System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining data from a designated source; means for analyzing the obtained data to extract key information; means for summarizing the extracted key information; means for formatting the summarized information into a report format; and means for transmitting the formatted report to a user terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's information society, gathering news and trend information is an important task, but manually collecting that information and creating summary reports poses a significant challenge: it takes a great deal of time and effort. In industries such as finance, where the latest news summary reports are required first thing in the morning, the workload is particularly heavy. Furthermore, there is a need for a method to process information efficiently while ensuring its reliability and accuracy. Therefore, there is a need for a system that solves these challenges and automates and streamlines the gathering of news and trend information and the creation of summary reports. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for acquiring data from specified information sources, a means for analyzing the acquired data to extract key information, a means for summarizing the extracted key information, a means for formatting the summarized information into a report, and a means for transmitting the formatted report to a user terminal. Furthermore, the present invention includes a means for shaping the summarized information into a specific format, thereby enabling reports to be provided in a format that is easily understandable to users. Furthermore, the present invention includes a means for managing access rights when acquiring data from specified information sources, ensuring security and reliability. In this way, the present invention provides a system that efficiently and automatically collects, summarizes, and creates reports on news and trend information, significantly reducing the workload of users.

[0006] "Specified sources" refers to news sites, databases, or other online sources identified by the user.

[0007] "Means for obtaining data" refers to the programs and technologies used to access designated sources and collect the required information.

[0008] "Means of analysis and extraction of key information" refers to the algorithms and methods used to identify and extract key information from collected data.

[0009] "Means of summarization" refers to natural language processing techniques and machine learning models that shorten and concisely summarize extracted information.

[0010] "Report formatting means" refers to templates or programs that format the summarized information in a format that is easy for users to understand.

[0011] "Means for sending to user terminal" refers to the communication means or protocol for delivering the generated report to the user.

[0012] "Formatting tools" refers to programs or techniques that further modify and arrange the summarized information in a particular format or style.

[0013] "Access authority management means" refers to a system or method for providing appropriate authentication and access control when retrieving data from designated sources. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] System configuration

[0036] The present invention is a system for acquiring data from a specified information source, analyzing the acquired data to extract key information, summarizing the extracted key information, formatting the summarized information into a report, and transmitting the formatted report to a user terminal. The system may further include means for formatting the summarized information into a specific format and means for managing access rights when acquiring data from a specified information source. This system is implemented by a server, a terminal, and a user working together.

[0037] System Operation

[0038] Specifying the news URL

[0039] Subject: User

[0040] The user specifies the URL of a news source using a terminal and sends it to the system. For example, the user enters a URL such as "https: / / example-news-site.com" in an input form on a browser and presses the send button.

[0041] News Gathering Requests

[0042] Subject: Terminal

[0043] The device sends a request containing the news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[0044] News gathering

[0045] Subject: Server

[0046] The server accesses the sent news URL and collects the news article. The server parses the HTML content and extracts the headline of the news article. For this purpose, an HTML parsing library such as BeautifulSoup can be used.

[0047] Summary Generation

[0048] Subject: Server

[0049] The server sends the extracted headlines as a summary generation request to a generative AI (e.g., GPT-3 (registered trademark)). The server combines multiple headlines and uses a generative AI model to summarize the key information. This allows for a concise summary of the key points of the news article.

[0050] Report Format

[0051] Subject: Server

[0052] The server formats the generated summary into a report, for example adding headers and timestamps to make it user-friendly. The report formatting is done according to a predefined template.

[0053] Report submission

[0054] Subject: Server

[0055] The server sends the completed report to the user's terminal, where the generated report is delivered to the user using an HTTP response or email.

[0056] Check the report

[0057] Subject: User

[0058] The user checks the received report on the device. The user browses the contents of the report on the device screen and obtains the necessary information. This allows the user to grasp important news information in a short amount of time.

[0059] Specific examples

[0060] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[0061] 1. The user enters a URL into the browser's input form and submits it.

[0062] 2. The device sends a news gathering request to the server.

[0063] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[0064] 4. The server requests the generation AI to summarize the extracted headlines.

[0065] 5. Generative AI generates a summary.

[0066] 6. The server formats the generated summary into a report.

[0067] 7. The server sends the report to the user's device.

[0068] 8. The user checks the report on the device.

[0069] In this way, this system allows users to obtain news summary reports efficiently and quickly, significantly reducing the burden of information gathering and report creation.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] Subject: User

[0073] The user specifies the news source URL using the device's browser. Specifically, the user enters "https: / / example-news-site.com" into the browser's input form and presses the send button.

[0074] Step 2:

[0075] Subject: Terminal

[0076] The device sends a request containing the specified news URL to the server, which uses the HTTP protocol and serves as a request to retrieve data from the news source.

[0077] Step 3:

[0078] Subject: Server

[0079] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0080] Step 4:

[0081] Subject: Server

[0082] Parse the HTML content retrieved by the server. Specifically, use an HTML parsing library such as BeautifulSoup to extract news article headlines (e.g., <h2>Extract the text inside the tag.

[0083] Step 5:

[0084] Subject: Server

[0085] The server combines the extracted headlines and sends a summary generation request to the generation AI (e.g., GPT-3). Multiple headlines are combined into a single text and sent as a complete summary request to the generation AI.

[0086] Step 6:

[0087] Subject: Generative AI model (e.g., GPT-3)

[0088] The generative AI model extracts important elements from the input text and generates a summary, which is then sent back to the server.

[0089] Step 7:

[0090] Subject: Server

[0091] The server receives the generated summary and formats it into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[0092] Step 8:

[0093] Subject: Server

[0094] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0095] Step 9:

[0096] Subject: User

[0097] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0098] This series of processes allows users to obtain news summary reports efficiently in a short time, significantly reducing the burden of information gathering and report creation.

[0099] Example 1

[0100] 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."

[0101] In today's information-saturated society, it is difficult for users to efficiently obtain the information they need. It also requires a great deal of effort to summarize the key information from a large amount of information, such as news articles, and understand it quickly. Furthermore, the process of organizing the obtained information into a user-friendly format is also cumbersome, and there is a need for a means to automate these tasks.

[0102] 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.

[0103] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, and means for summarizing the extracted key information using a generative AI model. This allows the server to efficiently extract and summarize key parts from large amounts of information such as news articles, enabling users to grasp important information in a short amount of time.

[0104] A "specified information source" is a source from which data is obtained, such as a URL entered by a user or a database.

[0105] "Means of obtaining data" refers to the methods and processes used to collect the required data from designated sources.

[0106] "Means of analyzing data and extracting key information" refers to methods and techniques for analyzing collected data and selecting important or necessary information.

[0107] "Generative AI model" refers to an algorithm or system used to generate, summarize, or analyze text or information using artificial intelligence techniques.

[0108] "Summarization methods" refer to methods and techniques for shortening the extracted key information and reconstructing it in a way that includes only the important points.

[0109] "Means for formatting into a report format" refers to a method or technique for formatting summarized information so that it is easy for a user to read, and compiling it into a report in a specified format.

[0110] "User terminal" refers to a device such as a computer or smartphone that a user uses to operate the system.

[0111] "Access rights management measures" refers to the methods and processes for verifying, approving, and managing the rights required to obtain data from designated sources.

[0112] The present invention provides a system that allows users to efficiently collect key information from information sources such as news sites and receive summarized reports. This system is implemented by a server, terminals, and users working together.

[0113] First, the user specifies the URL of a news source using the device. For example, they enter a URL such as "https: / / example-news-site.com" using an input form on the browser and press the send button. This URL is then sent from the device to the server.

[0114] The server then accesses the specified news URL and collects the news article. The server retrieves the HTML data using an HTTP request and parses the HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[0115] The extracted headlines are sent from the server to a generative AI model (e.g., GPT-3 by OpenAI (registered trademark)). A prompt sentence is used as input to the generative AI model. An example of a prompt sentence is "Please generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'." Based on this prompt sentence, the generative AI model summarizes the important information and returns the results to the server.

[0116] The server then formats the generated summary into a report, according to a predefined template, adding headers and the date and time of generation for user readability, and then sends the report in a specific format to the user's device.

[0117] Finally, the user checks the received report on the terminal. The user can view the report contents on the terminal screen and quickly grasp the necessary information.

[0118] This system allows users to efficiently extract key information from vast amounts of news content and receive summarized reports, significantly improving the efficiency of information gathering and report creation.

[0119] The hardware required to implement the specific operation of this system includes high-performance computers and cloud services as servers, and personal computers and smartphones as user devices.The software used includes HTML analysis libraries such as BeautifulSoup, libraries for HTTP communication, and GPT-3 as a generative AI model.

[0120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0121] Step 1: Specify the news URL

[0122] Subject: User

[0123] The user specifies the URL of a news source using a terminal. Specifically, the user enters the URL "https: / / example-news-site.com" into the browser's input form and presses the submit button. This operation sends the URL to the system.

[0124] Input: URL of the news source (e.g. "https: / / example-news-site.com")

[0125] Output: A request sent from the device to the server for the specified URL

[0126] Step 2: Submit a newsgathering request

[0127] Subject: Terminal

[0128] The device sends a request including a news URL to the server. This request uses the HTTP protocol to obtain data from the news source. Specifically, an HTTP GET request is generated that includes the URL and user information.

[0129] Input: The specified URL (e.g. "https: / / example-news-site.com")

[0130] Output: A newsgathering request is sent to the server

[0131] Step 3: Gathering news

[0132] Subject: Server

[0133] The server accesses the received news URL and collects the news article. It retrieves the HTML data using an HTTP request and parses the retrieved HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[0134] Input: Newsgathering request (HTTP GET request)

[0135] Output: HTML data and extracted news headlines

[0136] Step 4: Summary generation

[0137] Subject: Server

[0138] The server compiles the extracted headlines, generates a prompt based on the summary, and sends it to a generative AI model (e.g., OpenAI GPT-3). The generative AI model then generates a summary based on the prompt.

[0139] Input: Extracted news headlines (e.g. "Headline 1, Headline 2, Headline 3")

[0140] Output: A summary generated by a generative AI model (e.g., "Generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'")

[0141] Step 5: Format the report

[0142] Subject: Server

[0143] The server formats the generated summary into a report by reading a template, inserting the generated summary at the appropriate position, adding headers and the date and time of generation, according to a predefined template.

[0144] Input: Generated summary

[0145] Output: Reports according to a standard format

[0146] Step 6: Submit the report

[0147] Subject: Server

[0148] The server sends the completed report to the user's terminal. The generated report is delivered to the user using an HTTP response or email. Specifically, if the report is returned as an HTTP response, it is returned in JSON or HTML format, and if it is sent by email, it is sent to the specified email address using the SMTP protocol.

[0149] Input: Formatted report

[0150] Output: Sending the report to the user's terminal

[0151] Step 7: Review the report

[0152] Subject: User

[0153] The user checks the received report on the device, for example, by opening the received report using a browser or email client and displaying its contents.

[0154] Input: Report sent to terminal

[0155] Output: User views the report and gets the information they need.

[0156] In this way, each step works in conjunction with the other steps, allowing the user to efficiently obtain a news summary report.

[0157] (Application example 1)

[0158] 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."

[0159] In modern society, there is a need to efficiently collect, summarize, and visualize important information from a vast number of sources. However, manually organizing and summarizing news articles and information is time-consuming and labor-intensive. It is also difficult to monitor multiple sources at once and extract important information in real time. Furthermore, a method is needed for users to easily browse summarized information and instantly obtain the information they need.

[0160] 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.

[0161] In this invention, the server includes means for acquiring data from specified information sources, means for analyzing the acquired data to extract key information, means for summarizing the extracted key information using a generative AI model, means for formatting the summarized information into a report, and means for transmitting the formatted report to a user terminal, thereby enabling a user to quickly summarize and acquire important information from multiple information sources and efficiently manage information on a daily basis.

[0162] A "designated information source" is an information provider designated by a user to obtain specific data.

[0163] "Means of acquiring data" means the mechanisms or systems used to collect data from designated sources.

[0164] "Means for analyzing data" refers to techniques and methods for analyzing acquired data and determining key information.

[0165] "Key information extraction" is the process for selecting important information from the analyzed data.

[0166] A "generative AI model" refers to an algorithm or computational model that uses artificial intelligence to process data and generate a result.

[0167] "Summarization methods" are techniques or methods for concisely summarizing extracted information.

[0168] A "report formatting means" is a method for displaying summarized information in a certain format.

[0169] A "user terminal" is a device that allows a user to receive and manipulate information.

[0170] "Transmitting means" refers to a method for sending data from the server to the user terminal.

[0171] The "means for checking" is a method by which the user views the information received at the terminal and checks the content.

[0172] System configuration and functions

[0173] As an embodiment of the present invention, we will specifically exemplify a system that extracts key information from news sources, summarizes it, and provides it to users. This system mainly consists of three elements: a server, a terminal, and a user.

[0174] News source registration

[0175] Subject: User

[0176] Users register the URL of a news site they are interested in in the application on their device by entering a URL such as "https: / / example-news-site.com" in the input form and pressing the submit button.

[0177] Data acquisition and analysis

[0178] Subject: Server

[0179] The server accesses the specified news URL and collects news articles. The server uses a library such as BeautifulSoup to parse the HTML content and extracts the article headlines and body text.

[0180] Summary Generation

[0181] Subject: Server

[0182] The server sends the extracted news article headlines and text to a generative AI model (e.g., GPT-3) to summarize the key information. The generative AI model generates a summary using a prompt sentence.

[0183] Prompt Sentence Examples

[0184] text

[0185] Generate a summary of a news article. Title: Example News Article Title

[0186] Body: Example news article body content, which includes various details and information about the event.

[0187] summary:

[0188] Report Format

[0189] Subject: Server

[0190] The server formats the generated summary into a report, following a predefined template, adding headers and the date and time of generation to make it user-friendly.

[0191] Report submission and confirmation

[0192] Subject: Server

[0193] The server sends the completed report to the user's device. The generated report is delivered to the user's device using HTTP responses, push notifications, or email.

[0194] Subject: User

[0195] Users can check the received reports on their devices. Using their smartphones or tablets, users can easily view summarized news reports and obtain the information they need.

[0196] Hardware and software used

[0197] The main hardware required to realize this system includes a server and a user device. The server is equipped with a high-performance processor and large-capacity memory to process the generative AI model, while the user device is typically a smartphone or tablet.

[0198] The software used includes BeautifulSoup (HTML parsing), HTTP request processing libraries (e.g., requests), generative AI models (e.g., GPT-3) on the server side, and formatting templates for formatting the results.

[0199] This allows users to quickly obtain key information from multiple sources and efficiently grasp the news.

[0200] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0201] Step 1:

[0202] Subject: User

[0203] The user enters the URL of a news source, which sets the designated information source. For example, a URL like "https: / / example-news-site.com" is entered and stored in the application's database. This information becomes the input for the next data collection.

[0204] Step 2:

[0205] Subject: Terminal

[0206] The terminal sends a request containing the URL of the registered news source to the server, where a news gathering request is generated using the HTTP protocol. The input of the request is the URL of the news source, which is then sent to the server.

[0207] Step 3:

[0208] Subject: Server

[0209] The server retrieves the news article from the specified URL. Specifically, it executes an HTTP request and analyzes the retrieved HTML content. It then parses the HTML content using an HTML analysis library such as BeautifulSoup to extract the headline and body of the news article. The input of this step is the retrieved HTML data, and the output is the parsed news headline and body.

[0210] Step 4:

[0211] Subject: Server

[0212] The server sends the extracted news headlines and text to a generative AI model to generate summaries, using prompts like the following:

[0213] text

[0214] Generate a summary of a news article. Title: Example News Article Title

[0215] Body: Example news article body content, which includes various details and information about the event.

[0216] summary:

[0217] Send a prompt to a generative AI model (e.g., GPT-3) to summarize key information. The input for this step is the news headline, the text, and the prompt, and the output is the generated summary.

[0218] Step 5:

[0219] Subject: Server

[0220] The server formats the generated summary into a report. Specifically, it uses a predefined template to create a report with a header, summary, and the date and time of generation. This process improves the report's readability and appearance. The input to this step is the generated summary, and the output is a formatted report.

[0221] Step 6:

[0222] Subject: Server

[0223] The server sends the formatted report to the user's device, making it easily accessible to the user using methods such as HTTP responses, push notifications, emails, etc. The input of this step is the formatted report, and the output is the report delivered to the user's device.

[0224] Step 7:

[0225] Subject: User

[0226] The user checks the received report on the device. The user quickly accesses important news information by opening notifications or emails on their smartphone or tablet and viewing the report content. The input of this step is the report sent to the device, and the output is the summary report checked by the user.

[0227] By performing the above steps in order, the user can efficiently obtain a summary of a news article.

[0228] 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.

