System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting or obtaining users' preferences; means for collecting relevant news based on the users' preferences; means for analyzing and classifying the collected news using natural-language processing techniques; means for evaluating the impact of the classified news on the world; means for filtering news based on the users' preferences and the impact of the news; means for summarizing the filtered news using a summarization generation and AI model; and means for providing the summarized news to users.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, the volume of information has grown so large that it is difficult for users to efficiently gather and digest the information they need. With the vast amount of news information being disseminated daily, users are particularly challenged to identify and quickly understand the news that is most important and relevant to them. Furthermore, because each user's preferences vary, information must be tailored to each individual, while also taking into account the impact of the news. Few existing systems meet these requirements, and the efficiency of providing information to users is not sufficiently ensured. [Means for solving the problem]

[0005] The present invention provides a system including a means for inputting or acquiring user preferences, a means for collecting news related to the user preferences, a means for analyzing and classifying the collected news using natural language processing technology, a means for evaluating the social impact of the classified news, a means for filtering news based on the user preferences and the impact of the news, a means for summarizing the filtered news using a summary generation AI model, and a means for providing the summarized news to users. This allows users to efficiently obtain news that matches their preferences and has a high social impact. Furthermore, by providing appropriate news summaries, users can grasp the necessary information in a short amount of time, enabling them to effectively utilize information without being overwhelmed by information overload.

[0006] "User preferences" are the news categories and topics that a particular user is interested in and cares about.

[0007] "News gathering means" refers to the technology or method for obtaining the latest news articles from multiple news sites and APIs on the Internet.

[0008] "Natural language processing technology" is a technology that allows computers to process, understand, and generate human language (natural language).

[0009] "News influence" is an indicator that shows the attention and response a news article receives within a certain period of time, and takes into account factors such as the number of shares on social media, the number of comments, and the number of views on news sites.

[0010] "Filtering" is the process of removing unnecessary information based on specific criteria and selecting only the necessary information.

[0011] A "summary generation AI model" is an artificial intelligence technology used to extract the main points of a news article and summarize it in a short, easy-to-understand format.

[0012] The "means for providing a summary" refers to a method or technology for providing the generated summary information to the user. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[0035] Obtaining user preferences

[0036] Terminal

[0037] When the terminal is used for the first time, it presents a questionnaire to the user, asking them to enter their preferences. For example, the questionnaire asks questions about news categories such as "politics," "economy," "sports," and "entertainment."

[0038] News data collection

[0039] server

[0040] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet. This collection is performed periodically and updated in real time.

[0041] News analysis and classification

[0042] server

[0043] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the news content, category, importance, and impact.

[0044] News impact assessment

[0045] server

[0046] The server evaluates the impact of the classified news, taking into account metrics such as the number of shares on social media, the number of comments, and the number of views on news sites. This evaluation identifies news that has a large social impact.

[0047] filtering

[0048] server

[0049] The server filters news based on the user's preferences and the impact of the news, and this filtering selects news that is most relevant to the user.

[0050] News summary generation

[0051] server

[0052] The server inputs the selected news into a summary generation AI model, extracts only the important key points, and generates a concise summary, allowing users to quickly grasp the essence of the news.

[0053] Providing news summaries

[0054] Server & Terminal

[0055] The server sends the generated summary news to the device, which receives it, notifies the user, and displays the summary news through an app or web browser.

[0056] Specific examples

[0057] Example: If the user is interested in "Economy" and "Entertainment"

[0058] First-time setup

[0059] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[0060] News gathering and classification

[0061] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[0062] Filtering and Summarization

[0063] The server evaluates the impact of news and selects economic and entertainment news with high impact. The news is then succinctly summarized using a summary generation AI model. For example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[0064] delivery

[0065] The server sends the news summary to the device, where it is displayed to the user via an app or the web.

[0066] This allows users to efficiently obtain and understand news that matches their preferences and has a high impact. The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is stored on the device. This preference data is used for future news filtering.

[0070] Step 2:

[0071] The server periodically visits multiple news sites and APIs on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[0072] Step 3:

[0073] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[0074] Step 4:

[0075] The server evaluates the impact of classified news on society. This evaluation utilizes data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the amount of attention the news is attracting to be quantified.

[0076] Step 5:

[0077] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that is of high interest to the user and has a high impact is selected.

[0078] Step 6:

[0079] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[0080] Step 7:

[0081] The server sends the generated summary news to the terminal, which receives the information and displays it to the user through an application or web browser. The user can view the summary news displayed on the screen and obtain important information efficiently and quickly.

[0082] Step 8:

[0083] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[0084] Through these processing steps, the news summarization system can collect, summarize, and provide appropriate news, taking into account the user's preferences and the impact of the news, allowing users to efficiently obtain useful information and solving the problem of information overload.

[0085] Example 1

[0086] 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."

[0087] In modern society, information overload makes it difficult to effectively obtain necessary information. It is also difficult to provide useful information tailored to users' interests in a short time. Furthermore, advanced technology is required to efficiently filter, summarize, and provide relevant news and articles, but current systems are unable to fully achieve this. To solve these issues, a system is needed that seamlessly collects, analyzes, summarizes, and provides information based on user preferences.

[0088] 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.

[0089] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the social impact of the classified information, means for filtering information based on the user preferences and the impact of the information, means for summarizing the information filtered by the generative AI model, means for providing the summarized information to the user, means for storing information in a database that saves user preferences, means for periodically acquiring data from news sites and APIs and storing it in the database, means for collecting data indicating impact from social media and web resources, means for calculating a score based on the impact data, means for inputting the acquired text to the generative AI model as a prompt sentence, and means for outputting the summary result to a display device. This allows users to efficiently obtain important news that suits their preferences in a short amount of time.

[0090] "User preferences" refers to information about news categories and topics of interest to a user.

[0091] "Input or acquisition means" refers to a method or device for detecting and recording user preferences.

[0092] "Related information" refers to data such as news and articles collected based on the user's preferences.

[0093] "Natural language processing technology" refers to algorithms and programs that analyze collected information and identify meanings and keywords.

[0094] A "classification means" is a method or device that uses natural language processing technology to separate collected information into categories or topics.

[0095] The "means for assessing the degree of influence" refers to a method or device for quantifying the social influence or response of classified information.

[0096] "Means for filtering information" refers to a method or device for selecting highly relevant information, taking into consideration the user's preferences and the influence of the information.

[0097] A "generative AI model" is an artificial intelligence model for summarizing filtered information.

[0098] A "summarizing means" is a method or device that uses a generative AI model to concisely summarize key points from filtered information.

[0099] "Means for providing" refers to a method or device for transmitting and displaying the summarized information to the user.

[0100] A "database" is an information system for storing preference information and collected news data.

[0101] "News sites and APIs" are web services that provide news data that is publicly available on the Internet.

[0102] "Data indicating impact" refers to metrics that indicate the social impact of news or information, such as the number of shares, comments, and views.

[0103] The "means for calculating a score" refers to a method or device for quantifying the importance or influence of information based on the impact data.

[0104] A "prompt sentence" is the input text provided to a generative AI model and is the sentence that serves as the basis for the summary.

[0105] A "display device" is a display or screen that visually presents the summary results to the user.

[0106] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[0107] First, the device is used to acquire the user's preferences. When the device is used for the first time, it displays a questionnaire screen and presents questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment." The user answers the questionnaire, and the device stores the answers in a database.

[0108] Next, we use a server to collect news data. The server periodically retrieves the latest news data from news sites and APIs (e.g., RSS feeds and news APIs) on the Internet and stores the data in a database. For this task, we can use the Python requests library to efficiently retrieve data from news APIs.

[0109] To analyze and classify the collected news data, the server uses natural language processing technology (e.g., spaCy or NLTK). The server performs text analysis on the news data and generates a topic model (e.g., LDA) to classify the news content into categories. The analysis results are updated in the database.

[0110] To evaluate the impact of classified news, the server collects data indicating impact, such as the number of shares, comments, and views, from social media and news sites. For example, it uses a Python API client (e.g., Tweepy for Twitter) or web scraping technology (e.g., BeautifulSoup). It calculates an impact score based on the collected data and evaluates the impact of each news article.

[0111] To filter important news, the server sorts data based on the user's preferences and the impact of the news. For example, if a user is interested in "Economy" and "Entertainment," high-impact news in these categories will be filtered.

[0112] To summarize the filtered news, the server uses a generative AI model (e.g., OpenAI's GPT-3). Specifically, the text of the news article is input to the generative AI model as a prompt: "Please summarize the following news: XX news content XX." The generated summary is concise and extracts only the important points.

[0113] In providing summarized news, the server sends summary data to the device. The device receives this data and displays it to the user through an app or web browser. For example, a news app can use the notification function to display the summarized news in real time, allowing the user to view it immediately.

[0114] Specific examples

[0115] If the user is interested in "economy" and "entertainment," the device presents the user with a questionnaire and, based on the results, records "economy" and "entertainment" in a preference database. The server collects the day's economy- and entertainment-related news, analyzes it using natural language processing technology, and classifies it into categories. Impact data is collected and, after evaluation, filtered based on the user's preferences. The generative AI model generates a summary of the news in the form of, for example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies." This summary news is sent to the device and notified to the user, where it is displayed in an app or on the web.

[0116] This system allows users to efficiently obtain news that matches their preferences and has a high impact, and to grasp the essence of the news in a short amount of time. This system will realize effective information provision in today's information-overloaded society.

[0117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0118] Step 1: Get user preferences

[0119] Specific actions

[0120] When the device is used for the first time, a survey screen will be displayed, presenting questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment."

[0121] Input: User's survey response

[0122] Data processing: The terminal extracts the categories selected by the user and formats them as structured data.

[0123] Output: Survey results (user preference information)

[0124] The terminal sends the survey results to the server's database and stores them.

[0125] Step 2: Gathering news data

[0126] Specific actions

[0127] The server periodically retrieves the latest news data from news sites or APIs (e.g., RSS feeds, news APIs).

[0128] Input: News data from various news sites and APIs

[0129] Data processing: The server converts the acquired news data from JSON format to SQL format and stores it in the database.

[0130] Output: News data stored in a database

[0131] Step 3: Analyze and categorize the news

[0132] Specific actions

[0133] The server analyzes the news data using natural language processing techniques (e.g., spaCy or NLTK).

[0134] Input: News data stored in a database

[0135] Data Computation: Analyze news text using natural language processing techniques, generate topic models, and classify news content by category.

[0136] Output: News data categorized by category

[0137] The server updates the analysis results to a database.

[0138] Step 4: News impact assessment

[0139] Specific actions

[0140] The server collects data from social media and news sites that indicates the degree of influence, such as the number of shares, comments, and views.

[0141] Input: Metric data from social media and news sites

[0142] Data calculation: Calculates an impact score based on the collected metrics data.

[0143] Output: News data with influence scores

[0144] The server adds the influence score to the news data and stores it in a database.

[0145] Step 5: Filtering

[0146] Specific actions

[0147] The server filters news based on the user's preferences and the impact of the news.

[0148] Input: User preference information, news data with influence scores

[0149] Data processing: Select highly relevant news based on preference information and impact scores.

[0150] Output: filtered news data

[0151] Step 6: News summary generation

[0152] Specific actions

[0153] The server feeds the filtered news data into a generative AI model (e.g., OpenAI's GPT-3).

[0154] Input: filtered news data

[0155] Data calculation: The prompt sentence "Please summarize the following news: XX news content XX" is provided to the generation AI model to generate a summary.

[0156] Output: Generated summary

[0157] The server stores the generated summary in a database.

[0158] Step 7: Providing a summary of news

[0159] Specific actions

[0160] The server transmits the generated summary news to the terminal.

[0161] Input: Generated news summary

[0162] Data processing: Converting data into a format that is easy for users to view on their devices.

[0163] Output: A news summary displayed to the user

[0164] The terminal outputs the summarized news to the display device and notifies the user.

[0165] Each processing step of the system allows users to efficiently obtain important news summaries that match their preferences.

[0166] (Application example 1)

[0167] 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."

[0168] The amount of information related to modern food delivery services is increasing, making it difficult for users to find important news and promotional information from the vast amount of information. Therefore, there is a need for a system that allows users to efficiently obtain important information that matches their preferences and respond quickly.

[0169] 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.

[0170] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news, means for analyzing and classifying the collected news, means for evaluating the influence of the classified news, means for filtering the news based on preferences and the influence of the news, means for summarizing using a summary generation AI model, means for providing summarized news and promotional information to the user, means for filtering the news and promotional information based on the evaluation score, means for notifying and displaying information that is likely to interest the user, and means for performing these processes using a series of data collected from the Internet, thereby enabling users to efficiently obtain important food delivery-related information that matches their preferences.

[0171] "User preferences" means the interests or concerns a User has regarding particular information or categories.

[0172] A "news gathering method" is a method for automatically obtaining relevant information from multiple sources on the Internet.

[0173] "Natural language processing technology" is a general term for technology that allows computers to understand and analyze human language.

[0174] "Influence" is an indicator that shows the degree of impact that a particular piece of news has on society and users.

[0175] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary information.

[0176] A "summary generation AI model" is an artificial intelligence technology that extracts important information from long pieces of text and summarizes it into short sentences.

[0177] "Promotional Information" refers to information about promotions and campaigns related to particular products or services.

[0178] An "evaluation score" is an index that evaluates an object and quantifies its importance and impact.

[0179] "Data collected from the internet" means information obtained automatically from websites, APIs, etc.

[0180] "Means for notification and display" refers to means for informing users of important information in real time and displaying it on the device.

[0181] This invention is a system that collects, filters, summarizes, and provides food delivery-related news and promotion information based on user preferences. An embodiment of this system will be described.

[0182] A means of obtaining user preferences

[0183] The device presents a questionnaire to the user upon first use, asking them to enter their preferences. The questionnaire consists of questions about categories such as "promotion information," "user reviews," and "industry news."

[0184] A means of gathering news and promotional information

[0185] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically and updated in real time.

[0186] A means of analyzing and classifying news and promotional information

[0187] The server analyzes the collected data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the content, category, and importance of news and promotional information. This process is performed using, for example, the "Summarizer" library.

[0188] Impact assessment tool for news and promotional information

[0189] The server evaluates the impact of the classified data. Specifically, it generates an evaluation score based on metrics such as the number of shares, comments, and views on social media. This evaluation identifies data with a large social impact.

[0190] Filtering Methods

[0191] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[0192] Summarization method using summary generation AI model

[0193] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[0194] A means of providing summary news and promotional information

[0195] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser.

[0196] Specific examples

[0197] Example: For users interested in food delivery

[0198] First-time setup

[0199] The device presents the user with a survey and records that they are interested in "promotional information" and "user reviews."

[0200] Data collection and classification

[0201] The server collects the day's news and promotion information related to food delivery from multiple sources, and uses natural language processing technology to categorize each piece of data into categories such as "promotion information" and "user reviews."

[0202] Filtering and Summarization

[0203] The server evaluates the impact of the data and selects the most influential news and promotional information. The data is then summarized succinctly using a summary generation AI model. For example, "A new promotion has been launched, offering significant discounts to new users."

[0204] delivery

[0205] The summarized information is sent from the server to the terminal, where it is displayed to the user via a dedicated app or the web.

[0206] Prompt Sentence Examples

[0207] "Collect recommended delivery news for Tabelog users. Summarize important information using the latest promotional information and customer reviews. Focus on content that users are likely to be interested in."

[0208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0209] Step 1:

[0210] Collection of preference data

[0211] The terminal presents a questionnaire to the user when they first use the terminal, and asks them to enter their preference data. The questionnaire includes questions about categories such as "promotion information," "user reviews," and "industry news." The user answers these questions, and the data is sent from the terminal to the server and stored in a database.

[0212] Input: User survey response data

[0213] Output: User preference data stored in a database on the server

[0214] Step 2:

[0215] To collect news and promotional information

[0216] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically, and the latest data is updated in real time.

[0217] Input: Internet news, promotional pages, social media, API

[0218] Output: Latest news and promotion information data stored on the server

[0219] Step 3:

[0220] Data analysis and classification

[0221] The server analyzes the collected data using natural language processing techniques, such as text analysis and clustering, to identify and classify the content, category, and importance of news and promotional information.

[0222] Input: News and promotion information data stored on the server

[0223] Output: Data classified into categories, importance, etc.

[0224] Step 4:

[0225] Impact Assessment

[0226] The server evaluates the impact of the classified data. Specifically, it calculates metrics such as the number of shares, comments, and views on social media, and generates an evaluation score. This evaluation identifies data with a large social impact.

[0227] Input: Categorized news and promotional information data

[0228] Output: Data with impact scores

[0229] Step 5:

[0230] Data filtering

[0231] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[0232] Input: User preference data, news and promotion information data with influence scores

[0233] Output: Filtered news and promotion information data

[0234] Step 6:

[0235] Application of summary generation AI model

[0236] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[0237] Input: Filtered news and promotion information data

[0238] Output: Summarized news and promotional information

[0239] Step 7:

[0240] Providing information

[0241] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser, allowing users to efficiently obtain important food delivery-related information that matches their preferences.

[0242] Input: Summarized news and promotional information

[0243] Output: Data that is communicated and displayed to the user

[0244] 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.

[0245] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[0246] Obtaining user preferences

[0247] Terminal

[0248] The device presents a questionnaire to the user when they first use the device, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data will be used for future news filtering.

