the user's selected mode and the recognized emotional state. The input is the user's selected mode, emotional state, and classified news data, and the output is the filtered news data. For example, in the "Show only positive news" mode, only positive news is extracted.

[0473] Step 7:

[0474] The filtered news data is further adjusted based on the emotion recognition results. The server converts the displayed content to soften it according to the user's current emotional state. The input is the filtered news data and the emotion recognition results, and the output is the adjusted news data.

[0475] Step 8:

[0476] The server sends the filtered and adjusted news data to the user terminal, where the input is the adjusted news data and the output is the transmission of the news data to the user terminal.

[0477] Step 9:

[0478] The user terminal displays the received news data. The input is the news data sent from the server, and the output is the display of the news feed. The user can view the news feed on the terminal.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] [Second embodiment]

[0483] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0484] 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.

[0485] 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).

[0486] 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.

[0487] 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.

[0488] 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).

[0489] 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.

[0490] 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.

[0491] 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.

[0492] 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.

[0493] In the smart glasses 214, the 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.

[0494] 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."

[0495] The present invention provides a system that reduces the mental burden on users when viewing news and allows them to obtain information more comfortably. This system performs a series of processes: news display mode selection, news data acquisition, analysis, filtering, and display.

[0496] A specific embodiment of this system is shown below.

[0497] 1. Accept the user's selection

[0498] When a user accesses a news site, the device presents a choice of news display modes: "Display only positive news" or "Reduce negative news and display only negative news."

[0499] 2. Data processing according to the selected mode

[0500] The server receives the user's selections and begins the process of generating a news feed based on the selections.

[0501] 3. Acquiring news data

[0502] The server sends a request to the news API to retrieve the latest news data, including metadata such as the title, content, and tags of the news article.

[0503] 4. News Data Analysis

[0504] The device analyzes the acquired news data using AI (natural language processing models, etc.), and the analysis categorizes the news data into positive and negative news.

[0505] 5. News filtering

[0506] The server filters the news based on the news display mode selected by the user.

[0507] When "Show only good news" mode is selected:

[0508] The server extracts only positive news and filters out negative news.

[0509] When "Reduce Bad News" mode is selected:

[0510] The server reduces the duplication of negative news and places it in a less important position.

[0511] Implement wording changes to soften headlines and content.

[0512] 6. Generate and send the news feed to be displayed

[0513] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the terminal.

[0514] 7. Viewing News Feeds

[0515] The device displays the received news feed to the user, who can then browse the news according to the selected mode and efficiently obtain the information they need.

[0516] Specific examples

[0517] Example 1: When the user selects the "Show only good news" mode

[0518] A user visits a news site and selects "Show only positive news."

[0519] The server receives this selection and retrieves the data from the news API.

[0520] The device analyzes news data and categorizes it into positive and negative news.

[0521] The server extracts only positive news and generates a filtered feed.

[0522] The server sends the generated feed to the device.

[0523] The device displays only positive news, allowing users to obtain information without mental stress.

[0524] Example 2: When the user selects the "Reduce Negative News" mode

[0525] A user accesses a news site and selects "Reduce and minimize negative news."

[0526] The server receives this selection and retrieves the data from the news API.

[0527] The device analyzes news data and categorizes it into positive and negative news.

[0528] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[0529] The server generates a filtered feed and sends it to the device.

[0530] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[0531] In this way, the system provides an environment in which the user can efficiently and mentally read the news in accordance with the display mode selected by the user.

[0532] The processing flow will be explained below.

[0533] Step 1:

[0534] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[0535] Step 2:

[0536] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[0537] Step 3:

[0538] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0539] Step 4:

[0540] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[0541] Step 5:

[0542] The server filters the news based on the display mode selected by the user.

[0543] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0544] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[0545] Step 6:

[0546] The server generates a news feed based on the filtered news data, and the feed content depends on the mode selected by the user.

[0547] Step 7:

[0548] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[0549] Step 8:

[0550] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[0551] Example 1

[0552] 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."

[0553] In conventional news viewing systems, users may feel a mental burden depending on the content of the news they view. In particular, when a lot of negative news is displayed, users may feel anxious or stressed. In response to this, there is a need for a means to adjust the news content according to the user's desired display mode and reduce the mental burden.

[0554] 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.

[0555] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for acquiring data from a news API, means for analyzing the news data using a natural language processing model, means for generating a news feed and transmitting it to the user's terminal, and means for displaying the filtered news. This allows the user to view news filtered based on the desired news display mode, thereby reducing mental strain.

[0556] A "user" is an entity that uses the system to view news.

[0557] "News display mode" is an option that allows the user to select the type of news to view and the display method.

[0558] "News data" is a collection of information about news, such as the title, content, tags, and publication date of a news article.

[0559] "Positive news" is news that has been classified as positive or optimistic through sentiment analysis of news data.

[0560] "Negative news" is news that has been classified as negative or pessimistic through sentiment analysis of news data.

[0561] "Filtering" is the process of selecting and organizing news data based on the news display mode selected by the user.

[0562] A "News API" is an interface for accessing external news data providers and obtaining news data.

[0563] A "natural language processing model" is an algorithm or software that uses artificial intelligence techniques to analyze and classify text.

[0564] A "news feed" is a filtered list of news articles displayed to a user.

[0565] A "terminal" is a hardware device (e.g., a smartphone, tablet, or PC) that a user uses to access a news site and view a news feed.

[0566] The present invention provides a news viewing system that aims to reduce the mental burden on users when viewing news by presenting them with a choice of news display modes, acquiring, analyzing, and filtering news data according to the selected mode, and ultimately displaying a news feed appropriate for the user.

[0567] composition

[0568] This system operates using a server, terminals, news APIs, and natural language processing (NLP) models. The specific hardware and software configuration is shown below.

[0569] 1. Server:

[0570] The server receives the user's selected display mode, retrieves, analyzes, filters, and generates a feed of news data.

[0571] Technologies used include web frameworks (e.g., Spring Boot, Django) and database systems (e.g., MySQL, PostgreSQL).

[0572] 2. Terminal:

[0573] The terminal accepts the user's selection, presents display mode options, and displays the filtered news feed.

[0574] The devices used include various user devices such as PCs, tablets, and smartphones.

[0575] 3. News API:

[0576] This is an interface for external services used to obtain news data. For example, it uses services that provide news data (e.g., Google News API, NewsAPI.org).

[0577] 4. Natural Language Processing Models (NLP Models):

[0578] It is an AI technology used to analyze news data and analyze the sentiment of text. Specific examples include models such as BERT and GPT-4.

[0579] This technology runs on machine learning frameworks such as TensorFlow and PyTorch.

[0580] Processing flow

[0581] When a user accesses a news site, the device presents a choice of news display modes. After the user selects a display mode, the device sends that information to the server. The server then sends a request to the news API to retrieve the latest news data. The retrieved news data is then analyzed on the device using an NLP model to classify it into positive and negative news.

[0582] The server filters the news based on the user's selection, generates a news feed, and sends it to the device. The device displays the filtered news feed to the user, allowing the user to view news according to the selected mode. This series of processes allows the user to efficiently obtain the information they need while reducing their mental burden.

[0583] Specific examples

[0584] Example 1: "Show only good news" mode

[0585] 1. A user visits a news site and selects "Show only positive news."

[0586] 2. The device sends the user's selection to the server.

[0587] 3. The server receives this selection and retrieves the news data from the news API.

[0588] 4. The device analyzes the news data and classifies it into positive and negative news.

[0589] 5. The server extracts only positive news and generates a news feed.

[0590] 6. The server sends the generated feed to the device, which displays only positive news.

[0591] Example 2: "Reduce negative news and display" mode

[0592] 1. A user visits a news site and selects "Reduce and minimize negative news."

[0593] 2. The device sends the user's selection to the server.

[0594] 3. The server receives this selection and retrieves the news data from the news API.

[0595] 4. The device analyzes the news data and classifies it into positive and negative news.

[0596] 5. The server reduces duplicate negative news and transforms it to soften the headline and content.

[0597] 6. The server generates a news feed and sends it to the device.

[0598] 7. The device will display negative news in a reduced volume, helping users reduce their mental burden.

[0599] In this way, the system provides an environment in which the user can efficiently and mentally read the news according to the display mode selected by the user.

[0600] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0601] Step 1: User visits a news site and selects a viewing mode

[0602] A user accesses a news site using a web browser or a dedicated app. The input is the user's access behavior.

[0603] The device presents a news display mode option ("Show only positive news" or "Show less negative news"), which is displayed as HTML or in the app's UI, allowing the user to click on the option.

[0604] Step 2: Receive the user's choice and send it to the server

[0605] The user selects one of the display modes. The selected mode (input) is either "display only positive news" or "reduced display with less negative news."

[0606] The device sends the user's selection to the server as a POST request (output). Data is sent in JSON format.

[0607] Step 3: Save the user's selections to the database

[0608] The server receives the user's selection (input).

[0609] The server saves the selection in a database (e.g. MySQL or PostgreSQL), making the user's selection persistent.

[0610] Step 4: Get news data from the News API

[0611] The server sends an HTTP request to the News API (output), which includes parameters (e.g., category, region) in JSON format.

[0612] The server receives response data from the API (input), which includes the news article title, content, tags, publication date, etc.

[0613] Step 5: Send news data to your device

[0614] The server sends the received news data to the terminal. Here, news data in JSON format is used (input).

[0615] The terminal temporarily stores the received data.

[0616] Step 6: Analyze the news data and categorize it into positive and negative news

[0617] The device analyzes (inputs) the stored news data using natural language processing (NLP) models, such as BERT and GPT-4, to perform sentiment analysis of the text.

[0618] The device classifies news articles into positive and negative news (output). Each news item is assigned a sentiment score and the classification results are saved in JSON format.

[0619] Step 7: Filter the news data

[0620] The server filters (inputs) news data based on the display mode selected by the user. Filtering is performed based on the analysis results.

[0621] If the "Show only positive news" mode is selected, the server extracts only positive news and excludes negative news (output).

[0622] When the "Reduce Negative News and Display" mode is selected, the server reduces the duplication of negative news and performs representation transformations to soften the headlines and content (output).

[0623] Step 8: Generate a filtered news feed

[0624] The server generates a news feed to display to the user based on the filtered news data (input). The feed is generated using HTML or JSON format.

[0625] The generated news feed is sent to the terminal (output).

[0626] Step 9: View your filtered news feed

[0627] The terminal displays the received news feed to the user (input).

[0628] Users get information by looking at the news feed, which displays news appropriately based on the selected display mode, reducing mental strain (output).

[0629] (Application example 1)

[0630] 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."

[0631] In modern society, reading the news is a part of everyday life, but the mental burden caused by negative news has become a problem. While there is a demand for systems that allow users to comfortably view specific information, there is a lack of means to provide users with appropriately personalized information amid the advancement of information provision in virtual spaces and smart devices. The present invention aims to solve these problems and provide a system that allows users to obtain information without feeling any mental burden.

[0632] 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.

[0633] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for displaying the filtered news on the user's terminal, and means for displaying a news feed on a device that provides information to the user in a virtual space. This reduces the mental burden on the user when viewing news and enables the user to receive optimal information in a personalized form even within the virtual space.

[0634] "News display mode" is a setting option that allows the user to select the format in which news is displayed.

[0635] "News data" refers to information including the title, content, and metadata of a news article.

[0636] "Analysis" is the process of classifying acquired news data into positive and negative news using natural language processing models, etc.

[0637] "Positive news" is a news article that is judged to have positive content and to have a positive impact on users.

[0638] "Negative news" refers to news articles that are deemed to have negative content and have a negative impact on users.

[0639] "Filtering" is the process of selecting and adjusting news data based on the news display mode selected by the user.

[0640] A "user terminal" is a user's information device used to display a news feed.

[0641] A "virtual space" is a virtual area in which users can carry out various activities within a digital environment.

[0642] A "smart device" is an electronic device equipped with internet connectivity that can display and operate information in a virtual space.

[0643] A "news feed" is an information list that organizes filtered news data and displays it to the user.

[0644] "Representation transformation" is the process of softening the headline and content of a news article to reduce the mental burden on the user.

[0645] The present invention provides a system that reduces the mental burden placed on users when viewing news and allows them to obtain information in a comfortable manner. The system is configured as follows.

[0646] Select news display mode

[0647] When a user accesses a news site through a device, the server presents a choice of news display modes. A screen is displayed asking the user to select either "Display only positive news" or "Reduce negative news and display." When the user makes a selection, the selection information is sent to the server.

[0648] Acquiring news data

[0649] The server sends a request to the news API to retrieve the latest news data. This data includes metadata such as the title, content, and tags of the news article. For example, the server retrieves the data using NewsAPI (https: / / newsapi.org / ).

[0650] News data analysis

[0651] The server analyzes the acquired news data using a natural language processing model (e.g., Hugging Face's Transformers library). Based on the analysis results, the news articles are classified into positive news and negative news.

[0652] For example, a news headline such as "A new clothing line has been launched" would be classified as positive news, while a headline such as "Some products need improvement" would be classified as negative news.

[0653] News filtering

[0654] The server filters the news based on the news display mode selected by the user.

[0655] When "Show only good news" mode is selected:

[0656] The server extracts only positive news and filters out negative news.

[0657] When "Reduce Bad News" mode is selected:

[0658] The server reduces the duplication of negative news and performs wording transformation to soften headlines and content. Wording transformation is expected to have the effect of softening negative expressions.

[0659] Generate and display a filtered news feed

[0660] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the device. The user can view news according to the selected mode, allowing for convenient information acquisition.