[0229] System configuration

[0230] The present invention is a system that acquires data from a specified information source, analyzes the acquired data to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[0231] System Operation

[0232] Specifying the news URL

[0233] Subject: User

[0234] The user uses the browser on their device to specify the news source URL and send it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the send button.

[0235] News Gathering Requests

[0236] Subject: Terminal

[0237] The device sends a request containing the specified news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[0238] News gathering

[0239] Subject: Server

[0240] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0241] News Analysis

[0242] Subject: Server

[0243] The server parses the retrieved HTML content and extracts the headlines of the main news articles. The server uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles in the page (e.g.< / h2> <h2>Extract the text inside the tag.

[0244] Summary Generation

[0245] Subject: Server

[0246] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent as an overall summary request to the generation AI.

[0247] sentiment analysis

[0248] Subject: Server

[0249] The server runs an emotion engine to recognize the user's emotions, based on their past actions and real-time inputs, such as keyboard and mouse movements, as well as voice and facial expressions.

[0250] Customize reports

[0251] Subject: Server

[0252] The server customizes the generated summary based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, it will prioritize positive news and concise summaries.

[0253] Report Format

[0254] Subject: Server

[0255] The server formats the summarized information into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[0256] Report submission

[0257] Subject: Server

[0258] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0259] Check the report

[0260] Subject: User

[0261] Users can check the received reports on their devices, browse the contents of the reports on their device screen, and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0262] Specific examples

[0263] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[0264] 1. The user enters a URL into the browser input form and submits it.

[0265] 2. The device sends a news gathering request to the server.

[0266] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[0267] 4. The server requests the generation AI to summarize the extracted headlines.

[0268] 5. Generative AI generates a summary.

[0269] 6. The server recognizes the user's emotions using an emotion engine.

[0270] 7. The server customizes the summary based on the recognized sentiment.

[0271] 8. The server formats the customized summary into a report.

[0272] 9. The server sends the report to the user's device.

[0273] 10. The user checks the report on the device.

[0274] In this way, this system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[0275] The processing flow will be explained below.

[0276] Step 1:

[0277] Subject: User

[0278] The user enters the news source URL in the device's browser and presses the send button. For example, the URL "https: / / example-news-site.com" is specified and sent.

[0279] Step 2:

[0280] Subject: Terminal

[0281] The device sends a request containing the news URL to the server, which uses the HTTP protocol and acts as a request to retrieve data from the news source.

[0282] Step 3:

[0283] Subject: Server

[0284] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0285] Step 4:

[0286] Subject: Server

[0287] The server parses the HTML content and extracts the headlines of major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the HTML structure and extract the headlines (e.g.,< / h2> <h2>Extract the text inside the tag.

[0288] Step 5:

[0289] Subject: Server

[0290] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent to the AI ​​model as a prompt for summary generation.

[0291] Step 6:

[0292] Subject: Generative AI model (e.g., GPT-3)

[0293] The generative AI model extracts important elements from the submitted text and generates a summary text, which is then sent back to the server.

[0294] Step 7:

[0295] Subject: Server

[0296] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard typing speed, mouse movement, voice input, and facial expression data).

[0297] Step 8:

[0298] Subject: Server

[0299] The server customizes the generated summary based on the user's emotional data obtained by the emotion engine. For example, if the user is feeling stressed, the server may adjust the summary to emphasize positive news or provide a concise summary.

[0300] Step 9:

[0301] Subject: Server

[0302] The server formats the customized summary into a report, adding headers, generation date and time, and other information to the summary text to make it easier for the user to understand.

[0303] Step 10:

[0304] Subject: Server

[0305] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0306] Step 11:

[0307] Subject: User

[0308] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0309] In this way, the system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[0310] Example 2

[0311] 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."

[0312] In conventional systems, the process of retrieving data from specified sources, extracting key information, and summarizing it is often performed manually, resulting in a lack of efficiency. Furthermore, the system lacks the ability to customize information based on the user's emotions, resulting in a less than satisfactory user experience. Therefore, there is a need to provide a system that efficiently retrieves data and customizes it according to the user's emotions.

[0313] 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.

[0314] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, means for using a generative AI model to summarize the extracted key information, means for generating a prompt sentence for the generative AI model, means for recognizing a user's emotion, means for customizing the summary based on the recognized user's emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal, thereby enabling automation of the entire system and improving the user experience.

[0315] A "designated source" is a source from which data is obtained, such as a specific website or database entered by the user.

[0316] "Means for retrieving data" refers to a function for collecting necessary data from a source such as a specified URL, and includes the process of sending an HTTP request to retrieve HTML content.

[0317] "Means for analyzing data and extracting key information" refers to a function for analyzing acquired data and selecting and extracting important information from it.

[0318] "Means for using a generative AI model" refers to a function for summarizing text information using a generative AI model (e.g., a natural language processing model).

[0319] A "means for generating prompt sentences" is a function that generates sentences to be input into a generative AI model, and provides them in an appropriately formatted form.

[0320] The "means for recognizing user emotions" is a function for analyzing user behavior data and real-time input data to determine the user's emotional state.

[0321] The "means for customizing a summary" is a function for adjusting the generated summary content in accordance with the recognized user's emotions and providing it in an optimal form.

[0322] The "means for formatting into a report format" is a function for formatting the generated summary information into a form that is easy for the user to understand and outputting it as a report.

[0323] "Means for sending to user terminal" refers to a function for sending a formatted report to a terminal designated by the user, and includes HTTP response and email transmission.

[0324] MODE FOR CARRYING OUT THE INVENTION

[0325] The present invention is a system that acquires data from a specified information source, analyzes it to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[0326] Specifying the news URL

[0327] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the submit button. This action sends the news URL to the server.

[0328] News Gathering Requests

[0329] The device sends an HTTP request containing the specified news URL to the server. Specifically, it generates an HTTP GET request to retrieve the news source data. For example:

[0330] GET / HTTP / 1.1

[0331] Host: example-news-site.com

[0332] News gathering

[0333] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com".

[0334] News Analysis

[0335] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles contained within the page (e.g.,< / h2> <h2>Extract the text inside the tag. Example:

[0336] soup = BeautifulSoup(html_content, 'html.parser')

[0337] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[0338] Summary Generation

[0339] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt, which requests the entire summary from the generation AI. An example of a prompt is:

[0340] "Here are the news headlines and their contents. I want you to summarize them."

[0341] sentiment analysis

[0342] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard and mouse movements, voice data) to determine the user's emotions.

[0343] Customize reports

[0344] The server customizes the generated summaries based on the user's perceived emotions, for example, prioritizing positive news and concise summaries if the user is feeling stressed.

[0345] Report Format

[0346] The server formats the summarized information into a report, including headers, generation date and time, and summary text, making it easy for the user to understand. For example:

[0347] Report Generated on: YYYY-MM-DD

[0348] -------------------

[0349] {summary}

[0350] Report submission

[0351] The server sends the completed report to the user's terminal, using HTTP responses or email to ensure that the generated report reaches the user.

[0352] Check the report

[0353] Users can check the received report on their device, view the report contents in a browser or email app, and obtain the necessary information. If more detailed news information is required, they can click on the link in the report to view the original article.

[0354] In this way, the system of the present invention allows users to easily obtain news, get summaries of the news, and further receive customized information based on the user's emotions.

[0355] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0356] Step 1:

[0357] Specifying the news URL

[0358] Subject: User

[0359] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter "https: / / example-news-site.com" and press the submit button. This action sends the URL as input to the system, which then uses the entered URL in the next step.

[0360] Step 2:

[0361] News Gathering Requests

[0362] Subject: Terminal

[0363] The device sends an HTTP request to the server containing the specified news URL, generating an HTTP GET request like this:

[0364] GET / HTTP / 1.1

[0365] Host: example-news-site.com

[0366] This request acts as a request to the server to retrieve the data. The output is sent to the server in the form of an HTTP GET request.

[0367] Step 3:

[0368] News gathering

[0369] Subject: Server

[0370] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com". The retrieved HTML data is used as input for the next step.

[0371] Step 4:

[0372] News Analysis

[0373] Subject: Server

[0374] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the text within the HTML tags. For example,< / h2> <h2>Extract the text inside a tag:

[0375] soup = BeautifulSoup(html_content, 'html.parser')

[0376] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[0377] The input is the retrieved HTML data and the output is a list of extracted headings.

[0378] Step 5:

[0379] Summary Generation

[0380] Subject: Server

[0381] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt and sent to the generation AI. An example of a prompt is:

[0382] "Here are the news headlines and their contents. I want you to summarize them."

[0383] The output from the generative AI is a summary text.

[0384] Step 6:

[0385] sentiment analysis

[0386] Subject: Server

[0387] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavioral data and real-time inputs (e.g., keyboard, mouse movements, and voice data) to determine the user's emotions. The input is the user's behavioral data, and the output is the recognized emotional state.

[0388] Step 7:

[0389] Customize reports

[0390] Subject: Server

[0391] The server customizes the generated summary based on the user's recognized emotions. For example, if the user is feeling stressed, it prioritizes positive news and provides a concise summary. The input is the summary text and emotion data, and the output is a customized summary.

[0392] Step 8:

[0393] Report Format

[0394] Subject: Server

[0395] The server formats the summarized information into a report, adding headers and a generated date and time to make it more user-friendly. For example:

[0396] Report Generated on: YYYY-MM-DD

[0397] -------------------

[0398] {summary}

[0399] The input is a customized summary and the output is a formatted report.

[0400] Step 9:

[0401] Report submission

[0402] Subject: Server

[0403] The server sends the completed report to the user's terminal. The generated report is delivered to the user using communication means such as HTTP response or email. The input is the formatted report, and the output is the transmission to the user's terminal.

[0404] Step 10:

[0405] Check the report

[0406] Subject: User

[0407] The user checks the received report on the device. They view the report contents in a browser or email app and obtain the necessary information. If more detailed news information is required, they click on the link in the report to view the original article. The input is the received report, and the output is improved user satisfaction.

[0408] (Application example 2)

[0409] 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."

[0410] Conventional information extraction and summarization systems have the problem that they provide users with uniform information and are unable to provide appropriate information according to the user's emotions and situation. There is also a need to improve the user experience by providing more positive information and concise summaries, especially for users who are highly stressed.

[0411] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data and extracting key information, means for summarizing the extracted key information, means for recognizing a user's emotion and customizing the summary content based on the recognized emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal. This makes it possible to provide appropriate information according to the user's emotion.

[0412] A "designated source" is a specific data source, such as a website or database, that contains news or information designated by the user.

[0413] "Means of obtaining data" refers to the methods and systems for extracting the required information from the specified source, including access methods using the HTTP protocol.

[0414] "Means of analyzing data and extracting key information" refers to algorithms or systems that identify and highlight important parts or keywords from the acquired data.

[0415] A "summarization means" is a method or system for concisely summarizing extracted key information, including, for example, a process for summarizing text using a generative AI model.

[0416] "Means for recognizing emotions" refers to systems or algorithms that analyze and recognize users' emotions in real time or based on past behavioral data.

[0417] A "means for customizing summary content" is a method or system for tailoring the content of summarized information based on the recognized emotional state of the user, to provide it in a more user-friendly form.

[0418] A "report formatting means" is a system or process for formatting summarized information into a report that is easy for users to understand.

[0419] "Means for sending to user terminal" refers to the method or protocol for sending the formatted report to the user terminal, including HTTP responses, sending emails, etc.

[0420] The system of the present invention acquires data from specified information sources, analyzes the acquired data to extract key information, summarizes the key information, and creates and provides a customized report based on the user's sentiment. The specific configuration and operation of this system are shown below.

[0421] System configuration

[0422] The system of the present invention comprises the following components:

[0423] 1. User Device

[0424] An interface (e.g., a browser) through which a user enters and submits the URL of a news source.

[0425] 2. Server

[0426] This is the core component for acquiring, analyzing, summarizing, and recognizing emotions from news data. The server includes the following functional modules:

[0427] Data Acquisition Module: Acquires HTML data from the specified news URL.

[0428] Analysis module: Analyzes the acquired HTML data and extracts the headlines of major news articles.

[0429] Summarization module: Summarizes the extracted headlines using a generative AI model (e.g., GPT-3).

[0430] Emotion Recognition Module: Recognizes user emotions using automated emotion analysis algorithms.

[0431] Customization module: Customize the summarized information based on the recognized sentiment.

[0432] Formatting module: Formats customized information into a report format.

[0433] Sending module: Sends the formatted report to the user terminal.

[0434] Program processing explanation

[0435] The server performs the following processing in natural language.

[0436] 1. Data Acquisition Module:

[0437] Receives a news URL specified by the user and retrieves the HTML content of that URL using an HTTP GET request. Specifically, it uses the requests library.

[0438] 2. Analysis module:

[0439] The retrieved HTML content is parsed using the BeautifulSoup library to extract the main news article headlines (e.g.< / h2> <h2>Extract as text within tags).

[0440] 3. Summary module:

[0441] The extracted headlines are fed into a generative AI model (e.g., GPT-3) to generate a full summary. The summary is generated using a prompt, such as "Please summarize the following text: \n{text}".

[0442] 4. Emotion Recognition Module:

[0443] We run an algorithm for sentiment analysis on the summarized text, specifically using the nlptown / bert-base-multilingual-uncased-sentiment model to analyze the user's emotional state.

[0444] 5. Customization Module:

[0445] Customize summary text based on recognized emotions, for example, if a user expresses negative emotions, generate a summary that emphasizes positive elements.

[0446] 6. Formatting Module:

[0447] Format the customized text into a report format, adding headers, generation date and time, etc. to make it easier for users to understand.

[0448] 7. Transmitting module:

[0449] The completed report is sent to the user's terminal via HTTP response or email.

[0450] Specific examples

[0451] For example, if a user specifies the URL of a news site "https: / / example-news-site.com", the server will do the following:

[0452] 1. The user enters a URL and submits it.

[0453] 2. The device sends a news gathering request to the server.

[0454] 3. The server retrieves the HTML from the URL and parses it using the BeautifulSoup library.

[0455] 4. The server extracts the headlines and sends a summary request to a generative AI model (e.g., GPT-3).

[0456] 5. The generative AI model generates a summary and sends it back to the server.

[0457] 6. The server performs sentiment analysis on the summary text using the sentiment recognition module.

[0458] 7. The server customizes the summary and formats it into a report.

[0459] 8. The server sends the completed report to the user's device.

[0460] 9. The user checks the report on the device.

[0461] This allows users to obtain news summary reports efficiently in a short time, and also provides a better user experience by customizing the reports according to their emotions.

[0462] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0463] Step 1:

[0464] The user specifies a news URL and sends it to the system from the device's browser. The input is the news site URL (e.g., https: / / example-news-site.com), and the output is a request to the server. Specifically, the user enters the news URL into the browser's input form and presses the submit button.

[0465] Step 2:

[0466] The terminal sends a request including the specified news URL to the server. The input is the news URL specified by the user, and the output is an HTTP GET request received by the server. Specifically, the terminal sends the request to the server using the HTTP protocol.

[0467] Step 3:

[0468] The server accesses the sent news URL and retrieves the HTML content. The input is an HTTP GET request, and the output is the retrieved HTML content. Specifically, the server uses the requests library to retrieve the page source code from the specified URL.

[0469] Step 4:

[0470] The server parses the retrieved HTML content and extracts the headlines of the major news articles. The input is the HTML content, and the output is a list of headlines. Specifically, the server uses the BeautifulSoup library to extract the headlines in the HTML.< / h2> <h2>Extract the text enclosed by the tags.

[0471] Step 5:

[0472] The server combines the extracted headlines and sends them to a generative AI model to generate a summary. The input is a list of headlines, and the output is the summary text. Specifically, the extracted headlines are compiled and input to a generative AI model such as GPT-3 along with a prompt. An example of the prompt is "Please summarize the following text: \n{text}".

[0473] Step 6:

[0474] The server runs an emotion recognition module to recognize the user's emotion. The input is the summarized text, and the output is the user's emotion data. Specifically, the summarized text is input to a sentiment analysis model (nlptown / bert-base-multilingual-uncased-sentiment) to obtain an emotion score.

[0475] Step 7:

[0476] The server customizes the summary content based on the recognized emotions. The input is the summary text and the user's emotion data, and the output is a customized summary text. Specifically, the content is adjusted based on the emotion data, such as emphasizing positive elements when negative.

[0477] Step 8:

[0478] The server formats the customized summary into a report. The input is the customized summary text, and the output is a report-formatted document, specifically by adding a header and a creation date to the summary text.

[0479] Step 9:

[0480] The server sends the completed report to the user's terminal. The input is a document in report format, and the output is a report displayed on the user's terminal. Specifically, the report is delivered to the user using communication methods such as HTTP responses or email.

[0481] Step 10:

[0482] The user checks the received report on the terminal. The input is the received report, and the output is the viewed report information. Specifically, the user checks the contents of the report through a browser or email application.

[0483] 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.

[0484] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0485] 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.

[0486] [Second embodiment]

[0487] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0488] 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.

