system

Abstract

Provide a system. The method comprises: collecting data from a reliable source; a means of analyzing the collected data to generate a summary of the discussion; means for providing the generated summary to a user; A system including:

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 recent years, the problems of fake news and information overload have become more serious, making it difficult to quickly and efficiently obtain reliable information. In particular, the time and effort required for users to understand information from multiple perspectives and make appropriate decisions is increasing. In this situation, there is a need for a system that can collect data from reliable sources, analyze it, and provide summaries of discussions to enable users to obtain information efficiently. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for collecting data from reliable information sources, a means for analyzing the collected data to generate summaries of discussions, and a means for providing the generated summaries to users. Specifically, the system uses web scraping technology to collect data from information sources, and natural language processing technology to analyze the data, extract important sentences, and generate summaries, thereby providing an environment in which users can efficiently obtain information from multiple perspectives.

[0006] A "reliable source" is a data source that is widely recognized and has been proven to provide accurate and unbiased information.

[0007] "Data collection methods" are technologies and methods for automatically capturing and storing relevant data from sources on the Internet.

[0008] "Means for analyzing data and generating a summary of the discussion" refers to techniques and methods for extracting important sentences and information from collected data and providing them to users in a concise format.

[0009] "Means for providing to users" refers to the technology and methods for displaying and delivering the generated summary information in a form that is accessible to users.

[0010] "Web scraping technology" is a technology for automatically obtaining information from specific websites on the Internet and analyzing their contents.

[0011] "Natural language processing technology" refers to a set of techniques and methods for analyzing human language using computers, and is used to extract meaning from text data and generate summaries. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0034] Server Roles

[0035] The server collects data from designated reliable sources. Specifically, it maintains a list of URLs of reliable news sites and sends HTTP requests to each news site to obtain its HTML content. The server then analyzes the obtained HTML content and extracts article links. This link extraction is performed using web scraping technology.

[0036] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL and parsing the article body as text, resulting in the raw article data.

[0037] The server then analyzes the retrieved article text and uses natural language processing technology to extract key sentences and generate a summary. The text is divided into sentences and the most important sentences are selected. This summary is condensed to about five sentences to help users understand the information efficiently.

[0038] Device Role

[0039] The terminal displays the final summary provided by the server to the user. The server generates a summary and sends it to the terminal in an appropriate format. The terminal receives the summary and displays it on its interface for the user to view.

[0040] User Roles

[0041] Users can check the summary provided through their device, which allows them to efficiently grasp reliable, multifaceted information. If necessary, they can also view detailed information by clicking on the original article link.

[0042] Specific examples

[0043] For example, a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. The server then uses natural language processing techniques to summarize each article and generate a final summary. These summaries are then sent to the device and displayed in a format that the user can view.

[0044] Users can view summaries on their devices and quickly obtain the information they need from the summaries. For example, if a user wants to know about a particular news item, they can simply read the summary to understand the main points. If they need more information, they can click on the provided link to the original article to access the detailed information.

[0045] In this way, the present invention provides a system that enables users to efficiently obtain information from reliable and multifaceted perspectives.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The server maintains a list of URLs for trusted news sites.

[0049] Step 2:

[0050] The server sends an HTTP request to each news site to retrieve its HTML content. For example, it uses requests.get to retrieve the page contents.

[0051] Step 3:

[0052] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0053] Step 4:

[0054] The server processes the collected article links one by one, analyzes the linked pages, and downloads and analyzes the article content. For analysis, it uses the Article class of the newspaper library.

[0055] Step 5:

[0056] The server saves the analyzed article text in text format, thereby accumulating raw text data.

[0057] Step 6:

[0058] The server analyzes the stored article text using a natural language processing tool (e.g., Spacy) and divides it into sentences. The text is analyzed using nlp objects.

[0059] Step 7:

[0060] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0061] Step 8:

[0062] The server collects the summaries it generates and saves them in a single file, such as summary.txt, allowing for centralized management of summary information.

[0063] Step 9:

[0064] The terminal retrieves the summary file from the server and displays it on the interface in a format that the user can view, allowing the user to quickly understand the important information.

[0065] Step 10:

[0066] If users need more information, they can access the original article link provided on their device and view the full text of the original article.

[0067] Example 1

[0068] 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."