[0661] Providing information in virtual space

[0662] This system has the ability to provide users with the most appropriate information even in virtual spaces. For example, it can display news, the latest information, product notifications, and more within a virtual store via a smart device. The information displayed is personalized based on the selected news display mode, reducing the user's mental burden.

[0663] Prompt Sentence Examples

[0664] "Classify your news data into positive and negative news. Analyze the following news headlines: 'A new clothing line has been launched', 'Some products need improvement'."

[0665] In this way, the system allows users to browse the news without feeling any mental strain, and also provides an optimal user experience, including information provision in a virtual space.

[0666] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0667] Step 1:

[0668] A user visits a news site and selects a viewing mode.

[0669] Input: A user visits a news site and is presented with a choice screen.

[0670] Behavior: The device presents the user with the option to "display only positive news" or "reduce negative news." The user selects one of these display modes.

[0671] Output: The user's selection is sent to the server.

[0672] Step 2:

[0673] The server retrieves news data

[0674] Input: User selections and request to News API.

[0675] How it works: The server uses a news API (e.g., NewsAPI) to retrieve the latest news data, including metadata such as title, content, and tags.

[0676] Output: The retrieved news data is stored on the server.

[0677] Step 3:

[0678] News data analysis

[0679] Input: Retrieved news data.

[0680] How it works: The server analyzes news data using Hugging Face's Transformers library. A natural language processing model classifies the news data into positive and negative news.

[0681] Output: Categorized news data. A list of positive and negative news is generated.

[0682] Step 4:

[0683] News filtering

[0684] Input: Categorized news data and user-selected news display mode.

[0685] How it works: The server filters based on the mode selected by the user.

[0686] In the positive news only display mode: Only positive news is extracted and negative news is removed.

[0687] In the "Reduce and lighten dark news" display mode: Reduces the duplication of negative news and performs wording transformations to soften headlines and content.

[0688] Output: Filtered news data.

[0689] Step 5:

[0690] Newsfeed generation and submission

[0691] Input: Filtered news data.

[0692] How it works: The server generates a news feed based on the filtered news data, and the generated feed is sent to the user's device.

[0693] Output: The news feed sent to the user's device.

[0694] Step 6:

[0695] Displaying news feeds on users' devices

[0696] Input: The news feed sent from the server.

[0697] How it works: The device displays the news feed to the user, who then browses the news according to the mode selected.

[0698] Output: The news feed displayed on the user's device.

[0699] Step 7:

[0700] Providing information in virtual space

[0701] Input: Filtered news data sent from the server.

[0702] How it works: Smart devices (e.g. smart glasses) display personalized news and notifications in a virtual space.

[0703] Output: Personalized news feed and notifications displayed on your smart device.

[0704] The above is the flow of processing steps from selecting the news display mode to providing information in the virtual space.

[0705] 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.

[0706] This invention provides a system that allows users to browse the news while maintaining their mental health. It combines a conventional news display system with an emotion engine that recognizes the user's emotions. This system realizes a series of steps from selecting the news display mode to emotion recognition, filtering the news, and displaying it.

[0707] A specific embodiment of this system is shown below.

[0708] 1. Select the news display mode

[0709] When a user accesses a news site, the device displays a news display mode selection screen, allowing the user to choose between "Display only positive news" or "Reduce negative news and display."

[0710] 2. Transmit and record the selected mode

[0711] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[0712] 3. Acquiring news data

[0713] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0714] 4. News Data Analysis

[0715] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[0716] 5. News filtering

[0717] The server filters the news based on the display mode selected by the user.

[0718] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0719] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[0720] 6. Emotional Engine Adjustment

[0721] The present invention further includes an emotion engine that recognizes the user's emotions. The emotion engine includes the following three functions:

[0722] 1. Real-time recognition and assessment of user emotions:

[0723] The server uses an emotion engine to evaluate the user's emotions in real time based on their facial expressions, voice, input, etc. Based on this evaluation, the server adjusts the news display mode and content.

[0724] 2. Emotion history learning:

[0725] By recording the user's emotion history, the server uses a learning algorithm to predict future news display modes based on past data, and provides more relevant news based on this prediction.

[0726] 3. Adjust content based on emotions:

[0727] The emotion engine further adjusts the filtered news content based on the user's current emotions: for example, if the user is feeling stressed, it will increase the proportion of positive news and use more calming language.

[0728] 7. Generate and send the news feed to be displayed

[0729] The server generates a news feed based on the filtered and adjusted news data by the emotion engine, and the generated feed is tailored to the user's selected mode and current emotional state.

[0730] 8. Viewing News Feeds

[0731] The terminal displays the received news feed to the user, who can browse the news feed on the terminal and obtain news according to the selected mode and current emotional state efficiently and mentally at ease.

[0732] Specific examples

[0733] Example 1: When the user selects the "Show only good news" mode

[0734] A user visits a news site and selects "Show only positive news."

[0735] The server receives this selection and retrieves the data from the news API.

[0736] The device analyzes news data and categorizes it into positive and negative news.

[0737] The server extracts only positive news and generates a filtered feed.

[0738] The emotion engine evaluates the user's emotions and enriches news that contains particularly gentle expressions.

[0739] The server sends the generated feed to the device.

[0740] The device displays only positive news, allowing users to obtain information without mental stress.

[0741] Example 2: When the user selects the "Reduce Negative News" mode

[0742] A user accesses a news site and selects "Reduce and minimize negative news."

[0743] The server receives this selection and retrieves the data from the news API.

[0744] The device analyzes news data and categorizes it into positive and negative news.

[0745] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[0746] The emotion engine assesses the user's emotions and further tailors the news content displayed based on that state.

[0747] The server generates a filtered feed and sends it to the device.

[0748] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[0749] In this way, the system takes into account the user's emotional state and provides an efficient and safe environment for browsing news according to the selected display mode.

[0750] The processing flow will be explained below.

[0751] Step 1:

[0752] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[0753] Step 2:

[0754] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode for use in subsequent processing.

[0755] Step 3:

[0756] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0757] Step 4:

[0758] The server analyzes the acquired news data using AI (such as natural language processing models), and the news data is classified into positive news and negative news.

[0759] Step 5:

[0760] The server filters the news based on the display mode selected by the user.

[0761] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[0762] When the "Reduce and lighten the display of negative news" mode is selected, the server reduces the duplication of negative news, places it in a less important position, and performs wording transformations to soften the headlines and content.

[0763] Step 6:

[0764] The server uses an emotion engine to recognize the user's current emotional state, collecting data such as the user's facial expressions, voice, and input from the device, and evaluating the user's emotions in real time.

[0765] Step 7:

[0766] The server adjusts the news display mode and content based on the emotional information acquired by the emotion engine. For example, if the user is assessed as feeling stressed, the server increases the proportion of positive news.

[0767] Step 8:

[0768] The emotion engine learns the user's past emotion history, and the server predicts future news display modes based on this and provides news based on the prediction.

[0769] Step 9:

[0770] The server generates a news feed based on the filtered news data, and ensures that the feed is in accordance with the user's selected mode and sentiment rating.

[0771] Step 10:

[0772] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[0773] Step 11:

[0774] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[0775] Example 2

[0776] 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."

[0777] Conventional news display systems simply display news as is and do not consider the user's emotional state, which can cause mental strain. Displaying a large amount of negative news, in particular, can have a negative impact on the user's mental health. Furthermore, systems that adjust news display based on the user's emotions have not yet been fully implemented. The present invention aims to provide an environment in which users can browse the news with peace of mind.

[0778] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0779] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results, means for generating a news feed based on the filtering and emotion recognition, means for transmitting the generated news feed to the user's terminal, means for readjusting the news feed based on the feedback, and means for displaying the filtered news on the user's terminal, thereby enabling the user to browse the news with peace of mind without feeling any mental burden.

[0780] The "means for accepting selection of a news display mode" is a means having a function of providing an interface that allows a user to select a news display mode and transmitting the selection to a server.

[0781] "Means for acquiring news data" refers to a means by which the server has the function of acquiring the latest news article data from an external news API.

[0782] "Means for analyzing news data and classifying it into positive and negative news" refers to a means that uses AI technology such as natural language processing models to analyze acquired news article data and classify it into positive and negative content.

[0783] The "means for filtering news" is a means having a function for selecting news to be displayed based on the news display mode selected by the user and the analysis results.

[0784] "Means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results" refers to a means that uses an emotion engine to analyze the user's facial expressions, voice, input content, etc. in real time, and adjusts the content and display method of the news based on the results.

[0785] The "means for generating a news feed based on filtering and emotion recognition" is a means having a function for generating an optimal news feed for a user based on filtered news and the user's emotion evaluation results.

[0786] The "means for transmitting the generated news feed to the user's terminal" refers to a means having a function for transmitting the news feed generated by the server to the user's terminal using a communication means.

[0787] The "means for readjusting a news feed based on feedback" refers to a means having a function for readjusting the content and display method of a news feed based on feedback information from a user.

[0788] The "means for displaying filtered news on a user's terminal" refers to a means having a function for displaying the final filtered news feed on a user's terminal so that the user can view it.

[0789] The present invention provides a system for selecting a news display mode, acquiring, analyzing, filtering, and recognizing emotions in news data, and generating and displaying a news feed, all of which are performed to enable users to browse news without feeling any mental strain.

[0790] Hardware and software used

[0791] Hardware

[0792] Terminal: A device operated by a user. Examples include computers, smartphones, and tablets.

[0793] Server: A computer system responsible for processing and storing data.

[0794] Emotion recognition devices: Devices such as cameras and microphones that capture the user's facial expressions and voice.

[0795] software

[0796] News API: API for obtaining external news data.

[0797] Natural language processing model (NLP model): An AI model for analyzing news data and classifying it into positive and negative news. Examples include BERT and GPT.

[0798] Emotion engine: Software for analyzing the user's emotional state in real time.

[0799] Filtering Algorithm: The algorithm for filtering the news data.

[0800] System Overview

[0801] Select news display mode

[0802] When a user accesses a news site, the device displays a news display mode selection screen, where the user can choose between "Display only positive news" or "Reduce negative news and display."

[0803] Mode transmission and recording

[0804] The terminal transmits information about the mode selected by the user to the server, which records this selection information in a database.

[0805] Acquiring news data

[0806] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news articles.

[0807] News analysis and classification

[0808] The server analyzes the news data using a natural language processing model and classifies articles into positive and negative news.

[0809] News filtering

[0810] The server filters news based on the mode selected by the user: "Show only positive news" mode extracts only positive news, while "Reduce and lighten negative news" mode reduces the overlap of negative news and softens the headlines.

[0811] Emotional engine regulation

[0812] The server uses an emotion engine to recognize the user's emotional state in real time and adjusts the news content displayed based on the evaluation, which may include increasing the proportion of positive news or converting the news content to a more gentle expression.

[0813] Newsfeed generation and submission

[0814] Based on the filtering and emotion recognition, the server generates a news feed and sends the news feed to the user's terminal.

[0815] Viewing the news feed

[0816] The device displays the received news feed to the user, allowing the user to comfortably browse news according to the selected mode and emotional state.

[0817] Specific examples

[0818] Example 1: When the user selects the "Show only good news" mode

[0819] The user selects the "Show only positive news" mode on their device.

[0820] The server receives this information and retrieves the latest news from the news API.

[0821] The server analyzes the news data using a natural language processing model and extracts only positive news.

[0822] The emotion engine assesses the user's emotions and adjusts the news content to be particularly gentle.

[0823] The server generates the final news feed and sends it to the device.

[0824] The device displays positive news, allowing users to obtain information without mental strain.

[0825] Example 2: When the user selects the "Reduce Negative News" mode

[0826] The user selects the "Reduce negative news and display" mode on the device.

[0827] The server receives this information and retrieves the latest news from the news API.

[0828] The server analyzes the news data using a natural language processing model and extracts negative news.

[0829] The server reduces duplicate negative news and transforms it to soften the headlines.

[0830] The emotion engine evaluates the user's emotions and further adjusts the displayed content.

[0831] The server sends the filtered news feed to the terminal.

[0832] The device displays negative news in a reduced manner, allowing users to obtain important information with peace of mind.

[0833] Example prompt sentence:

[0834] "Show us the latest news and filter it to positive news."

[0835] "Please reduce the negative news and present softened headlines."

[0836] In this way, the system provides a safe news viewing environment based on the user's emotional state and the selected display mode.

[0837] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0838] Step 1: Select the news display mode

[0839] Input: The user accesses a news site on their device.

[0840] Processing: The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news and display."

[0841] Output: The news display mode selected by the user.

[0842] Specific operation: Display options on the device screen using radio buttons or a drop-down menu, and allow the user to select one.

[0843] Step 2: Send and record the selected mode

[0844] Input: The news display mode selected by the user.

[0845] Processing: The terminal sends the selected mode to the server, which receives this information and records it in a database.

[0846] Output: Selected mode recorded data.

[0847] Specific operation: The terminal sends an HTTP request to the server, and the server receives the request and stores it in a database.

[0848] Step 3: Getting news data

[0849] Input: The server sends a request to retrieve news data.

[0850] Processing: The server sends a request to an external news API to get the latest news data. The data is received in JSON format.

[0851] Output: The retrieved news data.

[0852] Specific operation: The server sends an HTTP request to the news API and parses the returned JSON data to extract the title, content, tags, etc. of the news article.

[0853] Step 4: News analysis and classification

[0854] Input: Retrieved news data.