[0489] 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).

[0490] 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.

[0491] 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.

[0492] 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).

[0493] 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.

[0494] 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.

[0495] 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.

[0496] 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.

[0497] 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.

[0498] 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."

[0499] System configuration

[0500] The present invention is a system for acquiring data from a specified information source, analyzing the acquired data to extract key information, summarizing the extracted key information, formatting the summarized information into a report, and transmitting the formatted report to a user terminal. The system may further include means for formatting the summarized information into a specific format and means for managing access rights when acquiring data from a specified information source. This system is implemented by a server, a terminal, and a user working together.

[0501] System Operation

[0502] Specifying the news URL

[0503] Subject: User

[0504] The user specifies the URL of a news source using a terminal and sends it to the system. For example, the user enters a URL such as "https: / / example-news-site.com" in an input form on a browser and presses the send button.

[0505] News Gathering Requests

[0506] Subject: Terminal

[0507] The device sends a request containing the news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[0508] News gathering

[0509] Subject: Server

[0510] The server accesses the sent news URL and collects the news article. The server parses the HTML content and extracts the headline of the news article. For this purpose, an HTML parsing library such as BeautifulSoup can be used.

[0511] Summary Generation

[0512] Subject: Server

[0513] The server sends the extracted headlines as a summary generation request to a generative AI (e.g., GPT-3). The server combines multiple headlines and uses a generative AI model to summarize the key information, resulting in a concise summary of the key points of the news article.

[0514] Report Format

[0515] Subject: Server

[0516] The server formats the generated summary into a report, for example adding headers and timestamps to make it user-friendly. The report formatting is done according to a predefined template.

[0517] Report submission

[0518] Subject: Server

[0519] The server sends the completed report to the user's terminal, where the generated report is delivered to the user using an HTTP response or email.

[0520] Check the report

[0521] Subject: User

[0522] The user checks the received report on the device. The user browses the contents of the report on the device screen and obtains the necessary information. This allows the user to grasp important news information in a short amount of time.

[0523] Specific examples

[0524] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[0525] 1. The user enters a URL into the browser's input form and submits it.

[0526] 2. The device sends a news gathering request to the server.

[0527] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[0528] 4. The server requests the generation AI to summarize the extracted headlines.

[0529] 5. Generative AI generates a summary.

[0530] 6. The server formats the generated summary into a report.

[0531] 7. The server sends the report to the user's device.

[0532] 8. The user checks the report on the device.

[0533] In this way, this system allows users to obtain news summary reports efficiently and quickly, significantly reducing the burden of information gathering and report creation.

[0534] The processing flow will be explained below.

[0535] Step 1:

[0536] Subject: User

[0537] The user specifies the news source URL using the device's browser. Specifically, the user enters "https: / / example-news-site.com" into the browser's input form and presses the send button.

[0538] Step 2:

[0539] Subject: Terminal

[0540] The device sends a request containing the specified news URL to the server, which uses the HTTP protocol and serves as a request to retrieve data from the news source.

[0541] Step 3:

[0542] Subject: Server

[0543] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0544] Step 4:

[0545] Subject: Server

[0546] Parse the HTML content retrieved by the server. Specifically, use an HTML parsing library such as BeautifulSoup to extract news article headlines (e.g., <h2>Extract the text inside the tag.

[0547] Step 5:

[0548] Subject: Server

[0549] The server combines the extracted headlines and sends a summary generation request to the generation AI (e.g., GPT-3). Multiple headlines are combined into a single text and sent as a complete summary request to the generation AI.

[0550] Step 6:

[0551] Subject: Generative AI model (e.g., GPT-3)

[0552] The generative AI model extracts important elements from the input text and generates a summary, which is then sent back to the server.

[0553] Step 7:

[0554] Subject: Server

[0555] The server receives the generated summary and formats it into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[0556] Step 8:

[0557] Subject: Server

[0558] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0559] Step 9:

[0560] Subject: User

[0561] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0562] This series of processes allows users to obtain news summary reports efficiently in a short time, significantly reducing the burden of information gathering and report creation.

[0563] Example 1

[0564] 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."

[0565] In today's information-saturated society, it is difficult for users to efficiently obtain the information they need. It also requires a great deal of effort to summarize the key information from a large amount of information, such as news articles, and understand it quickly. Furthermore, the process of organizing the obtained information into a user-friendly format is also cumbersome, and there is a need for a means to automate these tasks.

[0566] 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.

[0567] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, and means for summarizing the extracted key information using a generative AI model. This allows the server to efficiently extract and summarize key parts from large amounts of information such as news articles, enabling users to grasp important information in a short amount of time.

[0568] A "specified information source" is a source from which data is obtained, such as a URL entered by a user or a database.

[0569] "Means of obtaining data" refers to the methods and processes used to collect the required data from designated sources.

[0570] "Means of analyzing data and extracting key information" refers to methods and techniques for analyzing collected data and selecting important or necessary information.

[0571] "Generative AI model" refers to an algorithm or system used to generate, summarize, or analyze text or information using artificial intelligence techniques.

[0572] "Summarization methods" refer to methods and techniques for shortening the extracted key information and reconstructing it in a way that includes only the important points.

[0573] "Means for formatting into a report format" refers to a method or technique for formatting summarized information so that it is easy for a user to read, and compiling it into a report in a specified format.

[0574] "User terminal" refers to a device such as a computer or smartphone that a user uses to operate the system.

[0575] "Access rights management measures" refers to the methods and processes for verifying, approving, and managing the rights required to obtain data from designated sources.

[0576] The present invention provides a system that allows users to efficiently collect key information from information sources such as news sites and receive summarized reports. This system is implemented by a server, terminals, and users working together.

[0577] First, the user specifies the URL of a news source using the device. For example, they enter a URL such as "https: / / example-news-site.com" using an input form on the browser and press the send button. This URL is then sent from the device to the server.

[0578] The server then accesses the specified news URL and collects the news article. The server retrieves the HTML data using an HTTP request and parses the HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[0579] The extracted headlines are sent from the server to a generative AI model (e.g., OpenAI's GPT-3). A prompt sentence is used as input to the generative AI model. An example of a prompt sentence is "Please generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'." Based on this prompt sentence, the generative AI model summarizes the important information and returns the results to the server.

[0580] The server then formats the generated summary into a report, according to a predefined template, adding headers and the date and time of generation for user readability, and then sends the report in a specific format to the user's device.

[0581] Finally, the user checks the received report on the terminal. The user can view the report contents on the terminal screen and quickly grasp the necessary information.

[0582] This system allows users to efficiently extract key information from vast amounts of news content and receive summarized reports, significantly improving the efficiency of information gathering and report creation.

[0583] The hardware required to implement the specific operation of this system includes high-performance computers and cloud services as servers, and personal computers and smartphones as user devices.The software used includes HTML analysis libraries such as BeautifulSoup, libraries for HTTP communication, and GPT-3 as a generative AI model.

[0584] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0585] Step 1: Specify the news URL

[0586] Subject: User

[0587] The user specifies the URL of a news source using a terminal. Specifically, the user enters the URL "https: / / example-news-site.com" into the browser's input form and presses the submit button. This operation sends the URL to the system.

[0588] Input: URL of the news source (e.g. "https: / / example-news-site.com")

[0589] Output: A request sent from the device to the server for the specified URL

[0590] Step 2: Submit a newsgathering request

[0591] Subject: Terminal

[0592] The device sends a request including a news URL to the server. This request uses the HTTP protocol to obtain data from the news source. Specifically, an HTTP GET request is generated that includes the URL and user information.

[0593] Input: The specified URL (e.g. "https: / / example-news-site.com")

[0594] Output: A newsgathering request is sent to the server

[0595] Step 3: Gathering news

[0596] Subject: Server

[0597] The server accesses the received news URL and collects the news article. It retrieves the HTML data using an HTTP request and parses the retrieved HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[0598] Input: Newsgathering request (HTTP GET request)

[0599] Output: HTML data and extracted news headlines

[0600] Step 4: Summary generation

[0601] Subject: Server

[0602] The server compiles the extracted headlines, generates a prompt based on the summary, and sends it to a generative AI model (e.g., OpenAI GPT-3). The generative AI model then generates a summary based on the prompt.

[0603] Input: Extracted news headlines (e.g. "Headline 1, Headline 2, Headline 3")

[0604] Output: A summary generated by a generative AI model (e.g., "Generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'")

[0605] Step 5: Format the report

[0606] Subject: Server

[0607] The server formats the generated summary into a report by reading a template, inserting the generated summary at the appropriate position, adding headers and the date and time of generation, according to a predefined template.

[0608] Input: Generated summary

[0609] Output: Reports according to a standard format

[0610] Step 6: Submit the report

[0611] Subject: Server

[0612] The server sends the completed report to the user's terminal. The generated report is delivered to the user using an HTTP response or email. Specifically, if the report is returned as an HTTP response, it is returned in JSON or HTML format, and if it is sent by email, it is sent to the specified email address using the SMTP protocol.

[0613] Input: Formatted report

[0614] Output: Sending the report to the user's terminal

[0615] Step 7: Review the report

[0616] Subject: User

[0617] The user checks the received report on the device, for example, by opening the received report using a browser or email client and displaying its contents.

[0618] Input: Report sent to terminal

[0619] Output: User views the report and gets the information they need.

[0620] In this way, each step works in conjunction with the other steps, allowing the user to efficiently obtain a news summary report.

[0621] (Application example 1)

[0622] 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."

[0623] In modern society, there is a need to efficiently collect, summarize, and visualize important information from a vast number of sources. However, manually organizing and summarizing news articles and information is time-consuming and labor-intensive. It is also difficult to monitor multiple sources at once and extract important information in real time. Furthermore, a method is needed for users to easily browse summarized information and instantly obtain the information they need.

[0624] 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.

[0625] In this invention, the server includes means for acquiring data from specified information sources, means for analyzing the acquired data to extract key information, means for summarizing the extracted key information using a generative AI model, means for formatting the summarized information into a report, and means for transmitting the formatted report to a user terminal, thereby enabling a user to quickly summarize and acquire important information from multiple information sources and efficiently manage information on a daily basis.

[0626] A "designated information source" is an information provider designated by a user to obtain specific data.

[0627] "Means of acquiring data" means the mechanisms or systems used to collect data from designated sources.

[0628] "Means for analyzing data" refers to techniques and methods for analyzing acquired data and determining key information.

[0629] "Key information extraction" is the process for selecting important information from the analyzed data.

[0630] A "generative AI model" refers to an algorithm or computational model that uses artificial intelligence to process data and generate a result.

[0631] "Summarization methods" are techniques or methods for concisely summarizing extracted information.

[0632] A "report formatting means" is a method for displaying summarized information in a certain format.

[0633] A "user terminal" is a device that allows a user to receive and manipulate information.

[0634] "Transmitting means" refers to a method for sending data from the server to the user terminal.

[0635] The "means for checking" is a method by which the user views the information received at the terminal and checks the content.

[0636] System configuration and functions

[0637] As an embodiment of the present invention, we will specifically exemplify a system that extracts key information from news sources, summarizes it, and provides it to users. This system mainly consists of three elements: a server, a terminal, and a user.

[0638] News source registration

[0639] Subject: User

[0640] Users register the URL of a news site they are interested in in the application on their device by entering a URL such as "https: / / example-news-site.com" in the input form and pressing the submit button.

[0641] Data acquisition and analysis

[0642] Subject: Server

[0643] The server accesses the specified news URL and collects news articles. The server uses a library such as BeautifulSoup to parse the HTML content and extracts the article headlines and body text.

[0644] Summary Generation

[0645] Subject: Server

[0646] The server sends the extracted news article headlines and text to a generative AI model (e.g., GPT-3) to summarize the key information. The generative AI model generates a summary using a prompt sentence.

[0647] Prompt Sentence Examples

[0648] text

[0649] Generate a summary of a news article. Title: Example News Article Title

[0650] Body: Example news article body content, which includes various details and information about the event.

[0651] summary:

[0652] Report Format

[0653] Subject: Server

[0654] The server formats the generated summary into a report, following a predefined template, adding headers and the date and time of generation to make it user-friendly.

[0655] Report submission and confirmation

[0656] Subject: Server

[0657] The server sends the completed report to the user's device. The generated report is delivered to the user's device using HTTP responses, push notifications, or email.

[0658] Subject: User

[0659] Users can check the received reports on their devices. Using their smartphones or tablets, users can easily view summarized news reports and obtain the information they need.

[0660] Hardware and software used

[0661] The main hardware required to realize this system includes a server and a user device. The server is equipped with a high-performance processor and large-capacity memory to process the generative AI model, while the user device is typically a smartphone or tablet.

[0662] The software used includes BeautifulSoup (HTML parsing), HTTP request processing libraries (e.g., requests), generative AI models (e.g., GPT-3) on the server side, and formatting templates for formatting the results.

[0663] This allows users to quickly obtain key information from multiple sources and efficiently grasp the news.

[0664] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0665] Step 1:

[0666] Subject: User

[0667] The user enters the URL of a news source, which sets the designated information source. For example, a URL like "https: / / example-news-site.com" is entered and stored in the application's database. This information becomes the input for the next data collection.

[0668] Step 2:

[0669] Subject: Terminal

[0670] The terminal sends a request containing the URL of the registered news source to the server, where a news gathering request is generated using the HTTP protocol. The input of the request is the URL of the news source, which is then sent to the server.

[0671] Step 3:

[0672] Subject: Server

[0673] The server retrieves the news article from the specified URL. Specifically, it executes an HTTP request and analyzes the retrieved HTML content. It then parses the HTML content using an HTML analysis library such as BeautifulSoup to extract the headline and body of the news article. The input of this step is the retrieved HTML data, and the output is the parsed news headline and body.

[0674] Step 4:

[0675] Subject: Server

[0676] The server sends the extracted news headlines and text to a generative AI model to generate summaries, using prompts like the following:

[0677] text

[0678] Generate a summary of a news article. Title: Example News Article Title

[0679] Body: Example news article body content, which includes various details and information about the event.

[0680] summary:

[0681] Send a prompt to a generative AI model (e.g., GPT-3) to summarize key information. The input for this step is the news headline, the text, and the prompt, and the output is the generated summary.

[0682] Step 5:

[0683] Subject: Server

[0684] The server formats the generated summary into a report. Specifically, it uses a predefined template to create a report with a header, summary, and the date and time of generation. This process improves the report's readability and appearance. The input to this step is the generated summary, and the output is a formatted report.

[0685] Step 6:

[0686] Subject: Server

[0687] The server sends the formatted report to the user's device, making it easily accessible to the user using methods such as HTTP responses, push notifications, emails, etc. The input of this step is the formatted report, and the output is the report delivered to the user's device.

[0688] Step 7:

[0689] Subject: User

[0690] The user checks the received report on the device. The user quickly accesses important news information by opening notifications or emails on their smartphone or tablet and viewing the report content. The input of this step is the report sent to the device, and the output is the summary report checked by the user.

[0691] By performing the above steps in order, the user can efficiently obtain a summary of a news article.

[0692] 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.

[0693] System configuration

[0694] The present invention is a system that acquires data from a specified information source, analyzes the acquired data to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[0695] System Operation

[0696] Specifying the news URL

[0697] Subject: User

[0698] The user uses the browser on their device to specify the news source URL and send it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the send button.

[0699] News Gathering Requests

[0700] Subject: Terminal

[0701] The device sends a request containing the specified news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[0702] News gathering

[0703] Subject: Server

[0704] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0705] News Analysis

[0706] Subject: Server

[0707] The server parses the retrieved HTML content and extracts the headlines of the main news articles. The server uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles in the page (e.g.< / h2> <h2>Extract the text inside the tag.

[0708] Summary Generation

[0709] Subject: Server

[0710] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent as an overall summary request to the generation AI.

[0711] sentiment analysis

[0712] Subject: Server

[0713] The server runs an emotion engine to recognize the user's emotions, based on their past actions and real-time inputs, such as keyboard and mouse movements, as well as voice and facial expressions.

[0714] Customize reports

[0715] Subject: Server

[0716] The server customizes the generated summary based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, it will prioritize positive news and concise summaries.

[0717] Report Format

[0718] Subject: Server

[0719] The server formats the summarized information into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[0720] Report submission

[0721] Subject: Server

[0722] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0723] Check the report

[0724] Subject: User

[0725] Users can check the received reports on their devices, browse the contents of the reports on their device screen, and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0726] Specific examples

[0727] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[0728] 1. The user enters a URL into the browser input form and submits it.

[0729] 2. The device sends a news gathering request to the server.

[0730] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[0731] 4. The server requests the generation AI to summarize the extracted headlines.

[0732] 5. Generative AI generates a summary.

[0733] 6. The server recognizes the user's emotions using an emotion engine.

[0734] 7. The server customizes the summary based on the recognized sentiment.

[0735] 8. The server formats the customized summary into a report.

[0736] 9. The server sends the report to the user's device.