[0249] News data collection

[0250] server

[0251] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet, and temporarily stores the collected news data in the server's database.

[0252] News analysis and classification

[0253] server

[0254] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, the text analysis algorithm reads the text of the news article and performs keyword extraction and document clustering.

[0255] News impact assessment

[0256] server

[0257] The server evaluates the impact of classified news on society by using data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the server to quantify how much attention the news is attracting.

[0258] filtering

[0259] server

[0260] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to categories that are of high interest to the user and have a high impact is selected.

[0261] User Emotion Recognition

[0262] Terminal

[0263] The device uses sensors such as cameras and microphones to recognize emotions from the user's facial expressions and voice. The recognized emotion data is labeled as "happiness," "anger," "sadness," etc., and sent to the server in real time.

[0264] News summary generation

[0265] server

[0266] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[0267] Providing news summaries

[0268] Server & Terminal

[0269] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state and is presented with an appropriate tone and content.

[0270] Specific examples

[0271] Example: If the user is interested in "Economy" and "Entertainment"

[0272] First-time setup

[0273] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[0274] News gathering and classification

[0275] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[0276] Filtering and Emotion Recognition

[0277] The server evaluates the impact of the news, filters it, and also receives the user's emotional data. If the user is feeling sad, for example, the tone of the news will be taken into account when displaying it.

[0278] Summary generation and delivery

[0279] The server uses a summary generation AI model to summarize the filtered news concisely and send it to the device. The device receives the news and displays it in a way that takes into account the user's emotions. For example, a summary of the news, such as "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies," is provided to the user based on their emotions.

[0280] This allows users to efficiently obtain and understand news that matches their preferences and current emotions and that will have a significant impact.The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[0281] The processing flow will be explained below.

[0282] Step 1:

[0283] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the news categories that interest them (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data is sent to the server and used for future news filtering.

[0284] Step 2:

[0285] The server periodically visits multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[0286] Step 3:

[0287] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[0288] Step 4:

[0289] The server evaluates the impact of the analyzed news data on society. This evaluation takes into account data such as the number of shares on social media, the number of comments, and the number of views on news sites. The evaluation results are quantified, and the impact of the news is calculated as a number.

[0290] Step 5:

[0291] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that the user is highly interested in and has a high impact is selected. For example, if a user is interested in "economy," news about a "significant rise in the stock market" with a high impact is selected.

[0292] Step 6:

[0293] The device uses sensors (camera and microphone) to analyze the user's facial expressions and voice in real time and recognizes the user's emotions. The recognized emotional data is labeled with, for example, "joy," "anger," or "sadness," and sent to the server.

[0294] Step 7:

[0295] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and generates a short summary such as, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[0296] Step 8:

[0297] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state. For example, if the user is feeling "sad," the news will be displayed in a gentle tone.

[0298] Step 9:

[0299] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[0300] Through the above processing steps, the news summarization system can collect, summarize, and provide appropriate news by taking into account the user's preferences, the impact of the news, and the user's emotions, allowing users to efficiently obtain useful information and solving the problem of information overload.

[0301] Example 2

[0302] 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."

[0303] In modern society, users are exposed to a huge amount of information, making it difficult to quickly and accurately extract information that is useful to them. In particular, when it comes to information such as news, it is necessary to take into account the importance of the content, individual preferences, and even the user's current emotions. This means that there is a demand for systems that allow users to obtain information that is appropriate for them without being overwhelmed by excessive information.

[0304] 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.

[0305] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information based on the user preferences, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the influence of the classified information, means for filtering information based on the user preferences and the influence of the information, means for recognizing the user's emotions, means for summarizing the filtered information using a summary generation AI model, and means for providing the summarized information to the user, thereby enabling the user to efficiently obtain highly influential information that matches their preferences and emotional state.

[0306] "Means for inputting or acquiring user preferences" refers to an interface that allows users to input information about categories or specific content that interest them, or technology that automatically collects preferences from past usage history, etc.

[0307] "Means for collecting relevant information" refers to technology that extracts and collects appropriate data from multiple sources on the Internet based on user preferences.

[0308] "Means of analyzing and classifying using natural language processing technology" refers to the technology of analyzing collected information using natural language processing (NLP) technology and classifying it by content and category.

[0309] "Means for assessing impact" refers to technology that quantifies and evaluates the social attention that classified information receives based on, for example, the number of shares, comments, and views on social media.

[0310] "Means of filtering information" refers to technology that selects appropriate information and eliminates other information based on the user's preferences and the influence of the information.

[0311] "Means for recognizing emotions" refers to technology that uses sensor devices such as cameras and microphones to recognize emotions from the user's facial expressions and voice, and converts them into data in real time.

[0312] "Method of summarizing using a summary generation AI model" refers to a technology that uses an AI (artificial intelligence) summary generation algorithm to summarize long pieces of information in a short and concise manner.

[0313] "Means for providing summarized information to a user" refers to technology that transmits summarized information to a terminal and displays it appropriately in a manner that takes into account the user's emotional state.

[0314] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[0315] The process of acquiring user preferences

[0316] Terminal

[0317] When the device first uses the system, it displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interest. This information is stored on the device and sent to the server.

[0318] Specific examples

[0319] Example prompt: Choose a news category that interests you (e.g., politics, economics, sports, entertainment)

[0320] The user selects "Economy" and "Entertainment." This selection information is saved on the device and sent to the server.

[0321] News data collection process

[0322] server

[0323] The server periodically collects new news data from news APIs, RSS feeds, etc. The server stores the collected news data in a database.

[0324] Specific examples

[0325] The server queries the news API to retrieve news in the economy and entertainment categories.

[0326] The acquired news data is stored in a database.

[0327] News analysis and classification process

[0328] server

[0329] The server uses natural language processing technology to perform text analysis on the stored news data, analyzing the text of news articles and identifying categories and importance through keyword extraction and clustering.

[0330] Specific examples

[0331] The server reads the news article and extracts key keywords and topics.

[0332] News is categorized into categories such as "Economy" and "Entertainment."

[0333] News impact assessment process

[0334] server

[0335] The server evaluates the impact of the collected news based on data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[0336] Specific examples

[0337] The server collects the number of social media shares and views for a particular article.

[0338] These data are used to quantify the impact of news (e.g., "high," "medium," or "low").

[0339] News filtering process

[0340] server

[0341] The server filters news based on the user's preference data and the impact of the news, selecting news articles that have a high impact and match the user's preferences.

[0342] Specific examples

[0343] The server selects news in the "Economy" category that is rated as having a "high" impact.

[0344] Generate a filtered list of news.

[0345] User emotion recognition process

[0346] Terminal

[0347] The device uses a camera and microphone to recognize the user's current emotion from their facial expressions and voice, and then labels the recognition results and sends them to the server.

[0348] Specific examples

[0349] The device captures the user's facial expression with the camera and calls a facial recognition API to determine whether the expression is "sad."

[0350] A request including emotion data is sent to the server.

[0351] News summary generation process

[0352] server

[0353] The server inputs the filtered text of the news article into a summary generation AI model to generate a concise summary of the main points.

[0354] Specific examples

[0355] The server inputs an economic news article stating, "Stock market rises due to new economic policies" into a summary generation AI model.

[0356] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[0357] Summary news delivery process

[0358] Server & Terminal

[0359] The server sends the generated summary news to the terminal, which then displays it to the user. For example, if the user is sad, the tone of the displayed news will be softened.

[0360] Specific examples

[0361] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[0362] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[0363] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0364] Step 1:

[0365] Obtaining user preferences

[0366] Terminal

[0367] When the user first uses the system, the terminal displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interests. Based on this input data, the terminal generates the user's preference data and sends it to the server.

[0368] Specific actions

[0369] The device will display the survey screen.

[0370] The user selects "Economy" and "Entertainment."

[0371] The input data is saved on the terminal and sent to the server.

[0372] Step 2:

[0373] News data collection

[0374] server

[0375] The server periodically collects new news data from news APIs, RSS feeds, etc. The news data obtained from these data sources is temporarily stored in the server's database. The input is information from the news APIs and RSS feeds, and the output is news data stored in the server's database.

[0376] Specific actions

[0377] The server queries the news API to get the latest news.

[0378] The acquired news is stored in a database.

[0379] Step 3:

[0380] News analysis and classification

[0381] server

[0382] The server performs text analysis on the stored news data using natural language processing (NLP) technology. The input is the news data stored in the database, and the output is news classified by category and its importance. The text of the news article is analyzed, and keywords are extracted and clustered to identify categories and importance.

[0383] Specific actions

[0384] The server reads the news article and extracts keywords.

[0385] News is categorized into categories such as "Economy" and "Entertainment."

[0386] Step 4:

[0387] News impact assessment

[0388] server

[0389] The server evaluates the impact of classified news based on data such as the number of shares on social media, the number of comments, the number of views on news sites, etc. The input is data such as the number of shares and comments on social media, and the output is news data with a quantified impact.

[0390] Specific actions

[0391] The server collects the number of social media shares and views for a particular article.

[0392] These data are used to quantify the impact (e.g., "high," "medium," or "low").

[0393] Step 5:

[0394] News filtering

[0395] server

[0396] The server filters news based on the user's preference data and the results of the impact assessment. The input is the user's preference data and the results of the impact assessment, and the output is the filtered news data. News articles with high impact and matching the user's preferences are selected.

[0397] Specific actions

[0398] The server selects news in the "Economy" category that is rated as having a "high" impact.

[0399] Generate a filtered list of news.

[0400] Step 6:

[0401] User Emotion Recognition

[0402] Terminal

[0403] The device uses a camera and microphone to recognize the user's current emotion from their facial expression and voice. The input is the user's facial expression and voice, and the output is the recognized emotion data. The recognition results are labeled and sent to the server.

[0404] Specific actions

[0405] The device captures the user's facial expressions using a camera.

[0406] A facial recognition API is called to determine "sadness."

[0407] A request including emotion data is sent to the server.

[0408] Step 7:

[0409] News summary generation

[0410] server

[0411] The server inputs the filtered news article text into a summary generation AI model to generate a concise summary that summarizes the main points. The input is the filtered news article text, and the output is the summarized news.

[0412] Specific actions

[0413] The server inputs a news article stating that "stock market rises due to new economic policies" into a summary generation AI model.

[0414] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[0415] Step 8:

[0416] Providing news summaries

[0417] Server & Terminal

[0418] The server sends the generated summary news to the terminal, which displays it to the user. The input is the summary news, and the output is the summary news provided to the user. In particular, if the user is sad, the tone of the displayed news is made gentler.

[0419] Specific actions

[0420] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[0421] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[0422] (Application example 2)

[0423] 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."

[0424] In modern society, we are overwhelmed with information, making it difficult for users to select the information they need. Furthermore, conventional news delivery systems only consider the user's preferences, and therefore are unable to provide news that reflects the user's current emotional state. This can lead to users being exposed to unpleasant news at inappropriate times, which often leads to stress in information consumption. Therefore, there is a need for a system that provides appropriate news by taking into account not only the user's preferences but also their emotional state.

[0425] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news based on the user preferences, means for analyzing and classifying the collected news using natural language processing technology, means for evaluating the social impact of the classified news, means for filtering the news based on the user preferences and the impact of the news, means for summarizing the filtered news using a summary generation AI model, means for recognizing the user's emotions, means for filtering the news based on the recognized emotions, means for providing the filtered news in a tone that matches the user's emotions, and means for providing the summarized news to the user. This enables more appropriate and less stressful news provision by simultaneously taking into account the user's preferences and emotions.

[0426] "User preferences" refer to the categories, themes, or content that interest a user.

[0427] "Emotion recognition" is a technology that identifies emotions from a user's facial expressions and voice.

[0428] "News gathering" refers to the process of obtaining the latest news data from multiple news sources on the Internet.

[0429] "Natural language processing technology" refers to a set of computer technologies for analyzing text, classifying it, generating summaries, and so on.

[0430] "News influence" is an indicator that evaluates how much attention a news article receives in the public and on social networks.

[0431] "News filtering" is the process of selecting relevant news based on user preferences, news impact, and emotions.

[0432] A "summary generation AI model" is an artificial intelligence technology that extracts important information from news text and generates concise summaries.

[0433] "Tone" refers to the tone and atmosphere of expression used to convey emotions and feelings in news or writing.

[0434] In order to put the present invention into practice, the following system is configured, and corresponding processing is performed at each step.

[0435] System configuration

[0436] The system includes a server, a user terminal, and an internet communication means. The server collects, analyzes, filters, and summarizes news data, while the user terminal acquires preference data and recognizes emotions.

[0437] The specific hardware and software used

[0438] Hardware

[0439] Smartphone camera and microphone: Used for emotion recognition.

[0440] software

[0441] OpenCV: Used to process images captured by the smartphone camera and recognize the user's facial expressions.

[0442] requests: Used to retrieve news data from the news API.

[0443] nltk: Used to perform text analysis and summarization of news articles.

[0444] TextBlob: Used to perform sentence sentiment analysis of news articles.

[0445] transformers: Used to utilize summary generation AI models.

[0446] Program processing flow

[0447] 1. Obtaining user preferences

[0448] When the app is launched for the first time, the user takes a survey, selects the categories that interest them (e.g., politics, economics, sports, entertainment), and saves that information on the device.

[0449] 2. News gathering

[0450] The server collects the latest news data from news sites on the Internet and news APIs (e.g., RSS feeds, news APIs) and temporarily stores it in the server's database.

[0451] 3. Emotion recognition

[0452] Using the smartphone's camera and microphone, the system recognizes emotions from the user's facial expressions and voice. For example, the emotions are labeled as joy, anger, sadness, etc. and sent to the server in real time.

[0453] 4. News analysis and classification

[0454] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news.

[0455] 5. News impact assessment

[0456] The server evaluates the impact of news on society, using data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[0457] 6. News Filtering

[0458] The server filters news based on the user's preferences and the impact of the news, and also selects appropriate news based on the results of emotion recognition.

[0459] 7. News Summarization

[0460] The server inputs the selected news articles into a summary generation AI model to generate concise summaries.

[0461] 8. Displaying News

[0462] The filtered news is presented in a tone that matches the user's emotions. For example, if the user is feeling "sad," the tone of the news will be displayed taking that into account.

[0463] Specific examples

[0464] For example, if a user is interested in "sports" and "entertainment" and is currently feeling "angry," the app will select articles related to sports and entertainment, but with a tone that will ease the user's anger. The specific prompt text is as follows:

[0465] Prompt Sentence Examples

[0466] User Preferences: Sports, Entertainment

[0467] User Emotion: Anger

[0468] News article: 'Football match results, new acting debut'

[0469] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0470] Step 1:

[0471] When the user's device is first started up, it presents a questionnaire and the user selects the category of interest (e.g., politics, economics, sports, entertainment). The results of this questionnaire are saved on the device as the user's preference data and sent to the server. The input is the results of the questionnaire, and the output is preference data.

[0472] Step 2:

[0473] The server collects the latest news data from news sites and news APIs on the Internet. The collected news data is temporarily stored in the server's database. The input is news sources on the Internet, and the output is the collected news data.

[0474] Step 3:

[0475] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and uses this to recognize emotions. The recognized emotion data is sent to the server in real time. The input is the user's facial expressions and voice data, and the output is the recognized emotion data.

[0476] Step 4:

[0477] The news data collected by the server is analyzed using natural language processing technology to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news. Specifically, a text analysis algorithm is used to read the text of the news article, extract keywords, and perform document clustering. The input is news data, and the output is analytical data with identified categories and importance.

[0478] Step 5:

[0479] The server evaluates how much attention a news article is attracting from around the world. The evaluation uses factors such as the number of shares on social media, the number of comments, and the number of views on news sites. This quantifies the impact of the news. The input is news data and attention data (number of social media shares, number of comments, number of views), and the output is impact assessment data.

[0480] Step 6:

[0481] The server filters news based on the user's preference data and news impact evaluation data. It also takes into account the results of emotion recognition to select news that best suits the user's current emotional state. The input is preference data, impact evaluation data, and emotion data, and the output is filtered news articles.

[0482] Step 7:

[0483] The server inputs the filtered news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in a short sentence format. The input is the filtered news article, and the output is the summarized news text.

[0484] Step 8:

[0485] The server sends the generated summary news to the terminal, which then provides it to the user. The displayed news is presented in a tone that matches the user's emotions. The input is the summary news text, and the output is the news displayed to the user.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] [Second embodiment]

[0490] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0491] 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.

[0492] 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).

[0493] 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.

[0494] 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.

[0495] 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).

[0496] 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.

[0497] 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.

[0498] 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.

[0499] 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.

[0500] 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.

[0501] 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."

[0502] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[0503] Obtaining user preferences

[0504] Terminal

[0505] When the terminal is used for the first time, it presents a questionnaire to the user, asking them to enter their preferences. For example, the questionnaire asks questions about news categories such as "politics," "economy," "sports," and "entertainment."

[0506] News data collection

[0507] server

[0508] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet. This collection is performed periodically and updated in real time.

[0509] News analysis and classification

[0510] server

[0511] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the news content, category, importance, and impact.

[0512] News impact assessment

[0513] server

[0514] The server evaluates the impact of the classified news, taking into account metrics such as the number of shares on social media, the number of comments, and the number of views on news sites. This evaluation identifies news that has a large social impact.