[0855] Processing: The server analyzes the news data using natural language processing models (e.g., BERT, GPT) and classifies each article into positive or negative news.

[0856] Output: Data categorized into positive and negative news.

[0857] Specific operation: A news article is input into a natural language processing model, and positive and negative scores are obtained and classified.

[0858] Step 5: Filtering the news

[0859] Input: Categorized news data, user selection mode.

[0860] Processing: The server filters the news based on the selection mode.

[0861] "Show only positive news" mode: Extracts only positive news.

[0862] "Reduce and soften negative news" mode: Reduces overlapping negative news and softens headlines.

[0863] Output: Filtered news data.

[0864] What it does: It uses algorithms to reprocess news and extract or edit the articles you want.

[0865] Step 6: Emotional Engine Alignment

[0866] Input: User's emotional information (facial expression, voice, input content), filtered news data.

[0867] Processing: The server uses an emotion engine to recognize the user's emotions in real time and adjusts the news content displayed based on the evaluation results.

[0868] Output: Adjusted news data.

[0869] Specific operation: Data is collected in real time from cameras and microphones, analyzed using emotion recognition algorithms, and the news data is adjusted based on the evaluation results.

[0870] Step 7: Generate and submit your news feed

[0871] Input: Adjusted news data.

[0872] Processing: The server generates the final news feed and sends it to the device.

[0873] Output: The generated news feed.

[0874] Specific operation: The news feed is packaged in HTML or JSON format and sent to the terminal as an HTTP response.

[0875] Step 8: View your news feed

[0876] Input: Received news feed.

[0877] Processing: The device displays the received news feed.

[0878] Output: The news feed displayed to the user.

[0879] What happens: The device's web browser renders the news feed and displays it on the screen.

[0880] The above are the specific steps of the program processing of this system.

[0881] (Application example 2)

[0882] 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."

[0883] In modern society, people are exposed to an enormous amount of information, often including negative news and stressful information. This has a serious impact on mental health. Furthermore, physical stores are not yet providing services that take into account the emotional state of customers, making improving customer satisfaction a key challenge. Therefore, there is a need for the development of a system that can recognize the emotional state of users and customers in real time and provide appropriate information based on that information.

[0884] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0885] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing and adjusting the user's emotional state in real time, means for further adjusting the news display content based on the felt emotions, means for learning past emotional data and predicting future news display modes, means for adjusting product information and promotions offered in stores according to the customer's emotional state, and means for displaying the filtered and adjusted news and product information on the user's or customer's terminal. This makes it possible to provide appropriate information while maintaining the mental health of the user or customer.

[0886] "News display mode" refers to a setting that a user selects when viewing news, and is used to tailor the news content to the user's preferences and emotional state.

[0887] "News data" refers to data containing the latest news article information, including titles, contents, tags, and other information.

[0888] "Emotion recognition" is a technology that analyzes a user's facial expressions, voice, input content, etc. to evaluate their current emotional state.

[0889] "Filtering" refers to the process of sorting acquired news data based on the mode selected by the user and adjusting the displayed content.

[0890] "Emotion history learning" is a technology that records and analyzes a user's past emotional data to predict future news display modes and information content.

[0891] "Adjusting the news display content" refers to the process of changing the news headline or content to a more toned-down expression based on the emotion recognition results, thereby changing the content to suit the user's emotional state.

[0892] "Promotion" means a marketing activity designed to inform customers about a particular product or service and encourage their purchase or use.

[0893] "Emotion-based product recommendation" is a technology that assesses a customer's current emotional state and provides them with product information and promotions accordingly.

[0894] This invention is a system that recognizes the emotional state of users and customers in real time and provides appropriate information and promotions based on that. This system can be used on news sites and in brick-and-mortar stores.

[0895] System Program

[0896] This system includes a user terminal, a server, and an emotion recognition engine. Specific examples of hardware and software include the following:

[0897] User devices: Tablet devices and smart employee robots

[0898] Server: Cloud server

[0899] Emotion recognition engine: Emotion API

[0900] News API: API to get the latest news data

[0901] Recommender system: A system that recommends product information and news

[0902] Program processing explanation

[0903] When a user uses a tablet device on a news site or in a physical store, the system works as follows:

[0904] 1. Emotion Recognition: Using the device's built-in camera and microphone, the Emotion API analyzes the user's emotions in real time, evaluating the customer's facial expressions and tone of voice to detect their current emotional state.

[0905] 2. Mode selection: When a user selects a news display mode, the selection and emotional state are sent to the server. News display modes include "display only positive news" and "reduced display of negative news." In physical stores, there are modes for "relaxing products" and "energetic products."

[0906] 3. Data Acquisition and Analysis: The server acquires the latest news data through the news API, analyzes the news data using AI and classifies it into positive news and negative news. Similarly, it uses the recommender system to acquire product information for physical stores.

[0907] 4. Filtering and Adjustment: Filter and adjust news and product information based on the user's selected mode and emotion recognition results. For example, for a user who is feeling stressed, increase positive news or recommend relaxing products.

[0908] 5. Display: Display tailored news and product information on the user's device. Users can browse their news feed and see recommended product information on their device.

[0909] Specific examples

[0910] As an example, the system processing when a customer selects the "Relaxing Products" mode using a tablet device and the Emotion API detects that the customer is feeling "stressed" is shown below.

[0911] 1. The customer's feelings are recognized as stress.

[0912] 2. The server filters information about products that have a relaxing effect based on the settings in the "Relaxing Products" mode.

[0913] 3. The filtered product information is displayed on the customer's tablet device.

[0914] Example prompts for generative AI models

[0915] Prompt: "Suggest relaxing products to customers who are feeling stressed. Generate a list of recommended products based on the following emotional data: Emotion Data: {'Emotion': 'Stress', 'Intensity': 'High'}"

[0916] In this way, it is possible to provide information and promotions tailored to the individual emotional state of the user or customer while maintaining their mental health.

[0917] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0918] Step 1:

[0919] The user selects a news display mode from the terminal. For example, the user may select "display only positive news" or "reduce negative news and display." This selection information is sent to the server. The input is the mode information selected by the user, and the output is the transmission of this information to the server.

[0920] Step 2:

[0921] Emotion recognition is performed in real time via the camera and microphone installed on the user's device. The device uses the Emotion API to analyze the user's facial expressions and voice to evaluate their emotional state. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[0922] Step 3:

[0923] The data of the news display mode selected by the user and the recognized emotional state are sent to the server. The input is the user's selected mode information and emotional state, and the output is the transmission of this information to the server.

[0924] Step 4:

[0925] The server retrieves the latest news data via the news API. The input is a request to the news API, and the output is the retrieved news data. The news data includes information such as title, content, and tags.

[0926] Step 5:

[0927] The server uses AI to analyze the acquired news data and classify it into positive news and negative news. The input is news data, and the output is data classified into positive news and negative news.

[0928] Step 6:

[0929] The server filters news based on the user's selected mode and the recognized emotional state. The input is the user's selected mode, emotional state, and classified news data, and the output is the filtered news data. For example, in the "Show only positive news" mode, only positive news is extracted.

[0930] Step 7:

[0931] The filtered news data is further adjusted based on the emotion recognition results. The server converts the displayed content to soften it according to the user's current emotional state. The input is the filtered news data and the emotion recognition results, and the output is the adjusted news data.

[0932] Step 8:

[0933] The server sends the filtered and adjusted news data to the user terminal, where the input is the adjusted news data and the output is the transmission of the news data to the user terminal.

[0934] Step 9:

[0935] The user terminal displays the received news data. The input is the news data sent from the server, and the output is the display of the news feed. The user can view the news feed on the terminal.

[0936] 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.

[0937] 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.

[0938] 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.

[0939] [Third embodiment]

[0940] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0941] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0942] 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).

[0943] 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.

[0944] 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.

[0945] 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).

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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."

[0952] The present invention provides a system that reduces the mental burden on users when viewing news and allows them to obtain information more comfortably. This system performs a series of processes: news display mode selection, news data acquisition, analysis, filtering, and display.

[0953] A specific embodiment of this system is shown below.

[0954] 1. Accept the user's selection

[0955] When a user accesses a news site, the device presents a choice of news display modes: "Display only positive news" or "Reduce negative news and display only negative news."

[0956] 2. Data processing according to the selected mode

[0957] The server receives the user's selections and begins the process of generating a news feed based on the selections.

[0958] 3. Acquiring news data

[0959] The server sends a request to the news API to retrieve the latest news data, including metadata such as the title, content, and tags of the news article.

[0960] 4. News Data Analysis

[0961] The device analyzes the acquired news data using AI (natural language processing models, etc.), and the analysis categorizes the news data into positive and negative news.

[0962] 5. News filtering

[0963] The server filters the news based on the news display mode selected by the user.

[0964] When "Show only good news" mode is selected:

[0965] The server extracts only positive news and filters out negative news.

[0966] When "Reduce Bad News" mode is selected:

[0967] The server reduces the duplication of negative news and places it in a less important position.

[0968] Implement wording changes to soften headlines and content.

[0969] 6. Generate and send the news feed to be displayed

[0970] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the terminal.

[0971] 7. Viewing News Feeds

[0972] The device displays the received news feed to the user, who can then browse the news according to the selected mode and efficiently obtain the information they need.

[0973] Specific examples

[0974] Example 1: When the user selects the "Show only good news" mode

[0975] A user visits a news site and selects "Show only positive news."

[0976] The server receives this selection and retrieves the data from the news API.

[0977] The device analyzes news data and categorizes it into positive and negative news.

[0978] The server extracts only positive news and generates a filtered feed.

[0979] The server sends the generated feed to the device.

[0980] The device displays only positive news, allowing users to obtain information without mental stress.

[0981] Example 2: When the user selects the "Reduce Negative News" mode

[0982] A user accesses a news site and selects "Reduce and minimize negative news."

[0983] The server receives this selection and retrieves the data from the news API.

[0984] The device analyzes news data and categorizes it into positive and negative news.

[0985] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[0986] The server generates a filtered feed and sends it to the device.

[0987] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[0988] In this way, the system provides an environment in which the user can efficiently and mentally read the news in accordance with the display mode selected by the user.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[0992] Step 2:

[0993] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[0994] Step 3:

[0995] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[0996] Step 4:

[0997] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[0998] Step 5:

[0999] The server filters the news based on the display mode selected by the user.

[1000] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1001] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[1002] Step 6:

[1003] The server generates a news feed based on the filtered news data, and the feed content depends on the mode selected by the user.

[1004] Step 7:

[1005] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[1006] Step 8:

[1007] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[1008] Example 1

[1009] 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."

[1010] In conventional news viewing systems, users may feel a mental burden depending on the content of the news they view. In particular, when a lot of negative news is displayed, users may feel anxious or stressed. In response to this, there is a need for a means to adjust the news content according to the user's desired display mode and reduce the mental burden.

[1011] 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.

[1012] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for acquiring data from a news API, means for analyzing the news data using a natural language processing model, means for generating a news feed and transmitting it to the user's terminal, and means for displaying the filtered news. This allows the user to view news filtered based on the desired news display mode, thereby reducing mental strain.

[1013] A "user" is an entity that uses the system to view news.

[1014] "News display mode" is an option that allows the user to select the type of news to view and the display method.

[1015] "News data" is a collection of information about news, such as the title, content, tags, and publication date of a news article.

[1016] "Positive news" is news that has been classified as positive or optimistic through sentiment analysis of news data.

[1017] "Negative news" is news that has been classified as negative or pessimistic through sentiment analysis of news data.

[1018] "Filtering" is the process of selecting and organizing news data based on the news display mode selected by the user.

[1019] A "News API" is an interface for accessing external news data providers and obtaining news data.

[1020] A "natural language processing model" is an algorithm or software that uses artificial intelligence techniques to analyze and classify text.

[1021] A "news feed" is a filtered list of news articles displayed to a user.

[1022] A "terminal" is a hardware device (e.g., a smartphone, tablet, or PC) that a user uses to access a news site and view a news feed.

[1023] The present invention provides a news viewing system that aims to reduce the mental burden on users when viewing news by presenting them with a choice of news display modes, acquiring, analyzing, and filtering news data according to the selected mode, and ultimately displaying a news feed appropriate for the user.

[1024] composition

[1025] This system operates using a server, terminals, news APIs, and natural language processing (NLP) models. The specific hardware and software configuration is shown below.

[1026] 1. Server:

[1027] The server receives the user's selected display mode, retrieves, analyzes, filters, and generates a feed of news data.

[1028] Technologies used include web frameworks (e.g., Spring Boot, Django) and database systems (e.g., MySQL, PostgreSQL).

[1029] 2. Terminal:

[1030] The terminal accepts the user's selection, presents display mode options, and displays the filtered news feed.

[1031] The devices used include various user devices such as PCs, tablets, and smartphones.

[1032] 3. News API:

[1033] This is an interface for external services used to obtain news data. For example, it uses services that provide news data (e.g., Google News API, NewsAPI.org).

[1034] 4. Natural Language Processing Models (NLP Models):

[1035] It is an AI technology used to analyze news data and analyze the sentiment of text. Specific examples include models such as BERT and GPT-4.

[1036] This technology runs on machine learning frameworks such as TensorFlow and PyTorch.

[1037] Processing flow

[1038] When a user accesses a news site, the device presents a choice of news display modes. After the user selects a display mode, the device sends that information to the server. The server then sends a request to the news API to retrieve the latest news data. The retrieved news data is then analyzed on the device using an NLP model to classify it into positive and negative news.