[0737] 10. The user checks the report on the device.

[0738] In this way, this system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[0739] The processing flow will be explained below.

[0740] Step 1:

[0741] Subject: User

[0742] The user enters the news source URL in the device's browser and presses the send button. For example, the URL "https: / / example-news-site.com" is specified and sent.

[0743] Step 2:

[0744] Subject: Terminal

[0745] The device sends a request containing the news URL to the server, which uses the HTTP protocol and acts as a request to retrieve data from the news source.

[0746] Step 3:

[0747] Subject: Server

[0748] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[0749] Step 4:

[0750] Subject: Server

[0751] The server parses the HTML content and extracts the headlines of major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the HTML structure and extract the headlines (e.g.,< / h2> <h2>Extract the text inside the tag.

[0752] Step 5:

[0753] Subject: Server

[0754] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent to the AI ​​model as a prompt for summary generation.

[0755] Step 6:

[0756] Subject: Generative AI model (e.g., GPT-3)

[0757] The generative AI model extracts important elements from the submitted text and generates a summary text, which is then sent back to the server.

[0758] Step 7:

[0759] Subject: Server

[0760] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard typing speed, mouse movement, voice input, and facial expression data).

[0761] Step 8:

[0762] Subject: Server

[0763] The server customizes the generated summary based on the user's emotional data obtained by the emotion engine. For example, if the user is feeling stressed, the server may adjust the summary to emphasize positive news or provide a concise summary.

[0764] Step 9:

[0765] Subject: Server

[0766] The server formats the customized summary into a report, adding headers, generation date and time, and other information to the summary text to make it easier for the user to understand.

[0767] Step 10:

[0768] Subject: Server

[0769] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[0770] Step 11:

[0771] Subject: User

[0772] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[0773] In this way, the system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[0774] Example 2

[0775] 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."

[0776] In conventional systems, the process of retrieving data from specified sources, extracting key information, and summarizing it is often performed manually, resulting in a lack of efficiency. Furthermore, the system lacks the ability to customize information based on the user's emotions, resulting in a less than satisfactory user experience. Therefore, there is a need to provide a system that efficiently retrieves data and customizes it according to the user's emotions.

[0777] 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.

[0778] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, means for using a generative AI model to summarize the extracted key information, means for generating a prompt sentence for the generative AI model, means for recognizing a user's emotion, means for customizing the summary based on the recognized user's emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal, thereby enabling automation of the entire system and improving the user experience.

[0779] A "designated source" is a source from which data is obtained, such as a specific website or database entered by the user.

[0780] "Means for retrieving data" refers to a function for collecting necessary data from a source such as a specified URL, and includes the process of sending an HTTP request to retrieve HTML content.

[0781] "Means for analyzing data and extracting key information" refers to a function for analyzing acquired data and selecting and extracting important information from it.

[0782] "Means for using a generative AI model" refers to a function for summarizing text information using a generative AI model (e.g., a natural language processing model).

[0783] A "means for generating prompt sentences" is a function that generates sentences to be input into a generative AI model, and provides them in an appropriately formatted form.

[0784] The "means for recognizing user emotions" is a function for analyzing user behavior data and real-time input data to determine the user's emotional state.

[0785] The "means for customizing a summary" is a function for adjusting the generated summary content in accordance with the recognized user's emotions and providing it in an optimal form.

[0786] The "means for formatting into a report format" is a function for formatting the generated summary information into a form that is easy for the user to understand and outputting it as a report.

[0787] "Means for sending to user terminal" refers to a function for sending a formatted report to a terminal designated by the user, and includes HTTP response and email transmission.

[0788] MODE FOR CARRYING OUT THE INVENTION

[0789] The present invention is a system that acquires data from a specified information source, analyzes it to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[0790] Specifying the news URL

[0791] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the submit button. This action sends the news URL to the server.

[0792] News Gathering Requests

[0793] The device sends an HTTP request containing the specified news URL to the server. Specifically, it generates an HTTP GET request to retrieve the news source data. For example:

[0794] GET / HTTP / 1.1

[0795] Host: example-news-site.com

[0796] News gathering

[0797] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com".

[0798] News Analysis

[0799] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles contained within the page (e.g.,< / h2> <h2>Extract the text inside the tag. Example:

[0800] soup = BeautifulSoup(html_content, 'html.parser')

[0801] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[0802] Summary Generation

[0803] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt, which requests the entire summary from the generation AI. An example of a prompt is:

[0804] "Here are the news headlines and their contents. I want you to summarize them."

[0805] sentiment analysis

[0806] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard and mouse movements, voice data) to determine the user's emotions.

[0807] Customize reports

[0808] The server customizes the generated summaries based on the user's perceived emotions, for example, prioritizing positive news and concise summaries if the user is feeling stressed.

[0809] Report Format

[0810] The server formats the summarized information into a report, including headers, generation date and time, and summary text, making it easy for the user to understand. For example:

[0811] Report Generated on: YYYY-MM-DD

[0812] -------------------

[0813] {summary}

[0814] Report submission

[0815] The server sends the completed report to the user's terminal, using HTTP responses or email to ensure that the generated report reaches the user.

[0816] Check the report

[0817] Users can check the received report on their device, view the report contents in a browser or email app, and obtain the necessary information. If more detailed news information is required, they can click on the link in the report to view the original article.

[0818] In this way, the system of the present invention allows users to easily obtain news, get summaries of the news, and further receive customized information based on the user's emotions.

[0819] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0820] Step 1:

[0821] Specifying the news URL

[0822] Subject: User

[0823] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter "https: / / example-news-site.com" and press the submit button. This action sends the URL as input to the system, which then uses the entered URL in the next step.

[0824] Step 2:

[0825] News Gathering Requests

[0826] Subject: Terminal

[0827] The device sends an HTTP request to the server containing the specified news URL, generating an HTTP GET request like this:

[0828] GET / HTTP / 1.1

[0829] Host: example-news-site.com

[0830] This request acts as a request to the server to retrieve the data. The output is sent to the server in the form of an HTTP GET request.

[0831] Step 3:

[0832] News gathering

[0833] Subject: Server

[0834] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com". The retrieved HTML data is used as input for the next step.

[0835] Step 4:

[0836] News Analysis

[0837] Subject: Server

[0838] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the text within the HTML tags. For example,< / h2> <h2>Extract the text inside a tag:

[0839] soup = BeautifulSoup(html_content, 'html.parser')

[0840] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[0841] The input is the retrieved HTML data and the output is a list of extracted headings.

[0842] Step 5:

[0843] Summary Generation

[0844] Subject: Server

[0845] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt and sent to the generation AI. An example of a prompt is:

[0846] "Here are the news headlines and their contents. I want you to summarize them."

[0847] The output from the generative AI is a summary text.

[0848] Step 6:

[0849] sentiment analysis

[0850] Subject: Server

[0851] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavioral data and real-time inputs (e.g., keyboard, mouse movements, and voice data) to determine the user's emotions. The input is the user's behavioral data, and the output is the recognized emotional state.

[0852] Step 7:

[0853] Customize reports

[0854] Subject: Server

[0855] The server customizes the generated summary based on the user's recognized emotions. For example, if the user is feeling stressed, it prioritizes positive news and provides a concise summary. The input is the summary text and emotion data, and the output is a customized summary.

[0856] Step 8:

[0857] Report Format

[0858] Subject: Server

[0859] The server formats the summarized information into a report, adding headers and a generated date and time to make it more user-friendly. For example:

[0860] Report Generated on: YYYY-MM-DD

[0861] -------------------

[0862] {summary}

[0863] The input is a customized summary and the output is a formatted report.

[0864] Step 9:

[0865] Report submission

[0866] Subject: Server

[0867] The server sends the completed report to the user's terminal. The generated report is delivered to the user using communication means such as HTTP response or email. The input is the formatted report, and the output is the transmission to the user's terminal.

[0868] Step 10:

[0869] Check the report

[0870] Subject: User

[0871] The user checks the received report on the device. They view the report contents in a browser or email app and obtain the necessary information. If more detailed news information is required, they click on the link in the report to view the original article. The input is the received report, and the output is improved user satisfaction.

[0872] (Application example 2)

[0873] 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."

[0874] Conventional information extraction and summarization systems have the problem that they provide users with uniform information and are unable to provide appropriate information according to the user's emotions and situation. There is also a need to improve the user experience by providing more positive information and concise summaries, especially for users who are highly stressed.

[0875] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data and extracting key information, means for summarizing the extracted key information, means for recognizing a user's emotion and customizing the summary content based on the recognized emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal. This makes it possible to provide appropriate information according to the user's emotion.

[0876] A "designated source" is a specific data source, such as a website or database, that contains news or information designated by the user.

[0877] "Means of obtaining data" refers to the methods and systems for extracting the required information from the specified source, including access methods using the HTTP protocol.

[0878] "Means of analyzing data and extracting key information" refers to algorithms or systems that identify and highlight important parts or keywords from the acquired data.

[0879] A "summarization means" is a method or system for concisely summarizing extracted key information, including, for example, a process for summarizing text using a generative AI model.

[0880] "Means for recognizing emotions" refers to systems or algorithms that analyze and recognize users' emotions in real time or based on past behavioral data.

[0881] A "means for customizing summary content" is a method or system for tailoring the content of summarized information based on the recognized emotional state of the user, to provide it in a more user-friendly form.

[0882] A "report formatting means" is a system or process for formatting summarized information into a report that is easy for users to understand.

[0883] "Means for sending to user terminal" refers to the method or protocol for sending the formatted report to the user terminal, including HTTP responses, sending emails, etc.

[0884] The system of the present invention acquires data from specified information sources, analyzes the acquired data to extract key information, summarizes the key information, and creates and provides a customized report based on the user's sentiment. The specific configuration and operation of this system are shown below.

[0885] System configuration

[0886] The system of the present invention comprises the following components:

[0887] 1. User Device

[0888] An interface (e.g., a browser) through which a user enters and submits the URL of a news source.

[0889] 2. Server

[0890] This is the core component for acquiring, analyzing, summarizing, and recognizing emotions from news data. The server includes the following functional modules:

[0891] Data Acquisition Module: Acquires HTML data from the specified news URL.

[0892] Analysis module: Analyzes the acquired HTML data and extracts the headlines of major news articles.

[0893] Summarization module: Summarizes the extracted headlines using a generative AI model (e.g., GPT-3).

[0894] Emotion Recognition Module: Recognizes user emotions using automated emotion analysis algorithms.

[0895] Customization module: Customize the summarized information based on the recognized sentiment.

[0896] Formatting module: Formats customized information into a report format.

[0897] Sending module: Sends the formatted report to the user terminal.

[0898] Program processing explanation

[0899] The server performs the following processing in natural language.

[0900] 1. Data Acquisition Module:

[0901] Receives a news URL specified by the user and retrieves the HTML content of that URL using an HTTP GET request. Specifically, it uses the requests library.

[0902] 2. Analysis module:

[0903] The retrieved HTML content is parsed using the BeautifulSoup library to extract the main news article headlines (e.g.< / h2> <h2>Extract as text within tags).

[0904] 3. Summary module:

[0905] The extracted headlines are fed into a generative AI model (e.g., GPT-3) to generate a full summary. The summary is generated using a prompt, such as "Please summarize the following text: \n{text}".

[0906] 4. Emotion Recognition Module:

[0907] We run an algorithm for sentiment analysis on the summarized text, specifically using the nlptown / bert-base-multilingual-uncased-sentiment model to analyze the user's emotional state.

[0908] 5. Customization Module:

[0909] Customize summary text based on recognized emotions, for example, if a user expresses negative emotions, generate a summary that emphasizes positive elements.

[0910] 6. Formatting Module:

[0911] Format the customized text into a report format, adding headers, generation date and time, etc. to make it easier for users to understand.

[0912] 7. Transmitting module:

[0913] The completed report is sent to the user's terminal via HTTP response or email.

[0914] Specific examples

[0915] For example, if a user specifies the URL of a news site "https: / / example-news-site.com", the server will do the following:

[0916] 1. The user enters a URL and submits it.

[0917] 2. The device sends a news gathering request to the server.

[0918] 3. The server retrieves the HTML from the URL and parses it using the BeautifulSoup library.

[0919] 4. The server extracts the headlines and sends a summary request to a generative AI model (e.g., GPT-3).

[0920] 5. The generative AI model generates a summary and sends it back to the server.

[0921] 6. The server performs sentiment analysis on the summary text using the sentiment recognition module.

[0922] 7. The server customizes the summary and formats it into a report.

[0923] 8. The server sends the completed report to the user's device.

[0924] 9. The user checks the report on the device.

[0925] This allows users to obtain news summary reports efficiently in a short time, and also provides a better user experience by customizing the reports according to their emotions.

[0926] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0927] Step 1:

[0928] The user specifies a news URL and sends it to the system from the device's browser. The input is the news site URL (e.g., https: / / example-news-site.com), and the output is a request to the server. Specifically, the user enters the news URL into the browser's input form and presses the submit button.

[0929] Step 2:

[0930] The terminal sends a request including the specified news URL to the server. The input is the news URL specified by the user, and the output is an HTTP GET request received by the server. Specifically, the terminal sends the request to the server using the HTTP protocol.

[0931] Step 3:

[0932] The server accesses the sent news URL and retrieves the HTML content. The input is an HTTP GET request, and the output is the retrieved HTML content. Specifically, the server uses the requests library to retrieve the page source code from the specified URL.

[0933] Step 4:

[0934] The server parses the retrieved HTML content and extracts the headlines of the major news articles. The input is the HTML content, and the output is a list of headlines. Specifically, the server uses the BeautifulSoup library to extract the headlines in the HTML.< / h2> <h2>Extract the text enclosed by the tags.

[0935] Step 5:

[0936] The server combines the extracted headlines and sends them to a generative AI model to generate a summary. The input is a list of headlines, and the output is the summary text. Specifically, the extracted headlines are compiled and input to a generative AI model such as GPT-3 along with a prompt. An example of the prompt is "Please summarize the following text: \n{text}".

[0937] Step 6:

[0938] The server runs an emotion recognition module to recognize the user's emotion. The input is the summarized text, and the output is the user's emotion data. Specifically, the summarized text is input to a sentiment analysis model (nlptown / bert-base-multilingual-uncased-sentiment) to obtain an emotion score.

[0939] Step 7:

[0940] The server customizes the summary content based on the recognized emotions. The input is the summary text and the user's emotion data, and the output is a customized summary text. Specifically, the content is adjusted based on the emotion data, such as emphasizing positive elements when negative.

[0941] Step 8:

[0942] The server formats the customized summary into a report. The input is the customized summary text, and the output is a report-formatted document, specifically by adding a header and a creation date to the summary text.

[0943] Step 9:

[0944] The server sends the completed report to the user's terminal. The input is a document in report format, and the output is a report displayed on the user's terminal. Specifically, the report is delivered to the user using communication methods such as HTTP responses or email.

[0945] Step 10:

[0946] The user checks the received report on the terminal. The input is the received report, and the output is the viewed report information. Specifically, the user checks the contents of the report through a browser or email application.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] [Third embodiment]

[0951] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0952] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0953] 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).

[0954] 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.

[0955] 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.

[0956] 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).

[0957] 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.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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."

[0963] System configuration

[0964] The present invention is a system for acquiring data from a specified information source, analyzing the acquired data to extract key information, summarizing the extracted key information, formatting the summarized information into a report, and transmitting the formatted report to a user terminal. The system may further include means for formatting the summarized information into a specific format and means for managing access rights when acquiring data from a specified information source. This system is implemented by a server, a terminal, and a user working together.

[0965] System Operation

[0966] Specifying the news URL

[0967] Subject: User

[0968] The user specifies the URL of a news source using a terminal and sends it to the system. For example, the user enters a URL such as "https: / / example-news-site.com" in an input form on a browser and presses the send button.

[0969] News Gathering Requests

[0970] Subject: Terminal

[0971] The device sends a request containing the news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[0972] News gathering

[0973] Subject: Server

[0974] The server accesses the sent news URL and collects the news article. The server parses the HTML content and extracts the headline of the news article. For this purpose, an HTML parsing library such as BeautifulSoup can be used.

[0975] Summary Generation

[0976] Subject: Server

[0977] The server sends the extracted headlines as a summary generation request to a generative AI (e.g., GPT-3). The server combines multiple headlines and uses a generative AI model to summarize the key information, resulting in a concise summary of the key points of the news article.

[0978] Report Format

[0979] Subject: Server

[0980] The server formats the generated summary into a report, for example adding headers and timestamps to make it user-friendly. The report formatting is done according to a predefined template.

[0981] Report submission

[0982] Subject: Server

[0983] The server sends the completed report to the user's terminal, where the generated report is delivered to the user using an HTTP response or email.

[0984] Check the report

[0985] Subject: User

[0986] The user checks the received report on the device. The user browses the contents of the report on the device screen and obtains the necessary information. This allows the user to grasp important news information in a short amount of time.