[0515] filtering

[0516] server

[0517] The server filters news based on the user's preferences and the impact of the news, and this filtering selects news that is most relevant to the user.

[0518] News summary generation

[0519] server

[0520] The server inputs the selected news into a summary generation AI model, extracts only the important key points, and generates a concise summary, allowing users to quickly grasp the essence of the news.

[0521] Providing news summaries

[0522] Server & Terminal

[0523] The server sends the generated summary news to the device, which receives it, notifies the user, and displays the summary news through an app or web browser.

[0524] Specific examples

[0525] Example: If the user is interested in "Economy" and "Entertainment"

[0526] First-time setup

[0527] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[0528] News gathering and classification

[0529] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[0530] Filtering and Summarization

[0531] The server evaluates the impact of news and selects economic and entertainment news with high impact. The news is then succinctly summarized using a summary generation AI model. For example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[0532] delivery

[0533] The server sends the news summary to the device, where it is displayed to the user via an app or the web.

[0534] This allows users to efficiently obtain and understand news that matches their preferences and has a high impact. The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[0535] The processing flow will be explained below.

[0536] Step 1:

[0537] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is stored on the device. This preference data is used for future news filtering.

[0538] Step 2:

[0539] The server periodically visits multiple news sites and APIs on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[0540] Step 3:

[0541] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[0542] Step 4:

[0543] The server evaluates the impact of classified news on society. This evaluation utilizes data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the amount of attention the news is attracting to be quantified.

[0544] Step 5:

[0545] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that is of high interest to the user and has a high impact is selected.

[0546] Step 6:

[0547] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[0548] Step 7:

[0549] The server sends the generated summary news to the terminal, which receives the information and displays it to the user through an application or web browser. The user can view the summary news displayed on the screen and obtain important information efficiently and quickly.

[0550] Step 8:

[0551] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[0552] Through these processing steps, the news summarization system can collect, summarize, and provide appropriate news, taking into account the user's preferences and the impact of the news, allowing users to efficiently obtain useful information and solving the problem of information overload.

[0553] Example 1

[0554] 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."

[0555] In modern society, information overload makes it difficult to effectively obtain necessary information. It is also difficult to provide useful information tailored to users' interests in a short time. Furthermore, advanced technology is required to efficiently filter, summarize, and provide relevant news and articles, but current systems are unable to fully achieve this. To solve these issues, a system is needed that seamlessly collects, analyzes, summarizes, and provides information based on user preferences.

[0556] 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.

[0557] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the social impact of the classified information, means for filtering information based on the user preferences and the impact of the information, means for summarizing the information filtered by the generative AI model, means for providing the summarized information to the user, means for storing information in a database that saves user preferences, means for periodically acquiring data from news sites and APIs and storing it in the database, means for collecting data indicating impact from social media and web resources, means for calculating a score based on the impact data, means for inputting the acquired text to the generative AI model as a prompt sentence, and means for outputting the summary result to a display device. This allows users to efficiently obtain important news that suits their preferences in a short amount of time.

[0558] "User preferences" refers to information about news categories and topics of interest to a user.

[0559] "Input or acquisition means" refers to a method or device for detecting and recording user preferences.

[0560] "Related information" refers to data such as news and articles collected based on the user's preferences.

[0561] "Natural language processing technology" refers to algorithms and programs that analyze collected information and identify meanings and keywords.

[0562] A "classification means" is a method or device that uses natural language processing technology to separate collected information into categories or topics.

[0563] The "means for assessing the degree of influence" refers to a method or device for quantifying the social influence or response of classified information.

[0564] "Means for filtering information" refers to a method or device for selecting highly relevant information, taking into consideration the user's preferences and the influence of the information.

[0565] A "generative AI model" is an artificial intelligence model for summarizing filtered information.

[0566] A "summarizing means" is a method or device that uses a generative AI model to concisely summarize key points from filtered information.

[0567] "Means for providing" refers to a method or device for transmitting and displaying the summarized information to the user.

[0568] A "database" is an information system for storing preference information and collected news data.

[0569] "News sites and APIs" are web services that provide news data that is publicly available on the Internet.

[0570] "Data indicating impact" refers to metrics that indicate the social impact of news or information, such as the number of shares, comments, and views.

[0571] The "means for calculating a score" refers to a method or device for quantifying the importance or influence of information based on the impact data.

[0572] A "prompt sentence" is the input text provided to a generative AI model and is the sentence that serves as the basis for the summary.

[0573] A "display device" is a display or screen that visually presents the summary results to the user.

[0574] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[0575] First, the device is used to acquire the user's preferences. When the device is used for the first time, it displays a questionnaire screen and presents questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment." The user answers the questionnaire, and the device stores the answers in a database.

[0576] Next, we use a server to collect news data. The server periodically retrieves the latest news data from news sites and APIs (e.g., RSS feeds and news APIs) on the Internet and stores the data in a database. For this task, we can use the Python requests library to efficiently retrieve data from news APIs.

[0577] To analyze and classify the collected news data, the server uses natural language processing technology (e.g., spaCy or NLTK). The server performs text analysis on the news data and generates a topic model (e.g., LDA) to classify the news content into categories. The analysis results are updated in the database.

[0578] To evaluate the impact of classified news, the server collects data indicating impact, such as the number of shares, comments, and views, from social media and news sites. For example, it uses a Python API client (e.g., Tweepy for Twitter) or web scraping technology (e.g., BeautifulSoup). It calculates an impact score based on the collected data and evaluates the impact of each news article.

[0579] To filter important news, the server sorts data based on the user's preferences and the impact of the news. For example, if a user is interested in "Economy" and "Entertainment," high-impact news in these categories will be filtered.

[0580] To summarize the filtered news, the server uses a generative AI model (e.g., OpenAI's GPT-3). Specifically, the text of the news article is input to the generative AI model as a prompt: "Please summarize the following news: XX news content XX." The generated summary is concise and extracts only the important points.

[0581] In providing summarized news, the server sends summary data to the device. The device receives this data and displays it to the user through an app or web browser. For example, a news app can use the notification function to display the summarized news in real time, allowing the user to view it immediately.

[0582] Specific examples

[0583] If the user is interested in "economy" and "entertainment," the device presents the user with a questionnaire and, based on the results, records "economy" and "entertainment" in a preference database. The server collects the day's economy- and entertainment-related news, analyzes it using natural language processing technology, and classifies it into categories. Impact data is collected and, after evaluation, filtered based on the user's preferences. The generative AI model generates a summary of the news in the form of, for example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies." This summary news is sent to the device and notified to the user, where it is displayed in an app or on the web.

[0584] This system allows users to efficiently obtain news that matches their preferences and has a high impact, and to grasp the essence of the news in a short amount of time. This system will realize effective information provision in today's information-overloaded society.

[0585] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0586] Step 1: Get user preferences

[0587] Specific actions

[0588] When the device is used for the first time, a survey screen will be displayed, presenting questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment."

[0589] Input: User's survey response

[0590] Data processing: The terminal extracts the categories selected by the user and formats them as structured data.

[0591] Output: Survey results (user preference information)

[0592] The terminal sends the survey results to the server's database and stores them.

[0593] Step 2: Gathering news data

[0594] Specific actions

[0595] The server periodically retrieves the latest news data from news sites or APIs (e.g., RSS feeds, news APIs).

[0596] Input: News data from various news sites and APIs

[0597] Data processing: The server converts the acquired news data from JSON format to SQL format and stores it in the database.

[0598] Output: News data stored in a database

[0599] Step 3: Analyze and categorize the news

[0600] Specific actions

[0601] The server analyzes the news data using natural language processing techniques (e.g., spaCy or NLTK).

[0602] Input: News data stored in a database

[0603] Data Computation: Analyze news text using natural language processing techniques, generate topic models, and classify news content by category.

[0604] Output: News data categorized by category

[0605] The server updates the analysis results to a database.

[0606] Step 4: News impact assessment

[0607] Specific actions

[0608] The server collects data from social media and news sites that indicates the degree of influence, such as the number of shares, comments, and views.

[0609] Input: Metric data from social media and news sites

[0610] Data calculation: Calculates an impact score based on the collected metrics data.

[0611] Output: News data with influence scores

[0612] The server adds the influence score to the news data and stores it in a database.

[0613] Step 5: Filtering

[0614] Specific actions

[0615] The server filters news based on the user's preferences and the impact of the news.

[0616] Input: User preference information, news data with influence scores

[0617] Data processing: Select highly relevant news based on preference information and impact scores.

[0618] Output: filtered news data

[0619] Step 6: News summary generation

[0620] Specific actions

[0621] The server feeds the filtered news data into a generative AI model (e.g., OpenAI's GPT-3).

[0622] Input: filtered news data

[0623] Data calculation: The prompt sentence "Please summarize the following news: XX news content XX" is provided to the generation AI model to generate a summary.

[0624] Output: Generated summary

[0625] The server stores the generated summary in a database.

[0626] Step 7: Providing a summary of news

[0627] Specific actions

[0628] The server transmits the generated summary news to the terminal.

[0629] Input: Generated news summary

[0630] Data processing: Converting data into a format that is easy for users to view on their devices.

[0631] Output: A news summary displayed to the user

[0632] The terminal outputs the summarized news to the display device and notifies the user.

[0633] Each processing step of the system allows users to efficiently obtain important news summaries that match their preferences.

[0634] (Application example 1)

[0635] 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."

[0636] The amount of information related to modern food delivery services is increasing, making it difficult for users to find important news and promotional information from the vast amount of information. Therefore, there is a need for a system that allows users to efficiently obtain important information that matches their preferences and respond quickly.

[0637] 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.

[0638] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news, means for analyzing and classifying the collected news, means for evaluating the influence of the classified news, means for filtering the news based on preferences and the influence of the news, means for summarizing using a summary generation AI model, means for providing summarized news and promotional information to the user, means for filtering the news and promotional information based on the evaluation score, means for notifying and displaying information that is likely to interest the user, and means for performing these processes using a series of data collected from the Internet, thereby enabling users to efficiently obtain important food delivery-related information that matches their preferences.

[0639] "User preferences" means the interests or concerns a User has regarding particular information or categories.

[0640] A "news gathering method" is a method for automatically obtaining relevant information from multiple sources on the Internet.

[0641] "Natural language processing technology" is a general term for technology that allows computers to understand and analyze human language.

[0642] "Influence" is an indicator that shows the degree of impact that a particular piece of news has on society and users.

[0643] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary information.

[0644] A "summary generation AI model" is an artificial intelligence technology that extracts important information from long pieces of text and summarizes it into short sentences.

[0645] "Promotional Information" refers to information about promotions and campaigns related to particular products or services.

[0646] An "evaluation score" is an index that evaluates an object and quantifies its importance and impact.

[0647] "Data collected from the internet" means information obtained automatically from websites, APIs, etc.

[0648] "Means for notification and display" refers to means for informing users of important information in real time and displaying it on the device.

[0649] This invention is a system that collects, filters, summarizes, and provides food delivery-related news and promotion information based on user preferences. An embodiment of this system will be described.

[0650] A means of obtaining user preferences

[0651] The device presents a questionnaire to the user upon first use, asking them to enter their preferences. The questionnaire consists of questions about categories such as "promotion information," "user reviews," and "industry news."

[0652] A means of gathering news and promotional information

[0653] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically and updated in real time.

[0654] A means of analyzing and classifying news and promotional information

[0655] The server analyzes the collected data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the content, category, and importance of news and promotional information. This process is performed using, for example, the "Summarizer" library.

[0656] Impact assessment tool for news and promotional information

[0657] The server evaluates the impact of the classified data. Specifically, it generates an evaluation score based on metrics such as the number of shares, comments, and views on social media. This evaluation identifies data with a large social impact.

[0658] Filtering Methods

[0659] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[0660] Summarization method using summary generation AI model

[0661] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[0662] A means of providing summary news and promotional information

[0663] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser.

[0664] Specific examples

[0665] Example: For users interested in food delivery

[0666] First-time setup

[0667] The device presents the user with a survey and records that they are interested in "promotional information" and "user reviews."

[0668] Data collection and classification

[0669] The server collects the day's news and promotion information related to food delivery from multiple sources, and uses natural language processing technology to categorize each piece of data into categories such as "promotion information" and "user reviews."

[0670] Filtering and Summarization

[0671] The server evaluates the impact of the data and selects the most influential news and promotional information. The data is then summarized succinctly using a summary generation AI model. For example, "A new promotion has been launched, offering significant discounts to new users."

[0672] delivery

[0673] The summarized information is sent from the server to the terminal, where it is displayed to the user via a dedicated app or the web.

[0674] Prompt Sentence Examples

[0675] "Collect recommended delivery news for Tabelog users. Summarize important information using the latest promotional information and customer reviews. Focus on content that users are likely to be interested in."

[0676] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0677] Step 1:

[0678] Collection of preference data

[0679] The terminal presents a questionnaire to the user when they first use the terminal, and asks them to enter their preference data. The questionnaire includes questions about categories such as "promotion information," "user reviews," and "industry news." The user answers these questions, and the data is sent from the terminal to the server and stored in a database.

[0680] Input: User survey response data

[0681] Output: User preference data stored in a database on the server

[0682] Step 2:

[0683] To collect news and promotional information

[0684] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically, and the latest data is updated in real time.

[0685] Input: Internet news, promotional pages, social media, API

[0686] Output: Latest news and promotion information data stored on the server

[0687] Step 3:

[0688] Data analysis and classification

[0689] The server analyzes the collected data using natural language processing techniques, such as text analysis and clustering, to identify and classify the content, category, and importance of news and promotional information.

[0690] Input: News and promotion information data stored on the server

[0691] Output: Data classified into categories, importance, etc.

[0692] Step 4:

[0693] Impact Assessment

[0694] The server evaluates the impact of the classified data. Specifically, it calculates metrics such as the number of shares, comments, and views on social media, and generates an evaluation score. This evaluation identifies data with a large social impact.

[0695] Input: Categorized news and promotional information data

[0696] Output: Data with impact scores

[0697] Step 5:

[0698] Data filtering

[0699] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[0700] Input: User preference data, news and promotion information data with influence scores

[0701] Output: Filtered news and promotion information data

[0702] Step 6:

[0703] Application of summary generation AI model

[0704] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[0705] Input: Filtered news and promotion information data

[0706] Output: Summarized news and promotional information

[0707] Step 7:

[0708] Providing information

[0709] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser, allowing users to efficiently obtain important food delivery-related information that matches their preferences.

[0710] Input: Summarized news and promotional information

[0711] Output: Data that is communicated and displayed to the user

[0712] 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.

[0713] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[0714] Obtaining user preferences

[0715] Terminal

[0716] The device presents a questionnaire to the user when they first use the device, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data will be used for future news filtering.

[0717] News data collection

[0718] server

[0719] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet, and temporarily stores the collected news data in the server's database.

[0720] News analysis and classification

[0721] server

[0722] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, the text analysis algorithm reads the text of the news article and performs keyword extraction and document clustering.

[0723] News impact assessment

[0724] server

[0725] The server evaluates the impact of classified news on society by using data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the server to quantify how much attention the news is attracting.

[0726] filtering

[0727] server

[0728] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to categories that are of high interest to the user and have a high impact is selected.

[0729] User Emotion Recognition

[0730] Terminal

[0731] The device uses sensors such as cameras and microphones to recognize emotions from the user's facial expressions and voice. The recognized emotion data is labeled as "happiness," "anger," "sadness," etc., and sent to the server in real time.

[0732] News summary generation

[0733] server

[0734] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[0735] Providing news summaries

[0736] Server & Terminal

[0737] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state and is presented with an appropriate tone and content.

[0738] Specific examples

[0739] Example: If the user is interested in "Economy" and "Entertainment"

[0740] First-time setup

[0741] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[0742] News gathering and classification

[0743] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[0744] Filtering and Emotion Recognition

[0745] The server evaluates the impact of the news, filters it, and also receives the user's emotional data. If the user is feeling sad, for example, the tone of the news will be taken into account when displaying it.

[0746] Summary generation and delivery

[0747] The server uses a summary generation AI model to summarize the filtered news concisely and send it to the device. The device receives the news and displays it in a way that takes into account the user's emotions. For example, a summary of the news, such as "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies," is provided to the user based on their emotions.

[0748] This allows users to efficiently obtain and understand news that matches their preferences and current emotions and that will have a significant impact.The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[0749] The processing flow will be explained below.

[0750] Step 1:

[0751] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the news categories that interest them (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data is sent to the server and used for future news filtering.

[0752] Step 2:

[0753] The server periodically visits multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[0754] Step 3:

[0755] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[0756] Step 4:

[0757] The server evaluates the impact of the analyzed news data on society. This evaluation takes into account data such as the number of shares on social media, the number of comments, and the number of views on news sites. The evaluation results are quantified, and the impact of the news is calculated as a number.

[0758] Step 5:

[0759] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that the user is highly interested in and has a high impact is selected. For example, if a user is interested in "economy," news about a "significant rise in the stock market" with a high impact is selected.

[0760] Step 6:

[0761] The device uses sensors (camera and microphone) to analyze the user's facial expressions and voice in real time and recognizes the user's emotions. The recognized emotional data is labeled with, for example, "joy," "anger," or "sadness," and sent to the server.