[1039] The server filters the news based on the user's selection, generates a news feed, and sends it to the device. The device displays the filtered news feed to the user, allowing the user to view news according to the selected mode. This series of processes allows the user to efficiently obtain the information they need while reducing their mental burden.

[1040] Specific examples

[1041] Example 1: "Show only good news" mode

[1042] 1. A user visits a news site and selects "Show only positive news."

[1043] 2. The device sends the user's selection to the server.

[1044] 3. The server receives this selection and retrieves the news data from the news API.

[1045] 4. The device analyzes the news data and classifies it into positive and negative news.

[1046] 5. The server extracts only positive news and generates a news feed.

[1047] 6. The server sends the generated feed to the device, which displays only positive news.

[1048] Example 2: "Reduce negative news and display" mode

[1049] 1. A user visits a news site and selects "Reduce and minimize negative news."

[1050] 2. The device sends the user's selection to the server.

[1051] 3. The server receives this selection and retrieves the news data from the news API.

[1052] 4. The device analyzes the news data and classifies it into positive and negative news.

[1053] 5. The server reduces duplicate negative news and transforms it to soften the headline and content.

[1054] 6. The server generates a news feed and sends it to the device.

[1055] 7. The device will display negative news in a reduced volume, helping users reduce their mental burden.

[1056] In this way, the system provides an environment in which the user can efficiently and mentally read the news according to the display mode selected by the user.

[1057] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1058] Step 1: User visits a news site and selects a viewing mode

[1059] A user accesses a news site using a web browser or a dedicated app. The input is the user's access behavior.

[1060] The device presents a news display mode option ("Show only positive news" or "Show less negative news"), which is displayed as HTML or in the app's UI, allowing the user to click on the option.

[1061] Step 2: Receive the user's choice and send it to the server

[1062] The user selects one of the display modes. The selected mode (input) is either "display only positive news" or "reduced display with less negative news."

[1063] The device sends the user's selection to the server as a POST request (output). Data is sent in JSON format.

[1064] Step 3: Save the user's selections to the database

[1065] The server receives the user's selection (input).

[1066] The server saves the selection in a database (e.g. MySQL or PostgreSQL), making the user's selection persistent.

[1067] Step 4: Get news data from the News API

[1068] The server sends an HTTP request to the News API (output), which includes parameters (e.g., category, region) in JSON format.

[1069] The server receives response data from the API (input), which includes the news article title, content, tags, publication date, etc.

[1070] Step 5: Send news data to your device

[1071] The server sends the received news data to the terminal. Here, news data in JSON format is used (input).

[1072] The terminal temporarily stores the received data.

[1073] Step 6: Analyze the news data and categorize it into positive and negative news

[1074] The device analyzes (inputs) the stored news data using natural language processing (NLP) models, such as BERT and GPT-4, to perform sentiment analysis of the text.

[1075] The device classifies news articles into positive and negative news (output). Each news item is assigned a sentiment score and the classification results are saved in JSON format.

[1076] Step 7: Filter the news data

[1077] The server filters (inputs) news data based on the display mode selected by the user. Filtering is performed based on the analysis results.

[1078] If the "Show only positive news" mode is selected, the server extracts only positive news and excludes negative news (output).

[1079] When the "Reduce Negative News and Display" mode is selected, the server reduces the duplication of negative news and performs representation transformations to soften the headlines and content (output).

[1080] Step 8: Generate a filtered news feed

[1081] The server generates a news feed to display to the user based on the filtered news data (input). The feed is generated using HTML or JSON format.

[1082] The generated news feed is sent to the terminal (output).

[1083] Step 9: View your filtered news feed

[1084] The terminal displays the received news feed to the user (input).

[1085] Users get information by looking at the news feed, which displays news appropriately based on the selected display mode, reducing mental strain (output).

[1086] (Application example 1)

[1087] 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."

[1088] In modern society, reading the news is a part of everyday life, but the mental burden caused by negative news has become a problem. While there is a demand for systems that allow users to comfortably view specific information, there is a lack of means to provide users with appropriately personalized information amid the advancement of information provision in virtual spaces and smart devices. The present invention aims to solve these problems and provide a system that allows users to obtain information without feeling any mental burden.

[1089] 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.

[1090] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for displaying the filtered news on the user's terminal, and means for displaying a news feed on a device that provides information to the user in a virtual space. This reduces the mental burden on the user when viewing news and enables the user to receive optimal information in a personalized form even within the virtual space.

[1091] "News display mode" is a setting option that allows the user to select the format in which news is displayed.

[1092] "News data" refers to information including the title, content, and metadata of a news article.

[1093] "Analysis" is the process of classifying acquired news data into positive and negative news using natural language processing models, etc.

[1094] "Positive news" is a news article that is judged to have positive content and to have a positive impact on users.

[1095] "Negative news" refers to news articles that are deemed to have negative content and have a negative impact on users.

[1096] "Filtering" is the process of selecting and adjusting news data based on the news display mode selected by the user.

[1097] A "user terminal" is a user's information device used to display a news feed.

[1098] A "virtual space" is a virtual area in which users can carry out various activities within a digital environment.

[1099] A "smart device" is an electronic device equipped with internet connectivity that can display and operate information in a virtual space.

[1100] A "news feed" is an information list that organizes filtered news data and displays it to the user.

[1101] "Representation transformation" is the process of softening the headline and content of a news article to reduce the mental burden on the user.

[1102] The present invention provides a system that reduces the mental burden placed on users when viewing news and allows them to obtain information in a comfortable manner. The system is configured as follows.

[1103] Select news display mode

[1104] When a user accesses a news site through a device, the server presents a choice of news display modes. A screen is displayed asking the user to select either "Display only positive news" or "Reduce negative news and display." When the user makes a selection, the selection information is sent to the server.

[1105] Acquiring news data

[1106] The server sends a request to the news API to retrieve the latest news data. This data includes metadata such as the title, content, and tags of the news article. For example, the server retrieves the data using NewsAPI (https: / / newsapi.org / ).

[1107] News data analysis

[1108] The server analyzes the acquired news data using a natural language processing model (e.g., Hugging Face's Transformers library). Based on the analysis results, the news articles are classified into positive news and negative news.

[1109] For example, a news headline such as "A new clothing line has been launched" would be classified as positive news, while a headline such as "Some products need improvement" would be classified as negative news.

[1110] News filtering

[1111] The server filters the news based on the news display mode selected by the user.

[1112] When "Show only good news" mode is selected:

[1113] The server extracts only positive news and filters out negative news.

[1114] When "Reduce Bad News" mode is selected:

[1115] The server reduces the duplication of negative news and performs wording transformation to soften headlines and content. Wording transformation is expected to have the effect of softening negative expressions.

[1116] Generate and display a filtered news feed

[1117] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the device. The user can view news according to the selected mode, allowing for convenient information acquisition.

[1118] Providing information in virtual space

[1119] This system has the ability to provide users with the most appropriate information even in virtual spaces. For example, it can display news, the latest information, product notifications, and more within a virtual store via a smart device. The information displayed is personalized based on the selected news display mode, reducing the user's mental burden.

[1120] Prompt Sentence Examples

[1121] "Classify your news data into positive and negative news. Analyze the following news headlines: 'A new clothing line has been launched', 'Some products need improvement'."

[1122] In this way, the system allows users to browse the news without feeling any mental strain, and also provides an optimal user experience, including information provision in a virtual space.

[1123] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1124] Step 1:

[1125] A user visits a news site and selects a viewing mode.

[1126] Input: A user visits a news site and is presented with a choice screen.

[1127] Behavior: The device presents the user with the option to "display only positive news" or "reduce negative news." The user selects one of these display modes.

[1128] Output: The user's selection is sent to the server.

[1129] Step 2:

[1130] The server retrieves news data

[1131] Input: User selections and request to News API.

[1132] How it works: The server uses a news API (e.g., NewsAPI) to retrieve the latest news data, including metadata such as title, content, and tags.

[1133] Output: The retrieved news data is stored on the server.

[1134] Step 3:

[1135] News data analysis

[1136] Input: Retrieved news data.

[1137] How it works: The server analyzes news data using Hugging Face's Transformers library. A natural language processing model classifies the news data into positive and negative news.

[1138] Output: Categorized news data. A list of positive and negative news is generated.

[1139] Step 4:

[1140] News filtering

[1141] Input: Categorized news data and user-selected news display mode.

[1142] How it works: The server filters based on the mode selected by the user.

[1143] In the positive news only display mode: Only positive news is extracted and negative news is removed.

[1144] In the "Reduce and lighten dark news" display mode: Reduces the duplication of negative news and performs wording transformations to soften headlines and content.

[1145] Output: Filtered news data.

[1146] Step 5:

[1147] Newsfeed generation and submission

[1148] Input: Filtered news data.

[1149] How it works: The server generates a news feed based on the filtered news data, and the generated feed is sent to the user's device.

[1150] Output: The news feed sent to the user's device.

[1151] Step 6:

[1152] Displaying news feeds on users' devices

[1153] Input: The news feed sent from the server.

[1154] How it works: The device displays the news feed to the user, who then browses the news according to the mode selected.

[1155] Output: The news feed displayed on the user's device.

[1156] Step 7:

[1157] Providing information in virtual space

[1158] Input: Filtered news data sent from the server.

[1159] How it works: Smart devices (e.g. smart glasses) display personalized news and notifications in a virtual space.

[1160] Output: Personalized news feed and notifications displayed on your smart device.

[1161] The above is the flow of processing steps from selecting the news display mode to providing information in the virtual space.

[1162] 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.

[1163] This invention provides a system that allows users to browse the news while maintaining their mental health. It combines a conventional news display system with an emotion engine that recognizes the user's emotions. This system realizes a series of steps from selecting the news display mode to emotion recognition, filtering the news, and displaying it.

[1164] A specific embodiment of this system is shown below.

[1165] 1. Select the news display mode

[1166] When a user accesses a news site, the device displays a news display mode selection screen, allowing the user to choose between "Display only positive news" or "Reduce negative news and display."

[1167] 2. Transmit and record the selected mode

[1168] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[1169] 3. Acquiring news data

[1170] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[1171] 4. News Data Analysis

[1172] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[1173] 5. News filtering

[1174] The server filters the news based on the display mode selected by the user.

[1175] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1176] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[1177] 6. Emotional Engine Adjustment

[1178] The present invention further includes an emotion engine that recognizes the user's emotions. The emotion engine includes the following three functions:

[1179] 1. Real-time recognition and assessment of user emotions:

[1180] The server uses an emotion engine to evaluate the user's emotions in real time based on their facial expressions, voice, input, etc. Based on this evaluation, the server adjusts the news display mode and content.

[1181] 2. Emotion history learning:

[1182] By recording the user's emotion history, the server uses a learning algorithm to predict future news display modes based on past data, and provides more relevant news based on this prediction.

[1183] 3. Adjust content based on emotions:

[1184] The emotion engine further adjusts the filtered news content based on the user's current emotions: for example, if the user is feeling stressed, it will increase the proportion of positive news and use more calming language.

[1185] 7. Generate and send the news feed to be displayed

[1186] The server generates a news feed based on the filtered and adjusted news data by the emotion engine, and the generated feed is tailored to the user's selected mode and current emotional state.

[1187] 8. Viewing News Feeds

[1188] The terminal displays the received news feed to the user, who can browse the news feed on the terminal and obtain news according to the selected mode and current emotional state efficiently and mentally at ease.

[1189] Specific examples

[1190] Example 1: When the user selects the "Show only good news" mode

[1191] A user visits a news site and selects "Show only positive news."

[1192] The server receives this selection and retrieves the data from the news API.

[1193] The device analyzes news data and categorizes it into positive and negative news.

[1194] The server extracts only positive news and generates a filtered feed.

[1195] The emotion engine evaluates the user's emotions and enriches news that contains particularly gentle expressions.

[1196] The server sends the generated feed to the device.

[1197] The device displays only positive news, allowing users to obtain information without mental stress.

[1198] Example 2: When the user selects the "Reduce Negative News" mode

[1199] A user accesses a news site and selects "Reduce and minimize negative news."

[1200] The server receives this selection and retrieves the data from the news API.

[1201] The device analyzes news data and categorizes it into positive and negative news.

[1202] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[1203] The emotion engine assesses the user's emotions and further tailors the news content displayed based on that state.

[1204] The server generates a filtered feed and sends it to the device.

[1205] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[1206] In this way, the system takes into account the user's emotional state and provides an efficient and safe environment for browsing news according to the selected display mode.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[1210] Step 2:

[1211] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode for use in subsequent processing.

[1212] Step 3:

[1213] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[1214] Step 4:

[1215] The server analyzes the acquired news data using AI (such as natural language processing models), and the news data is classified into positive news and negative news.

[1216] Step 5:

[1217] The server filters the news based on the display mode selected by the user.

[1218] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1219] When the "Reduce and lighten the display of negative news" mode is selected, the server reduces the duplication of negative news, places it in a less important position, and performs wording transformations to soften the headlines and content.

[1220] Step 6:

[1221] The server uses an emotion engine to recognize the user's current emotional state, collecting data such as the user's facial expressions, voice, and input from the device, and evaluating the user's emotions in real time.

[1222] Step 7:

[1223] The server adjusts the news display mode and content based on the emotional information acquired by the emotion engine. For example, if the user is assessed as feeling stressed, the server increases the proportion of positive news.

[1224] Step 8:

[1225] The emotion engine learns the user's past emotion history, and the server predicts future news display modes based on this and provides news based on the prediction.

[1226] Step 9:

[1227] The server generates a news feed based on the filtered news data, and ensures that the feed is in accordance with the user's selected mode and sentiment rating.