[0987] Specific examples

[0988] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[0989] 1. The user enters a URL into the browser's input form and submits it.

[0990] 2. The device sends a news gathering request to the server.

[0991] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[0992] 4. The server requests the generation AI to summarize the extracted headlines.

[0993] 5. Generative AI generates a summary.

[0994] 6. The server formats the generated summary into a report.

[0995] 7. The server sends the report to the user's device.

[0996] 8. The user checks the report on the device.

[0997] In this way, this system allows users to obtain news summary reports efficiently and quickly, significantly reducing the burden of information gathering and report creation.

[0998] The processing flow will be explained below.

[0999] Step 1:

[1000] Subject: User

[1001] The user specifies the news source URL using the device's browser. Specifically, the user enters "https: / / example-news-site.com" into the browser's input form and presses the send button.

[1002] Step 2:

[1003] Subject: Terminal

[1004] The device sends a request containing the specified news URL to the server, which uses the HTTP protocol and serves as a request to retrieve data from the news source.

[1005] Step 3:

[1006] Subject: Server

[1007] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1008] Step 4:

[1009] Subject: Server

[1010] Parse the HTML content retrieved by the server. Specifically, use an HTML parsing library such as BeautifulSoup to extract news article headlines (e.g., <h2>Extract the text inside the tag.

[1011] Step 5:

[1012] Subject: Server

[1013] The server combines the extracted headlines and sends a summary generation request to the generation AI (e.g., GPT-3). Multiple headlines are combined into a single text and sent as a complete summary request to the generation AI.

[1014] Step 6:

[1015] Subject: Generative AI model (e.g., GPT-3)

[1016] The generative AI model extracts important elements from the input text and generates a summary, which is then sent back to the server.

[1017] Step 7:

[1018] Subject: Server

[1019] The server receives the generated summary and formats it into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[1020] Step 8:

[1021] Subject: Server

[1022] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1023] Step 9:

[1024] Subject: User

[1025] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1026] This series of processes allows users to obtain news summary reports efficiently in a short time, significantly reducing the burden of information gathering and report creation.

[1027] Example 1

[1028] 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."

[1029] In today's information-saturated society, it is difficult for users to efficiently obtain the information they need. It also requires a great deal of effort to summarize the key information from a large amount of information, such as news articles, and understand it quickly. Furthermore, the process of organizing the obtained information into a user-friendly format is also cumbersome, and there is a need for a means to automate these tasks.

[1030] 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.

[1031] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, and means for summarizing the extracted key information using a generative AI model. This allows the server to efficiently extract and summarize key parts from large amounts of information such as news articles, enabling users to grasp important information in a short amount of time.

[1032] A "specified information source" is a source from which data is obtained, such as a URL entered by a user or a database.

[1033] "Means of obtaining data" refers to the methods and processes used to collect the required data from designated sources.

[1034] "Means of analyzing data and extracting key information" refers to methods and techniques for analyzing collected data and selecting important or necessary information.

[1035] "Generative AI model" refers to an algorithm or system used to generate, summarize, or analyze text or information using artificial intelligence techniques.

[1036] "Summarization methods" refer to methods and techniques for shortening the extracted key information and reconstructing it in a way that includes only the important points.

[1037] "Means for formatting into a report format" refers to a method or technique for formatting summarized information so that it is easy for a user to read, and compiling it into a report in a specified format.

[1038] "User terminal" refers to a device such as a computer or smartphone that a user uses to operate the system.

[1039] "Access rights management measures" refers to the methods and processes for verifying, approving, and managing the rights required to obtain data from designated sources.

[1040] The present invention provides a system that allows users to efficiently collect key information from information sources such as news sites and receive summarized reports. This system is implemented by a server, terminals, and users working together.

[1041] First, the user specifies the URL of a news source using the device. For example, they enter a URL such as "https: / / example-news-site.com" using an input form on the browser and press the send button. This URL is then sent from the device to the server.

[1042] The server then accesses the specified news URL and collects the news article. The server retrieves the HTML data using an HTTP request and parses the HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[1043] The extracted headlines are sent from the server to a generative AI model (e.g., OpenAI's GPT-3). A prompt sentence is used as input to the generative AI model. An example of a prompt sentence is "Please generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'." Based on this prompt sentence, the generative AI model summarizes the important information and returns the results to the server.

[1044] The server then formats the generated summary into a report, according to a predefined template, adding headers and the date and time of generation for user readability, and then sends the report in a specific format to the user's device.

[1045] Finally, the user checks the received report on the terminal. The user can view the report contents on the terminal screen and quickly grasp the necessary information.

[1046] This system allows users to efficiently extract key information from vast amounts of news content and receive summarized reports, significantly improving the efficiency of information gathering and report creation.

[1047] The hardware required to implement the specific operation of this system includes high-performance computers and cloud services as servers, and personal computers and smartphones as user devices.The software used includes HTML analysis libraries such as BeautifulSoup, libraries for HTTP communication, and GPT-3 as a generative AI model.

[1048] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1049] Step 1: Specify the news URL

[1050] Subject: User

[1051] The user specifies the URL of a news source using a terminal. Specifically, the user enters the URL "https: / / example-news-site.com" into the browser's input form and presses the submit button. This operation sends the URL to the system.

[1052] Input: URL of the news source (e.g. "https: / / example-news-site.com")

[1053] Output: A request sent from the device to the server for the specified URL

[1054] Step 2: Submit a newsgathering request

[1055] Subject: Terminal

[1056] The device sends a request including a news URL to the server. This request uses the HTTP protocol to obtain data from the news source. Specifically, an HTTP GET request is generated that includes the URL and user information.

[1057] Input: The specified URL (e.g. "https: / / example-news-site.com")

[1058] Output: A newsgathering request is sent to the server

[1059] Step 3: Gathering news

[1060] Subject: Server

[1061] The server accesses the received news URL and collects the news article. It retrieves the HTML data using an HTTP request and parses the retrieved HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[1062] Input: Newsgathering request (HTTP GET request)

[1063] Output: HTML data and extracted news headlines

[1064] Step 4: Summary generation

[1065] Subject: Server

[1066] The server compiles the extracted headlines, generates a prompt based on the summary, and sends it to a generative AI model (e.g., OpenAI GPT-3). The generative AI model then generates a summary based on the prompt.

[1067] Input: Extracted news headlines (e.g. "Headline 1, Headline 2, Headline 3")

[1068] Output: A summary generated by a generative AI model (e.g., "Generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'")

[1069] Step 5: Format the report

[1070] Subject: Server

[1071] The server formats the generated summary into a report by reading a template, inserting the generated summary at the appropriate position, adding headers and the date and time of generation, according to a predefined template.

[1072] Input: Generated summary

[1073] Output: Reports according to a standard format

[1074] Step 6: Submit the report

[1075] Subject: Server

[1076] The server sends the completed report to the user's terminal. The generated report is delivered to the user using an HTTP response or email. Specifically, if the report is returned as an HTTP response, it is returned in JSON or HTML format, and if it is sent by email, it is sent to the specified email address using the SMTP protocol.

[1077] Input: Formatted report

[1078] Output: Sending the report to the user's terminal

[1079] Step 7: Review the report

[1080] Subject: User

[1081] The user checks the received report on the device, for example, by opening the received report using a browser or email client and displaying its contents.

[1082] Input: Report sent to terminal

[1083] Output: User views the report and gets the information they need.

[1084] In this way, each step works in conjunction with the other steps, allowing the user to efficiently obtain a news summary report.

[1085] (Application example 1)

[1086] 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."

[1087] In modern society, there is a need to efficiently collect, summarize, and visualize important information from a vast number of sources. However, manually organizing and summarizing news articles and information is time-consuming and labor-intensive. It is also difficult to monitor multiple sources at once and extract important information in real time. Furthermore, a method is needed for users to easily browse summarized information and instantly obtain the information they need.

[1088] 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.

[1089] In this invention, the server includes means for acquiring data from specified information sources, means for analyzing the acquired data to extract key information, means for summarizing the extracted key information using a generative AI model, means for formatting the summarized information into a report, and means for transmitting the formatted report to a user terminal, thereby enabling a user to quickly summarize and acquire important information from multiple information sources and efficiently manage information on a daily basis.

[1090] A "designated information source" is an information provider designated by a user to obtain specific data.

[1091] "Means of acquiring data" means the mechanisms or systems used to collect data from designated sources.

[1092] "Means for analyzing data" refers to techniques and methods for analyzing acquired data and determining key information.

[1093] "Key information extraction" is the process for selecting important information from the analyzed data.

[1094] A "generative AI model" refers to an algorithm or computational model that uses artificial intelligence to process data and generate a result.

[1095] "Summarization methods" are techniques or methods for concisely summarizing extracted information.

[1096] A "report formatting means" is a method for displaying summarized information in a certain format.

[1097] A "user terminal" is a device that allows a user to receive and manipulate information.

[1098] "Transmitting means" refers to a method for sending data from the server to the user terminal.

[1099] The "means for checking" is a method by which the user views the information received at the terminal and checks the content.

[1100] System configuration and functions

[1101] As an embodiment of the present invention, we will specifically exemplify a system that extracts key information from news sources, summarizes it, and provides it to users. This system mainly consists of three elements: a server, a terminal, and a user.

[1102] News source registration

[1103] Subject: User

[1104] Users register the URL of a news site they are interested in in the application on their device by entering a URL such as "https: / / example-news-site.com" in the input form and pressing the submit button.

[1105] Data acquisition and analysis

[1106] Subject: Server

[1107] The server accesses the specified news URL and collects news articles. The server uses a library such as BeautifulSoup to parse the HTML content and extracts the article headlines and body text.

[1108] Summary Generation

[1109] Subject: Server

[1110] The server sends the extracted news article headlines and text to a generative AI model (e.g., GPT-3) to summarize the key information. The generative AI model generates a summary using a prompt sentence.

[1111] Prompt Sentence Examples

[1112] text

[1113] Generate a summary of a news article. Title: Example News Article Title

[1114] Body: Example news article body content, which includes various details and information about the event.

[1115] summary:

[1116] Report Format

[1117] Subject: Server

[1118] The server formats the generated summary into a report, following a predefined template, adding headers and the date and time of generation to make it user-friendly.

[1119] Report submission and confirmation

[1120] Subject: Server

[1121] The server sends the completed report to the user's device. The generated report is delivered to the user's device using HTTP responses, push notifications, or email.

[1122] Subject: User

[1123] Users can check the received reports on their devices. Using their smartphones or tablets, users can easily view summarized news reports and obtain the information they need.

[1124] Hardware and software used

[1125] The main hardware required to realize this system includes a server and a user device. The server is equipped with a high-performance processor and large-capacity memory to process the generative AI model, while the user device is typically a smartphone or tablet.

[1126] The software used includes BeautifulSoup (HTML parsing), HTTP request processing libraries (e.g., requests), generative AI models (e.g., GPT-3) on the server side, and formatting templates for formatting the results.

[1127] This allows users to quickly obtain key information from multiple sources and efficiently grasp the news.

[1128] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1129] Step 1:

[1130] Subject: User

[1131] The user enters the URL of a news source, which sets the designated information source. For example, a URL like "https: / / example-news-site.com" is entered and stored in the application's database. This information becomes the input for the next data collection.

[1132] Step 2:

[1133] Subject: Terminal

[1134] The terminal sends a request containing the URL of the registered news source to the server, where a news gathering request is generated using the HTTP protocol. The input of the request is the URL of the news source, which is then sent to the server.

[1135] Step 3:

[1136] Subject: Server

[1137] The server retrieves the news article from the specified URL. Specifically, it executes an HTTP request and analyzes the retrieved HTML content. It then parses the HTML content using an HTML analysis library such as BeautifulSoup to extract the headline and body of the news article. The input of this step is the retrieved HTML data, and the output is the parsed news headline and body.

[1138] Step 4:

[1139] Subject: Server

[1140] The server sends the extracted news headlines and text to a generative AI model to generate summaries, using prompts like the following:

[1141] text

[1142] Generate a summary of a news article. Title: Example News Article Title

[1143] Body: Example news article body content, which includes various details and information about the event.

[1144] summary:

[1145] Send a prompt to a generative AI model (e.g., GPT-3) to summarize key information. The input for this step is the news headline, the text, and the prompt, and the output is the generated summary.

[1146] Step 5:

[1147] Subject: Server

[1148] The server formats the generated summary into a report. Specifically, it uses a predefined template to create a report with a header, summary, and the date and time of generation. This process improves the report's readability and appearance. The input to this step is the generated summary, and the output is a formatted report.

[1149] Step 6:

[1150] Subject: Server

[1151] The server sends the formatted report to the user's device, making it easily accessible to the user using methods such as HTTP responses, push notifications, emails, etc. The input of this step is the formatted report, and the output is the report delivered to the user's device.

[1152] Step 7:

[1153] Subject: User

[1154] The user checks the received report on the device. The user quickly accesses important news information by opening notifications or emails on their smartphone or tablet and viewing the report content. The input of this step is the report sent to the device, and the output is the summary report checked by the user.

[1155] By performing the above steps in order, the user can efficiently obtain a summary of a news article.

[1156] 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.

[1157] System configuration

[1158] The present invention is a system that acquires data from a specified information source, analyzes the acquired data to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[1159] System Operation

[1160] Specifying the news URL

[1161] Subject: User

[1162] The user uses the browser on their device to specify the news source URL and send it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the send button.

[1163] News Gathering Requests

[1164] Subject: Terminal

[1165] The device sends a request containing the specified news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[1166] News gathering

[1167] Subject: Server

[1168] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1169] News Analysis

[1170] Subject: Server

[1171] The server parses the retrieved HTML content and extracts the headlines of the main news articles. The server uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles in the page (e.g.< / h2> <h2>Extract the text inside the tag.

[1172] Summary Generation

[1173] Subject: Server

[1174] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent as an overall summary request to the generation AI.

[1175] sentiment analysis

[1176] Subject: Server

[1177] The server runs an emotion engine to recognize the user's emotions, based on their past actions and real-time inputs, such as keyboard and mouse movements, as well as voice and facial expressions.

[1178] Customize reports

[1179] Subject: Server

[1180] The server customizes the generated summary based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, it will prioritize positive news and concise summaries.

[1181] Report Format

[1182] Subject: Server

[1183] The server formats the summarized information into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[1184] Report submission

[1185] Subject: Server

[1186] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1187] Check the report

[1188] Subject: User

[1189] Users can check the received reports on their devices, browse the contents of the reports on their device screen, and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1190] Specific examples

[1191] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[1192] 1. The user enters a URL into the browser input form and submits it.

[1193] 2. The device sends a news gathering request to the server.

[1194] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[1195] 4. The server requests the generation AI to summarize the extracted headlines.

[1196] 5. Generative AI generates a summary.

[1197] 6. The server recognizes the user's emotions using an emotion engine.

[1198] 7. The server customizes the summary based on the recognized sentiment.

[1199] 8. The server formats the customized summary into a report.

[1200] 9. The server sends the report to the user's device.

[1201] 10. The user checks the report on the device.

[1202] In this way, this system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[1203] The processing flow will be explained below.

[1204] Step 1:

[1205] Subject: User

[1206] The user enters the news source URL in the device's browser and presses the send button. For example, the URL "https: / / example-news-site.com" is specified and sent.

[1207] Step 2:

[1208] Subject: Terminal

[1209] The device sends a request containing the news URL to the server, which uses the HTTP protocol and acts as a request to retrieve data from the news source.

[1210] Step 3:

[1211] Subject: Server

[1212] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1213] Step 4:

[1214] Subject: Server

[1215] The server parses the HTML content and extracts the headlines of major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the HTML structure and extract the headlines (e.g.,< / h2> <h2>Extract the text inside the tag.

[1216] Step 5:

[1217] Subject: Server

[1218] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent to the AI ​​model as a prompt for summary generation.

[1219] Step 6:

[1220] Subject: Generative AI model (e.g., GPT-3)

[1221] The generative AI model extracts important elements from the submitted text and generates a summary text, which is then sent back to the server.

[1222] Step 7:

[1223] Subject: Server

[1224] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard typing speed, mouse movement, voice input, and facial expression data).

[1225] Step 8:

[1226] Subject: Server

[1227] The server customizes the generated summary based on the user's emotional data obtained by the emotion engine. For example, if the user is feeling stressed, the server may adjust the summary to emphasize positive news or provide a concise summary.

[1228] Step 9:

[1229] Subject: Server

[1230] The server formats the customized summary into a report, adding headers, generation date and time, and other information to the summary text to make it easier for the user to understand.

[1231] Step 10:

[1232] Subject: Server

[1233] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1234] Step 11:

[1235] Subject: User

[1236] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1237] In this way, the system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[1238] Example 2

[1239] 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."