[0069] In today's information society, a large amount of information is scattered across the Internet, and there is a need to efficiently collect information from reliable sources, summarize it, and provide it to users. However, manually collecting data from reliable sources, analyzing it, and generating summaries is time-consuming, labor-intensive, and inefficient. Furthermore, generating summaries requires advanced natural language processing technology, and there are currently no easy ways to do this. Therefore, there is a need for a system that can automate the collection, analysis, and summarization of information and make it available efficiently.

[0070] 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.

[0071] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the HTML content of the collected data and extracting article links, means for acquiring article text from the extracted article links and saving it as text, means for generating summaries of the saved article text using natural language processing technology, and means for transmitting the generated summaries to a terminal and providing them to a user. This makes it possible to automate the collection of information from reliable information sources, data analysis, and summary generation, and efficiently provide them to users.

[0072] A "reliable source of information" refers to an information provider or site whose information is guaranteed to be accurate and objective.

[0073] "Data collection methods" refers to the technologies and methods used to automatically obtain the required information from sources on the Internet.

[0074] "HTML Content" refers to content written in HTML, a markup language that defines the structure of web pages.

[0075] "Article Link" means a URL that provides access to a specific article on a web page.

[0076] "Article body" refers to text data that contains the main information of news articles, blog articles, etc.

[0077] "Means of saving as text" refers to the technology or method of saving acquired information in a string format in a file, etc.

[0078] "Natural language processing technology" refers to computer technology for understanding and analyzing human language.

[0079] A "summary generator" refers to a technique or method for extracting important parts from a long text and summarizing them in a shorter form.

[0080] "Device" refers to a device used by a User, such as a computer, smartphone, or tablet.

[0081] "User" refers to any individual or organization that uses the information collection system.

[0082] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0083] Server Roles

[0084] The server is responsible for collecting data from designated reliable sources. Specifically, it maintains a list of URLs for reliable news sites, sends HTTP requests to each news site, and retrieves their HTML content. The HTTP requests are sent using Python's requests library. The retrieved HTML content is then analyzed using BeautifulSoup to extract article links. Web scraping technology is used to extract these links.

[0085] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL, parsing the article body, and saving it as text. This process also uses the BeautifulSoup and requests libraries.

[0086] The server then analyzes the retrieved article text using natural language processing technology, extracts key sentences, and generates a summary. Specifically, it uses natural language processing libraries such as nltk and spaCy to divide the text into sentences and select the most important sentences. This summary is condensed to about five sentences, allowing users to efficiently understand the information.

[0087] Device Role

[0088] The terminal is responsible for displaying the final summary provided by the server to the user. The summary generated by the server is sent to the terminal in an appropriate format. For example, the summary information sent in JSON format is received and displayed on the terminal's web interface. This display is implemented using JavaScript (registered trademark) and HTML so that the summary is presented in a user-friendly format.

[0089] User Roles

[0090] Users can efficiently grasp reliable, multifaceted information by checking the summary provided through their device. If necessary, they can also access detailed information by clicking on a link to the original article. Specifically, users read the summary, quickly obtain key information from its contents, and then access the original article as needed.

[0091] Specific examples

[0092] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. It then uses natural language processing technology to summarize each article and generate a final summary. This summary is then sent to the device and displayed in a format that the user can view.

[0093] Users can view summaries on their devices and quickly understand key points. For example, if a user wants to know about a particular piece of news, they can request information from the system using the prompt "Show me the latest news summary." They can then quickly obtain the information they need by reading the summary, and if they need more details, they can click on the provided link to the original article to access the details. In this way, the present invention provides users with a powerful tool for efficiently obtaining and understanding information.

[0094] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0095] Step 1:

[0096] The server collects data from reliable sources. It receives a list of URLs of reliable news sites as input and sends HTTP requests to each news site. Specifically, it uses the requests library to send requests to each URL and retrieve HTML content. The retrieved HTML content is the output.

[0097] Step 2:

[0098] The HTML content retrieved by the server is analyzed and article links are extracted. HTML content is received as input and the HTML is parsed using BeautifulSoup. Links to news articles are extracted from the parsed HTML. The extracted article links are the output. Specifically, using BeautifulSoup Search for links contained in tags and collect article links in list format.

[0099] Step 3:

[0100] The server retrieves the body of each article from the extracted article links and saves it in text format. It receives the article links as input, sends an HTTP request to each link again to retrieve the HTML content, extracts the body of the article from the retrieved HTML, converts it to text format, and saves it. The saved article text is obtained as output. Specifically, the article URL is accessed, and the retrieved HTML is analyzed again with BeautifulSoup to extract the main content.