[1228] Step 10:

[1229] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[1230] Step 11:

[1231] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[1232] Example 2

[1233] 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."

[1234] Conventional news display systems simply display news as is and do not consider the user's emotional state, which can cause mental strain. Displaying a large amount of negative news, in particular, can have a negative impact on the user's mental health. Furthermore, systems that adjust news display based on the user's emotions have not yet been fully implemented. The present invention aims to provide an environment in which users can browse the news with peace of mind.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1236] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results, means for generating a news feed based on the filtering and emotion recognition, means for transmitting the generated news feed to the user's terminal, means for readjusting the news feed based on the feedback, and means for displaying the filtered news on the user's terminal, thereby enabling the user to browse the news with peace of mind without feeling any mental burden.

[1237] The "means for accepting selection of a news display mode" is a means having a function of providing an interface that allows a user to select a news display mode and transmitting the selection to a server.

[1238] "Means for acquiring news data" refers to a means by which the server has the function of acquiring the latest news article data from an external news API.

[1239] "Means for analyzing news data and classifying it into positive and negative news" refers to a means that uses AI technology such as natural language processing models to analyze acquired news article data and classify it into positive and negative content.

[1240] The "means for filtering news" is a means having a function for selecting news to be displayed based on the news display mode selected by the user and the analysis results.

[1241] "Means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results" refers to a means that uses an emotion engine to analyze the user's facial expressions, voice, input content, etc. in real time, and adjusts the content and display method of the news based on the results.

[1242] The "means for generating a news feed based on filtering and emotion recognition" is a means having a function for generating an optimal news feed for a user based on filtered news and the user's emotion evaluation results.

[1243] The "means for transmitting the generated news feed to the user's terminal" refers to a means having a function for transmitting the news feed generated by the server to the user's terminal using a communication means.

[1244] The "means for readjusting a news feed based on feedback" refers to a means having a function for readjusting the content and display method of a news feed based on feedback information from a user.

[1245] The "means for displaying filtered news on a user's terminal" refers to a means having a function for displaying the final filtered news feed on a user's terminal so that the user can view it.

[1246] The present invention provides a system for selecting a news display mode, acquiring, analyzing, filtering, and recognizing emotions in news data, and generating and displaying a news feed, all of which are performed to enable users to browse news without feeling any mental strain.

[1247] Hardware and software used

[1248] Hardware

[1249] Terminal: A device operated by a user. Examples include computers, smartphones, and tablets.

[1250] Server: A computer system responsible for processing and storing data.

[1251] Emotion recognition devices: Devices such as cameras and microphones that capture the user's facial expressions and voice.

[1252] software

[1253] News API: API for obtaining external news data.

[1254] Natural language processing model (NLP model): An AI model for analyzing news data and classifying it into positive and negative news. Examples include BERT and GPT.

[1255] Emotion engine: Software for analyzing the user's emotional state in real time.

[1256] Filtering Algorithm: The algorithm for filtering the news data.

[1257] System Overview

[1258] Select news display mode

[1259] When a user accesses a news site, the device displays a news display mode selection screen, where the user can choose between "Display only positive news" or "Reduce negative news and display."

[1260] Mode transmission and recording

[1261] The terminal transmits information about the mode selected by the user to the server, which records this selection information in a database.

[1262] Acquiring news data

[1263] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news articles.

[1264] News analysis and classification

[1265] The server analyzes the news data using a natural language processing model and classifies articles into positive and negative news.

[1266] News filtering

[1267] The server filters news based on the mode selected by the user: "Show only positive news" mode extracts only positive news, while "Reduce and lighten negative news" mode reduces the overlap of negative news and softens the headlines.

[1268] Emotional engine regulation

[1269] The server uses an emotion engine to recognize the user's emotional state in real time and adjusts the news content displayed based on the evaluation, which may include increasing the proportion of positive news or converting the news content to a more gentle expression.

[1270] Newsfeed generation and submission

[1271] Based on the filtering and emotion recognition, the server generates a news feed and sends the news feed to the user's terminal.

[1272] Viewing the news feed

[1273] The device displays the received news feed to the user, allowing the user to comfortably browse news according to the selected mode and emotional state.

[1274] Specific examples

[1275] Example 1: When the user selects the "Show only good news" mode

[1276] The user selects the "Show only positive news" mode on their device.

[1277] The server receives this information and retrieves the latest news from the news API.

[1278] The server analyzes the news data using a natural language processing model and extracts only positive news.

[1279] The emotion engine assesses the user's emotions and adjusts the news content to be particularly gentle.

[1280] The server generates the final news feed and sends it to the device.

[1281] The device displays positive news, allowing users to obtain information without mental strain.

[1282] Example 2: When the user selects the "Reduce Negative News" mode

[1283] The user selects the "Reduce negative news and display" mode on the device.

[1284] The server receives this information and retrieves the latest news from the news API.

[1285] The server analyzes the news data using a natural language processing model and extracts negative news.

[1286] The server reduces duplicate negative news and transforms it to soften the headlines.

[1287] The emotion engine evaluates the user's emotions and further adjusts the displayed content.

[1288] The server sends the filtered news feed to the terminal.

[1289] The device displays negative news in a reduced manner, allowing users to obtain important information with peace of mind.

[1290] Example prompt sentence:

[1291] "Show us the latest news and filter it to positive news."

[1292] "Please reduce the negative news and present softened headlines."

[1293] In this way, the system provides a safe news viewing environment based on the user's emotional state and the selected display mode.

[1294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1295] Step 1: Select the news display mode

[1296] Input: The user accesses a news site on their device.

[1297] Processing: The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news and display."

[1298] Output: The news display mode selected by the user.

[1299] Specific operation: Display options on the device screen using radio buttons or a drop-down menu, and allow the user to select one.

[1300] Step 2: Send and record the selected mode

[1301] Input: The news display mode selected by the user.

[1302] Processing: The terminal sends the selected mode to the server, which receives this information and records it in a database.

[1303] Output: Selected mode recorded data.

[1304] Specific operation: The terminal sends an HTTP request to the server, and the server receives the request and stores it in a database.

[1305] Step 3: Getting news data

[1306] Input: The server sends a request to retrieve news data.

[1307] Processing: The server sends a request to an external news API to get the latest news data. The data is received in JSON format.

[1308] Output: The retrieved news data.

[1309] Specific operation: The server sends an HTTP request to the news API and parses the returned JSON data to extract the title, content, tags, etc. of the news article.

[1310] Step 4: News analysis and classification

[1311] Input: Retrieved news data.

[1312] Processing: The server analyzes the news data using natural language processing models (e.g., BERT, GPT) and classifies each article into positive or negative news.

[1313] Output: Data categorized into positive and negative news.

[1314] Specific operation: A news article is input into a natural language processing model, and positive and negative scores are obtained and classified.

[1315] Step 5: Filtering the news

[1316] Input: Categorized news data, user selection mode.

[1317] Processing: The server filters the news based on the selection mode.

[1318] "Show only positive news" mode: Extracts only positive news.

[1319] "Reduce and soften negative news" mode: Reduces overlapping negative news and softens headlines.

[1320] Output: Filtered news data.

[1321] What it does: It uses algorithms to reprocess news and extract or edit the articles you want.

[1322] Step 6: Emotional Engine Alignment

[1323] Input: User's emotional information (facial expression, voice, input content), filtered news data.

[1324] Processing: The server uses an emotion engine to recognize the user's emotions in real time and adjusts the news content displayed based on the evaluation results.

[1325] Output: Adjusted news data.

[1326] Specific operation: Data is collected in real time from cameras and microphones, analyzed using emotion recognition algorithms, and the news data is adjusted based on the evaluation results.

[1327] Step 7: Generate and submit your news feed

[1328] Input: Adjusted news data.

[1329] Processing: The server generates the final news feed and sends it to the device.

[1330] Output: The generated news feed.

[1331] Specific operation: The news feed is packaged in HTML or JSON format and sent to the terminal as an HTTP response.

[1332] Step 8: View your news feed

[1333] Input: Received news feed.

[1334] Processing: The device displays the received news feed.

[1335] Output: The news feed displayed to the user.

[1336] What happens: The device's web browser renders the news feed and displays it on the screen.

[1337] The above are the specific steps of the program processing of this system.

[1338] (Application example 2)

[1339] 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."

[1340] In modern society, people are exposed to an enormous amount of information, often including negative news and stressful information. This has a serious impact on mental health. Furthermore, physical stores are not yet providing services that take into account the emotional state of customers, making improving customer satisfaction a key challenge. Therefore, there is a need for the development of a system that can recognize the emotional state of users and customers in real time and provide appropriate information based on that information.

[1341] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1342] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing and adjusting the user's emotional state in real time, means for further adjusting the news display content based on the felt emotions, means for learning past emotional data and predicting future news display modes, means for adjusting product information and promotions offered in stores according to the customer's emotional state, and means for displaying the filtered and adjusted news and product information on the user's or customer's terminal. This makes it possible to provide appropriate information while maintaining the mental health of the user or customer.

[1343] "News display mode" refers to a setting that a user selects when viewing news, and is used to tailor the news content to the user's preferences and emotional state.

[1344] "News data" refers to data containing the latest news article information, including titles, contents, tags, and other information.

[1345] "Emotion recognition" is a technology that analyzes a user's facial expressions, voice, input content, etc. to evaluate their current emotional state.

[1346] "Filtering" refers to the process of sorting acquired news data based on the mode selected by the user and adjusting the displayed content.

[1347] "Emotion history learning" is a technology that records and analyzes a user's past emotional data to predict future news display modes and information content.

[1348] "Adjusting the news display content" refers to the process of changing the news headline or content to a more toned-down expression based on the emotion recognition results, thereby changing the content to suit the user's emotional state.

[1349] "Promotion" means a marketing activity designed to inform customers about a particular product or service and encourage their purchase or use.

[1350] "Emotion-based product recommendation" is a technology that assesses a customer's current emotional state and provides them with product information and promotions accordingly.

[1351] This invention is a system that recognizes the emotional state of users and customers in real time and provides appropriate information and promotions based on that. This system can be used on news sites and in brick-and-mortar stores.

[1352] System Program

[1353] This system includes a user terminal, a server, and an emotion recognition engine. Specific examples of hardware and software include the following:

[1354] User devices: Tablet devices and smart employee robots

[1355] Server: Cloud server

[1356] Emotion recognition engine: Emotion API

[1357] News API: API to get the latest news data

[1358] Recommender system: A system that recommends product information and news

[1359] Program processing explanation

[1360] When a user uses a tablet device on a news site or in a physical store, the system works as follows:

[1361] 1. Emotion Recognition: Using the device's built-in camera and microphone, the Emotion API analyzes the user's emotions in real time, evaluating the customer's facial expressions and tone of voice to detect their current emotional state.

[1362] 2. Mode selection: When a user selects a news display mode, the selection and emotional state are sent to the server. News display modes include "display only positive news" and "reduced display of negative news." In physical stores, there are modes for "relaxing products" and "energetic products."

[1363] 3. Data Acquisition and Analysis: The server acquires the latest news data through the news API, analyzes the news data using AI and classifies it into positive news and negative news. Similarly, it uses the recommender system to acquire product information for physical stores.

[1364] 4. Filtering and Adjustment: Filter and adjust news and product information based on the user's selected mode and emotion recognition results. For example, for a user who is feeling stressed, increase positive news or recommend relaxing products.

[1365] 5. Display: Display tailored news and product information on the user's device. Users can browse their news feed and see recommended product information on their device.

[1366] Specific examples

[1367] As an example, the system processing when a customer selects the "Relaxing Products" mode using a tablet device and the Emotion API detects that the customer is feeling "stressed" is shown below.

[1368] 1. The customer's feelings are recognized as stress.

[1369] 2. The server filters information about products that have a relaxing effect based on the settings in the "Relaxing Products" mode.

[1370] 3. The filtered product information is displayed on the customer's tablet device.

[1371] Example prompts for generative AI models

[1372] Prompt: "Suggest relaxing products to customers who are feeling stressed. Generate a list of recommended products based on the following emotional data: Emotion Data: {'Emotion': 'Stress', 'Intensity': 'High'}"

[1373] In this way, it is possible to provide information and promotions tailored to the individual emotional state of the user or customer while maintaining their mental health.

[1374] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1375] Step 1:

[1376] The user selects a news display mode from the terminal. For example, the user may select "display only positive news" or "reduce negative news and display." This selection information is sent to the server. The input is the mode information selected by the user, and the output is the transmission of this information to the server.

[1377] Step 2:

[1378] Emotion recognition is performed in real time via the camera and microphone installed on the user's device. The device uses the Emotion API to analyze the user's facial expressions and voice to evaluate their emotional state. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[1379] Step 3:

[1380] The data of the news display mode selected by the user and the recognized emotional state are sent to the server. The input is the user's selected mode information and emotional state, and the output is the transmission of this information to the server.

[1381] Step 4:

[1382] The server retrieves the latest news data via the news API. The input is a request to the news API, and the output is the retrieved news data. The news data includes information such as title, content, and tags.

[1383] Step 5:

[1384] The server uses AI to analyze the acquired news data and classify it into positive news and negative news. The input is news data, and the output is data classified into positive news and negative news.

[1385] Step 6:

[1386] The server filters news based on the user's selected mode and the recognized emotional state. The input is the user's selected mode, emotional state, and classified news data, and the output is the filtered news data. For example, in the "Show only positive news" mode, only positive news is extracted.