[1240] In conventional systems, the process of retrieving data from specified sources, extracting key information, and summarizing it is often performed manually, resulting in a lack of efficiency. Furthermore, the system lacks the ability to customize information based on the user's emotions, resulting in a less than satisfactory user experience. Therefore, there is a need to provide a system that efficiently retrieves data and customizes it according to the user's emotions.

[1241] 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.

[1242] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, means for using a generative AI model to summarize the extracted key information, means for generating a prompt sentence for the generative AI model, means for recognizing a user's emotion, means for customizing the summary based on the recognized user's emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal, thereby enabling automation of the entire system and improving the user experience.

[1243] A "designated source" is a source from which data is obtained, such as a specific website or database entered by the user.

[1244] "Means for retrieving data" refers to a function for collecting necessary data from a source such as a specified URL, and includes the process of sending an HTTP request to retrieve HTML content.

[1245] "Means for analyzing data and extracting key information" refers to a function for analyzing acquired data and selecting and extracting important information from it.

[1246] "Means for using a generative AI model" refers to a function for summarizing text information using a generative AI model (e.g., a natural language processing model).

[1247] A "means for generating prompt sentences" is a function that generates sentences to be input into a generative AI model, and provides them in an appropriately formatted form.

[1248] The "means for recognizing user emotions" is a function for analyzing user behavior data and real-time input data to determine the user's emotional state.

[1249] The "means for customizing a summary" is a function for adjusting the generated summary content in accordance with the recognized user's emotions and providing it in an optimal form.

[1250] The "means for formatting into a report format" is a function for formatting the generated summary information into a form that is easy for the user to understand and outputting it as a report.

[1251] "Means for sending to user terminal" refers to a function for sending a formatted report to a terminal designated by the user, and includes HTTP response and email transmission.

[1252] MODE FOR CARRYING OUT THE INVENTION

[1253] The present invention is a system that acquires data from a specified information source, analyzes it to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[1254] Specifying the news URL

[1255] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the submit button. This action sends the news URL to the server.

[1256] News Gathering Requests

[1257] The device sends an HTTP request containing the specified news URL to the server. Specifically, it generates an HTTP GET request to retrieve the news source data. For example:

[1258] GET / HTTP / 1.1

[1259] Host: example-news-site.com

[1260] News gathering

[1261] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com".

[1262] News Analysis

[1263] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles contained within the page (e.g.,< / h2> <h2>Extract the text inside the tag. Example:

[1264] soup = BeautifulSoup(html_content, 'html.parser')

[1265] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[1266] Summary Generation

[1267] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt, which requests the entire summary from the generation AI. An example of a prompt is:

[1268] "Here are the news headlines and their contents. I want you to summarize them."

[1269] sentiment analysis

[1270] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard and mouse movements, voice data) to determine the user's emotions.

[1271] Customize reports

[1272] The server customizes the generated summaries based on the user's perceived emotions, for example, prioritizing positive news and concise summaries if the user is feeling stressed.

[1273] Report Format

[1274] The server formats the summarized information into a report, including headers, generation date and time, and summary text, making it easy for the user to understand. For example:

[1275] Report Generated on: YYYY-MM-DD

[1276] -------------------

[1277] {summary}

[1278] Report submission

[1279] The server sends the completed report to the user's terminal, using HTTP responses or email to ensure that the generated report reaches the user.

[1280] Check the report

[1281] Users can check the received report on their device, view the report contents in a browser or email app, and obtain the necessary information. If more detailed news information is required, they can click on the link in the report to view the original article.

[1282] In this way, the system of the present invention allows users to easily obtain news, get summaries of the news, and further receive customized information based on the user's emotions.

[1283] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1284] Step 1:

[1285] Specifying the news URL

[1286] Subject: User

[1287] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter "https: / / example-news-site.com" and press the submit button. This action sends the URL as input to the system, which then uses the entered URL in the next step.

[1288] Step 2:

[1289] News Gathering Requests

[1290] Subject: Terminal

[1291] The device sends an HTTP request to the server containing the specified news URL, generating an HTTP GET request like this:

[1292] GET / HTTP / 1.1

[1293] Host: example-news-site.com

[1294] This request acts as a request to the server to retrieve the data. The output is sent to the server in the form of an HTTP GET request.

[1295] Step 3:

[1296] News gathering

[1297] Subject: Server

[1298] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com". The retrieved HTML data is used as input for the next step.

[1299] Step 4:

[1300] News Analysis

[1301] Subject: Server

[1302] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the text within the HTML tags. For example,< / h2> <h2>Extract the text inside a tag:

[1303] soup = BeautifulSoup(html_content, 'html.parser')

[1304] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[1305] The input is the retrieved HTML data and the output is a list of extracted headings.

[1306] Step 5:

[1307] Summary Generation

[1308] Subject: Server

[1309] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt and sent to the generation AI. An example of a prompt is:

[1310] "Here are the news headlines and their contents. I want you to summarize them."

[1311] The output from the generative AI is a summary text.

[1312] Step 6:

[1313] sentiment analysis

[1314] Subject: Server

[1315] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavioral data and real-time inputs (e.g., keyboard, mouse movements, and voice data) to determine the user's emotions. The input is the user's behavioral data, and the output is the recognized emotional state.

[1316] Step 7:

[1317] Customize reports

[1318] Subject: Server

[1319] The server customizes the generated summary based on the user's recognized emotions. For example, if the user is feeling stressed, it prioritizes positive news and provides a concise summary. The input is the summary text and emotion data, and the output is a customized summary.

[1320] Step 8:

[1321] Report Format

[1322] Subject: Server

[1323] The server formats the summarized information into a report, adding headers and a generated date and time to make it more user-friendly. For example:

[1324] Report Generated on: YYYY-MM-DD

[1325] -------------------

[1326] {summary}

[1327] The input is a customized summary and the output is a formatted report.

[1328] Step 9:

[1329] Report submission

[1330] Subject: Server

[1331] The server sends the completed report to the user's terminal. The generated report is delivered to the user using communication means such as HTTP response or email. The input is the formatted report, and the output is the transmission to the user's terminal.

[1332] Step 10:

[1333] Check the report

[1334] Subject: User

[1335] The user checks the received report on the device. They view the report contents in a browser or email app and obtain the necessary information. If more detailed news information is required, they click on the link in the report to view the original article. The input is the received report, and the output is improved user satisfaction.

[1336] (Application example 2)

[1337] 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."

[1338] Conventional information extraction and summarization systems have the problem that they provide users with uniform information and are unable to provide appropriate information according to the user's emotions and situation. There is also a need to improve the user experience by providing more positive information and concise summaries, especially for users who are highly stressed.

[1339] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data and extracting key information, means for summarizing the extracted key information, means for recognizing a user's emotion and customizing the summary content based on the recognized emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal. This makes it possible to provide appropriate information according to the user's emotion.

[1340] A "designated source" is a specific data source, such as a website or database, that contains news or information designated by the user.

[1341] "Means of obtaining data" refers to the methods and systems for extracting the required information from the specified source, including access methods using the HTTP protocol.

[1342] "Means of analyzing data and extracting key information" refers to algorithms or systems that identify and highlight important parts or keywords from the acquired data.

[1343] A "summarization means" is a method or system for concisely summarizing extracted key information, including, for example, a process for summarizing text using a generative AI model.

[1344] "Means for recognizing emotions" refers to systems or algorithms that analyze and recognize users' emotions in real time or based on past behavioral data.

[1345] A "means for customizing summary content" is a method or system for tailoring the content of summarized information based on the recognized emotional state of the user, to provide it in a more user-friendly form.

[1346] A "report formatting means" is a system or process for formatting summarized information into a report that is easy for users to understand.

[1347] "Means for sending to user terminal" refers to the method or protocol for sending the formatted report to the user terminal, including HTTP responses, sending emails, etc.

[1348] The system of the present invention acquires data from specified information sources, analyzes the acquired data to extract key information, summarizes the key information, and creates and provides a customized report based on the user's sentiment. The specific configuration and operation of this system are shown below.

[1349] System configuration

[1350] The system of the present invention comprises the following components:

[1351] 1. User Device

[1352] An interface (e.g., a browser) through which a user enters and submits the URL of a news source.

[1353] 2. Server

[1354] This is the core component for acquiring, analyzing, summarizing, and recognizing emotions from news data. The server includes the following functional modules:

[1355] Data Acquisition Module: Acquires HTML data from the specified news URL.

[1356] Analysis module: Analyzes the acquired HTML data and extracts the headlines of major news articles.

[1357] Summarization module: Summarizes the extracted headlines using a generative AI model (e.g., GPT-3).

[1358] Emotion Recognition Module: Recognizes user emotions using automated emotion analysis algorithms.

[1359] Customization module: Customize the summarized information based on the recognized sentiment.

[1360] Formatting module: Formats customized information into a report format.

[1361] Sending module: Sends the formatted report to the user terminal.

[1362] Program processing explanation

[1363] The server performs the following processing in natural language.

[1364] 1. Data Acquisition Module:

[1365] Receives a news URL specified by the user and retrieves the HTML content of that URL using an HTTP GET request. Specifically, it uses the requests library.

[1366] 2. Analysis module:

[1367] The retrieved HTML content is parsed using the BeautifulSoup library to extract the main news article headlines (e.g.< / h2> <h2>Extract as text within tags).

[1368] 3. Summary module:

[1369] The extracted headlines are fed into a generative AI model (e.g., GPT-3) to generate a full summary. The summary is generated using a prompt, such as "Please summarize the following text: \n{text}".

[1370] 4. Emotion Recognition Module:

[1371] We run an algorithm for sentiment analysis on the summarized text, specifically using the nlptown / bert-base-multilingual-uncased-sentiment model to analyze the user's emotional state.

[1372] 5. Customization Module:

[1373] Customize summary text based on recognized emotions, for example, if a user expresses negative emotions, generate a summary that emphasizes positive elements.

[1374] 6. Formatting Module:

[1375] Format the customized text into a report format, adding headers, generation date and time, etc. to make it easier for users to understand.

[1376] 7. Transmitting module:

[1377] The completed report is sent to the user's terminal via HTTP response or email.

[1378] Specific examples

[1379] For example, if a user specifies the URL of a news site "https: / / example-news-site.com", the server will do the following:

[1380] 1. The user enters a URL and submits it.

[1381] 2. The device sends a news gathering request to the server.

[1382] 3. The server retrieves the HTML from the URL and parses it using the BeautifulSoup library.

[1383] 4. The server extracts the headlines and sends a summary request to a generative AI model (e.g., GPT-3).

[1384] 5. The generative AI model generates a summary and sends it back to the server.

[1385] 6. The server performs sentiment analysis on the summary text using the sentiment recognition module.

[1386] 7. The server customizes the summary and formats it into a report.

[1387] 8. The server sends the completed report to the user's device.

[1388] 9. The user checks the report on the device.

[1389] This allows users to obtain news summary reports efficiently in a short time, and also provides a better user experience by customizing the reports according to their emotions.

[1390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1391] Step 1:

[1392] The user specifies a news URL and sends it to the system from the device's browser. The input is the news site URL (e.g., https: / / example-news-site.com), and the output is a request to the server. Specifically, the user enters the news URL into the browser's input form and presses the submit button.

[1393] Step 2:

[1394] The terminal sends a request including the specified news URL to the server. The input is the news URL specified by the user, and the output is an HTTP GET request received by the server. Specifically, the terminal sends the request to the server using the HTTP protocol.

[1395] Step 3:

[1396] The server accesses the sent news URL and retrieves the HTML content. The input is an HTTP GET request, and the output is the retrieved HTML content. Specifically, the server uses the requests library to retrieve the page source code from the specified URL.

[1397] Step 4:

[1398] The server parses the retrieved HTML content and extracts the headlines of the major news articles. The input is the HTML content, and the output is a list of headlines. Specifically, the server uses the BeautifulSoup library to extract the headlines in the HTML.< / h2> <h2>Extract the text enclosed by the tags.

[1399] Step 5:

[1400] The server combines the extracted headlines and sends them to a generative AI model to generate a summary. The input is a list of headlines, and the output is the summary text. Specifically, the extracted headlines are compiled and input to a generative AI model such as GPT-3 along with a prompt. An example of the prompt is "Please summarize the following text: \n{text}".

[1401] Step 6:

[1402] The server runs an emotion recognition module to recognize the user's emotion. The input is the summarized text, and the output is the user's emotion data. Specifically, the summarized text is input to a sentiment analysis model (nlptown / bert-base-multilingual-uncased-sentiment) to obtain an emotion score.

[1403] Step 7:

[1404] The server customizes the summary content based on the recognized emotions. The input is the summary text and the user's emotion data, and the output is a customized summary text. Specifically, the content is adjusted based on the emotion data, such as emphasizing positive elements when negative.

[1405] Step 8:

[1406] The server formats the customized summary into a report. The input is the customized summary text, and the output is a report-formatted document, specifically by adding a header and a creation date to the summary text.

[1407] Step 9:

[1408] The server sends the completed report to the user's terminal. The input is a document in report format, and the output is a report displayed on the user's terminal. Specifically, the report is delivered to the user using communication methods such as HTTP responses or email.

[1409] Step 10:

[1410] The user checks the received report on the terminal. The input is the received report, and the output is the viewed report information. Specifically, the user checks the contents of the report through a browser or email application.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] [Fourth embodiment]

[1415] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1416] 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.

[1417] 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).

[1418] 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.

[1419] 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.

[1420] 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).

[1421] 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.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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."

[1428] System configuration

[1429] The present invention is a system for acquiring data from a specified information source, analyzing the acquired data to extract key information, summarizing the extracted key information, formatting the summarized information into a report, and transmitting the formatted report to a user terminal. The system may further include means for formatting the summarized information into a specific format and means for managing access rights when acquiring data from a specified information source. This system is implemented by a server, a terminal, and a user working together.

[1430] System Operation

[1431] Specifying the news URL

[1432] Subject: User

[1433] The user specifies the URL of a news source using a terminal and sends it to the system. For example, the user enters a URL such as "https: / / example-news-site.com" in an input form on a browser and presses the send button.

[1434] News Gathering Requests

[1435] Subject: Terminal

[1436] The device sends a request containing the news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[1437] News gathering

[1438] Subject: Server

[1439] The server accesses the sent news URL and collects the news article. The server parses the HTML content and extracts the headline of the news article. For this purpose, an HTML parsing library such as BeautifulSoup can be used.

[1440] Summary Generation

[1441] Subject: Server

[1442] The server sends the extracted headlines as a summary generation request to a generative AI (e.g., GPT-3). The server combines multiple headlines and uses a generative AI model to summarize the key information, resulting in a concise summary of the key points of the news article.

[1443] Report Format

[1444] Subject: Server

[1445] The server formats the generated summary into a report, for example adding headers and timestamps to make it user-friendly. The report formatting is done according to a predefined template.

[1446] Report submission

[1447] Subject: Server

[1448] The server sends the completed report to the user's terminal, where the generated report is delivered to the user using an HTTP response or email.

[1449] Check the report

[1450] Subject: User

[1451] The user checks the received report on the device. The user browses the contents of the report on the device screen and obtains the necessary information. This allows the user to grasp important news information in a short amount of time.

[1452] Specific examples

[1453] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[1454] 1. The user enters a URL into the browser's input form and submits it.

[1455] 2. The device sends a news gathering request to the server.

[1456] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[1457] 4. The server requests the generation AI to summarize the extracted headlines.

[1458] 5. Generative AI generates a summary.

[1459] 6. The server formats the generated summary into a report.

[1460] 7. The server sends the report to the user's device.

[1461] 8. The user checks the report on the device.

[1462] In this way, this system allows users to obtain news summary reports efficiently and quickly, significantly reducing the burden of information gathering and report creation.

[1463] The processing flow will be explained below.

[1464] Step 1:

[1465] Subject: User

[1466] The user specifies the news source URL using the device's browser. Specifically, the user enters "https: / / example-news-site.com" into the browser's input form and presses the send button.

[1467] Step 2:

[1468] Subject: Terminal

[1469] The device sends a request containing the specified news URL to the server, which uses the HTTP protocol and serves as a request to retrieve data from the news source.

[1470] Step 3:

[1471] Subject: Server

[1472] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1473] Step 4:

[1474] Subject: Server

[1475] Parse the HTML content retrieved by the server. Specifically, use an HTML parsing library such as BeautifulSoup to extract news article headlines (e.g., <h2>Extract the text inside the tag.

[1476] Step 5:

[1477] Subject: Server

[1478] The server combines the extracted headlines and sends a summary generation request to the generation AI (e.g., GPT-3). Multiple headlines are combined into a single text and sent as a complete summary request to the generation AI.

[1479] Step 6:

[1480] Subject: Generative AI model (e.g., GPT-3)

[1481] The generative AI model extracts important elements from the input text and generates a summary, which is then sent back to the server.

[1482] Step 7:

[1483] Subject: Server

[1484] The server receives the generated summary and formats it into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[1485] Step 8:

[1486] Subject: Server

[1487] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1488] Step 9:

[1489] Subject: User

[1490] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1491] This series of processes allows users to obtain news summary reports efficiently in a short time, significantly reducing the burden of information gathering and report creation.