[0762] Step 7:

[0763] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and generates a short summary such as, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[0764] Step 8:

[0765] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state. For example, if the user is feeling "sad," the news will be displayed in a gentle tone.

[0766] Step 9:

[0767] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[0768] Through the above processing steps, the news summarization system can collect, summarize, and provide appropriate news by taking into account the user's preferences, the impact of the news, and the user's emotions, allowing users to efficiently obtain useful information and solving the problem of information overload.

[0769] Example 2

[0770] 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."

[0771] In modern society, users are exposed to a huge amount of information, making it difficult to quickly and accurately extract information that is useful to them. In particular, when it comes to information such as news, it is necessary to take into account the importance of the content, individual preferences, and even the user's current emotions. This means that there is a demand for systems that allow users to obtain information that is appropriate for them without being overwhelmed by excessive information.

[0772] 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.

[0773] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information based on the user preferences, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the influence of the classified information, means for filtering information based on the user preferences and the influence of the information, means for recognizing the user's emotions, means for summarizing the filtered information using a summary generation AI model, and means for providing the summarized information to the user, thereby enabling the user to efficiently obtain highly influential information that matches their preferences and emotional state.

[0774] "Means for inputting or acquiring user preferences" refers to an interface that allows users to input information about categories or specific content that interest them, or technology that automatically collects preferences from past usage history, etc.

[0775] "Means for collecting relevant information" refers to technology that extracts and collects appropriate data from multiple sources on the Internet based on user preferences.

[0776] "Means of analyzing and classifying using natural language processing technology" refers to the technology of analyzing collected information using natural language processing (NLP) technology and classifying it by content and category.

[0777] "Means for assessing impact" refers to technology that quantifies and evaluates the social attention that classified information receives based on, for example, the number of shares, comments, and views on social media.

[0778] "Means of filtering information" refers to technology that selects appropriate information and eliminates other information based on the user's preferences and the influence of the information.

[0779] "Means for recognizing emotions" refers to technology that uses sensor devices such as cameras and microphones to recognize emotions from the user's facial expressions and voice, and converts them into data in real time.

[0780] "Method of summarizing using a summary generation AI model" refers to a technology that uses an AI (artificial intelligence) summary generation algorithm to summarize long pieces of information in a short and concise manner.

[0781] "Means for providing summarized information to a user" refers to technology that transmits summarized information to a terminal and displays it appropriately in a manner that takes into account the user's emotional state.

[0782] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[0783] The process of acquiring user preferences

[0784] Terminal

[0785] When the device first uses the system, it displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interest. This information is stored on the device and sent to the server.

[0786] Specific examples

[0787] Example prompt: Choose a news category that interests you (e.g., politics, economics, sports, entertainment)

[0788] The user selects "Economy" and "Entertainment." This selection information is saved on the device and sent to the server.

[0789] News data collection process

[0790] server

[0791] The server periodically collects new news data from news APIs, RSS feeds, etc. The server stores the collected news data in a database.

[0792] Specific examples

[0793] The server queries the news API to retrieve news in the economy and entertainment categories.

[0794] The acquired news data is stored in a database.

[0795] News analysis and classification process

[0796] server

[0797] The server uses natural language processing technology to perform text analysis on the stored news data, analyzing the text of news articles and identifying categories and importance through keyword extraction and clustering.

[0798] Specific examples

[0799] The server reads the news article and extracts key keywords and topics.

[0800] News is categorized into categories such as "Economy" and "Entertainment."

[0801] News impact assessment process

[0802] server

[0803] The server evaluates the impact of the collected news based on data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[0804] Specific examples

[0805] The server collects the number of social media shares and views for a particular article.

[0806] These data are used to quantify the impact of news (e.g., "high," "medium," or "low").

[0807] News filtering process

[0808] server

[0809] The server filters news based on the user's preference data and the impact of the news, selecting news articles that have a high impact and match the user's preferences.

[0810] Specific examples

[0811] The server selects news in the "Economy" category that is rated as having a "high" impact.

[0812] Generate a filtered list of news.

[0813] User emotion recognition process

[0814] Terminal

[0815] The device uses a camera and microphone to recognize the user's current emotion from their facial expressions and voice, and then labels the recognition results and sends them to the server.

[0816] Specific examples

[0817] The device captures the user's facial expression with the camera and calls a facial recognition API to determine whether the expression is "sad."

[0818] A request including emotion data is sent to the server.

[0819] News summary generation process

[0820] server

[0821] The server inputs the filtered text of the news article into a summary generation AI model to generate a concise summary of the main points.

[0822] Specific examples

[0823] The server inputs an economic news article stating, "Stock market rises due to new economic policies" into a summary generation AI model.

[0824] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[0825] Summary news delivery process

[0826] Server & Terminal

[0827] The server sends the generated summary news to the terminal, which then displays it to the user. For example, if the user is sad, the tone of the displayed news will be softened.

[0828] Specific examples

[0829] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[0830] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[0831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0832] Step 1:

[0833] Obtaining user preferences

[0834] Terminal

[0835] When the user first uses the system, the terminal displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interests. Based on this input data, the terminal generates the user's preference data and sends it to the server.

[0836] Specific actions

[0837] The device will display the survey screen.

[0838] The user selects "Economy" and "Entertainment."

[0839] The input data is saved on the terminal and sent to the server.

[0840] Step 2:

[0841] News data collection

[0842] server

[0843] The server periodically collects new news data from news APIs, RSS feeds, etc. The news data obtained from these data sources is temporarily stored in the server's database. The input is information from the news APIs and RSS feeds, and the output is news data stored in the server's database.

[0844] Specific actions

[0845] The server queries the news API to get the latest news.

[0846] The acquired news is stored in a database.

[0847] Step 3:

[0848] News analysis and classification

[0849] server

[0850] The server performs text analysis on the stored news data using natural language processing (NLP) technology. The input is the news data stored in the database, and the output is news classified by category and its importance. The text of the news article is analyzed, and keywords are extracted and clustered to identify categories and importance.

[0851] Specific actions

[0852] The server reads the news article and extracts keywords.

[0853] News is categorized into categories such as "Economy" and "Entertainment."

[0854] Step 4:

[0855] News impact assessment

[0856] server

[0857] The server evaluates the impact of classified news based on data such as the number of shares on social media, the number of comments, the number of views on news sites, etc. The input is data such as the number of shares and comments on social media, and the output is news data with a quantified impact.

[0858] Specific actions

[0859] The server collects the number of social media shares and views for a particular article.

[0860] These data are used to quantify the impact (e.g., "high," "medium," or "low").

[0861] Step 5:

[0862] News filtering

[0863] server

[0864] The server filters news based on the user's preference data and the results of the impact assessment. The input is the user's preference data and the results of the impact assessment, and the output is the filtered news data. News articles with high impact and matching the user's preferences are selected.

[0865] Specific actions

[0866] The server selects news in the "Economy" category that is rated as having a "high" impact.

[0867] Generate a filtered list of news.

[0868] Step 6:

[0869] User Emotion Recognition

[0870] Terminal

[0871] The device uses a camera and microphone to recognize the user's current emotion from their facial expression and voice. The input is the user's facial expression and voice, and the output is the recognized emotion data. The recognition results are labeled and sent to the server.

[0872] Specific actions

[0873] The device captures the user's facial expressions using a camera.

[0874] A facial recognition API is called to determine "sadness."

[0875] A request including emotion data is sent to the server.

[0876] Step 7:

[0877] News summary generation

[0878] server

[0879] The server inputs the filtered news article text into a summary generation AI model to generate a concise summary that summarizes the main points. The input is the filtered news article text, and the output is the summarized news.

[0880] Specific actions

[0881] The server inputs a news article stating that "stock market rises due to new economic policies" into a summary generation AI model.

[0882] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[0883] Step 8:

[0884] Providing news summaries

[0885] Server & Terminal

[0886] The server sends the generated summary news to the terminal, which displays it to the user. The input is the summary news, and the output is the summary news provided to the user. In particular, if the user is sad, the tone of the displayed news is made gentler.

[0887] Specific actions

[0888] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[0889] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[0890] (Application example 2)

[0891] 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."

[0892] In modern society, we are overwhelmed with information, making it difficult for users to select the information they need. Furthermore, conventional news delivery systems only consider the user's preferences, and therefore are unable to provide news that reflects the user's current emotional state. This can lead to users being exposed to unpleasant news at inappropriate times, which often leads to stress in information consumption. Therefore, there is a need for a system that provides appropriate news by taking into account not only the user's preferences but also their emotional state.

[0893] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news based on the user preferences, means for analyzing and classifying the collected news using natural language processing technology, means for evaluating the social impact of the classified news, means for filtering the news based on the user preferences and the impact of the news, means for summarizing the filtered news using a summary generation AI model, means for recognizing the user's emotions, means for filtering the news based on the recognized emotions, means for providing the filtered news in a tone that matches the user's emotions, and means for providing the summarized news to the user. This enables more appropriate and less stressful news provision by simultaneously taking into account the user's preferences and emotions.

[0894] "User preferences" refer to the categories, themes, or content that interest a user.

[0895] "Emotion recognition" is a technology that identifies emotions from a user's facial expressions and voice.

[0896] "News gathering" refers to the process of obtaining the latest news data from multiple news sources on the Internet.

[0897] "Natural language processing technology" refers to a set of computer technologies for analyzing text, classifying it, generating summaries, and so on.

[0898] "News influence" is an indicator that evaluates how much attention a news article receives in the public and on social networks.

[0899] "News filtering" is the process of selecting relevant news based on user preferences, news impact, and emotions.

[0900] A "summary generation AI model" is an artificial intelligence technology that extracts important information from news text and generates concise summaries.

[0901] "Tone" refers to the tone and atmosphere of expression used to convey emotions and feelings in news or writing.

[0902] In order to put the present invention into practice, the following system is configured, and corresponding processing is performed at each step.

[0903] System configuration

[0904] The system includes a server, a user terminal, and an internet communication means. The server collects, analyzes, filters, and summarizes news data, while the user terminal acquires preference data and recognizes emotions.

[0905] The specific hardware and software used

[0906] Hardware

[0907] Smartphone camera and microphone: Used for emotion recognition.

[0908] software

[0909] OpenCV: Used to process images captured by the smartphone camera and recognize the user's facial expressions.

[0910] requests: Used to retrieve news data from the news API.

[0911] nltk: Used to perform text analysis and summarization of news articles.

[0912] TextBlob: Used to perform sentence sentiment analysis of news articles.

[0913] transformers: Used to utilize summary generation AI models.

[0914] Program processing flow

[0915] 1. Obtaining user preferences

[0916] When the app is launched for the first time, the user takes a survey, selects the categories that interest them (e.g., politics, economics, sports, entertainment), and saves that information on the device.

[0917] 2. News gathering

[0918] The server collects the latest news data from news sites on the Internet and news APIs (e.g., RSS feeds, news APIs) and temporarily stores it in the server's database.

[0919] 3. Emotion recognition

[0920] Using the smartphone's camera and microphone, the system recognizes emotions from the user's facial expressions and voice. For example, the emotions are labeled as joy, anger, sadness, etc. and sent to the server in real time.

[0921] 4. News analysis and classification

[0922] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news.

[0923] 5. News impact assessment

[0924] The server evaluates the impact of news on society, using data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[0925] 6. News Filtering

[0926] The server filters news based on the user's preferences and the impact of the news, and also selects appropriate news based on the results of emotion recognition.

[0927] 7. News Summarization

[0928] The server inputs the selected news articles into a summary generation AI model to generate concise summaries.

[0929] 8. Displaying News

[0930] The filtered news is presented in a tone that matches the user's emotions. For example, if the user is feeling "sad," the tone of the news will be displayed taking that into account.

[0931] Specific examples

[0932] For example, if a user is interested in "sports" and "entertainment" and is currently feeling "angry," the app will select articles related to sports and entertainment, but with a tone that will ease the user's anger. The specific prompt text is as follows:

[0933] Prompt Sentence Examples

[0934] User Preferences: Sports, Entertainment

[0935] User Emotion: Anger

[0936] News article: 'Football match results, new acting debut'

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

[0938] Step 1:

[0939] When the user's device is first started up, it presents a questionnaire and the user selects the category of interest (e.g., politics, economics, sports, entertainment). The results of this questionnaire are saved on the device as the user's preference data and sent to the server. The input is the results of the questionnaire, and the output is preference data.

[0940] Step 2:

[0941] The server collects the latest news data from news sites and news APIs on the Internet. The collected news data is temporarily stored in the server's database. The input is news sources on the Internet, and the output is the collected news data.

[0942] Step 3:

[0943] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and uses this to recognize emotions. The recognized emotion data is sent to the server in real time. The input is the user's facial expressions and voice data, and the output is the recognized emotion data.

[0944] Step 4:

[0945] The news data collected by the server is analyzed using natural language processing technology to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news. Specifically, a text analysis algorithm is used to read the text of the news article, extract keywords, and perform document clustering. The input is news data, and the output is analytical data with identified categories and importance.

[0946] Step 5:

[0947] The server evaluates how much attention a news article is attracting from around the world. The evaluation uses factors such as the number of shares on social media, the number of comments, and the number of views on news sites. This quantifies the impact of the news. The input is news data and attention data (number of social media shares, number of comments, number of views), and the output is impact assessment data.

[0948] Step 6:

[0949] The server filters news based on the user's preference data and news impact evaluation data. It also takes into account the results of emotion recognition to select news that best suits the user's current emotional state. The input is preference data, impact evaluation data, and emotion data, and the output is filtered news articles.

[0950] Step 7:

[0951] The server inputs the filtered news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in a short sentence format. The input is the filtered news article, and the output is the summarized news text.

[0952] Step 8:

[0953] The server sends the generated summary news to the terminal, which then provides it to the user. The displayed news is presented in a tone that matches the user's emotions. The input is the summary news text, and the output is the news displayed to the user.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] [Third embodiment]

[0958] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0959] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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).

[0964] 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.

[0965] 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.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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."

[0970] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[0971] Obtaining user preferences

[0972] Terminal

[0973] When the terminal is used for the first time, it presents a questionnaire to the user, asking them to enter their preferences. For example, the questionnaire asks questions about news categories such as "politics," "economy," "sports," and "entertainment."

[0974] News data collection

[0975] server

[0976] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet. This collection is performed periodically and updated in real time.

[0977] News analysis and classification

[0978] server

[0979] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the news content, category, importance, and impact.

[0980] News impact assessment

[0981] server

[0982] The server evaluates the impact of the classified news, taking into account metrics such as the number of shares on social media, the number of comments, and the number of views on news sites. This evaluation identifies news that has a large social impact.

[0983] filtering

[0984] server

[0985] The server filters news based on the user's preferences and the impact of the news, and this filtering selects news that is most relevant to the user.

[0986] News summary generation

[0987] server

[0988] The server inputs the selected news into a summary generation AI model, extracts only the important key points, and generates a concise summary, allowing users to quickly grasp the essence of the news.

[0989] Providing news summaries

[0990] Server & Terminal

[0991] The server sends the generated summary news to the device, which receives it, notifies the user, and displays the summary news through an app or web browser.

[0992] Specific examples

[0993] Example: If the user is interested in "Economy" and "Entertainment"

[0994] First-time setup

[0995] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[0996] News gathering and classification

[0997] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[0998] Filtering and Summarization

[0999] The server evaluates the impact of news and selects economic and entertainment news with high impact. The news is then succinctly summarized using a summary generation AI model. For example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[1000] delivery

[1001] The server sends the news summary to the device, where it is displayed to the user via an app or the web.

[1002] This allows users to efficiently obtain and understand news that matches their preferences and has a high impact. The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[1003] The processing flow will be explained below.

[1004] Step 1:

[1005] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is stored on the device. This preference data is used for future news filtering.

[1006] Step 2:

[1007] The server periodically visits multiple news sites and APIs on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[1008] Step 3:

[1009] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[1010] Step 4:

[1011] The server evaluates the impact of classified news on society. This evaluation utilizes data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the amount of attention the news is attracting to be quantified.

[1012] Step 5:

[1013] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that is of high interest to the user and has a high impact is selected.

[1014] Step 6:

[1015] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[1016] Step 7:

[1017] The server sends the generated summary news to the terminal, which receives the information and displays it to the user through an application or web browser. The user can view the summary news displayed on the screen and obtain important information efficiently and quickly.

[1018] Step 8:

[1019] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[1020] Through these processing steps, the news summarization system can collect, summarize, and provide appropriate news, taking into account the user's preferences and the impact of the news, allowing users to efficiently obtain useful information and solving the problem of information overload.

[1021] Example 1

[1022] 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."

[1023] In modern society, information overload makes it difficult to effectively obtain necessary information. It is also difficult to provide useful information tailored to users' interests in a short time. Furthermore, advanced technology is required to efficiently filter, summarize, and provide relevant news and articles, but current systems are unable to fully achieve this. To solve these issues, a system is needed that seamlessly collects, analyzes, summarizes, and provides information based on user preferences.

[1024] 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.

[1025] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the social impact of the classified information, means for filtering information based on the user preferences and the impact of the information, means for summarizing the information filtered by the generative AI model, means for providing the summarized information to the user, means for storing information in a database that saves user preferences, means for periodically acquiring data from news sites and APIs and storing it in the database, means for collecting data indicating impact from social media and web resources, means for calculating a score based on the impact data, means for inputting the acquired text to the generative AI model as a prompt sentence, and means for outputting the summary result to a display device. This allows users to efficiently obtain important news that suits their preferences in a short amount of time.