[1387] Step 7:

[1388] The filtered news data is further adjusted based on the emotion recognition results. The server converts the displayed content to soften it according to the user's current emotional state. The input is the filtered news data and the emotion recognition results, and the output is the adjusted news data.

[1389] Step 8:

[1390] The server sends the filtered and adjusted news data to the user terminal, where the input is the adjusted news data and the output is the transmission of the news data to the user terminal.

[1391] Step 9:

[1392] The user terminal displays the received news data. The input is the news data sent from the server, and the output is the display of the news feed. The user can view the news feed on the terminal.

[1393] 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.

[1394] 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.

[1395] 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.

[1396] [Fourth embodiment]

[1397] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1398] 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.

[1399] 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).

[1400] 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.

[1401] 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.

[1402] 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).

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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."

[1410] The present invention provides a system that reduces the mental burden on users when viewing news and allows them to obtain information more comfortably. This system performs a series of processes: news display mode selection, news data acquisition, analysis, filtering, and display.

[1411] A specific embodiment of this system is shown below.

[1412] 1. Accept the user's selection

[1413] When a user accesses a news site, the device presents a choice of news display modes: "Display only positive news" or "Reduce negative news and display only negative news."

[1414] 2. Data processing according to the selected mode

[1415] The server receives the user's selections and begins the process of generating a news feed based on the selections.

[1416] 3. Acquiring news data

[1417] The server sends a request to the news API to retrieve the latest news data, including metadata such as the title, content, and tags of the news article.

[1418] 4. News Data Analysis

[1419] The device analyzes the acquired news data using AI (natural language processing models, etc.), and the analysis categorizes the news data into positive and negative news.

[1420] 5. News filtering

[1421] The server filters the news based on the news display mode selected by the user.

[1422] When "Show only good news" mode is selected:

[1423] The server extracts only positive news and filters out negative news.

[1424] When "Reduce Bad News" mode is selected:

[1425] The server reduces the duplication of negative news and places it in a less important position.

[1426] Implement wording changes to soften headlines and content.

[1427] 6. Generate and send the news feed to be displayed

[1428] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the terminal.

[1429] 7. Viewing News Feeds

[1430] The device displays the received news feed to the user, who can then browse the news according to the selected mode and efficiently obtain the information they need.

[1431] Specific examples

[1432] Example 1: When the user selects the "Show only good news" mode

[1433] A user visits a news site and selects "Show only positive news."

[1434] The server receives this selection and retrieves the data from the news API.

[1435] The device analyzes news data and categorizes it into positive and negative news.

[1436] The server extracts only positive news and generates a filtered feed.

[1437] The server sends the generated feed to the device.

[1438] The device displays only positive news, allowing users to obtain information without mental stress.

[1439] Example 2: When the user selects the "Reduce Negative News" mode

[1440] A user accesses a news site and selects "Reduce and minimize negative news."

[1441] The server receives this selection and retrieves the data from the news API.

[1442] The device analyzes news data and categorizes it into positive and negative news.

[1443] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[1444] The server generates a filtered feed and sends it to the device.

[1445] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[1446] In this way, the system provides an environment in which the user can efficiently and mentally read the news in accordance with the display mode selected by the user.

[1447] The processing flow will be explained below.

[1448] Step 1:

[1449] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[1450] Step 2:

[1451] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[1452] Step 3:

[1453] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[1454] Step 4:

[1455] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[1456] Step 5:

[1457] The server filters the news based on the display mode selected by the user.

[1458] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1459] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[1460] Step 6:

[1461] The server generates a news feed based on the filtered news data, and the feed content depends on the mode selected by the user.

[1462] Step 7:

[1463] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[1464] Step 8:

[1465] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[1466] Example 1

[1467] 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."

[1468] In conventional news viewing systems, users may feel a mental burden depending on the content of the news they view. In particular, when a lot of negative news is displayed, users may feel anxious or stressed. In response to this, there is a need for a means to adjust the news content according to the user's desired display mode and reduce the mental burden.

[1469] 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.

[1470] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for acquiring data from a news API, means for analyzing the news data using a natural language processing model, means for generating a news feed and transmitting it to the user's terminal, and means for displaying the filtered news. This allows the user to view news filtered based on the desired news display mode, thereby reducing mental strain.

[1471] A "user" is an entity that uses the system to view news.

[1472] "News display mode" is an option that allows the user to select the type of news to view and the display method.

[1473] "News data" is a collection of information about news, such as the title, content, tags, and publication date of a news article.

[1474] "Positive news" is news that has been classified as positive or optimistic through sentiment analysis of news data.

[1475] "Negative news" is news that has been classified as negative or pessimistic through sentiment analysis of news data.

[1476] "Filtering" is the process of selecting and organizing news data based on the news display mode selected by the user.

[1477] A "News API" is an interface for accessing external news data providers and obtaining news data.

[1478] A "natural language processing model" is an algorithm or software that uses artificial intelligence techniques to analyze and classify text.

[1479] A "news feed" is a filtered list of news articles displayed to a user.

[1480] A "terminal" is a hardware device (e.g., a smartphone, tablet, or PC) that a user uses to access a news site and view a news feed.

[1481] The present invention provides a news viewing system that aims to reduce the mental burden on users when viewing news by presenting them with a choice of news display modes, acquiring, analyzing, and filtering news data according to the selected mode, and ultimately displaying a news feed appropriate for the user.

[1482] composition

[1483] This system operates using a server, terminals, news APIs, and natural language processing (NLP) models. The specific hardware and software configuration is shown below.

[1484] 1. Server:

[1485] The server receives the user's selected display mode, retrieves, analyzes, filters, and generates a feed of news data.

[1486] Technologies used include web frameworks (e.g., Spring Boot, Django) and database systems (e.g., MySQL, PostgreSQL).

[1487] 2. Terminal:

[1488] The terminal accepts the user's selection, presents display mode options, and displays the filtered news feed.

[1489] The devices used include various user devices such as PCs, tablets, and smartphones.

[1490] 3. News API:

[1491] This is an interface for external services used to obtain news data. For example, it uses services that provide news data (e.g., Google News API, NewsAPI.org).

[1492] 4. Natural Language Processing Models (NLP Models):

[1493] It is an AI technology used to analyze news data and analyze the sentiment of text. Specific examples include models such as BERT and GPT-4.

[1494] This technology runs on machine learning frameworks such as TensorFlow and PyTorch.

[1495] Processing flow

[1496] When a user accesses a news site, the device presents a choice of news display modes. After the user selects a display mode, the device sends that information to the server. The server then sends a request to the news API to retrieve the latest news data. The retrieved news data is then analyzed on the device using an NLP model to classify it into positive and negative news.

[1497] The server filters the news based on the user's selection, generates a news feed, and sends it to the device. The device displays the filtered news feed to the user, allowing the user to view news according to the selected mode. This series of processes allows the user to efficiently obtain the information they need while reducing their mental burden.

[1498] Specific examples

[1499] Example 1: "Show only good news" mode

[1500] 1. A user visits a news site and selects "Show only positive news."

[1501] 2. The device sends the user's selection to the server.

[1502] 3. The server receives this selection and retrieves the news data from the news API.

[1503] 4. The device analyzes the news data and classifies it into positive and negative news.

[1504] 5. The server extracts only positive news and generates a news feed.

[1505] 6. The server sends the generated feed to the device, which displays only positive news.

[1506] Example 2: "Reduce negative news and display" mode

[1507] 1. A user visits a news site and selects "Reduce and minimize negative news."

[1508] 2. The device sends the user's selection to the server.

[1509] 3. The server receives this selection and retrieves the news data from the news API.

[1510] 4. The device analyzes the news data and classifies it into positive and negative news.

[1511] 5. The server reduces duplicate negative news and transforms it to soften the headline and content.

[1512] 6. The server generates a news feed and sends it to the device.

[1513] 7. The device will display negative news in a reduced volume, helping users reduce their mental burden.

[1514] In this way, the system provides an environment in which the user can efficiently and mentally read the news according to the display mode selected by the user.

[1515] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1516] Step 1: User visits a news site and selects a viewing mode

[1517] A user accesses a news site using a web browser or a dedicated app. The input is the user's access behavior.

[1518] The device presents a news display mode option ("Show only positive news" or "Show less negative news"), which is displayed as HTML or in the app's UI, allowing the user to click on the option.

[1519] Step 2: Receive the user's choice and send it to the server

[1520] The user selects one of the display modes. The selected mode (input) is either "display only positive news" or "reduced display with less negative news."

[1521] The device sends the user's selection to the server as a POST request (output). Data is sent in JSON format.

[1522] Step 3: Save the user's selections to the database

[1523] The server receives the user's selection (input).

[1524] The server saves the selection in a database (e.g. MySQL or PostgreSQL), making the user's selection persistent.

[1525] Step 4: Get news data from the News API

[1526] The server sends an HTTP request to the News API (output), which includes parameters (e.g., category, region) in JSON format.

[1527] The server receives response data from the API (input), which includes the news article title, content, tags, publication date, etc.

[1528] Step 5: Send news data to your device

[1529] The server sends the received news data to the terminal. Here, news data in JSON format is used (input).

[1530] The terminal temporarily stores the received data.

[1531] Step 6: Analyze the news data and categorize it into positive and negative news

[1532] The device analyzes (inputs) the stored news data using natural language processing (NLP) models, such as BERT and GPT-4, to perform sentiment analysis of the text.

[1533] The device classifies news articles into positive and negative news (output). Each news item is assigned a sentiment score and the classification results are saved in JSON format.

[1534] Step 7: Filter the news data

[1535] The server filters (inputs) news data based on the display mode selected by the user. Filtering is performed based on the analysis results.

[1536] If the "Show only positive news" mode is selected, the server extracts only positive news and excludes negative news (output).

[1537] When the "Reduce Negative News and Display" mode is selected, the server reduces the duplication of negative news and performs representation transformations to soften the headlines and content (output).

[1538] Step 8: Generate a filtered news feed

[1539] The server generates a news feed to display to the user based on the filtered news data (input). The feed is generated using HTML or JSON format.

[1540] The generated news feed is sent to the terminal (output).

[1541] Step 9: View your filtered news feed

[1542] The terminal displays the received news feed to the user (input).

[1543] Users get information by looking at the news feed, which displays news appropriately based on the selected display mode, reducing mental strain (output).

[1544] (Application example 1)

[1545] 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."

[1546] In modern society, reading the news is a part of everyday life, but the mental burden caused by negative news has become a problem. While there is a demand for systems that allow users to comfortably view specific information, there is a lack of means to provide users with appropriately personalized information amid the advancement of information provision in virtual spaces and smart devices. The present invention aims to solve these problems and provide a system that allows users to obtain information without feeling any mental burden.

[1547] 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.

[1548] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for displaying the filtered news on the user's terminal, and means for displaying a news feed on a device that provides information to the user in a virtual space. This reduces the mental burden on the user when viewing news and enables the user to receive optimal information in a personalized form even within the virtual space.

[1549] "News display mode" is a setting option that allows the user to select the format in which news is displayed.

[1550] "News data" refers to information including the title, content, and metadata of a news article.

[1551] "Analysis" is the process of classifying acquired news data into positive and negative news using natural language processing models, etc.

[1552] "Positive news" is a news article that is judged to have positive content and to have a positive impact on users.

[1553] "Negative news" refers to news articles that are deemed to have negative content and have a negative impact on users.

[1554] "Filtering" is the process of selecting and adjusting news data based on the news display mode selected by the user.

[1555] A "user terminal" is a user's information device used to display a news feed.

[1556] A "virtual space" is a virtual area in which users can carry out various activities within a digital environment.

[1557] A "smart device" is an electronic device equipped with internet connectivity that can display and operate information in a virtual space.

[1558] A "news feed" is an information list that organizes filtered news data and displays it to the user.

[1559] "Representation transformation" is the process of softening the headline and content of a news article to reduce the mental burden on the user.

[1560] The present invention provides a system that reduces the mental burden placed on users when viewing news and allows them to obtain information in a comfortable manner. The system is configured as follows.

[1561] Select news display mode

[1562] When a user accesses a news site through a device, the server presents a choice of news display modes. A screen is displayed asking the user to select either "Display only positive news" or "Reduce negative news and display." When the user makes a selection, the selection information is sent to the server.

[1563] Acquiring news data

[1564] The server sends a request to the news API to retrieve the latest news data. This data includes metadata such as the title, content, and tags of the news article. For example, the server retrieves the data using NewsAPI (https: / / newsapi.org / ).

[1565] News data analysis

[1566] The server analyzes the acquired news data using a natural language processing model (e.g., Hugging Face's Transformers library). Based on the analysis results, the news articles are classified into positive news and negative news.

[1567] For example, a news headline such as "A new clothing line has been launched" would be classified as positive news, while a headline such as "Some products need improvement" would be classified as negative news.

[1568] News filtering

[1569] The server filters the news based on the news display mode selected by the user.

[1570] When "Show only good news" mode is selected:

[1571] The server extracts only positive news and filters out negative news.

[1572] When "Reduce Bad News" mode is selected:

[1573] The server reduces the duplication of negative news and performs wording transformation to soften headlines and content. Wording transformation is expected to have the effect of softening negative expressions.

[1574] Generate and display a filtered news feed

[1575] The server generates a news feed to be displayed to the user based on the filtered news data and sends it to the device. The user can view news according to the selected mode, allowing for convenient information acquisition.

[1576] Providing information in virtual space

[1577] This system has the ability to provide users with the most appropriate information even in virtual spaces. For example, it can display news, the latest information, product notifications, and more within a virtual store via a smart device. The information displayed is personalized based on the selected news display mode, reducing the user's mental burden.