[1492] Example 1

[1493] 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."

[1494] In today's information-saturated society, it is difficult for users to efficiently obtain the information they need. It also requires a great deal of effort to summarize the key information from a large amount of information, such as news articles, and understand it quickly. Furthermore, the process of organizing the obtained information into a user-friendly format is also cumbersome, and there is a need for a means to automate these tasks.

[1495] 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.

[1496] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, and means for summarizing the extracted key information using a generative AI model. This allows the server to efficiently extract and summarize key parts from large amounts of information such as news articles, enabling users to grasp important information in a short amount of time.

[1497] A "specified information source" is a source from which data is obtained, such as a URL entered by a user or a database.

[1498] "Means of obtaining data" refers to the methods and processes used to collect the required data from designated sources.

[1499] "Means of analyzing data and extracting key information" refers to methods and techniques for analyzing collected data and selecting important or necessary information.

[1500] "Generative AI model" refers to an algorithm or system used to generate, summarize, or analyze text or information using artificial intelligence techniques.

[1501] "Summarization methods" refer to methods and techniques for shortening the extracted key information and reconstructing it in a way that includes only the important points.

[1502] "Means for formatting into a report format" refers to a method or technique for formatting summarized information so that it is easy for a user to read, and compiling it into a report in a specified format.

[1503] "User terminal" refers to a device such as a computer or smartphone that a user uses to operate the system.

[1504] "Access rights management measures" refers to the methods and processes for verifying, approving, and managing the rights required to obtain data from designated sources.

[1505] The present invention provides a system that allows users to efficiently collect key information from information sources such as news sites and receive summarized reports. This system is implemented by a server, terminals, and users working together.

[1506] First, the user specifies the URL of a news source using the device. For example, they enter a URL such as "https: / / example-news-site.com" using an input form on the browser and press the send button. This URL is then sent from the device to the server.

[1507] The server then accesses the specified news URL and collects the news article. The server retrieves the HTML data using an HTTP request and parses the HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[1508] The extracted headlines are sent from the server to a generative AI model (e.g., OpenAI's GPT-3). A prompt sentence is used as input to the generative AI model. An example of a prompt sentence is "Please generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'." Based on this prompt sentence, the generative AI model summarizes the important information and returns the results to the server.

[1509] The server then formats the generated summary into a report, according to a predefined template, adding headers and the date and time of generation for user readability, and then sends the report in a specific format to the user's device.

[1510] Finally, the user checks the received report on the terminal. The user can view the report contents on the terminal screen and quickly grasp the necessary information.

[1511] This system allows users to efficiently extract key information from vast amounts of news content and receive summarized reports, significantly improving the efficiency of information gathering and report creation.

[1512] The hardware required to implement the specific operation of this system includes high-performance computers and cloud services as servers, and personal computers and smartphones as user devices.The software used includes HTML analysis libraries such as BeautifulSoup, libraries for HTTP communication, and GPT-3 as a generative AI model.

[1513] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1514] Step 1: Specify the news URL

[1515] Subject: User

[1516] The user specifies the URL of a news source using a terminal. Specifically, the user enters the URL "https: / / example-news-site.com" into the browser's input form and presses the submit button. This operation sends the URL to the system.

[1517] Input: URL of the news source (e.g. "https: / / example-news-site.com")

[1518] Output: A request sent from the device to the server for the specified URL

[1519] Step 2: Submit a newsgathering request

[1520] Subject: Terminal

[1521] The device sends a request including a news URL to the server. This request uses the HTTP protocol to obtain data from the news source. Specifically, an HTTP GET request is generated that includes the URL and user information.

[1522] Input: The specified URL (e.g. "https: / / example-news-site.com")

[1523] Output: A newsgathering request is sent to the server

[1524] Step 3: Gathering news

[1525] Subject: Server

[1526] The server accesses the received news URL and collects the news article. It retrieves the HTML data using an HTTP request and parses the retrieved HTML content using an HTML parsing library such as BeautifulSoup. This extracts key information such as the headline of the news article.

[1527] Input: Newsgathering request (HTTP GET request)

[1528] Output: HTML data and extracted news headlines

[1529] Step 4: Summary generation

[1530] Subject: Server

[1531] The server compiles the extracted headlines, generates a prompt based on the summary, and sends it to a generative AI model (e.g., OpenAI GPT-3). The generative AI model then generates a summary based on the prompt.

[1532] Input: Extracted news headlines (e.g. "Headline 1, Headline 2, Headline 3")

[1533] Output: A summary generated by a generative AI model (e.g., "Generate a summary based on the following news headlines: 'Headline 1, Headline 2, Headline 3'")

[1534] Step 5: Format the report

[1535] Subject: Server

[1536] The server formats the generated summary into a report by reading a template, inserting the generated summary at the appropriate position, adding headers and the date and time of generation, according to a predefined template.

[1537] Input: Generated summary

[1538] Output: Reports according to a standard format

[1539] Step 6: Submit the report

[1540] Subject: Server

[1541] The server sends the completed report to the user's terminal. The generated report is delivered to the user using an HTTP response or email. Specifically, if the report is returned as an HTTP response, it is returned in JSON or HTML format, and if it is sent by email, it is sent to the specified email address using the SMTP protocol.

[1542] Input: Formatted report

[1543] Output: Sending the report to the user's terminal

[1544] Step 7: Review the report

[1545] Subject: User

[1546] The user checks the received report on the device, for example, by opening the received report using a browser or email client and displaying its contents.

[1547] Input: Report sent to terminal

[1548] Output: User views the report and gets the information they need.

[1549] In this way, each step works in conjunction with the other steps, allowing the user to efficiently obtain a news summary report.

[1550] (Application example 1)

[1551] 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."

[1552] In modern society, there is a need to efficiently collect, summarize, and visualize important information from a vast number of sources. However, manually organizing and summarizing news articles and information is time-consuming and labor-intensive. It is also difficult to monitor multiple sources at once and extract important information in real time. Furthermore, a method is needed for users to easily browse summarized information and instantly obtain the information they need.

[1553] 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.

[1554] In this invention, the server includes means for acquiring data from specified information sources, means for analyzing the acquired data to extract key information, means for summarizing the extracted key information using a generative AI model, means for formatting the summarized information into a report, and means for transmitting the formatted report to a user terminal, thereby enabling a user to quickly summarize and acquire important information from multiple information sources and efficiently manage information on a daily basis.

[1555] A "designated information source" is an information provider designated by a user to obtain specific data.

[1556] "Means of acquiring data" means the mechanisms or systems used to collect data from designated sources.

[1557] "Means for analyzing data" refers to techniques and methods for analyzing acquired data and determining key information.

[1558] "Key information extraction" is the process for selecting important information from the analyzed data.

[1559] A "generative AI model" refers to an algorithm or computational model that uses artificial intelligence to process data and generate a result.

[1560] "Summarization methods" are techniques or methods for concisely summarizing extracted information.

[1561] A "report formatting means" is a method for displaying summarized information in a certain format.

[1562] A "user terminal" is a device that allows a user to receive and manipulate information.

[1563] "Transmitting means" refers to a method for sending data from the server to the user terminal.

[1564] The "means for checking" is a method by which the user views the information received at the terminal and checks the content.

[1565] System configuration and functions

[1566] As an embodiment of the present invention, we will specifically exemplify a system that extracts key information from news sources, summarizes it, and provides it to users. This system mainly consists of three elements: a server, a terminal, and a user.

[1567] News source registration

[1568] Subject: User

[1569] Users register the URL of a news site they are interested in in the application on their device by entering a URL such as "https: / / example-news-site.com" in the input form and pressing the submit button.

[1570] Data acquisition and analysis

[1571] Subject: Server

[1572] The server accesses the specified news URL and collects news articles. The server uses a library such as BeautifulSoup to parse the HTML content and extracts the article headlines and body text.

[1573] Summary Generation

[1574] Subject: Server

[1575] The server sends the extracted news article headlines and text to a generative AI model (e.g., GPT-3) to summarize the key information. The generative AI model generates a summary using a prompt sentence.

[1576] Prompt Sentence Examples

[1577] text

[1578] Generate a summary of a news article. Title: Example News Article Title

[1579] Body: Example news article body content, which includes various details and information about the event.

[1580] summary:

[1581] Report Format

[1582] Subject: Server

[1583] The server formats the generated summary into a report, following a predefined template, adding headers and the date and time of generation to make it user-friendly.

[1584] Report submission and confirmation

[1585] Subject: Server

[1586] The server sends the completed report to the user's device. The generated report is delivered to the user's device using HTTP responses, push notifications, or email.

[1587] Subject: User

[1588] Users can check the received reports on their devices. Using their smartphones or tablets, users can easily view summarized news reports and obtain the information they need.

[1589] Hardware and software used

[1590] The main hardware required to realize this system includes a server and a user device. The server is equipped with a high-performance processor and large-capacity memory to process the generative AI model, while the user device is typically a smartphone or tablet.

[1591] The software used includes BeautifulSoup (HTML parsing), HTTP request processing libraries (e.g., requests), generative AI models (e.g., GPT-3) on the server side, and formatting templates for formatting the results.

[1592] This allows users to quickly obtain key information from multiple sources and efficiently grasp the news.

[1593] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1594] Step 1:

[1595] Subject: User

[1596] The user enters the URL of a news source, which sets the designated information source. For example, a URL like "https: / / example-news-site.com" is entered and stored in the application's database. This information becomes the input for the next data collection.

[1597] Step 2:

[1598] Subject: Terminal

[1599] The terminal sends a request containing the URL of the registered news source to the server, where a news gathering request is generated using the HTTP protocol. The input of the request is the URL of the news source, which is then sent to the server.

[1600] Step 3:

[1601] Subject: Server

[1602] The server retrieves the news article from the specified URL. Specifically, it executes an HTTP request and analyzes the retrieved HTML content. It then parses the HTML content using an HTML analysis library such as BeautifulSoup to extract the headline and body of the news article. The input of this step is the retrieved HTML data, and the output is the parsed news headline and body.

[1603] Step 4:

[1604] Subject: Server

[1605] The server sends the extracted news headlines and text to a generative AI model to generate summaries, using prompts like the following:

[1606] text

[1607] Generate a summary of a news article. Title: Example News Article Title

[1608] Body: Example news article body content, which includes various details and information about the event.

[1609] summary:

[1610] Send a prompt to a generative AI model (e.g., GPT-3) to summarize key information. The input for this step is the news headline, the text, and the prompt, and the output is the generated summary.

[1611] Step 5:

[1612] Subject: Server

[1613] The server formats the generated summary into a report. Specifically, it uses a predefined template to create a report with a header, summary, and the date and time of generation. This process improves the report's readability and appearance. The input to this step is the generated summary, and the output is a formatted report.

[1614] Step 6:

[1615] Subject: Server

[1616] The server sends the formatted report to the user's device, making it easily accessible to the user using methods such as HTTP responses, push notifications, emails, etc. The input of this step is the formatted report, and the output is the report delivered to the user's device.

[1617] Step 7:

[1618] Subject: User

[1619] The user checks the received report on the device. The user quickly accesses important news information by opening notifications or emails on their smartphone or tablet and viewing the report content. The input of this step is the report sent to the device, and the output is the summary report checked by the user.

[1620] By performing the above steps in order, the user can efficiently obtain a summary of a news article.

[1621] 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.

[1622] System configuration

[1623] The present invention is a system that acquires data from a specified information source, analyzes the acquired data to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[1624] System Operation

[1625] Specifying the news URL

[1626] Subject: User

[1627] The user uses the browser on their device to specify the news source URL and send it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the send button.

[1628] News Gathering Requests

[1629] Subject: Terminal

[1630] The device sends a request containing the specified news URL to the server. This request is sent using the HTTP protocol and serves as a request to retrieve data from the news source.

[1631] News gathering

[1632] Subject: Server

[1633] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1634] News Analysis

[1635] Subject: Server

[1636] The server parses the retrieved HTML content and extracts the headlines of the main news articles. The server uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles in the page (e.g.< / h2> <h2>Extract the text inside the tag.

[1637] Summary Generation

[1638] Subject: Server

[1639] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent as an overall summary request to the generation AI.

[1640] sentiment analysis

[1641] Subject: Server

[1642] The server runs an emotion engine to recognize the user's emotions, based on their past actions and real-time inputs, such as keyboard and mouse movements, as well as voice and facial expressions.

[1643] Customize reports

[1644] Subject: Server

[1645] The server customizes the generated summary based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, it will prioritize positive news and concise summaries.

[1646] Report Format

[1647] Subject: Server

[1648] The server formats the summarized information into a report, adding headers and the date and time of generation to the summary text to make it more user-friendly.

[1649] Report submission

[1650] Subject: Server

[1651] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1652] Check the report

[1653] Subject: User

[1654] Users can check the received reports on their devices, browse the contents of the reports on their device screen, and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1655] Specific examples

[1656] For example, if a user specifies the URL of a news site "https: / / example-news-site.com" and sends it to the system, the following processing will occur.

[1657] 1. The user enters a URL into the browser input form and submits it.

[1658] 2. The device sends a news gathering request to the server.

[1659] 3. The server retrieves the HTML from the specified URL and extracts the headings.

[1660] 4. The server requests the generation AI to summarize the extracted headlines.

[1661] 5. Generative AI generates a summary.

[1662] 6. The server recognizes the user's emotions using an emotion engine.

[1663] 7. The server customizes the summary based on the recognized sentiment.

[1664] 8. The server formats the customized summary into a report.

[1665] 9. The server sends the report to the user's device.

[1666] 10. The user checks the report on the device.

[1667] In this way, this system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[1668] The processing flow will be explained below.

[1669] Step 1:

[1670] Subject: User

[1671] The user enters the news source URL in the device's browser and presses the send button. For example, the URL "https: / / example-news-site.com" is specified and sent.

[1672] Step 2:

[1673] Subject: Terminal

[1674] The device sends a request containing the news URL to the server, which uses the HTTP protocol and acts as a request to retrieve data from the news source.

[1675] Step 3:

[1676] Subject: Server

[1677] The server accesses the submitted news URL and retrieves the HTML content. The server uses an HTTP GET request to retrieve the page source code from the specified URL.

[1678] Step 4:

[1679] Subject: Server

[1680] The server parses the HTML content and extracts the headlines of major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the HTML structure and extract the headlines (e.g.,< / h2> <h2>Extract the text inside the tag.

[1681] Step 5:

[1682] Subject: Server

[1683] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single text and sent to the AI ​​model as a prompt for summary generation.

[1684] Step 6:

[1685] Subject: Generative AI model (e.g., GPT-3)

[1686] The generative AI model extracts important elements from the submitted text and generates a summary text, which is then sent back to the server.

[1687] Step 7:

[1688] Subject: Server

[1689] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard typing speed, mouse movement, voice input, and facial expression data).

[1690] Step 8:

[1691] Subject: Server

[1692] The server customizes the generated summary based on the user's emotional data obtained by the emotion engine. For example, if the user is feeling stressed, the server may adjust the summary to emphasize positive news or provide a concise summary.

[1693] Step 9:

[1694] Subject: Server

[1695] The server formats the customized summary into a report, adding headers, generation date and time, and other information to the summary text to make it easier for the user to understand.

[1696] Step 10:

[1697] Subject: Server

[1698] The server sends the completed report to the user's terminal. At this time, the generated report is delivered to the user using a communication means such as an HTTP response or email.

[1699] Step 11:

[1700] Subject: User

[1701] Users can check the reports they receive on their devices. They can view the report contents on their device screen and obtain the necessary information. If more detailed news information is required, they can also refer to the original article.

[1702] In this way, the system allows users to obtain news summary reports efficiently and quickly, and also provides a better user experience by customizing the reports according to their emotions.

[1703] Example 2

[1704] 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."

[1705] In conventional systems, the process of retrieving data from specified sources, extracting key information, and summarizing it is often performed manually, resulting in a lack of efficiency. Furthermore, the system lacks the ability to customize information based on the user's emotions, resulting in a less than satisfactory user experience. Therefore, there is a need to provide a system that efficiently retrieves data and customizes it according to the user's emotions.

[1706] 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.

[1707] In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data to extract key information, means for using a generative AI model to summarize the extracted key information, means for generating a prompt sentence for the generative AI model, means for recognizing a user's emotion, means for customizing the summary based on the recognized user's emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal, thereby enabling automation of the entire system and improving the user experience.

[1708] A "designated source" is a source from which data is obtained, such as a specific website or database entered by the user.

[1709] "Means for retrieving data" refers to a function for collecting necessary data from a source such as a specified URL, and includes the process of sending an HTTP request to retrieve HTML content.

[1710] "Means for analyzing data and extracting key information" refers to a function for analyzing acquired data and selecting and extracting important information from it.