[0101] Step 4:

[0102] The server uses natural language processing technology to analyze article text stored on the server, extracting important sentences and generating a summary. It receives the stored article text as input and uses nltk or spaCy to divide the text into sentences. It evaluates the importance of each sentence, selects the most important sentence, and generates a summary of about five sentences. The generated summary is output. Specifically, it uses NLP techniques such as morphological analysis and sentence importance score calculation.

[0103] Step 5:

[0104] The server sends the generated summary to the terminal. It receives the generated summary as input and sends it to the terminal in an appropriate format (e.g., JSON format). As output, it obtains the JSON format summary data that was sent. Specifically, it sends the summary data as an HTTP response.

[0105] Step 6:

[0106] The terminal displays the received summary to the user. It receives the received JSON format summary data as input and displays the summary on a web interface. As output, the displayed summary is provided to the user. Specifically, it formats the summary data using JavaScript and HTML and displays it on the browser.

[0107] Step 7:

[0108] The user reviews the summary through their device and accesses the original article if necessary. The input is the displayed summary, and they obtain the necessary information. The output is the information the user obtained and access to the original article. Specifically, they read the summary to understand the main points, and if they need more details, they click the link to view the original article.

[0109] (Application example 1)

[0110] 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."

[0111] In the current information distribution system, a huge amount of information is generated every day, making it difficult for users to efficiently obtain reliable information. Browsing through many sources and articles takes time, and important information may be overlooked. Furthermore, there is a lack of real-time notifications of important information based on users' areas of interest and quick access to the original detailed information.

[0112] 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.

[0113] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for providing the generated summary to the user, means for notifying the user of important information based on the user's interests in real time, and means for providing a link from the summarized information to the original detailed information. This makes it possible to efficiently collect and summarize reliable information and provide important information based on the user's interests in real time. It also enables quick access to detailed information from the summarized information.

[0114] "Reliable sources" refer to trusted news sites and official websites that provide accurate and objective information.

[0115] "Means of collecting data" refers to the means of obtaining the necessary information from designated sources, such as using web scraping technology.

[0116] "Means for analyzing data" refers to means for analyzing collected text data and extracting important information using natural language processing technology.

[0117] "Means for generating summaries of discussions" refers to means for generating summaries of articles or discussions based on the extracted important information.

[0118] The "means for providing a summary to a user" refers to a means for displaying the generated summary on the user's terminal.

[0119] "Means of notifying users of important information in real time based on their interests" refers to means of collecting important information from reliable sources based on users' areas of interest and keywords, and notifying them in a timely manner.

[0120] "Means for providing links from the summarized information to the original detailed information" refers to means for providing links from the generated summary to the original article or detailed information, allowing users to access the detailed information.

[0121] This invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0122] Server Roles

[0123] The server first collects data from reliable sources. In this process, it uses web scraping technology to obtain the necessary data from the sources. Specifically, it uses BeautifulSoup (Python) to extract HTML content from news sites and collect article links.

[0124] Next, each article is retrieved based on the collected links and its contents are saved in text format. This involves sending an HTTP request and parsing the article's HTML to extract the text. The retrieved article text is then analyzed using natural language processing techniques. Here, techniques such as spaCy (Python) and GPT-3 (registered trademark) (OpenAI (registered trademark)) are used to extract important sentences and generate a summary.

[0125] The generated summary is sent to the terminal in an appropriate format. The server stores this information in a database and updates it as needed. PostgreSQL is used for the database, improving data management and access efficiency.

[0126] Device Role

[0127] The device displays the summaries provided by the server to the user, provides an appropriate user interface so that the user can view the summaries through a browser or a dedicated smartphone app, and notifies the user of important information in real time from the server based on the user's areas of interest and keywords.

[0128] Furthermore, the summary also provides a link to the original detailed information, allowing users to access the detailed information at their discretion. The interface for this purpose is designed to be easy for users to operate.

[0129] User Roles

[0130] Users can quickly understand important information by checking the summaries provided through their devices. Users can receive important information in real time based on their own interests. For example, when news about "environmental issues" is updated, users will automatically receive a summary and can access the detailed original article from the summary article.

[0131] Specific examples

[0132] For example, a server might collect articles about environmental issues from a news site and generate summaries of the articles. The summaries are generated using prompts such as:

[0133] Example prompt sentence:

[0134] Generate a summary of a news article:

[0135] 1. Load articles collected from trusted news sites.