[1578] Prompt Sentence Examples

[1579] "Classify your news data into positive and negative news. Analyze the following news headlines: 'A new clothing line has been launched', 'Some products need improvement'."

[1580] In this way, the system allows users to browse the news without feeling any mental strain, and also provides an optimal user experience, including information provision in a virtual space.

[1581] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1582] Step 1:

[1583] A user visits a news site and selects a viewing mode.

[1584] Input: A user visits a news site and is presented with a choice screen.

[1585] Behavior: The device presents the user with the option to "display only positive news" or "reduce negative news." The user selects one of these display modes.

[1586] Output: The user's selection is sent to the server.

[1587] Step 2:

[1588] The server retrieves news data

[1589] Input: User selections and request to News API.

[1590] How it works: The server uses a news API (e.g., NewsAPI) to retrieve the latest news data, including metadata such as title, content, and tags.

[1591] Output: The retrieved news data is stored on the server.

[1592] Step 3:

[1593] News data analysis

[1594] Input: Retrieved news data.

[1595] How it works: The server analyzes news data using Hugging Face's Transformers library. A natural language processing model classifies the news data into positive and negative news.

[1596] Output: Categorized news data. A list of positive and negative news is generated.

[1597] Step 4:

[1598] News filtering

[1599] Input: Categorized news data and user-selected news display mode.

[1600] How it works: The server filters based on the mode selected by the user.

[1601] In the positive news only display mode: Only positive news is extracted and negative news is removed.

[1602] In the "Reduce and lighten dark news" display mode: Reduces the duplication of negative news and performs wording transformations to soften headlines and content.

[1603] Output: Filtered news data.

[1604] Step 5:

[1605] Newsfeed generation and submission

[1606] Input: Filtered news data.

[1607] How it works: The server generates a news feed based on the filtered news data, and the generated feed is sent to the user's device.

[1608] Output: The news feed sent to the user's device.

[1609] Step 6:

[1610] Displaying news feeds on users' devices

[1611] Input: The news feed sent from the server.

[1612] How it works: The device displays the news feed to the user, who then browses the news according to the mode selected.

[1613] Output: The news feed displayed on the user's device.

[1614] Step 7:

[1615] Providing information in virtual space

[1616] Input: Filtered news data sent from the server.

[1617] How it works: Smart devices (e.g. smart glasses) display personalized news and notifications in a virtual space.

[1618] Output: Personalized news feed and notifications displayed on your smart device.

[1619] The above is the flow of processing steps from selecting the news display mode to providing information in the virtual space.

[1620] 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.

[1621] This invention provides a system that allows users to browse the news while maintaining their mental health. It combines a conventional news display system with an emotion engine that recognizes the user's emotions. This system realizes a series of steps from selecting the news display mode to emotion recognition, filtering the news, and displaying it.

[1622] A specific embodiment of this system is shown below.

[1623] 1. Select the news display mode

[1624] When a user accesses a news site, the device displays a news display mode selection screen, allowing the user to choose between "Display only positive news" or "Reduce negative news and display."

[1625] 2. Transmit and record the selected mode

[1626] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode.

[1627] 3. Acquiring news data

[1628] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[1629] 4. News Data Analysis

[1630] The server analyzes the acquired news data using AI (such as natural language processing models), which categorizes the news data into positive and negative news.

[1631] 5. News filtering

[1632] The server filters the news based on the display mode selected by the user.

[1633] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1634] When the "Reduce Negative News" mode is selected, the server reduces the number of negative news items and places them in a lower-priority position. It also performs wording conversion to soften the headlines and content.

[1635] 6. Emotional Engine Adjustment

[1636] The present invention further includes an emotion engine that recognizes the user's emotions. The emotion engine includes the following three functions:

[1637] 1. Real-time recognition and assessment of user emotions:

[1638] The server uses an emotion engine to evaluate the user's emotions in real time based on their facial expressions, voice, input, etc. Based on this evaluation, the server adjusts the news display mode and content.

[1639] 2. Emotion history learning:

[1640] By recording the user's emotion history, the server uses a learning algorithm to predict future news display modes based on past data, and provides more relevant news based on this prediction.

[1641] 3. Adjust content based on emotions:

[1642] The emotion engine further adjusts the filtered news content based on the user's current emotions: for example, if the user is feeling stressed, it will increase the proportion of positive news and use more calming language.

[1643] 7. Generate and send the news feed to be displayed

[1644] The server generates a news feed based on the filtered and adjusted news data by the emotion engine, and the generated feed is tailored to the user's selected mode and current emotional state.

[1645] 8. Viewing News Feeds

[1646] The terminal displays the received news feed to the user, who can browse the news feed on the terminal and obtain news according to the selected mode and current emotional state efficiently and mentally at ease.

[1647] Specific examples

[1648] Example 1: When the user selects the "Show only good news" mode

[1649] A user visits a news site and selects "Show only positive news."

[1650] The server receives this selection and retrieves the data from the news API.

[1651] The device analyzes news data and categorizes it into positive and negative news.

[1652] The server extracts only positive news and generates a filtered feed.

[1653] The emotion engine evaluates the user's emotions and enriches news that contains particularly gentle expressions.

[1654] The server sends the generated feed to the device.

[1655] The device displays only positive news, allowing users to obtain information without mental stress.

[1656] Example 2: When the user selects the "Reduce Negative News" mode

[1657] A user accesses a news site and selects "Reduce and minimize negative news."

[1658] The server receives this selection and retrieves the data from the news API.

[1659] The device analyzes news data and categorizes it into positive and negative news.

[1660] The server reduces duplication of negative news and performs wording transformations to soften headlines and content.

[1661] The emotion engine assesses the user's emotions and further tailors the news content displayed based on that state.

[1662] The server generates a filtered feed and sends it to the device.

[1663] The device displays negative news in a reduced volume, allowing users to obtain important information while reducing mental stress.

[1664] In this way, the system takes into account the user's emotional state and provides an efficient and safe environment for browsing news according to the selected display mode.

[1665] The processing flow will be explained below.

[1666] Step 1:

[1667] A user accesses a news site. The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news."

[1668] Step 2:

[1669] The terminal transmits information about the news display mode selected by the user to the server, and the server records the received information about the selected mode for use in subsequent processing.

[1670] Step 3:

[1671] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news article.

[1672] Step 4:

[1673] The server analyzes the acquired news data using AI (such as natural language processing models), and the news data is classified into positive news and negative news.

[1674] Step 5:

[1675] The server filters the news based on the display mode selected by the user.

[1676] If the "Show only positive news" mode is selected, the server will extract only positive news and filter out negative news.

[1677] When the "Reduce and lighten the display of negative news" mode is selected, the server reduces the duplication of negative news, places it in a less important position, and performs wording transformations to soften the headlines and content.

[1678] Step 6:

[1679] The server uses an emotion engine to recognize the user's current emotional state, collecting data such as the user's facial expressions, voice, and input from the device, and evaluating the user's emotions in real time.

[1680] Step 7:

[1681] The server adjusts the news display mode and content based on the emotional information acquired by the emotion engine. For example, if the user is assessed as feeling stressed, the server increases the proportion of positive news.

[1682] Step 8:

[1683] The emotion engine learns the user's past emotion history, and the server predicts future news display modes based on this and provides news based on the prediction.

[1684] Step 9:

[1685] The server generates a news feed based on the filtered news data, and ensures that the feed is in accordance with the user's selected mode and sentiment rating.

[1686] Step 10:

[1687] The server sends the generated news feed to the terminal, which then displays the received news feed to the user.

[1688] Step 11:

[1689] Users can browse the news feed on their devices and obtain news according to the selected mode efficiently and with peace of mind.

[1690] Example 2

[1691] 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."

[1692] Conventional news display systems simply display news as is and do not consider the user's emotional state, which can cause mental strain. Displaying a large amount of negative news, in particular, can have a negative impact on the user's mental health. Furthermore, systems that adjust news display based on the user's emotions have not yet been fully implemented. The present invention aims to provide an environment in which users can browse the news with peace of mind.

[1693] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1694] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results, means for generating a news feed based on the filtering and emotion recognition, means for transmitting the generated news feed to the user's terminal, means for readjusting the news feed based on the feedback, and means for displaying the filtered news on the user's terminal, thereby enabling the user to browse the news with peace of mind without feeling any mental burden.

[1695] The "means for accepting selection of a news display mode" is a means having a function of providing an interface that allows a user to select a news display mode and transmitting the selection to a server.

[1696] "Means for acquiring news data" refers to a means by which the server has the function of acquiring the latest news article data from an external news API.

[1697] "Means for analyzing news data and classifying it into positive and negative news" refers to a means that uses AI technology such as natural language processing models to analyze acquired news article data and classify it into positive and negative content.

[1698] The "means for filtering news" is a means having a function for selecting news to be displayed based on the news display mode selected by the user and the analysis results.

[1699] "Means for recognizing the user's emotional state in real time and adjusting the news display content based on the evaluation results" refers to a means that uses an emotion engine to analyze the user's facial expressions, voice, input content, etc. in real time, and adjusts the content and display method of the news based on the results.

[1700] The "means for generating a news feed based on filtering and emotion recognition" is a means having a function for generating an optimal news feed for a user based on filtered news and the user's emotion evaluation results.

[1701] The "means for transmitting the generated news feed to the user's terminal" refers to a means having a function for transmitting the news feed generated by the server to the user's terminal using a communication means.

[1702] The "means for readjusting a news feed based on feedback" refers to a means having a function for readjusting the content and display method of a news feed based on feedback information from a user.

[1703] The "means for displaying filtered news on a user's terminal" refers to a means having a function for displaying the final filtered news feed on a user's terminal so that the user can view it.

[1704] The present invention provides a system for selecting a news display mode, acquiring, analyzing, filtering, and recognizing emotions in news data, and generating and displaying a news feed, all of which are performed to enable users to browse news without feeling any mental strain.

[1705] Hardware and software used

[1706] Hardware

[1707] Terminal: A device operated by a user. Examples include computers, smartphones, and tablets.

[1708] Server: A computer system responsible for processing and storing data.

[1709] Emotion recognition devices: Devices such as cameras and microphones that capture the user's facial expressions and voice.

[1710] software

[1711] News API: API for obtaining external news data.

[1712] Natural language processing model (NLP model): An AI model for analyzing news data and classifying it into positive and negative news. Examples include BERT and GPT.

[1713] Emotion engine: Software for analyzing the user's emotional state in real time.

[1714] Filtering Algorithm: The algorithm for filtering the news data.

[1715] System Overview

[1716] Select news display mode

[1717] When a user accesses a news site, the device displays a news display mode selection screen, where the user can choose between "Display only positive news" or "Reduce negative news and display."

[1718] Mode transmission and recording

[1719] The terminal transmits information about the mode selected by the user to the server, which records this selection information in a database.

[1720] Acquiring news data

[1721] The server sends a request to the news API to retrieve the latest news data, including the title, content, and tags of the news articles.

[1722] News analysis and classification

[1723] The server analyzes the news data using a natural language processing model and classifies articles into positive and negative news.

[1724] News filtering

[1725] The server filters news based on the mode selected by the user: "Show only positive news" mode extracts only positive news, while "Reduce and lighten negative news" mode reduces the overlap of negative news and softens the headlines.

[1726] Emotional engine regulation

[1727] The server uses an emotion engine to recognize the user's emotional state in real time and adjusts the news content displayed based on the evaluation, which may include increasing the proportion of positive news or converting the news content to a more gentle expression.

[1728] Newsfeed generation and submission

[1729] Based on the filtering and emotion recognition, the server generates a news feed and sends the news feed to the user's terminal.

[1730] Viewing the news feed

[1731] The device displays the received news feed to the user, allowing the user to comfortably browse news according to the selected mode and emotional state.

[1732] Specific examples

[1733] Example 1: When the user selects the "Show only good news" mode

[1734] The user selects the "Show only positive news" mode on their device.

[1735] The server receives this information and retrieves the latest news from the news API.

[1736] The server analyzes the news data using a natural language processing model and extracts only positive news.

[1737] The emotion engine assesses the user's emotions and adjusts the news content to be particularly gentle.

[1738] The server generates the final news feed and sends it to the device.

[1739] The device displays positive news, allowing users to obtain information without mental strain.

[1740] Example 2: When the user selects the "Reduce Negative News" mode

[1741] The user selects the "Reduce negative news and display" mode on the device.

[1742] The server receives this information and retrieves the latest news from the news API.

[1743] The server analyzes the news data using a natural language processing model and extracts negative news.

[1744] The server reduces duplicate negative news and transforms it to soften the headlines.

[1745] The emotion engine evaluates the user's emotions and further adjusts the displayed content.

[1746] The server sends the filtered news feed to the terminal.

[1747] The device displays negative news in a reduced manner, allowing users to obtain important information with peace of mind.

[1748] Example prompt sentence:

[1749] "Show us the latest news and filter it to positive news."

[1750] "Please reduce the negative news and present softened headlines."

[1751] In this way, the system provides a safe news viewing environment based on the user's emotional state and the selected display mode.

[1752] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1753] Step 1: Select the news display mode

[1754] Input: The user accesses a news site on their device.

[1755] Processing: The device displays a news display mode selection screen. The user selects either "Display only positive news" or "Reduce negative news and display."

[1756] Output: The news display mode selected by the user.

[1757] Specific operation: Display options on the device screen using radio buttons or a drop-down menu, and allow the user to select one.

[1758] Step 2: Send and record the selected mode

[1759] Input: The news display mode selected by the user.