[1026] "User preferences" refers to information about news categories and topics of interest to a user.

[1027] "Input or acquisition means" refers to a method or device for detecting and recording user preferences.

[1028] "Related information" refers to data such as news and articles collected based on the user's preferences.

[1029] "Natural language processing technology" refers to algorithms and programs that analyze collected information and identify meanings and keywords.

[1030] A "classification means" is a method or device that uses natural language processing technology to separate collected information into categories or topics.

[1031] The "means for assessing the degree of influence" refers to a method or device for quantifying the social influence or response of classified information.

[1032] "Means for filtering information" refers to a method or device for selecting highly relevant information, taking into consideration the user's preferences and the influence of the information.

[1033] A "generative AI model" is an artificial intelligence model for summarizing filtered information.

[1034] A "summarizing means" is a method or device that uses a generative AI model to concisely summarize key points from filtered information.

[1035] "Means for providing" refers to a method or device for transmitting and displaying the summarized information to the user.

[1036] A "database" is an information system for storing preference information and collected news data.

[1037] "News sites and APIs" are web services that provide news data that is publicly available on the Internet.

[1038] "Data indicating impact" refers to metrics that indicate the social impact of news or information, such as the number of shares, comments, and views.

[1039] The "means for calculating a score" refers to a method or device for quantifying the importance or influence of information based on the impact data.

[1040] A "prompt sentence" is the input text provided to a generative AI model and is the sentence that serves as the basis for the summary.

[1041] A "display device" is a display or screen that visually presents the summary results to the user.

[1042] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[1043] First, the device is used to acquire the user's preferences. When the device is used for the first time, it displays a questionnaire screen and presents questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment." The user answers the questionnaire, and the device stores the answers in a database.

[1044] Next, we use a server to collect news data. The server periodically retrieves the latest news data from news sites and APIs (e.g., RSS feeds and news APIs) on the Internet and stores the data in a database. For this task, we can use the Python requests library to efficiently retrieve data from news APIs.

[1045] To analyze and classify the collected news data, the server uses natural language processing technology (e.g., spaCy or NLTK). The server performs text analysis on the news data and generates a topic model (e.g., LDA) to classify the news content into categories. The analysis results are updated in the database.

[1046] To evaluate the impact of classified news, the server collects data indicating impact, such as the number of shares, comments, and views, from social media and news sites. For example, it uses a Python API client (e.g., Tweepy for Twitter) or web scraping technology (e.g., BeautifulSoup). It calculates an impact score based on the collected data and evaluates the impact of each news article.

[1047] To filter important news, the server sorts data based on the user's preferences and the impact of the news. For example, if a user is interested in "Economy" and "Entertainment," high-impact news in these categories will be filtered.

[1048] To summarize the filtered news, the server uses a generative AI model (e.g., OpenAI's GPT-3). Specifically, the text of the news article is input to the generative AI model as a prompt: "Please summarize the following news: XX news content XX." The generated summary is concise and extracts only the important points.

[1049] In providing summarized news, the server sends summary data to the device. The device receives this data and displays it to the user through an app or web browser. For example, a news app can use the notification function to display the summarized news in real time, allowing the user to view it immediately.

[1050] Specific examples

[1051] If the user is interested in "economy" and "entertainment," the device presents the user with a questionnaire and, based on the results, records "economy" and "entertainment" in a preference database. The server collects the day's economy- and entertainment-related news, analyzes it using natural language processing technology, and classifies it into categories. Impact data is collected and, after evaluation, filtered based on the user's preferences. The generative AI model generates a summary of the news in the form of, for example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies." This summary news is sent to the device and notified to the user, where it is displayed in an app or on the web.

[1052] This system allows users to efficiently obtain news that matches their preferences and has a high impact, and to grasp the essence of the news in a short amount of time. This system will realize effective information provision in today's information-overloaded society.

[1053] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1054] Step 1: Get user preferences

[1055] Specific actions

[1056] When the device is used for the first time, a survey screen will be displayed, presenting questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment."

[1057] Input: User's survey response

[1058] Data processing: The terminal extracts the categories selected by the user and formats them as structured data.

[1059] Output: Survey results (user preference information)

[1060] The terminal sends the survey results to the server's database and stores them.

[1061] Step 2: Gathering news data

[1062] Specific actions

[1063] The server periodically retrieves the latest news data from news sites or APIs (e.g., RSS feeds, news APIs).

[1064] Input: News data from various news sites and APIs

[1065] Data processing: The server converts the acquired news data from JSON format to SQL format and stores it in the database.

[1066] Output: News data stored in a database

[1067] Step 3: Analyze and categorize the news

[1068] Specific actions

[1069] The server analyzes the news data using natural language processing techniques (e.g., spaCy or NLTK).

[1070] Input: News data stored in a database

[1071] Data Computation: Analyze news text using natural language processing techniques, generate topic models, and classify news content by category.

[1072] Output: News data categorized by category

[1073] The server updates the analysis results to a database.

[1074] Step 4: News impact assessment

[1075] Specific actions

[1076] The server collects data from social media and news sites that indicates the degree of influence, such as the number of shares, comments, and views.

[1077] Input: Metric data from social media and news sites

[1078] Data calculation: Calculates an impact score based on the collected metrics data.

[1079] Output: News data with influence scores

[1080] The server adds the influence score to the news data and stores it in a database.

[1081] Step 5: Filtering

[1082] Specific actions

[1083] The server filters news based on the user's preferences and the impact of the news.

[1084] Input: User preference information, news data with influence scores

[1085] Data processing: Select highly relevant news based on preference information and impact scores.

[1086] Output: filtered news data

[1087] Step 6: News summary generation

[1088] Specific actions

[1089] The server feeds the filtered news data into a generative AI model (e.g., OpenAI's GPT-3).

[1090] Input: filtered news data

[1091] Data calculation: The prompt sentence "Please summarize the following news: XX news content XX" is provided to the generation AI model to generate a summary.

[1092] Output: Generated summary

[1093] The server stores the generated summary in a database.

[1094] Step 7: Providing a summary of news

[1095] Specific actions

[1096] The server transmits the generated summary news to the terminal.

[1097] Input: Generated news summary

[1098] Data processing: Converting data into a format that is easy for users to view on their devices.

[1099] Output: A news summary displayed to the user

[1100] The terminal outputs the summarized news to the display device and notifies the user.

[1101] Each processing step of the system allows users to efficiently obtain important news summaries that match their preferences.

[1102] (Application example 1)

[1103] 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."

[1104] The amount of information related to modern food delivery services is increasing, making it difficult for users to find important news and promotional information from the vast amount of information. Therefore, there is a need for a system that allows users to efficiently obtain important information that matches their preferences and respond quickly.

[1105] 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.

[1106] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news, means for analyzing and classifying the collected news, means for evaluating the influence of the classified news, means for filtering the news based on preferences and the influence of the news, means for summarizing using a summary generation AI model, means for providing summarized news and promotional information to the user, means for filtering the news and promotional information based on the evaluation score, means for notifying and displaying information that is likely to interest the user, and means for performing these processes using a series of data collected from the Internet, thereby enabling users to efficiently obtain important food delivery-related information that matches their preferences.

[1107] "User preferences" means the interests or concerns a User has regarding particular information or categories.

[1108] A "news gathering method" is a method for automatically obtaining relevant information from multiple sources on the Internet.

[1109] "Natural language processing technology" is a general term for technology that allows computers to understand and analyze human language.

[1110] "Influence" is an indicator that shows the degree of impact that a particular piece of news has on society and users.

[1111] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary information.

[1112] A "summary generation AI model" is an artificial intelligence technology that extracts important information from long pieces of text and summarizes it into short sentences.

[1113] "Promotional Information" refers to information about promotions and campaigns related to particular products or services.

[1114] An "evaluation score" is an index that evaluates an object and quantifies its importance and impact.

[1115] "Data collected from the internet" means information obtained automatically from websites, APIs, etc.

[1116] "Means for notification and display" refers to means for informing users of important information in real time and displaying it on the device.

[1117] This invention is a system that collects, filters, summarizes, and provides food delivery-related news and promotion information based on user preferences. An embodiment of this system will be described.

[1118] A means of obtaining user preferences

[1119] The device presents a questionnaire to the user upon first use, asking them to enter their preferences. The questionnaire consists of questions about categories such as "promotion information," "user reviews," and "industry news."

[1120] A means of gathering news and promotional information

[1121] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically and updated in real time.

[1122] A means of analyzing and classifying news and promotional information

[1123] The server analyzes the collected data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the content, category, and importance of news and promotional information. This process is performed using, for example, the "Summarizer" library.

[1124] Impact assessment tool for news and promotional information

[1125] The server evaluates the impact of the classified data. Specifically, it generates an evaluation score based on metrics such as the number of shares, comments, and views on social media. This evaluation identifies data with a large social impact.

[1126] Filtering Methods

[1127] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[1128] Summarization method using summary generation AI model

[1129] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[1130] A means of providing summary news and promotional information

[1131] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser.

[1132] Specific examples

[1133] Example: For users interested in food delivery

[1134] First-time setup

[1135] The device presents the user with a survey and records that they are interested in "promotional information" and "user reviews."

[1136] Data collection and classification

[1137] The server collects the day's news and promotion information related to food delivery from multiple sources, and uses natural language processing technology to categorize each piece of data into categories such as "promotion information" and "user reviews."

[1138] Filtering and Summarization

[1139] The server evaluates the impact of the data and selects the most influential news and promotional information. The data is then summarized succinctly using a summary generation AI model. For example, "A new promotion has been launched, offering significant discounts to new users."

[1140] delivery

[1141] The summarized information is sent from the server to the terminal, where it is displayed to the user via a dedicated app or the web.

[1142] Prompt Sentence Examples

[1143] "Collect recommended delivery news for Tabelog users. Summarize important information using the latest promotional information and customer reviews. Focus on content that users are likely to be interested in."

[1144] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1145] Step 1:

[1146] Collection of preference data

[1147] The terminal presents a questionnaire to the user when they first use the terminal, and asks them to enter their preference data. The questionnaire includes questions about categories such as "promotion information," "user reviews," and "industry news." The user answers these questions, and the data is sent from the terminal to the server and stored in a database.

[1148] Input: User survey response data

[1149] Output: User preference data stored in a database on the server

[1150] Step 2:

[1151] To collect news and promotional information

[1152] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically, and the latest data is updated in real time.

[1153] Input: Internet news, promotional pages, social media, API

[1154] Output: Latest news and promotion information data stored on the server

[1155] Step 3:

[1156] Data analysis and classification

[1157] The server analyzes the collected data using natural language processing techniques, such as text analysis and clustering, to identify and classify the content, category, and importance of news and promotional information.

[1158] Input: News and promotion information data stored on the server

[1159] Output: Data classified into categories, importance, etc.

[1160] Step 4:

[1161] Impact Assessment

[1162] The server evaluates the impact of the classified data. Specifically, it calculates metrics such as the number of shares, comments, and views on social media, and generates an evaluation score. This evaluation identifies data with a large social impact.

[1163] Input: Categorized news and promotional information data

[1164] Output: Data with impact scores

[1165] Step 5:

[1166] Data filtering

[1167] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[1168] Input: User preference data, news and promotion information data with influence scores

[1169] Output: Filtered news and promotion information data

[1170] Step 6:

[1171] Application of summary generation AI model

[1172] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[1173] Input: Filtered news and promotion information data

[1174] Output: Summarized news and promotional information

[1175] Step 7:

[1176] Providing information

[1177] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser, allowing users to efficiently obtain important food delivery-related information that matches their preferences.

[1178] Input: Summarized news and promotional information

[1179] Output: Data that is communicated and displayed to the user

[1180] 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.

[1181] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[1182] Obtaining user preferences

[1183] Terminal

[1184] The device presents a questionnaire to the user when they first use the device, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data will be used for future news filtering.

[1185] News data collection

[1186] server

[1187] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet, and temporarily stores the collected news data in the server's database.

[1188] News analysis and classification

[1189] server

[1190] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, the text analysis algorithm reads the text of the news article and performs keyword extraction and document clustering.

[1191] News impact assessment

[1192] server

[1193] The server evaluates the impact of classified news on society by using data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the server to quantify how much attention the news is attracting.

[1194] filtering

[1195] server

[1196] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to categories that are of high interest to the user and have a high impact is selected.

[1197] User Emotion Recognition

[1198] Terminal

[1199] The device uses sensors such as cameras and microphones to recognize emotions from the user's facial expressions and voice. The recognized emotion data is labeled as "happiness," "anger," "sadness," etc., and sent to the server in real time.

[1200] News summary generation

[1201] server

[1202] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[1203] Providing news summaries

[1204] Server & Terminal

[1205] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state and is presented with an appropriate tone and content.

[1206] Specific examples

[1207] Example: If the user is interested in "Economy" and "Entertainment"

[1208] First-time setup

[1209] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[1210] News gathering and classification

[1211] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[1212] Filtering and Emotion Recognition

[1213] The server evaluates the impact of the news, filters it, and also receives the user's emotional data. If the user is feeling sad, for example, the tone of the news will be taken into account when displaying it.

[1214] Summary generation and delivery

[1215] The server uses a summary generation AI model to summarize the filtered news concisely and send it to the device. The device receives the news and displays it in a way that takes into account the user's emotions. For example, a summary of the news, such as "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies," is provided to the user based on their emotions.

[1216] This allows users to efficiently obtain and understand news that matches their preferences and current emotions and that will have a significant impact.The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[1217] The processing flow will be explained below.

[1218] Step 1:

[1219] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the news categories that interest them (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data is sent to the server and used for future news filtering.

[1220] Step 2:

[1221] The server periodically visits multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[1222] Step 3:

[1223] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[1224] Step 4:

[1225] The server evaluates the impact of the analyzed news data on society. This evaluation takes into account data such as the number of shares on social media, the number of comments, and the number of views on news sites. The evaluation results are quantified, and the impact of the news is calculated as a number.

[1226] Step 5:

[1227] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that the user is highly interested in and has a high impact is selected. For example, if a user is interested in "economy," news about a "significant rise in the stock market" with a high impact is selected.

[1228] Step 6:

[1229] The device uses sensors (camera and microphone) to analyze the user's facial expressions and voice in real time and recognizes the user's emotions. The recognized emotional data is labeled with, for example, "joy," "anger," or "sadness," and sent to the server.

[1230] Step 7:

[1231] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and generates a short summary such as, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[1232] Step 8:

[1233] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state. For example, if the user is feeling "sad," the news will be displayed in a gentle tone.

[1234] Step 9:

[1235] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[1236] Through the above processing steps, the news summarization system can collect, summarize, and provide appropriate news by taking into account the user's preferences, the impact of the news, and the user's emotions, allowing users to efficiently obtain useful information and solving the problem of information overload.

[1237] Example 2

[1238] 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."

[1239] In modern society, users are exposed to a huge amount of information, making it difficult to quickly and accurately extract information that is useful to them. In particular, when it comes to information such as news, it is necessary to take into account the importance of the content, individual preferences, and even the user's current emotions. This means that there is a demand for systems that allow users to obtain information that is appropriate for them without being overwhelmed by excessive information.

[1240] 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.

[1241] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information based on the user preferences, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the influence of the classified information, means for filtering information based on the user preferences and the influence of the information, means for recognizing the user's emotions, means for summarizing the filtered information using a summary generation AI model, and means for providing the summarized information to the user, thereby enabling the user to efficiently obtain highly influential information that matches their preferences and emotional state.

[1242] "Means for inputting or acquiring user preferences" refers to an interface that allows users to input information about categories or specific content that interest them, or technology that automatically collects preferences from past usage history, etc.

[1243] "Means for collecting relevant information" refers to technology that extracts and collects appropriate data from multiple sources on the Internet based on user preferences.

[1244] "Means of analyzing and classifying using natural language processing technology" refers to the technology of analyzing collected information using natural language processing (NLP) technology and classifying it by content and category.

[1245] "Means for assessing impact" refers to technology that quantifies and evaluates the social attention that classified information receives based on, for example, the number of shares, comments, and views on social media.

[1246] "Means of filtering information" refers to technology that selects appropriate information and eliminates other information based on the user's preferences and the influence of the information.

[1247] "Means for recognizing emotions" refers to technology that uses sensor devices such as cameras and microphones to recognize emotions from the user's facial expressions and voice, and converts them into data in real time.

[1248] "Method of summarizing using a summary generation AI model" refers to a technology that uses an AI (artificial intelligence) summary generation algorithm to summarize long pieces of information in a short and concise manner.

[1249] "Means for providing summarized information to a user" refers to technology that transmits summarized information to a terminal and displays it appropriately in a manner that takes into account the user's emotional state.

[1250] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[1251] The process of acquiring user preferences

[1252] Terminal

[1253] When the device first uses the system, it displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interest. This information is stored on the device and sent to the server.

[1254] Specific examples

[1255] Example prompt: Choose a news category that interests you (e.g., politics, economics, sports, entertainment)

[1256] The user selects "Economy" and "Entertainment." This selection information is saved on the device and sent to the server.

[1257] News data collection process

[1258] server

[1259] The server periodically collects new news data from news APIs, RSS feeds, etc. The server stores the collected news data in a database.