[0136] 2. Extract the key points from the article and summarize them in about five sentences.

[0137] 3. Return the summary.

[0138] (Article text)

[0139] "..."

[0140] ...

[0141] "

[0142] (summary)

[0143] 1. In this article...

[0144] 2. ...

[0145] This allows users to quickly grasp important information and access detailed information as needed. The system efficiently collects and summarizes reliable information, providing important information based on the user's interests in real time. Furthermore, it enables quick access to detailed information from the summarized information, significantly reducing the burden on users when it comes to obtaining information.

[0146] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0147] Step 1:

[0148] The server retrieves the URLs of news sites from a specified list of reliable sources. Then, it sends an HTTP request to retrieve the HTML content of each news site. It then parses the HTML content using BeautifulSoup (Python) to extract article links. The input is a list of news site URLs, and the output is a list of article links.

[0149] Step 2:

[0150] The server retrieves the content of each article based on the extracted article links. Specifically, it sends an HTTP request to each link again to retrieve the article's HTML, and then uses BeautifulSoup (Python) to extract the article's body text. The input is a list of article links, and the output is the text of each article's body.

[0151] Step 3:

[0152] The server analyzes the retrieved article text using natural language processing technology. For example, it uses spaCy (Python) to divide the article text into sentences and GPT-3 (OpenAI) to extract important sentences. The following sentence is used as an example of a prompt sentence:

[0153] Example prompt sentence:

[0154] Generate a summary of a news article:

[0155] 1. Load articles collected from trusted news sites.

[0156] 2. Extract the key points from the article and summarize them in about five sentences.

[0157] 3. Return the summary.

[0158] (Article text)

[0159] "..."

[0160] ...

[0161] "

[0162] (summary)

[0163] 1. In this article...

[0164] 2. ...

[0165] The input is the text of the article, and the output is a summary of about five sentences.

[0166] Step 4:

[0167] The server saves the generated summary and sends it to the terminal in an appropriate format. During this process, the summary and the link to the original article are stored in a database (PostgreSQL) and sent to the front end to provide a user interface. The input is the summary text and the link to the original article, and the output is the summary displayed on the user terminal.

[0168] Step 5:

[0169] The terminal displays the summary received from the server to the user. The user interface is simple and provides a summary and a link to the original article. The input is the summary text received from the server and the link to the original article, and the output is the display to the user.

[0170] Step 6:

[0171] The device notifies users of important information in real time based on their profile and areas of interest. It receives updates from the server, filters them based on their interests, and sends push notifications to users. The input is the user's interest information and summary text, and the output is the information sent to the user as a push notification.

[0172] Step 7:

[0173] Users can view the summary on their device and, if necessary, click on the link to the original article to access more detailed information. This allows users to efficiently grasp important information and easily view detailed information. The input is the summary and article link displayed on the device, and the output is the information the user obtains.

[0174] 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.

[0175] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and then uses an emotion engine to recognize and analyze the user's emotions, customizing the generated summary to suit the user's emotions. This system aims to provide users with highly reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0176] Server Roles

[0177] The server must first maintain a list of URLs for reliable news sites. The server then sends an HTTP request to each news site to retrieve its HTML content. The retrieved HTML content is then parsed using BeautifulSoup to extract article links. This link extraction is performed using web scraping techniques.

[0178] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library, and the raw article text is obtained by analyzing it. This data is then analyzed using natural language processing techniques, divided into sentences, and key sentences are extracted to generate a summary of about five sentences.

[0179] The generated summary is customized according to the user's emotional state by the emotion engine, which recognizes and analyzes the user's emotions and adjusts the content and expression of the summary based on the analysis results.

[0180] Device Role

[0181] The device analyzes the user's emotions using the emotion engine before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the device to provide the most effective information to the user.

[0182] User Roles

[0183] The user checks the summary provided through their device. This summary is customized to take into account the user's emotions, so the user can receive the information in the format that is most receptive to them. If necessary, they can also view more detailed information by clicking on the link to the original article.

[0184] Specific examples

[0185] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0186] The server then recognizes and analyzes the user's emotions in real time and customizes the summary based on the results of the emotion analysis. For example, if the user is feeling stressed, the server will change the summary content to more positive expressions.

[0187] The device displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0188] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0189] The processing flow will be explained below.

[0190] Step 1:

[0191] The server maintains a list of URLs for reputable news sites that are known to provide trustworthy information.