[1711] "Means for using a generative AI model" refers to a function for summarizing text information using a generative AI model (e.g., a natural language processing model).

[1712] A "means for generating prompt sentences" is a function that generates sentences to be input into a generative AI model, and provides them in an appropriately formatted form.

[1713] The "means for recognizing user emotions" is a function for analyzing user behavior data and real-time input data to determine the user's emotional state.

[1714] The "means for customizing a summary" is a function for adjusting the generated summary content in accordance with the recognized user's emotions and providing it in an optimal form.

[1715] The "means for formatting into a report format" is a function for formatting the generated summary information into a form that is easy for the user to understand and outputting it as a report.

[1716] "Means for sending to user terminal" refers to a function for sending a formatted report to a terminal designated by the user, and includes HTTP response and email transmission.

[1717] MODE FOR CARRYING OUT THE INVENTION

[1718] The present invention is a system that acquires data from a specified information source, analyzes it to extract key information, summarizes the extracted key information, formats the summarized information into a report, and transmits the formatted report to a user terminal. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the content of the report can be customized based on the user's emotions.

[1719] Specifying the news URL

[1720] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter a URL such as "https: / / example-news-site.com" and press the submit button. This action sends the news URL to the server.

[1721] News Gathering Requests

[1722] The device sends an HTTP request containing the specified news URL to the server. Specifically, it generates an HTTP GET request to retrieve the news source data. For example:

[1723] GET / HTTP / 1.1

[1724] Host: example-news-site.com

[1725] News gathering

[1726] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com".

[1727] News Analysis

[1728] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to extract the headlines of the news articles contained within the page (e.g.,< / h2> <h2>Extract the text inside the tag. Example:

[1729] soup = BeautifulSoup(html_content, 'html.parser')

[1730] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[1731] Summary Generation

[1732] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt, which requests the entire summary from the generation AI. An example of a prompt is:

[1733] "Here are the news headlines and their contents. I want you to summarize them."

[1734] sentiment analysis

[1735] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavior data and real-time input (e.g., keyboard and mouse movements, voice data) to determine the user's emotions.

[1736] Customize reports

[1737] The server customizes the generated summaries based on the user's perceived emotions, for example, prioritizing positive news and concise summaries if the user is feeling stressed.

[1738] Report Format

[1739] The server formats the summarized information into a report, including headers, generation date and time, and summary text, making it easy for the user to understand. For example:

[1740] Report Generated on: YYYY-MM-DD

[1741] -------------------

[1742] {summary}

[1743] Report submission

[1744] The server sends the completed report to the user's terminal, using HTTP responses or email to ensure that the generated report reaches the user.

[1745] Check the report

[1746] Users can check the received report on their device, view the report contents in a browser or email app, and obtain the necessary information. If more detailed news information is required, they can click on the link in the report to view the original article.

[1747] In this way, the system of the present invention allows users to easily obtain news, get summaries of the news, and further receive customized information based on the user's emotions.

[1748] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1749] Step 1:

[1750] Specifying the news URL

[1751] Subject: User

[1752] The user uses the browser on their device to enter a specific news source URL and submit it to the system. For example, they enter "https: / / example-news-site.com" and press the submit button. This action sends the URL as input to the system, which then uses the entered URL in the next step.

[1753] Step 2:

[1754] News Gathering Requests

[1755] Subject: Terminal

[1756] The device sends an HTTP request to the server containing the specified news URL, generating an HTTP GET request like this:

[1757] GET / HTTP / 1.1

[1758] Host: example-news-site.com

[1759] This request acts as a request to the server to retrieve the data. The output is sent to the server in the form of an HTTP GET request.

[1760] Step 3:

[1761] News gathering

[1762] Subject: Server

[1763] The server receives the request and accesses the specified news URL to retrieve the HTML content. The server uses an HTTP GET request to retrieve the page source code from "https: / / example-news-site.com". The retrieved HTML data is used as input for the next step.

[1764] Step 4:

[1765] News Analysis

[1766] Subject: Server

[1767] The server parses the HTML content and extracts the headlines of the major news articles. Specifically, it uses an HTML parsing library such as BeautifulSoup to parse the text within the HTML tags. For example,< / h2> <h2>Extract the text inside a tag:

[1768] soup = BeautifulSoup(html_content, 'html.parser')

[1769] headlines = [h2.get_text() for h2 in soup.find_all('h2')]

[1770] The input is the retrieved HTML data and the output is a list of extracted headings.

[1771] Step 5:

[1772] Summary Generation

[1773] Subject: Server

[1774] The server combines the extracted headlines and sends them to a generation AI (e.g., GPT-3) to generate a summary. Multiple headlines are combined into a single prompt and sent to the generation AI. An example of a prompt is:

[1775] "Here are the news headlines and their contents. I want you to summarize them."

[1776] The output from the generative AI is a summary text.

[1777] Step 6:

[1778] sentiment analysis

[1779] Subject: Server

[1780] The server runs an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's past behavioral data and real-time inputs (e.g., keyboard, mouse movements, and voice data) to determine the user's emotions. The input is the user's behavioral data, and the output is the recognized emotional state.

[1781] Step 7:

[1782] Customize reports

[1783] Subject: Server

[1784] The server customizes the generated summary based on the user's recognized emotions. For example, if the user is feeling stressed, it prioritizes positive news and provides a concise summary. The input is the summary text and emotion data, and the output is a customized summary.

[1785] Step 8:

[1786] Report Format

[1787] Subject: Server

[1788] The server formats the summarized information into a report, adding headers and a generated date and time to make it more user-friendly. For example:

[1789] Report Generated on: YYYY-MM-DD

[1790] -------------------

[1791] {summary}

[1792] The input is a customized summary and the output is a formatted report.

[1793] Step 9:

[1794] Report submission

[1795] Subject: Server

[1796] The server sends the completed report to the user's terminal. The generated report is delivered to the user using communication means such as HTTP response or email. The input is the formatted report, and the output is the transmission to the user's terminal.

[1797] Step 10:

[1798] Check the report

[1799] Subject: User

[1800] The user checks the received report on the device. They view the report contents in a browser or email app and obtain the necessary information. If more detailed news information is required, they click on the link in the report to view the original article. The input is the received report, and the output is improved user satisfaction.

[1801] (Application example 2)

[1802] 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."

[1803] Conventional information extraction and summarization systems have the problem that they provide users with uniform information and are unable to provide appropriate information according to the user's emotions and situation. There is also a need to improve the user experience by providing more positive information and concise summaries, especially for users who are highly stressed.

[1804] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring data from a specified information source, means for analyzing the acquired data and extracting key information, means for summarizing the extracted key information, means for recognizing a user's emotion and customizing the summary content based on the recognized emotion, means for formatting the summarized information into a report format, and means for transmitting the formatted report to a user terminal. This makes it possible to provide appropriate information according to the user's emotion.

[1805] A "designated source" is a specific data source, such as a website or database, that contains news or information designated by the user.

[1806] "Means of obtaining data" refers to the methods and systems for extracting the required information from the specified source, including access methods using the HTTP protocol.

[1807] "Means of analyzing data and extracting key information" refers to algorithms or systems that identify and highlight important parts or keywords from the acquired data.

[1808] A "summarization means" is a method or system for concisely summarizing extracted key information, including, for example, a process for summarizing text using a generative AI model.

[1809] "Means for recognizing emotions" refers to systems or algorithms that analyze and recognize users' emotions in real time or based on past behavioral data.

[1810] A "means for customizing summary content" is a method or system for tailoring the content of summarized information based on the recognized emotional state of the user, to provide it in a more user-friendly form.

[1811] A "report formatting means" is a system or process for formatting summarized information into a report that is easy for users to understand.

[1812] "Means for sending to user terminal" refers to the method or protocol for sending the formatted report to the user terminal, including HTTP responses, sending emails, etc.

[1813] The system of the present invention acquires data from specified information sources, analyzes the acquired data to extract key information, summarizes the key information, and creates and provides a customized report based on the user's sentiment. The specific configuration and operation of this system are shown below.

[1814] System configuration

[1815] The system of the present invention comprises the following components:

[1816] 1. User Device

[1817] An interface (e.g., a browser) through which a user enters and submits the URL of a news source.

[1818] 2. Server

[1819] This is the core component for acquiring, analyzing, summarizing, and recognizing emotions from news data. The server includes the following functional modules:

[1820] Data Acquisition Module: Acquires HTML data from the specified news URL.

[1821] Analysis module: Analyzes the acquired HTML data and extracts the headlines of major news articles.

[1822] Summarization module: Summarizes the extracted headlines using a generative AI model (e.g., GPT-3).

[1823] Emotion Recognition Module: Recognizes user emotions using automated emotion analysis algorithms.

[1824] Customization module: Customize the summarized information based on the recognized sentiment.

[1825] Formatting module: Formats customized information into a report format.

[1826] Sending module: Sends the formatted report to the user terminal.

[1827] Program processing explanation

[1828] The server performs the following processing in natural language.

[1829] 1. Data Acquisition Module:

[1830] Receives a news URL specified by the user and retrieves the HTML content of that URL using an HTTP GET request. Specifically, it uses the requests library.

[1831] 2. Analysis module:

[1832] The retrieved HTML content is parsed using the BeautifulSoup library to extract the main news article headlines (e.g.< / h2> <h2>Extract as text within tags).

[1833] 3. Summary module:

[1834] The extracted headlines are fed into a generative AI model (e.g., GPT-3) to generate a full summary. The summary is generated using a prompt, such as "Please summarize the following text: \n{text}".

[1835] 4. Emotion Recognition Module:

[1836] We run an algorithm for sentiment analysis on the summarized text, specifically using the nlptown / bert-base-multilingual-uncased-sentiment model to analyze the user's emotional state.

[1837] 5. Customization Module:

[1838] Customize summary text based on recognized emotions, for example, if a user expresses negative emotions, generate a summary that emphasizes positive elements.

[1839] 6. Formatting Module:

[1840] Format the customized text into a report format, adding headers, generation date and time, etc. to make it easier for users to understand.

[1841] 7. Transmitting module:

[1842] The completed report is sent to the user's terminal via HTTP response or email.

[1843] Specific examples

[1844] For example, if a user specifies the URL of a news site "https: / / example-news-site.com", the server will do the following:

[1845] 1. The user enters a URL and submits it.

[1846] 2. The device sends a news gathering request to the server.

[1847] 3. The server retrieves the HTML from the URL and parses it using the BeautifulSoup library.

[1848] 4. The server extracts the headlines and sends a summary request to a generative AI model (e.g., GPT-3).

[1849] 5. The generative AI model generates a summary and sends it back to the server.

[1850] 6. The server performs sentiment analysis on the summary text using the sentiment recognition module.

[1851] 7. The server customizes the summary and formats it into a report.

[1852] 8. The server sends the completed report to the user's device.

[1853] 9. The user checks the report on the device.

[1854] This allows users to obtain news summary reports efficiently in a short time, and also provides a better user experience by customizing the reports according to their emotions.

[1855] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1856] Step 1:

[1857] The user specifies a news URL and sends it to the system from the device's browser. The input is the news site URL (e.g., https: / / example-news-site.com), and the output is a request to the server. Specifically, the user enters the news URL into the browser's input form and presses the submit button.

[1858] Step 2:

[1859] The terminal sends a request including the specified news URL to the server. The input is the news URL specified by the user, and the output is an HTTP GET request received by the server. Specifically, the terminal sends the request to the server using the HTTP protocol.

[1860] Step 3:

[1861] The server accesses the sent news URL and retrieves the HTML content. The input is an HTTP GET request, and the output is the retrieved HTML content. Specifically, the server uses the requests library to retrieve the page source code from the specified URL.

[1862] Step 4:

[1863] The server parses the retrieved HTML content and extracts the headlines of the major news articles. The input is the HTML content, and the output is a list of headlines. Specifically, the server uses the BeautifulSoup library to extract the headlines in the HTML.< / h2> <h2>Extract the text enclosed by the tags.

[1864] Step 5:

[1865] The server combines the extracted headlines and sends them to a generative AI model to generate a summary. The input is a list of headlines, and the output is the summary text. Specifically, the extracted headlines are compiled and input to a generative AI model such as GPT-3 along with a prompt. An example of the prompt is "Please summarize the following text: \n{text}".

[1866] Step 6:

[1867] The server runs an emotion recognition module to recognize the user's emotion. The input is the summarized text, and the output is the user's emotion data. Specifically, the summarized text is input to a sentiment analysis model (nlptown / bert-base-multilingual-uncased-sentiment) to obtain an emotion score.

[1868] Step 7:

[1869] The server customizes the summary content based on the recognized emotions. The input is the summary text and the user's emotion data, and the output is a customized summary text. Specifically, the content is adjusted based on the emotion data, such as emphasizing positive elements when negative.

[1870] Step 8:

[1871] The server formats the customized summary into a report. The input is the customized summary text, and the output is a report-formatted document, specifically by adding a header and a creation date to the summary text.

[1872] Step 9:

[1873] The server sends the completed report to the user's terminal. The input is a document in report format, and the output is a report displayed on the user's terminal. Specifically, the report is delivered to the user using communication methods such as HTTP responses or email.

[1874] Step 10:

[1875] The user checks the received report on the terminal. The input is the received report, and the output is the viewed report information. Specifically, the user checks the contents of the report through a browser or email application.

[1876] 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.

[1877] 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.

[1878] 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.

[1879] 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.

[1880] 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.

[1881] 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.

[1882] 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).

[1883] 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.

[1884] 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."

[1885] 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.

[1886] 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).

[1887] 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.

[1888] 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.

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] 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.

[1895] 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.

[1896] 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.

[1897] The following is further disclosed regarding the above embodiment.

[1898] (Claim 1)

[1899] a means of obtaining data from designated sources;

[1900] A means of analyzing the acquired data to extract key information;

[1901] a means of summarizing the key information extracted;

[1902] a means for formatting the summarized information into a report;

[1903] The system includes means for transmitting the formatted report to a user terminal.

[1904] (Claim 2)

[1905] 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

[1906] (Claim 3)

[1907] 10. The system of claim 1, further comprising means for managing access rights when retrieving data from a specified source.

[1908] "Example 1"

[1909] (Claim 1)

[1910] a means of obtaining data from designated sources;

[1911] A means of analyzing the acquired data to extract key information;

[1912] A means for summarizing the extracted key information using a generative AI model; and

[1913] a means for formatting the summarized information into a report;

[1914] The system includes means for transmitting the formatted report to a user terminal.

[1915] (Claim 2)

[1916] 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

[1917] (Claim 3)

[1918] 10. The system of claim 1, further comprising means for managing access rights when retrieving data from a specified source.

[1919] "Application Example 1"

[1920] (Claim 1)

[1921] a means of obtaining data from designated sources;

[1922] A means of analyzing the acquired data to extract key information;

[1923] A means for summarizing the extracted key information using a generative AI model; and

[1924] a means for formatting the summarized information into a report;

[1925] means for transmitting the formatted report to a user terminal;

[1926] The system includes means for viewing the summary report on a user terminal.

[1927] (Claim 2)

[1928] 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

[1929] (Claim 3)

[1930] 10. The system of claim 1, further comprising means for managing access rights when retrieving data from a specified source.

[1931] "Example 2: Combining Emotion Engines"

[1932] (Claim 1)

[1933] a means of obtaining data from designated sources;

[1934] A means of analyzing the acquired data to extract key information;

[1935] a means for using a generative AI model to summarize the extracted key information;

[1936] a means for generating a prompt sentence for the generative AI model;

[1937] means for recognizing a user's emotion;

[1938] means for customizing summaries based on the recognized user sentiment;

[1939] a means for formatting the summarized information into a report;

[1940] The system includes means for transmitting the formatted report to a user terminal.

[1941] (Claim 2)

[1942] 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

[1943] (Claim 3)

[1944] 10. The system of claim 1, further comprising means for managing access rights when retrieving data from a specified source.

[1945] "Application example 2 when combining emotion engines"

[1946] (Claim 1)

[1947] a means of obtaining data from designated sources;

[1948] A means of analyzing the acquired data to extract key information;

[1949] a means of summarizing the key information extracted;

[1950] means for recognizing a user's emotion and customizing summary content based on the recognized emotion;

[1951] a means for formatting the summarized information into a report;

[1952] The system includes means for transmitting the formatted report to a user terminal.

[1953] (Claim 2)

[1954] 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

[1955] (Claim 3)

[1956] 10. The system of claim 1, further comprising means for managing access rights when retrieving data from a specified source. [Explanation of symbols]

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Claims

1. a means of obtaining data from designated sources; A means of analyzing the acquired data to extract key information; a means of summarizing the key information extracted; a means for formatting the summarized information into a report; The system includes means for transmitting the formatted report to a user terminal.

2. 10. The system of claim 1, further comprising means for formatting the summarized information in a particular format.

3. 2. The system of claim 1, further comprising means for managing access rights when retrieving data from a designated information source.

Images