[1760] Processing: The terminal sends the selected mode to the server, which receives this information and records it in a database.

[1761] Output: Selected mode recorded data.

[1762] Specific operation: The terminal sends an HTTP request to the server, and the server receives the request and stores it in a database.

[1763] Step 3: Getting news data

[1764] Input: The server sends a request to retrieve news data.

[1765] Processing: The server sends a request to an external news API to get the latest news data. The data is received in JSON format.

[1766] Output: The retrieved news data.

[1767] Specific operation: The server sends an HTTP request to the news API and parses the returned JSON data to extract the title, content, tags, etc. of the news article.

[1768] Step 4: News analysis and classification

[1769] Input: Retrieved news data.

[1770] Processing: The server analyzes the news data using natural language processing models (e.g., BERT, GPT) and classifies each article into positive or negative news.

[1771] Output: Data categorized into positive and negative news.

[1772] Specific operation: A news article is input into a natural language processing model, and positive and negative scores are obtained and classified.

[1773] Step 5: Filtering the news

[1774] Input: Categorized news data, user selection mode.

[1775] Processing: The server filters the news based on the selection mode.

[1776] "Show only positive news" mode: Extracts only positive news.

[1777] "Reduce and soften negative news" mode: Reduces overlapping negative news and softens headlines.

[1778] Output: Filtered news data.

[1779] What it does: It uses algorithms to reprocess news and extract or edit the articles you want.

[1780] Step 6: Emotional Engine Alignment

[1781] Input: User's emotional information (facial expression, voice, input content), filtered news data.

[1782] Processing: The server uses an emotion engine to recognize the user's emotions in real time and adjusts the news content displayed based on the evaluation results.

[1783] Output: Adjusted news data.

[1784] Specific operation: Data is collected in real time from cameras and microphones, analyzed using emotion recognition algorithms, and the news data is adjusted based on the evaluation results.

[1785] Step 7: Generate and submit your news feed

[1786] Input: Adjusted news data.

[1787] Processing: The server generates the final news feed and sends it to the device.

[1788] Output: The generated news feed.

[1789] Specific operation: The news feed is packaged in HTML or JSON format and sent to the terminal as an HTTP response.

[1790] Step 8: View your news feed

[1791] Input: Received news feed.

[1792] Processing: The device displays the received news feed.

[1793] Output: The news feed displayed to the user.

[1794] What happens: The device's web browser renders the news feed and displays it on the screen.

[1795] The above are the specific steps of the program processing of this system.

[1796] (Application example 2)

[1797] 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."

[1798] In modern society, people are exposed to an enormous amount of information, often including negative news and stressful information. This has a serious impact on mental health. Furthermore, physical stores are not yet providing services that take into account the emotional state of customers, making improving customer satisfaction a key challenge. Therefore, there is a need for the development of a system that can recognize the emotional state of users and customers in real time and provide appropriate information based on that information.

[1799] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1800] In this invention, the server includes means for accepting a news display mode selection from a user, means for acquiring news data, means for analyzing the acquired news data and classifying it into positive news and negative news, means for filtering the news based on the mode selected by the user, means for recognizing and adjusting the user's emotional state in real time, means for further adjusting the news display content based on the felt emotions, means for learning past emotional data and predicting future news display modes, means for adjusting product information and promotions offered in stores according to the customer's emotional state, and means for displaying the filtered and adjusted news and product information on the user's or customer's terminal. This makes it possible to provide appropriate information while maintaining the mental health of the user or customer.

[1801] "News display mode" refers to a setting that a user selects when viewing news, and is used to tailor the news content to the user's preferences and emotional state.

[1802] "News data" refers to data containing the latest news article information, including titles, contents, tags, and other information.

[1803] "Emotion recognition" is a technology that analyzes a user's facial expressions, voice, input content, etc. to evaluate their current emotional state.

[1804] "Filtering" refers to the process of sorting acquired news data based on the mode selected by the user and adjusting the displayed content.

[1805] "Emotion history learning" is a technology that records and analyzes a user's past emotional data to predict future news display modes and information content.

[1806] "Adjusting the news display content" refers to the process of changing the news headline or content to a more toned-down expression based on the emotion recognition results, thereby changing the content to suit the user's emotional state.

[1807] "Promotion" means a marketing activity designed to inform customers about a particular product or service and encourage their purchase or use.

[1808] "Emotion-based product recommendation" is a technology that assesses a customer's current emotional state and provides them with product information and promotions accordingly.

[1809] This invention is a system that recognizes the emotional state of users and customers in real time and provides appropriate information and promotions based on that. This system can be used on news sites and in brick-and-mortar stores.

[1810] System Program

[1811] This system includes a user terminal, a server, and an emotion recognition engine. Specific examples of hardware and software include the following:

[1812] User devices: Tablet devices and smart employee robots

[1813] Server: Cloud server

[1814] Emotion recognition engine: Emotion API

[1815] News API: API to get the latest news data

[1816] Recommender system: A system that recommends product information and news

[1817] Program processing explanation

[1818] When a user uses a tablet device on a news site or in a physical store, the system works as follows:

[1819] 1. Emotion Recognition: Using the device's built-in camera and microphone, the Emotion API analyzes the user's emotions in real time, evaluating the customer's facial expressions and tone of voice to detect their current emotional state.

[1820] 2. Mode selection: When a user selects a news display mode, the selection and emotional state are sent to the server. News display modes include "display only positive news" and "reduced display of negative news." In physical stores, there are modes for "relaxing products" and "energetic products."

[1821] 3. Data Acquisition and Analysis: The server acquires the latest news data through the news API, analyzes the news data using AI and classifies it into positive news and negative news. Similarly, it uses the recommender system to acquire product information for physical stores.

[1822] 4. Filtering and Adjustment: Filter and adjust news and product information based on the user's selected mode and emotion recognition results. For example, for a user who is feeling stressed, increase positive news or recommend relaxing products.

[1823] 5. Display: Display tailored news and product information on the user's device. Users can browse their news feed and see recommended product information on their device.

[1824] Specific examples

[1825] As an example, the system processing when a customer selects the "Relaxing Products" mode using a tablet device and the Emotion API detects that the customer is feeling "stressed" is shown below.

[1826] 1. The customer's feelings are recognized as stress.

[1827] 2. The server filters information about products that have a relaxing effect based on the settings in the "Relaxing Products" mode.

[1828] 3. The filtered product information is displayed on the customer's tablet device.

[1829] Example prompts for generative AI models

[1830] Prompt: "Suggest relaxing products to customers who are feeling stressed. Generate a list of recommended products based on the following emotional data: Emotion Data: {'Emotion': 'Stress', 'Intensity': 'High'}"

[1831] In this way, it is possible to provide information and promotions tailored to the individual emotional state of the user or customer while maintaining their mental health.

[1832] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1833] Step 1:

[1834] The user selects a news display mode from the terminal. For example, the user may select "display only positive news" or "reduce negative news and display." This selection information is sent to the server. The input is the mode information selected by the user, and the output is the transmission of this information to the server.

[1835] Step 2:

[1836] Emotion recognition is performed in real time via the camera and microphone installed on the user's device. The device uses the Emotion API to analyze the user's facial expressions and voice to evaluate their emotional state. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[1837] Step 3:

[1838] The data of the news display mode selected by the user and the recognized emotional state are sent to the server. The input is the user's selected mode information and emotional state, and the output is the transmission of this information to the server.

[1839] Step 4:

[1840] The server retrieves the latest news data via the news API. The input is a request to the news API, and the output is the retrieved news data. The news data includes information such as title, content, and tags.

[1841] Step 5:

[1842] The server uses AI to analyze the acquired news data and classify it into positive news and negative news. The input is news data, and the output is data classified into positive news and negative news.

[1843] Step 6:

[1844] The server filters news based on the user's selected mode and the recognized emotional state. The input is the user's selected mode, emotional state, and classified news data, and the output is the filtered news data. For example, in the "Show only positive news" mode, only positive news is extracted.

[1845] Step 7:

[1846] The filtered news data is further adjusted based on the emotion recognition results. The server converts the displayed content to soften it according to the user's current emotional state. The input is the filtered news data and the emotion recognition results, and the output is the adjusted news data.

[1847] Step 8:

[1848] The server sends the filtered and adjusted news data to the user terminal, where the input is the adjusted news data and the output is the transmission of the news data to the user terminal.

[1849] Step 9:

[1850] The user terminal displays the received news data. The input is the news data sent from the server, and the output is the display of the news feed. The user can view the news feed on the terminal.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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.

[1856] 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.

[1857] 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).

[1858] 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.

[1859] 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."

[1860] 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.

[1861] 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).

[1862] 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.

[1863] 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.

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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.

[1868] 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.

[1869] 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.

[1870] 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.

[1871] 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.

[1872] The following is further disclosed regarding the above embodiment.

[1873] (Claim 1)

[1874] means for receiving a news display mode selection from a user;

[1875] a means for acquiring news data;

[1876] A means of analyzing the acquired news data and classifying it into positive news and negative news;

[1877] means for filtering news based on a user selected mode;

[1878] The system includes means for displaying the filtered news on a user's terminal.

[1879] (Claim 2)

[1880] 2. The system of claim 1, wherein the filtered news is only positive news.

[1881] (Claim 3)

[1882] The system according to claim 1, wherein the filtered news includes a means for reducing duplication of negative news and making its display less prominent, and further includes an expression conversion means for softening headlines and content.

[1883] "Example 1"

[1884] (Claim 1)

[1885] means for receiving a news display mode selection from a user;

[1886] a means for acquiring news data;

[1887] A means of analyzing the acquired news data and classifying it into positive news and negative news;

[1888] means for filtering news based on a user selected mode;

[1889] A means of retrieving data from the news API;

[1890] a means for analyzing news data using a natural language processing model;

[1891] means for generating and transmitting a news feed to a user's device;

[1892] A system including a means for displaying filtered news.

[1893] (Claim 2)

[1894] 2. The system of claim 1, wherein the filtered news is only positive news.

[1895] (Claim 3)

[1896] The system according to claim 1, wherein the filtered news includes a means for reducing duplication of negative news and making its display less prominent, and further includes an expression conversion means for softening headlines and content.

[1897] "Application Example 1"

[1898] (Claim 1)

[1899] means for receiving a news display mode selection from a user;

[1900] a means for acquiring news data;

[1901] A means of analyzing the acquired news data and classifying it into positive news and negative news;

[1902] means for filtering news based on a user selected mode;

[1903] means for displaying the filtered news on a user's terminal;

[1904] A system including means for displaying a news feed on a device that provides information to a user in a virtual space.

[1905] (Claim 2)

[1906] 2. The system of claim 1, wherein the filtered news is only positive news.

[1907] (Claim 3)

[1908] The system according to claim 1, wherein the filtered news includes a means for reducing duplication of negative news and making its display less prominent, and further includes an expression conversion means for softening headlines and content.

[1909] (Claim 4)

[1910] The system of claim 1, wherein the information provided in the virtual space is displayed to the user using a smart device.

[1911] "Example 2: Combining Emotion Engines"

[1912] (Claim 1)

[1913] means for receiving a news display mode selection from a user;

[1914] a means for acquiring news data;

[1915] A means of analyzing the acquired news data and classifying it into positive news and negative news;

[1916] means for filtering news based on a user selected mode;

[1917] means for recognizing the emotional state of a user in real time and adjusting the displayed news content based on the evaluation result;

[1918] means for generating a news feed based on filtering and emotion recognition;

[1919] means for transmitting the generated news feed to a user's terminal;

[1920] A way to retune your news feed based on feedback, and

[1921] The system includes means for displaying the filtered news on a user's terminal.

[1922] (Claim 2)

[1923] 10. The system of claim 1, wherein the filtered news is positive news only, and the displayed content is adjusted based on the user's emotional state.

[1924] (Claim 3)

[1925] The system of claim 1, wherein the filtered news includes a means for reducing duplication of negative news and making the display less prominent, and further includes an expression conversion means for softening headlines and content, and the displayed content is adjusted based on the user's emotional state.

[1926] "Application example 2 when combining emotion engines"

[1927] (Claim 1)

[1928] means for receiving a news display mode selection from a user;

[1929] a means for acquiring news data;

[1930] A means of analyzing the acquired news data and classifying it into positive news and negative news;

[1931] means for filtering news based on a user selected mode;

[1932] emotion recognition means for recognizing and adjusting the user's emotional state in real time;

[1933] means for further tailoring the news presentation based on the felt emotions;

[1934] A means for learning past emotion data and predicting future news display modes;

[1935] a means of tailoring product information and promotions offered in stores to the customer's emotional state;

[1936] The system includes means for displaying filtered and tailored news and product information on a user or customer terminal.

[1937] (Claim 2)

[1938] 2. The system of claim 1, wherein the filtered news is only positive news.

[1939] (Claim 3)

[1940] 2. The system according to claim 1, wherein the filtered news includes a means for reducing duplication of negative news and making its display less conspicuous, and further includes an expression conversion means for softening headlines and content. [Explanation of symbols]

[1941] 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. means for receiving a news display mode selection from a user; a means for acquiring news data; A means of analyzing the acquired news data and classifying it into positive news and negative news; means for filtering news based on a user selected mode; The system includes means for displaying the filtered news on a user's terminal.

2. The system of claim 1 , wherein the filtered news is only positive news.

3. The system according to claim 1, wherein the filtered news includes a means for reducing the duplication of negative news and making the display less conspicuous, and further includes an expression conversion means for softening headlines and contents.

Images