[0192] Step 2:

[0193] The server sends an HTTP request to each news site to retrieve its HTML content, and uses the requests.get method to retrieve the page data for each site.

[0194] Step 3:

[0195] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0196] Step 4:

[0197] The server processes the extracted article links in order, parses the linked pages, and saves the article content in text format. It uses the Article class from the newspaper library to download and parse the article body.

[0198] Step 5:

[0199] The server saves the downloaded and analyzed article text, and analyzes the text data using natural language processing technology. Specifically, it uses a natural language processing library such as spacy to divide the text into sentences.

[0200] Step 6:

[0201] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0202] Step 7:

[0203] After the server generates the summary, it prepares it for emotion analysis by the emotion engine in the server, which is a software module for recognizing the user's emotional state.

[0204] Step 8:

[0205] To recognize the user's emotions, the device collects the user's voice, text input, or facial expression data, for example, by using a microphone or camera to capture real-time data.

[0206] Step 9:

[0207] The device sends the collected data to an emotion engine, which then analyzes the data to determine the user's emotional state, for example, by identifying stress levels through voice analysis or assessing happiness through facial expression analysis.

[0208] Step 10:

[0209] The server customizes the content and expression of the generated summary based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the summary will be changed to more positive wording.

[0210] Step 11:

[0211] The server sends the customized summary to the terminal, which receives the summary and displays it in a user-viewable format.

[0212] Step 12:

[0213] The user views the customized summary provided through the device, allowing the user to obtain information in a format that takes their emotions into consideration.

[0214] Step 13:

[0215] If the user needs more detailed information, they can access the original article link provided and view the full text of the original article.

[0216] In this way, the present invention is a system that efficiently provides highly reliable, multifaceted information while taking into consideration the feelings of the user.

[0217] Example 2

[0218] 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."

[0219] Conventional information collection and provision systems were able to efficiently collect and analyze highly reliable information. However, they did not provide information according to the user's emotional state, and did not take into account the psychological burden that users experience when receiving information. Therefore, there is a need for optimal information provision according to the user's emotional state.

[0220] 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.

[0221] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for customizing the generated summary according to the emotional state of the user, and means for providing the customized summary to the user, thereby enabling optimal information provision that takes into account the emotional state of the user.

[0222] A "reliable source" is one that has been proven to provide accurate and consistent data with little misinformation or false information.

[0223] "Means of collecting data" refers to technologies and methods that have the ability to extract and collect data from various sources on the Internet.

[0224] "Means of analyzing data" refers to a method of converting collected data into a form that is easy to understand by using certain algorithms or techniques.

[0225] A "means for generating a summary of a discussion" is a technology that extracts important points from collected and analyzed data and provides them in a concise summary.

[0226] "Means for customizing according to the user's emotional state" refers to a method for analyzing the user's current emotions and adjusting the content and format of the information provided based on the analysis results.

[0227] A "means for providing a customized summary" is a technique for displaying or providing a summary to a user that is tailored to take into account the user's emotional state.

[0228] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0229] "Web scraping technology" is a technology that automatically extracts data from websites.

[0230] A "machine learning model" is a system that has an algorithm that learns from data and makes predictions and judgments.

[0231] A "terminal" is a device or equipment through which a user receives information.

[0232] This invention relates to a system that uses advanced information collection, analysis, and customization techniques to provide optimal information to users. This system is realized mainly by three roles: a server, a terminal, and a user.

[0233] Server Roles

[0234] The server first collects data from reliable sources. To do this, it has a pre-defined list of URLs for news sites, etc. The server uses the requests library to send HTTP requests to each news site and obtain the HTML content. It then uses BeautifulSoup to parse the HTML content and extract article links. Using web scraping technology, reliable information can be collected efficiently.

[0235] Next, the server parses the collected article links and uses the newspaper library to save the article content in text format. The article is downloaded using the Article class of this library and parsed to obtain the raw text. Natural language processing (NLP) techniques are then used to split the text into sentences, extract key sentences, and generate summaries. For example, NLP libraries such as spaCy and NLTK are used.

[0236] Device Role

[0237] The device has the ability to analyze the user's emotions before displaying the summary provided by the server to the user. Sentiment analysis uses machine learning models such as TENSORFLOW (registered trademark) and PyTorch. Emotions can be analyzed in real time from the user's camera footage and text input.

[0238] Based on the analysis results, the device customizes the summary sent from the server according to the user's emotional state. For example, if the analysis indicates that the user is feeling stressed, the device will change the summary content to more positive expressions. This reduces the user's psychological burden and enables the provision of optimal information.