[1260] Specific examples

[1261] The server queries the news API to retrieve news in the economy and entertainment categories.

[1262] The acquired news data is stored in a database.

[1263] News analysis and classification process

[1264] server

[1265] The server uses natural language processing technology to perform text analysis on the stored news data, analyzing the text of news articles and identifying categories and importance through keyword extraction and clustering.

[1266] Specific examples

[1267] The server reads the news article and extracts key keywords and topics.

[1268] News is categorized into categories such as "Economy" and "Entertainment."

[1269] News impact assessment process

[1270] server

[1271] The server evaluates the impact of the collected news based on data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[1272] Specific examples

[1273] The server collects the number of social media shares and views for a particular article.

[1274] These data are used to quantify the impact of news (e.g., "high," "medium," or "low").

[1275] News filtering process

[1276] server

[1277] The server filters news based on the user's preference data and the impact of the news, selecting news articles that have a high impact and match the user's preferences.

[1278] Specific examples

[1279] The server selects news in the "Economy" category that is rated as having a "high" impact.

[1280] Generate a filtered list of news.

[1281] User emotion recognition process

[1282] Terminal

[1283] The device uses a camera and microphone to recognize the user's current emotion from their facial expressions and voice, and then labels the recognition results and sends them to the server.

[1284] Specific examples

[1285] The device captures the user's facial expression with the camera and calls a facial recognition API to determine whether the expression is "sad."

[1286] A request including emotion data is sent to the server.

[1287] News summary generation process

[1288] server

[1289] The server inputs the filtered text of the news article into a summary generation AI model to generate a concise summary of the main points.

[1290] Specific examples

[1291] The server inputs an economic news article stating, "Stock market rises due to new economic policies" into a summary generation AI model.

[1292] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[1293] Summary news delivery process

[1294] Server & Terminal

[1295] The server sends the generated summary news to the terminal, which then displays it to the user. For example, if the user is sad, the tone of the displayed news will be softened.

[1296] Specific examples

[1297] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[1298] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[1299] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1300] Step 1:

[1301] Obtaining user preferences

[1302] Terminal

[1303] When the user first uses the system, the terminal displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interests. Based on this input data, the terminal generates the user's preference data and sends it to the server.

[1304] Specific actions

[1305] The device will display the survey screen.

[1306] The user selects "Economy" and "Entertainment."

[1307] The input data is saved on the terminal and sent to the server.

[1308] Step 2:

[1309] News data collection

[1310] server

[1311] The server periodically collects new news data from news APIs, RSS feeds, etc. The news data obtained from these data sources is temporarily stored in the server's database. The input is information from the news APIs and RSS feeds, and the output is news data stored in the server's database.

[1312] Specific actions

[1313] The server queries the news API to get the latest news.

[1314] The acquired news is stored in a database.

[1315] Step 3:

[1316] News analysis and classification

[1317] server

[1318] The server performs text analysis on the stored news data using natural language processing (NLP) technology. The input is the news data stored in the database, and the output is news classified by category and its importance. The text of the news article is analyzed, and keywords are extracted and clustered to identify categories and importance.

[1319] Specific actions

[1320] The server reads the news article and extracts keywords.

[1321] News is categorized into categories such as "Economy" and "Entertainment."

[1322] Step 4:

[1323] News impact assessment

[1324] server

[1325] The server evaluates the impact of classified news based on data such as the number of shares on social media, the number of comments, the number of views on news sites, etc. The input is data such as the number of shares and comments on social media, and the output is news data with a quantified impact.

[1326] Specific actions

[1327] The server collects the number of social media shares and views for a particular article.

[1328] These data are used to quantify the impact (e.g., "high," "medium," or "low").

[1329] Step 5:

[1330] News filtering

[1331] server

[1332] The server filters news based on the user's preference data and the results of the impact assessment. The input is the user's preference data and the results of the impact assessment, and the output is the filtered news data. News articles with high impact and matching the user's preferences are selected.

[1333] Specific actions

[1334] The server selects news in the "Economy" category that is rated as having a "high" impact.

[1335] Generate a filtered list of news.

[1336] Step 6:

[1337] User Emotion Recognition

[1338] Terminal

[1339] The device uses a camera and microphone to recognize the user's current emotion from their facial expression and voice. The input is the user's facial expression and voice, and the output is the recognized emotion data. The recognition results are labeled and sent to the server.

[1340] Specific actions

[1341] The device captures the user's facial expressions using a camera.

[1342] A facial recognition API is called to determine "sadness."

[1343] A request including emotion data is sent to the server.

[1344] Step 7:

[1345] News summary generation

[1346] server

[1347] The server inputs the filtered news article text into a summary generation AI model to generate a concise summary that summarizes the main points. The input is the filtered news article text, and the output is the summarized news.

[1348] Specific actions

[1349] The server inputs a news article stating that "stock market rises due to new economic policies" into a summary generation AI model.

[1350] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[1351] Step 8:

[1352] Providing news summaries

[1353] Server & Terminal

[1354] The server sends the generated summary news to the terminal, which displays it to the user. The input is the summary news, and the output is the summary news provided to the user. In particular, if the user is sad, the tone of the displayed news is made gentler.

[1355] Specific actions

[1356] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[1357] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[1358] (Application example 2)

[1359] 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."

[1360] In modern society, we are overwhelmed with information, making it difficult for users to select the information they need. Furthermore, conventional news delivery systems only consider the user's preferences, and therefore are unable to provide news that reflects the user's current emotional state. This can lead to users being exposed to unpleasant news at inappropriate times, which often leads to stress in information consumption. Therefore, there is a need for a system that provides appropriate news by taking into account not only the user's preferences but also their emotional state.

[1361] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news based on the user preferences, means for analyzing and classifying the collected news using natural language processing technology, means for evaluating the social impact of the classified news, means for filtering the news based on the user preferences and the impact of the news, means for summarizing the filtered news using a summary generation AI model, means for recognizing the user's emotions, means for filtering the news based on the recognized emotions, means for providing the filtered news in a tone that matches the user's emotions, and means for providing the summarized news to the user. This enables more appropriate and less stressful news provision by simultaneously taking into account the user's preferences and emotions.

[1362] "User preferences" refer to the categories, themes, or content that interest a user.

[1363] "Emotion recognition" is a technology that identifies emotions from a user's facial expressions and voice.

[1364] "News gathering" refers to the process of obtaining the latest news data from multiple news sources on the Internet.

[1365] "Natural language processing technology" refers to a set of computer technologies for analyzing text, classifying it, generating summaries, and so on.

[1366] "News influence" is an indicator that evaluates how much attention a news article receives in the public and on social networks.

[1367] "News filtering" is the process of selecting relevant news based on user preferences, news impact, and emotions.

[1368] A "summary generation AI model" is an artificial intelligence technology that extracts important information from news text and generates concise summaries.

[1369] "Tone" refers to the tone and atmosphere of expression used to convey emotions and feelings in news or writing.

[1370] In order to put the present invention into practice, the following system is configured, and corresponding processing is performed at each step.

[1371] System configuration

[1372] The system includes a server, a user terminal, and an internet communication means. The server collects, analyzes, filters, and summarizes news data, while the user terminal acquires preference data and recognizes emotions.

[1373] The specific hardware and software used

[1374] Hardware

[1375] Smartphone camera and microphone: Used for emotion recognition.

[1376] software

[1377] OpenCV: Used to process images captured by the smartphone camera and recognize the user's facial expressions.

[1378] requests: Used to retrieve news data from the news API.

[1379] nltk: Used to perform text analysis and summarization of news articles.

[1380] TextBlob: Used to perform sentence sentiment analysis of news articles.

[1381] transformers: Used to utilize summary generation AI models.

[1382] Program processing flow

[1383] 1. Obtaining user preferences

[1384] When the app is launched for the first time, the user takes a survey, selects the categories that interest them (e.g., politics, economics, sports, entertainment), and saves that information on the device.

[1385] 2. News gathering

[1386] The server collects the latest news data from news sites on the Internet and news APIs (e.g., RSS feeds, news APIs) and temporarily stores it in the server's database.

[1387] 3. Emotion recognition

[1388] Using the smartphone's camera and microphone, the system recognizes emotions from the user's facial expressions and voice. For example, the emotions are labeled as joy, anger, sadness, etc. and sent to the server in real time.

[1389] 4. News analysis and classification

[1390] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news.

[1391] 5. News impact assessment

[1392] The server evaluates the impact of news on society, using data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[1393] 6. News Filtering

[1394] The server filters news based on the user's preferences and the impact of the news, and also selects appropriate news based on the results of emotion recognition.

[1395] 7. News Summarization

[1396] The server inputs the selected news articles into a summary generation AI model to generate concise summaries.

[1397] 8. Displaying News

[1398] The filtered news is presented in a tone that matches the user's emotions. For example, if the user is feeling "sad," the tone of the news will be displayed taking that into account.

[1399] Specific examples

[1400] For example, if a user is interested in "sports" and "entertainment" and is currently feeling "angry," the app will select articles related to sports and entertainment, but with a tone that will ease the user's anger. The specific prompt text is as follows:

[1401] Prompt Sentence Examples

[1402] User Preferences: Sports, Entertainment

[1403] User Emotion: Anger

[1404] News article: 'Football match results, new acting debut'

[1405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1406] Step 1:

[1407] When the user's device is first started up, it presents a questionnaire and the user selects the category of interest (e.g., politics, economics, sports, entertainment). The results of this questionnaire are saved on the device as the user's preference data and sent to the server. The input is the results of the questionnaire, and the output is preference data.

[1408] Step 2:

[1409] The server collects the latest news data from news sites and news APIs on the Internet. The collected news data is temporarily stored in the server's database. The input is news sources on the Internet, and the output is the collected news data.

[1410] Step 3:

[1411] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and uses this to recognize emotions. The recognized emotion data is sent to the server in real time. The input is the user's facial expressions and voice data, and the output is the recognized emotion data.

[1412] Step 4:

[1413] The news data collected by the server is analyzed using natural language processing technology to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news. Specifically, a text analysis algorithm is used to read the text of the news article, extract keywords, and perform document clustering. The input is news data, and the output is analytical data with identified categories and importance.

[1414] Step 5:

[1415] The server evaluates how much attention a news article is attracting from around the world. The evaluation uses factors such as the number of shares on social media, the number of comments, and the number of views on news sites. This quantifies the impact of the news. The input is news data and attention data (number of social media shares, number of comments, number of views), and the output is impact assessment data.

[1416] Step 6:

[1417] The server filters news based on the user's preference data and news impact evaluation data. It also takes into account the results of emotion recognition to select news that best suits the user's current emotional state. The input is preference data, impact evaluation data, and emotion data, and the output is filtered news articles.

[1418] Step 7:

[1419] The server inputs the filtered news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in a short sentence format. The input is the filtered news article, and the output is the summarized news text.

[1420] Step 8:

[1421] The server sends the generated summary news to the terminal, which then provides it to the user. The displayed news is presented in a tone that matches the user's emotions. The input is the summary news text, and the output is the news displayed to the user.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] [Fourth embodiment]

[1426] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1427] 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.

[1428] 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).

[1429] 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.

[1430] 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.

[1431] 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).

[1432] 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.

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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."

[1439] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[1440] Obtaining user preferences

[1441] Terminal

[1442] When the terminal is used for the first time, it presents a questionnaire to the user, asking them to enter their preferences. For example, the questionnaire asks questions about news categories such as "politics," "economy," "sports," and "entertainment."

[1443] News data collection

[1444] server

[1445] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet. This collection is performed periodically and updated in real time.

[1446] News analysis and classification

[1447] server

[1448] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the news content, category, importance, and impact.

[1449] News impact assessment

[1450] server

[1451] The server evaluates the impact of the classified news, taking into account metrics such as the number of shares on social media, the number of comments, and the number of views on news sites. This evaluation identifies news that has a large social impact.

[1452] filtering

[1453] server

[1454] The server filters news based on the user's preferences and the impact of the news, and this filtering selects news that is most relevant to the user.

[1455] News summary generation

[1456] server

[1457] The server inputs the selected news into a summary generation AI model, extracts only the important key points, and generates a concise summary, allowing users to quickly grasp the essence of the news.

[1458] Providing news summaries

[1459] Server & Terminal

[1460] The server sends the generated summary news to the device, which receives it, notifies the user, and displays the summary news through an app or web browser.

[1461] Specific examples

[1462] Example: If the user is interested in "Economy" and "Entertainment"

[1463] First-time setup

[1464] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[1465] News gathering and classification

[1466] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[1467] Filtering and Summarization

[1468] The server evaluates the impact of news and selects economic and entertainment news with high impact. The news is then succinctly summarized using a summary generation AI model. For example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[1469] delivery

[1470] The server sends the news summary to the device, where it is displayed to the user via an app or the web.

[1471] This allows users to efficiently obtain and understand news that matches their preferences and has a high impact. The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[1472] The processing flow will be explained below.

[1473] Step 1:

[1474] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is stored on the device. This preference data is used for future news filtering.

[1475] Step 2:

[1476] The server periodically visits multiple news sites and APIs on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[1477] Step 3:

[1478] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[1479] Step 4:

[1480] The server evaluates the impact of classified news on society. This evaluation utilizes data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the amount of attention the news is attracting to be quantified.

[1481] Step 5:

[1482] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that is of high interest to the user and has a high impact is selected.

[1483] Step 6:

[1484] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[1485] Step 7:

[1486] The server sends the generated summary news to the terminal, which receives the information and displays it to the user through an application or web browser. The user can view the summary news displayed on the screen and obtain important information efficiently and quickly.

[1487] Step 8:

[1488] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[1489] Through these processing steps, the news summarization system can collect, summarize, and provide appropriate news, taking into account the user's preferences and the impact of the news, allowing users to efficiently obtain useful information and solving the problem of information overload.

[1490] Example 1

[1491] 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."

[1492] In modern society, information overload makes it difficult to effectively obtain necessary information. It is also difficult to provide useful information tailored to users' interests in a short time. Furthermore, advanced technology is required to efficiently filter, summarize, and provide relevant news and articles, but current systems are unable to fully achieve this. To solve these issues, a system is needed that seamlessly collects, analyzes, summarizes, and provides information based on user preferences.

[1493] 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.

[1494] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the social impact of the classified information, means for filtering information based on the user preferences and the impact of the information, means for summarizing the information filtered by the generative AI model, means for providing the summarized information to the user, means for storing information in a database that saves user preferences, means for periodically acquiring data from news sites and APIs and storing it in the database, means for collecting data indicating impact from social media and web resources, means for calculating a score based on the impact data, means for inputting the acquired text to the generative AI model as a prompt sentence, and means for outputting the summary result to a display device. This allows users to efficiently obtain important news that suits their preferences in a short amount of time.

[1495] "User preferences" refers to information about news categories and topics of interest to a user.

[1496] "Input or acquisition means" refers to a method or device for detecting and recording user preferences.

[1497] "Related information" refers to data such as news and articles collected based on the user's preferences.

[1498] "Natural language processing technology" refers to algorithms and programs that analyze collected information and identify meanings and keywords.

[1499] A "classification means" is a method or device that uses natural language processing technology to separate collected information into categories or topics.

[1500] The "means for assessing the degree of influence" refers to a method or device for quantifying the social influence or response of classified information.

[1501] "Means for filtering information" refers to a method or device for selecting highly relevant information, taking into consideration the user's preferences and the influence of the information.

[1502] A "generative AI model" is an artificial intelligence model for summarizing filtered information.

[1503] A "summarizing means" is a method or device that uses a generative AI model to concisely summarize key points from filtered information.

[1504] "Means for providing" refers to a method or device for transmitting and displaying the summarized information to the user.

[1505] A "database" is an information system for storing preference information and collected news data.

[1506] "News sites and APIs" are web services that provide news data that is publicly available on the Internet.

[1507] "Data indicating impact" refers to metrics that indicate the social impact of news or information, such as the number of shares, comments, and views.

[1508] The "means for calculating a score" refers to a method or device for quantifying the importance or influence of information based on the impact data.

[1509] A "prompt sentence" is the input text provided to a generative AI model and is the sentence that serves as the basis for the summary.

[1510] A "display device" is a display or screen that visually presents the summary results to the user.

[1511] This invention relates to a news summarization system, and more particularly to a system that collects, filters, summarizes, and provides news while taking into account user preferences and the impact of the news. Hereinafter, an embodiment of this system will be described.

[1512] First, the device is used to acquire the user's preferences. When the device is used for the first time, it displays a questionnaire screen and presents questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment." The user answers the questionnaire, and the device stores the answers in a database.

[1513] Next, we use a server to collect news data. The server periodically retrieves the latest news data from news sites and APIs (e.g., RSS feeds and news APIs) on the Internet and stores the data in a database. For this task, we can use the Python requests library to efficiently retrieve data from news APIs.

[1514] To analyze and classify the collected news data, the server uses natural language processing technology (e.g., spaCy or NLTK). The server performs text analysis on the news data and generates a topic model (e.g., LDA) to classify the news content into categories. The analysis results are updated in the database.

[1515] To evaluate the impact of classified news, the server collects data indicating impact, such as the number of shares, comments, and views, from social media and news sites. For example, it uses a Python API client (e.g., Tweepy for Twitter) or web scraping technology (e.g., BeautifulSoup). It calculates an impact score based on the collected data and evaluates the impact of each news article.

[1516] To filter important news, the server sorts data based on the user's preferences and the impact of the news. For example, if a user is interested in "Economy" and "Entertainment," high-impact news in these categories will be filtered.

[1517] To summarize the filtered news, the server uses a generative AI model (e.g., OpenAI's GPT-3). Specifically, the text of the news article is input to the generative AI model as a prompt: "Please summarize the following news: XX news content XX." The generated summary is concise and extracts only the important points.

[1518] In providing summarized news, the server sends summary data to the device. The device receives this data and displays it to the user through an app or web browser. For example, a news app can use the notification function to display the summarized news in real time, allowing the user to view it immediately.

[1519] Specific examples

[1520] If the user is interested in "economy" and "entertainment," the device presents the user with a questionnaire and, based on the results, records "economy" and "entertainment" in a preference database. The server collects the day's economy- and entertainment-related news, analyzes it using natural language processing technology, and classifies it into categories. Impact data is collected and, after evaluation, filtered based on the user's preferences. The generative AI model generates a summary of the news in the form of, for example, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies." This summary news is sent to the device and notified to the user, where it is displayed in an app or on the web.

[1521] This system allows users to efficiently obtain news that matches their preferences and has a high impact, and to grasp the essence of the news in a short amount of time. This system will realize effective information provision in today's information-overloaded society.

[1522] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1523] Step 1: Get user preferences

[1524] Specific actions

[1525] When the device is used for the first time, a survey screen will be displayed, presenting questions about news categories such as "Politics," "Economy," "Sports," and "Entertainment."

[1526] Input: User's survey response

[1527] Data processing: The terminal extracts the categories selected by the user and formats them as structured data.

[1528] Output: Survey results (user preference information)

[1529] The terminal sends the survey results to the server's database and stores them.

[1530] Step 2: Gathering news data

[1531] Specific actions

[1532] The server periodically retrieves the latest news data from news sites or APIs (e.g., RSS feeds, news APIs).

[1533] Input: News data from various news sites and APIs

[1534] Data processing: The server converts the acquired news data from JSON format to SQL format and stores it in the database.

[1535] Output: News data stored in a database

[1536] Step 3: Analyze and categorize the news

[1537] Specific actions

[1538] The server analyzes the news data using natural language processing techniques (e.g., spaCy or NLTK).

[1539] Input: News data stored in a database

[1540] Data Computation: Analyze news text using natural language processing techniques, generate topic models, and classify news content by category.

[1541] Output: News data categorized by category

[1542] The server updates the analysis results to a database.

[1543] Step 4: News impact assessment

[1544] Specific actions

[1545] The server collects data from social media and news sites that indicates the degree of influence, such as the number of shares, comments, and views.

[1546] Input: Metric data from social media and news sites

[1547] Data calculation: Calculates an impact score based on the collected metrics data.

[1548] Output: News data with influence scores

[1549] The server adds the influence score to the news data and stores it in a database.

[1550] Step 5: Filtering

[1551] Specific actions

[1552] The server filters news based on the user's preferences and the impact of the news.

[1553] Input: User preference information, news data with influence scores

[1554] Data processing: Select highly relevant news based on preference information and impact scores.

[1555] Output: filtered news data

[1556] Step 6: News summary generation

[1557] Specific actions

[1558] The server feeds the filtered news data into a generative AI model (e.g., OpenAI's GPT-3).

[1559] Input: filtered news data

[1560] Data calculation: The prompt sentence "Please summarize the following news: XX news content XX" is provided to the generation AI model to generate a summary.

[1561] Output: Generated summary

[1562] The server stores the generated summary in a database.

[1563] Step 7: Providing a summary of news

[1564] Specific actions

[1565] The server transmits the generated summary news to the terminal.

[1566] Input: Generated news summary

[1567] Data processing: Converting data into a format that is easy for users to view on their devices.

[1568] Output: A news summary displayed to the user

[1569] The terminal outputs the summarized news to the display device and notifies the user.

[1570] Each processing step of the system allows users to efficiently obtain important news summaries that match their preferences.

[1571] (Application example 1)

[1572] 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."

[1573] The amount of information related to modern food delivery services is increasing, making it difficult for users to find important news and promotional information from the vast amount of information. Therefore, there is a need for a system that allows users to efficiently obtain important information that matches their preferences and respond quickly.

[1574] 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.

[1575] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news, means for analyzing and classifying the collected news, means for evaluating the influence of the classified news, means for filtering the news based on preferences and the influence of the news, means for summarizing using a summary generation AI model, means for providing summarized news and promotional information to the user, means for filtering the news and promotional information based on the evaluation score, means for notifying and displaying information that is likely to interest the user, and means for performing these processes using a series of data collected from the Internet, thereby enabling users to efficiently obtain important food delivery-related information that matches their preferences.

[1576] "User preferences" means the interests or concerns a User has regarding particular information or categories.

[1577] A "news gathering method" is a method for automatically obtaining relevant information from multiple sources on the Internet.

[1578] "Natural language processing technology" is a general term for technology that allows computers to understand and analyze human language.

[1579] "Influence" is an indicator that shows the degree of impact that a particular piece of news has on society and users.

[1580] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary information.

[1581] A "summary generation AI model" is an artificial intelligence technology that extracts important information from long pieces of text and summarizes it into short sentences.

[1582] "Promotional Information" refers to information about promotions and campaigns related to particular products or services.

[1583] An "evaluation score" is an index that evaluates an object and quantifies its importance and impact.

[1584] "Data collected from the internet" means information obtained automatically from websites, APIs, etc.

[1585] "Means for notification and display" refers to means for informing users of important information in real time and displaying it on the device.

[1586] This invention is a system that collects, filters, summarizes, and provides food delivery-related news and promotion information based on user preferences. An embodiment of this system will be described.

[1587] A means of obtaining user preferences

[1588] The device presents a questionnaire to the user upon first use, asking them to enter their preferences. The questionnaire consists of questions about categories such as "promotion information," "user reviews," and "industry news."

[1589] A means of gathering news and promotional information

[1590] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically and updated in real time.

[1591] A means of analyzing and classifying news and promotional information

[1592] The server analyzes the collected data using natural language processing techniques (e.g., text analysis, clustering) to identify and classify the content, category, and importance of news and promotional information. This process is performed using, for example, the "Summarizer" library.

[1593] Impact assessment tool for news and promotional information

[1594] The server evaluates the impact of the classified data. Specifically, it generates an evaluation score based on metrics such as the number of shares, comments, and views on social media. This evaluation identifies data with a large social impact.

[1595] Filtering Methods

[1596] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[1597] Summarization method using summary generation AI model

[1598] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[1599] A means of providing summary news and promotional information

[1600] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser.

[1601] Specific examples

[1602] Example: For users interested in food delivery

[1603] First-time setup

[1604] The device presents the user with a survey and records that they are interested in "promotional information" and "user reviews."

[1605] Data collection and classification

[1606] The server collects the day's news and promotion information related to food delivery from multiple sources, and uses natural language processing technology to categorize each piece of data into categories such as "promotion information" and "user reviews."

[1607] Filtering and Summarization

[1608] The server evaluates the impact of the data and selects the most influential news and promotional information. The data is then summarized succinctly using a summary generation AI model. For example, "A new promotion has been launched, offering significant discounts to new users."

[1609] delivery

[1610] The summarized information is sent from the server to the terminal, where it is displayed to the user via a dedicated app or the web.

[1611] Prompt Sentence Examples

[1612] "Collect recommended delivery news for Tabelog users. Summarize important information using the latest promotional information and customer reviews. Focus on content that users are likely to be interested in."

[1613] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1614] Step 1:

[1615] Collection of preference data

[1616] The terminal presents a questionnaire to the user when they first use the terminal, and asks them to enter their preference data. The questionnaire includes questions about categories such as "promotion information," "user reviews," and "industry news." The user answers these questions, and the data is sent from the terminal to the server and stored in a database.

[1617] Input: User survey response data

[1618] Output: User preference data stored in a database on the server

[1619] Step 2:

[1620] To collect news and promotional information

[1621] The server collects the latest information related to food delivery from multiple news sites, promotion pages, SNS, and APIs (e.g., RSS feeds, promotion information APIs) on the Internet. This collection is performed periodically, and the latest data is updated in real time.

[1622] Input: Internet news, promotional pages, social media, API

[1623] Output: Latest news and promotion information data stored on the server

[1624] Step 3:

[1625] Data analysis and classification

[1626] The server analyzes the collected data using natural language processing techniques, such as text analysis and clustering, to identify and classify the content, category, and importance of news and promotional information.

[1627] Input: News and promotion information data stored on the server

[1628] Output: Data classified into categories, importance, etc.

[1629] Step 4:

[1630] Impact Assessment

[1631] The server evaluates the impact of the classified data. Specifically, it calculates metrics such as the number of shares, comments, and views on social media, and generates an evaluation score. This evaluation identifies data with a large social impact.

[1632] Input: Categorized news and promotional information data

[1633] Output: Data with impact scores

[1634] Step 5:

[1635] Data filtering

[1636] The server filters the data based on the user's preferences and rating scores, allowing it to select news and promotional information that is most relevant to the user.

[1637] Input: User preference data, news and promotion information data with influence scores

[1638] Output: Filtered news and promotion information data

[1639] Step 6:

[1640] Application of summary generation AI model

[1641] The server inputs the selected data into a summary generation AI model, extracts only the important key points, and generates a concise summary. This process uses pre-set prompts to control the generation AI model.

[1642] Input: Filtered news and promotion information data

[1643] Output: Summarized news and promotional information

[1644] Step 7:

[1645] Providing information

[1646] The server sends the generated summary to the device, which receives it, notifies the user, and displays the data through a dedicated app or web browser, allowing users to efficiently obtain important food delivery-related information that matches their preferences.

[1647] Input: Summarized news and promotional information

[1648] Output: Data that is communicated and displayed to the user

[1649] 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.

[1650] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[1651] Obtaining user preferences

[1652] Terminal

[1653] The device presents a questionnaire to the user when they first use the device, asking them to enter their preferences. The user selects the categories of interest (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data will be used for future news filtering.

[1654] News data collection

[1655] server

[1656] The server collects the latest news data from multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet, and temporarily stores the collected news data in the server's database.

[1657] News analysis and classification

[1658] server

[1659] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, the text analysis algorithm reads the text of the news article and performs keyword extraction and document clustering.

[1660] News impact assessment

[1661] server

[1662] The server evaluates the impact of classified news on society by using data such as the number of shares on social media, the number of comments, and the number of views on news sites. This allows the server to quantify how much attention the news is attracting.

[1663] filtering

[1664] server

[1665] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to categories that are of high interest to the user and have a high impact is selected.

[1666] User Emotion Recognition

[1667] Terminal

[1668] The device uses sensors such as cameras and microphones to recognize emotions from the user's facial expressions and voice. The recognized emotion data is labeled as "happiness," "anger," "sadness," etc., and sent to the server in real time.

[1669] News summary generation

[1670] server

[1671] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in short sentences.

[1672] Providing news summaries

[1673] Server & Terminal

[1674] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state and is presented with an appropriate tone and content.

[1675] Specific examples

[1676] Example: If the user is interested in "Economy" and "Entertainment"

[1677] First-time setup

[1678] The device presents the user with a questionnaire and records that they are interested in "economy" and "entertainment."

[1679] News gathering and classification

[1680] The server collects the day's economic and entertainment news from multiple news sites, and each news item is classified into a category such as "Economy" or "Entertainment" using natural language processing technology.

[1681] Filtering and Emotion Recognition

[1682] The server evaluates the impact of the news, filters it, and also receives the user's emotional data. If the user is feeling sad, for example, the tone of the news will be taken into account when displaying it.

[1683] Summary generation and delivery

[1684] The server uses a summary generation AI model to summarize the filtered news concisely and send it to the device. The device receives the news and displays it in a way that takes into account the user's emotions. For example, a summary of the news, such as "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies," is provided to the user based on their emotions.

[1685] This allows users to efficiently obtain and understand news that matches their preferences and current emotions and that will have a significant impact.The system of the present invention has the effect of providing useful information in a short amount of time in today's information-overloaded society.

[1686] The processing flow will be explained below.

[1687] Step 1:

[1688] The device presents a questionnaire to the user, asking them to enter their preferences. The user selects the news categories that interest them (e.g., politics, economics, sports, entertainment), and the information is saved on the device. This preference data is sent to the server and used for future news filtering.

[1689] Step 2:

[1690] The server periodically visits multiple news sites and APIs (e.g., RSS feeds, news APIs) on the Internet to collect the latest news data, which is then temporarily stored in the server's database.

[1691] Step 3:

[1692] The server analyzes the collected news data using natural language processing technology to identify the content, category (e.g., economy, sports), and importance of the news. Specifically, a text analysis algorithm reads the text of the news article, extracts keywords, and clusters documents.

[1693] Step 4:

[1694] The server evaluates the impact of the analyzed news data on society. This evaluation takes into account data such as the number of shares on social media, the number of comments, and the number of views on news sites. The evaluation results are quantified, and the impact of the news is calculated as a number.

[1695] Step 5:

[1696] The server filters news based on the user's preferences and the impact of the news. In this process, news that belongs to a category that the user is highly interested in and has a high impact is selected. For example, if a user is interested in "economy," news about a "significant rise in the stock market" with a high impact is selected.

[1697] Step 6:

[1698] The device uses sensors (camera and microphone) to analyze the user's facial expressions and voice in real time and recognizes the user's emotions. The recognized emotional data is labeled with, for example, "joy," "anger," or "sadness," and sent to the server.

[1699] Step 7:

[1700] The server inputs the selected news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and generates a short summary such as, "The stock market is showing a significant rise. The main cause is believed to be the impact of new economic policies."

[1701] Step 8:

[1702] The server sends the generated news summary to the device, which receives the information and displays it to the user through an application or web browser. The news provided takes into account the user's current emotional state. For example, if the user is feeling "sad," the news will be displayed in a gentle tone.

[1703] Step 9:

[1704] The device periodically collects user feedback and records changes in preferences. Users provide feedback on the displayed news, such as "interested" or "not interested," and this data is used to filter the content for future visits.

[1705] Through the above processing steps, the news summarization system can collect, summarize, and provide appropriate news by taking into account the user's preferences, the impact of the news, and the user's emotions, allowing users to efficiently obtain useful information and solving the problem of information overload.

[1706] Example 2

[1707] 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."

[1708] In modern society, users are exposed to a huge amount of information, making it difficult to quickly and accurately extract information that is useful to them. In particular, when it comes to information such as news, it is necessary to take into account the importance of the content, individual preferences, and even the user's current emotions. This means that there is a demand for systems that allow users to obtain information that is appropriate for them without being overwhelmed by excessive information.

[1709] 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.

[1710] In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related information based on the user preferences, means for analyzing and classifying the collected information using natural language processing technology, means for evaluating the influence of the classified information, means for filtering information based on the user preferences and the influence of the information, means for recognizing the user's emotions, means for summarizing the filtered information using a summary generation AI model, and means for providing the summarized information to the user, thereby enabling the user to efficiently obtain highly influential information that matches their preferences and emotional state.

[1711] "Means for inputting or acquiring user preferences" refers to an interface that allows users to input information about categories or specific content that interest them, or technology that automatically collects preferences from past usage history, etc.

[1712] "Means for collecting relevant information" refers to technology that extracts and collects appropriate data from multiple sources on the Internet based on user preferences.

[1713] "Means of analyzing and classifying using natural language processing technology" refers to the technology of analyzing collected information using natural language processing (NLP) technology and classifying it by content and category.

[1714] "Means for assessing impact" refers to technology that quantifies and evaluates the social attention that classified information receives based on, for example, the number of shares, comments, and views on social media.

[1715] "Means of filtering information" refers to technology that selects appropriate information and eliminates other information based on the user's preferences and the influence of the information.

[1716] "Means for recognizing emotions" refers to technology that uses sensor devices such as cameras and microphones to recognize emotions from the user's facial expressions and voice, and converts them into data in real time.

[1717] "Method of summarizing using a summary generation AI model" refers to a technology that uses an AI (artificial intelligence) summary generation algorithm to summarize long pieces of information in a short and concise manner.

[1718] "Means for providing summarized information to a user" refers to technology that transmits summarized information to a terminal and displays it appropriately in a manner that takes into account the user's emotional state.

[1719] This invention combines a news summarization system with an emotion engine that recognizes user emotions, and relates to a system that collects, filters, summarizes, and provides news while taking into account the user's preferences, the impact of the news, and the user's emotions. Below, we will explain an embodiment of this system.

[1720] The process of acquiring user preferences

[1721] Terminal

[1722] When the device first uses the system, it displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interest. This information is stored on the device and sent to the server.

[1723] Specific examples

[1724] Example prompt: Choose a news category that interests you (e.g., politics, economics, sports, entertainment)

[1725] The user selects "Economy" and "Entertainment." This selection information is saved on the device and sent to the server.

[1726] News data collection process

[1727] server

[1728] The server periodically collects new news data from news APIs, RSS feeds, etc. The server stores the collected news data in a database.

[1729] Specific examples

[1730] The server queries the news API to retrieve news in the economy and entertainment categories.

[1731] The acquired news data is stored in a database.

[1732] News analysis and classification process

[1733] server

[1734] The server uses natural language processing technology to perform text analysis on the stored news data, analyzing the text of news articles and identifying categories and importance through keyword extraction and clustering.

[1735] Specific examples

[1736] The server reads the news article and extracts key keywords and topics.

[1737] News is categorized into categories such as "Economy" and "Entertainment."

[1738] News impact assessment process

[1739] server

[1740] The server evaluates the impact of the collected news based on data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[1741] Specific examples

[1742] The server collects the number of social media shares and views for a particular article.

[1743] These data are used to quantify the impact of news (e.g., "high," "medium," or "low").

[1744] News filtering process

[1745] server

[1746] The server filters news based on the user's preference data and the impact of the news, selecting news articles that have a high impact and match the user's preferences.

[1747] Specific examples

[1748] The server selects news in the "Economy" category that is rated as having a "high" impact.

[1749] Generate a filtered list of news.

[1750] User emotion recognition process

[1751] Terminal

[1752] The device uses a camera and microphone to recognize the user's current emotion from their facial expressions and voice, and then labels the recognition results and sends them to the server.

[1753] Specific examples

[1754] The device captures the user's facial expression with the camera and calls a facial recognition API to determine whether the expression is "sad."

[1755] A request including emotion data is sent to the server.

[1756] News summary generation process

[1757] server

[1758] The server inputs the filtered text of the news article into a summary generation AI model to generate a concise summary of the main points.

[1759] Specific examples

[1760] The server inputs an economic news article stating, "Stock market rises due to new economic policies" into a summary generation AI model.

[1761] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[1762] Summary news delivery process

[1763] Server & Terminal

[1764] The server sends the generated summary news to the terminal, which then displays it to the user. For example, if the user is sad, the tone of the displayed news will be softened.

[1765] Specific examples

[1766] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[1767] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[1768] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1769] Step 1:

[1770] Obtaining user preferences

[1771] Terminal

[1772] When the user first uses the system, the terminal displays a questionnaire screen and asks the user to select their preferred news category (e.g., politics, economy, sports, entertainment). The user clicks on the options on the screen to express their interests. Based on this input data, the terminal generates the user's preference data and sends it to the server.

[1773] Specific actions

[1774] The device will display the survey screen.

[1775] The user selects "Economy" and "Entertainment."

[1776] The input data is saved on the terminal and sent to the server.

[1777] Step 2:

[1778] News data collection

[1779] server

[1780] The server periodically collects new news data from news APIs, RSS feeds, etc. The news data obtained from these data sources is temporarily stored in the server's database. The input is information from the news APIs and RSS feeds, and the output is news data stored in the server's database.

[1781] Specific actions

[1782] The server queries the news API to get the latest news.

[1783] The acquired news is stored in a database.

[1784] Step 3:

[1785] News analysis and classification

[1786] server

[1787] The server performs text analysis on the stored news data using natural language processing (NLP) technology. The input is the news data stored in the database, and the output is news classified by category and its importance. The text of the news article is analyzed, and keywords are extracted and clustered to identify categories and importance.

[1788] Specific actions

[1789] The server reads the news article and extracts keywords.

[1790] News is categorized into categories such as "Economy" and "Entertainment."

[1791] Step 4:

[1792] News impact assessment

[1793] server

[1794] The server evaluates the impact of classified news based on data such as the number of shares on social media, the number of comments, the number of views on news sites, etc. The input is data such as the number of shares and comments on social media, and the output is news data with a quantified impact.

[1795] Specific actions

[1796] The server collects the number of social media shares and views for a particular article.

[1797] These data are used to quantify the impact (e.g., "high," "medium," or "low").

[1798] Step 5:

[1799] News filtering

[1800] server

[1801] The server filters news based on the user's preference data and the results of the impact assessment. The input is the user's preference data and the results of the impact assessment, and the output is the filtered news data. News articles with high impact and matching the user's preferences are selected.

[1802] Specific actions

[1803] The server selects news in the "Economy" category that is rated as having a "high" impact.

[1804] Generate a filtered list of news.

[1805] Step 6:

[1806] User Emotion Recognition

[1807] Terminal

[1808] The device uses a camera and microphone to recognize the user's current emotion from their facial expression and voice. The input is the user's facial expression and voice, and the output is the recognized emotion data. The recognition results are labeled and sent to the server.

[1809] Specific actions

[1810] The device captures the user's facial expressions using a camera.

[1811] A facial recognition API is called to determine "sadness."

[1812] A request including emotion data is sent to the server.

[1813] Step 7:

[1814] News summary generation

[1815] server

[1816] The server inputs the filtered news article text into a summary generation AI model to generate a concise summary that summarizes the main points. The input is the filtered news article text, and the output is the summarized news.

[1817] Specific actions

[1818] The server inputs a news article stating that "stock market rises due to new economic policies" into a summary generation AI model.

[1819] The summary generation AI model generates the summary "The stock market is rising due to the influence of new economic policies."

[1820] Step 8:

[1821] Providing news summaries

[1822] Server & Terminal

[1823] The server sends the generated summary news to the terminal, which displays it to the user. The input is the summary news, and the output is the summary news provided to the user. In particular, if the user is sad, the tone of the displayed news is made gentler.

[1824] Specific actions

[1825] The server sends a summary news item "Stock market rises due to new economic policies" to the terminal.

[1826] The device receives the news and displays the emotion of "sadness" to the user in a considerate, gentle tone.

[1827] (Application example 2)

[1828] 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."

[1829] In modern society, we are overwhelmed with information, making it difficult for users to select the information they need. Furthermore, conventional news delivery systems only consider the user's preferences, and therefore are unable to provide news that reflects the user's current emotional state. This can lead to users being exposed to unpleasant news at inappropriate times, which often leads to stress in information consumption. Therefore, there is a need for a system that provides appropriate news by taking into account not only the user's preferences but also their emotional state.

[1830] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting or acquiring user preferences, means for collecting related news based on the user preferences, means for analyzing and classifying the collected news using natural language processing technology, means for evaluating the social impact of the classified news, means for filtering the news based on the user preferences and the impact of the news, means for summarizing the filtered news using a summary generation AI model, means for recognizing the user's emotions, means for filtering the news based on the recognized emotions, means for providing the filtered news in a tone that matches the user's emotions, and means for providing the summarized news to the user. This enables more appropriate and less stressful news provision by simultaneously taking into account the user's preferences and emotions.

[1831] "User preferences" refer to the categories, themes, or content that interest a user.

[1832] "Emotion recognition" is a technology that identifies emotions from a user's facial expressions and voice.

[1833] "News gathering" refers to the process of obtaining the latest news data from multiple news sources on the Internet.

[1834] "Natural language processing technology" refers to a set of computer technologies for analyzing text, classifying it, generating summaries, and so on.

[1835] "News influence" is an indicator that evaluates how much attention a news article receives in the public and on social networks.

[1836] "News filtering" is the process of selecting relevant news based on user preferences, news impact, and emotions.

[1837] A "summary generation AI model" is an artificial intelligence technology that extracts important information from news text and generates concise summaries.

[1838] "Tone" refers to the tone and atmosphere of expression used to convey emotions and feelings in news or writing.

[1839] In order to put the present invention into practice, the following system is configured, and corresponding processing is performed at each step.

[1840] System configuration

[1841] The system includes a server, a user terminal, and an internet communication means. The server collects, analyzes, filters, and summarizes news data, while the user terminal acquires preference data and recognizes emotions.

[1842] The specific hardware and software used

[1843] Hardware

[1844] Smartphone camera and microphone: Used for emotion recognition.

[1845] software

[1846] OpenCV: Used to process images captured by the smartphone camera and recognize the user's facial expressions.

[1847] requests: Used to retrieve news data from the news API.

[1848] nltk: Used to perform text analysis and summarization of news articles.

[1849] TextBlob: Used to perform sentence sentiment analysis of news articles.

[1850] transformers: Used to utilize summary generation AI models.

[1851] Program processing flow

[1852] 1. Obtaining user preferences

[1853] When the app is launched for the first time, the user takes a survey, selects the categories that interest them (e.g., politics, economics, sports, entertainment), and saves that information on the device.

[1854] 2. News gathering

[1855] The server collects the latest news data from news sites on the Internet and news APIs (e.g., RSS feeds, news APIs) and temporarily stores it in the server's database.

[1856] 3. Emotion recognition

[1857] Using the smartphone's camera and microphone, the system recognizes emotions from the user's facial expressions and voice. For example, the emotions are labeled as joy, anger, sadness, etc. and sent to the server in real time.

[1858] 4. News analysis and classification

[1859] The server analyzes the collected news data using natural language processing techniques (e.g., text analysis, clustering) to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news.

[1860] 5. News impact assessment

[1861] The server evaluates the impact of news on society, using data such as the number of shares on social media, the number of comments, and the number of views on news sites.

[1862] 6. News Filtering

[1863] The server filters news based on the user's preferences and the impact of the news, and also selects appropriate news based on the results of emotion recognition.

[1864] 7. News Summarization

[1865] The server inputs the selected news articles into a summary generation AI model to generate concise summaries.

[1866] 8. Displaying News

[1867] The filtered news is presented in a tone that matches the user's emotions. For example, if the user is feeling "sad," the tone of the news will be displayed taking that into account.

[1868] Specific examples

[1869] For example, if a user is interested in "sports" and "entertainment" and is currently feeling "angry," the app will select articles related to sports and entertainment, but with a tone that will ease the user's anger. The specific prompt text is as follows:

[1870] Prompt Sentence Examples

[1871] User Preferences: Sports, Entertainment

[1872] User Emotion: Anger

[1873] News article: 'Football match results, new acting debut'

[1874] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1875] Step 1:

[1876] When the user's device is first started up, it presents a questionnaire and the user selects the category of interest (e.g., politics, economics, sports, entertainment). The results of this questionnaire are saved on the device as the user's preference data and sent to the server. The input is the results of the questionnaire, and the output is preference data.

[1877] Step 2:

[1878] The server collects the latest news data from news sites and news APIs on the Internet. The collected news data is temporarily stored in the server's database. The input is news sources on the Internet, and the output is the collected news data.

[1879] Step 3:

[1880] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and uses this to recognize emotions. The recognized emotion data is sent to the server in real time. The input is the user's facial expressions and voice data, and the output is the recognized emotion data.

[1881] Step 4:

[1882] The news data collected by the server is analyzed using natural language processing technology to identify the content, category (e.g., politics, economics, sports, entertainment), and importance of the news. Specifically, a text analysis algorithm is used to read the text of the news article, extract keywords, and perform document clustering. The input is news data, and the output is analytical data with identified categories and importance.

[1883] Step 5:

[1884] The server evaluates how much attention a news article is attracting from around the world. The evaluation uses factors such as the number of shares on social media, the number of comments, and the number of views on news sites. This quantifies the impact of the news. The input is news data and attention data (number of social media shares, number of comments, number of views), and the output is impact assessment data.

[1885] Step 6:

[1886] The server filters news based on the user's preference data and news impact evaluation data. It also takes into account the results of emotion recognition to select news that best suits the user's current emotional state. The input is preference data, impact evaluation data, and emotion data, and the output is filtered news articles.

[1887] Step 7:

[1888] The server inputs the filtered news articles into a summary generation AI model to generate a concise summary. The summary generation AI model extracts important key points from the news text and summarizes them concisely in a short sentence format. The input is the filtered news article, and the output is the summarized news text.

[1889] Step 8:

[1890] The server sends the generated summary news to the terminal, which then provides it to the user. The displayed news is presented in a tone that matches the user's emotions. The input is the summary news text, and the output is the news displayed to the user.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] 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.

[1895] 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.

[1896] 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.

[1897] 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).

[1898] 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.

[1899] 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."

[1900] 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.

[1901] 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).

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] 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.

[1909] 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.

[1910] 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.

[1911] 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.

[1912] The following is further disclosed regarding the above embodiment.

[1913] (Claim 1)

[1914] a means for inputting or obtaining user preferences;

[1915] means for collecting relevant news based on the user's preferences;

[1916] A means for analyzing and classifying the collected news using natural language processing technology;

[1917] A means for evaluating the impact of the classified news on society;

[1918] means for filtering news based on user preferences and news impact;

[1919] A means for summarizing the filtered news using a summary generation AI model;

[1920] A system including means for providing said summarized news to a user.

[1921] (Claim 2)

[1922] 10. The system of claim 1, further comprising means for setting preferences based on initial user input.

[1923] (Claim 3)

[1924] 10. The system of claim 1, further comprising means for periodically or ad-hoc updating user preferences.

[1925] (Claim 4)

[1926] 10. The system of claim 1, further comprising means for taking into account the number of shares, comments, and views of the news on social media when calculating the impact of the news.

[1927] (Claim 5)

[1928] 2. The system according to claim 1, further comprising means for determining a priority of news to be provided to the user based on the user's preference and the impact of the news.

[1929] "Example 1"

[1930] (Claim 1)

[1931] a means for inputting or obtaining user preferences;

[1932] means for collecting relevant information based on the user's preferences;

[1933] A means for analyzing and classifying the collected information using natural language processing techniques;

[1934] A means for evaluating the impact of the classified information on society;

[1935] means for filtering information based on user preferences and the impact of the information;

[1936] A means for summarizing the filtered information using a generative AI model; and

[1937] means for providing said summarized information to a user;

[1938] means for storing the information in a database that stores user preferences;

[1939] A method to periodically retrieve data from news sites and APIs and store it in a database,

[1940] A means of collecting data showing the degree of impact from social media and web resources,

[1941] means for calculating a score based on the impact data;

[1942] A means for inputting the obtained text into a generative AI model as a prompt sentence;

[1943] means for outputting the summary result to a display device;

[1944] A system including:

[1945] (Claim 2)

[1946] 10. The system of claim 1, further comprising means for setting preferences based on initial user input.

[1947] (Claim 3)

[1948] 10. The system of claim 1, further comprising means for periodically or ad-hoc updating user preferences.

[1949] "Application Example 1"

[1950] (Claim 1)

[1951] a means for inputting or obtaining user preferences;

[1952] means for collecting relevant news based on the user's preferences;

[1953] A means for analyzing and classifying the collected news using natural language processing technology;

[1954] A means for evaluating the impact of the classified news on society;

[1955] means for filtering news based on user preferences and news impact;

[1956] A means for summarizing the filtered news using a summary generation AI model;

[1957] means for providing said summarized news and promotional information to a user;

[1958] means for filtering the news and promotion information based on a rating score;

[1959] A means of notifying and displaying information that is likely to be of interest to users;

[1960] A system including a means for utilizing a set of data collected from the Internet and carrying out these processes.

[1961] (Claim 2)

[1962] 10. The system of claim 1, further comprising means for setting preferences based on initial user input.

[1963] (Claim 3)

[1964] 10. The system of claim 1, further comprising means for periodically or ad-hoc updating user preferences.

[1965] "Example 2: Combining Emotion Engines"

[1966] (Claim 1)

[1967] a means for inputting or obtaining user preferences;

[1968] means for collecting relevant information based on the user's preferences;

[1969] A means for analyzing and classifying the collected information using natural language processing techniques;

[1970] means for evaluating the impact of the classified information;

[1971] means for filtering information based on user preferences and the impact of the information;

[1972] a means for recognizing a user's emotion;

[1973] A means for summarizing the filtered information using a summary generation AI model;

[1974] means for providing said summarized information to a user.

[1975] (Claim 2)

[1976] 10. The system of claim 1, further comprising means for setting preferences based on initial user input.

[1977] (Claim 3)

[1978] 10. The system of claim 1, further comprising means for periodically or ad-hoc updating user preferences.

[1979] "Application example 2 when combining emotion engines"

[1980] (Claim 1)

[1981] a means for inputting or obtaining user preferences;

[1982] means for collecting relevant news based on the user's preferences;

[1983] A means for analyzing and classifying the collected news using natural language processing technology;

[1984] A means for evaluating the impact of the classified news on society;

[1985] means for filtering news based on user preferences and news impact;

[1986] A means for summarizing the filtered news using a summary generation AI model;

[1987] a means for recognizing a user's emotion;

[1988] means for filtering news based on the recognized sentiment;

[1989] A means for providing the filtered news in a tone that matches the user's emotions;

[1990] A system including means for providing said summarized news to a user.

[1991] (Claim 2)

[1992] 10. The system of claim 1, further comprising means for setting preferences based on initial user input and means for recognizing emotions.

[1993] (Claim 3)

[1994] 10. The system of claim 1, further comprising means for periodically or occasionally updating user preferences and means for updating emotion data. [Explanation of symbols]

[1995] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting or obtaining user preferences; means for collecting relevant news based on the user's preferences; A means for analyzing and classifying the collected news using natural language processing technology; A means for evaluating the impact of the classified news on society; means for filtering news based on user preferences and news impact; A means for summarizing the filtered news using a summary generation AI model; A system including means for providing said summarized news to a user.

2. 10. The system of claim 1, further comprising means for setting preferences based on initial user input.

3. 10. The system of claim 1, further comprising means for periodically or ad-hoc updating user preferences.

4. The system of claim 1 , further comprising: means for taking into account the number of shares, comments, and views of the news on social media when calculating the impact of the news.

5. 2. The system according to claim 1, further comprising means for determining the priority of news to be provided to the user based on the user's preferences and the impact of the news.

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