[0239] User Roles

[0240] The user can view the summary provided through their device. The summary is customized based on the user's emotional state, allowing them to receive information in the most easily understandable format. If necessary, they can also view detailed information by clicking on a link to the original article.

[0241] Specific examples

[0242] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages of each link and saves the article text in text format. It then uses natural language processing technology to summarize each article in about five sentences. Next, the device analyzes the user's emotional state and, for example, if the user is feeling stressed, changes the summary to more positive expressions. Finally, the device displays the customized summary to the user, allowing the user to efficiently obtain the information they need.

[0243] Prompt Sentence Examples

[0244] Prompt to create a list of news article links:

[0245] "Collect information from the following news sites: News Site A: [URL], News Site B: [URL]."

[0246] Article summary prompt:

[0247] "Using natural language processing techniques, summarize the following article in five sentences: [Text content]"

[0248] User emotion recognition prompts:

[0249] "Analyze the user's current emotions and customize the following summary based on the results: [Summary]"

[0250] As a result, the present invention realizes a system that efficiently provides highly reliable and multifaceted information while taking into consideration the feelings of the user.

[0251] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0252] Step 1:

[0253] The server collects data from reliable sources. Specifically, the server has a pre-defined list of news site URLs and uses the requests library to send HTTP requests to each news site, thereby obtaining HTML content. The input is the list of news site URLs, and the output is the obtained HTML content.

[0254] Step 2:

[0255] The server parses the HTML content and extracts article links. Specifically, the server parses the HTML content and extracts article links using the BeautifulSoup library. This uses web scraping technology. The input is the retrieved HTML content, and the output is a list of extracted article links.

[0256] Step 3:

[0257] The server analyzes the article links, retrieves the article text, and saves it in text format. Specifically, the server uses the Article class of the newspaper library to download and analyze the articles, saving the article text in text format. The input is a list of article links, and the output is the text data of the saved article text.

[0258] Step 4:

[0259] The server uses natural language processing technology to analyze the article text and generate a summary. Specifically, the server uses an NLP library such as spaCy or NLTK to divide the article text into sentences, extract important sentences, and generate a summary of about five sentences. The input is the text data of the article text, and the output is the generated summary.

[0260] Step 5:

[0261] The device analyzes the user's emotions. Specifically, the device uses machine learning models such as TensorFlow and PyTorch to analyze emotions from the user's camera footage and text input. The input is the user's video or text data, and the output is the analyzed emotional state.

[0262] Step 6:

[0263] The device customizes the summary based on the emotion analysis results. Specifically, the device appropriately adjusts the content of the summary provided by the server based on the emotion analysis results obtained by the device. For example, if the user is feeling stressed, the device changes the summary to a more positive expression. The input is the emotion analysis results and the summary provided by the server, and the output is the adjusted summary.

[0264] Step 7:

[0265] The terminal displays the customized summary to the user. Specifically, the terminal displays the tailored summary on the screen for the user to review. The input is the tailored summary, and the output is the screen display for the user to review.

[0266] Specific operation example

[0267] In step 1, the server maintains a list of URLs, such as "https: / / news-site-a.com", and uses the requests library to retrieve the HTML content.

[0268] In step 2, article links such as "https: / / news-site-a.com / article / 123" are extracted from the retrieved HTML content using the BeautifulSoup library.

[0269] In step 3, the linked page is parsed using the newspaper library and the article text is saved in text format.

[0270] In step 4, the spaCy library is used to split the article into sentences, extract the key sentences, and create a five-sentence summary.

[0271] In step 5, the device analyzes the user's video using a machine learning model to determine whether the user is feeling stressed.

[0272] In step 6, negative expressions in the summary are changed to positive ones to adapt to the user's emotional state.

[0273] In step 7, the customized summary is displayed on the device screen for the user to review.

[0274] (Application example 2)

[0275] 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."

[0276] In today's world, many users desire to quickly and efficiently gather reliable information on a daily basis. However, providing this information without regard to the user's emotional state can lead to problems such as stress and information overload. To address this issue, a system that provides information customized to the user's emotional state is required. However, current technology does not provide a system that combines data collection from reliable information sources, summary generation, and emotion-based customization. This makes it difficult to provide information in a format that is optimal for the user.

[0277] The specific processing by the specific 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 collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, and means for customizing the generated summary according to the user's emotions. This makes it possible to provide efficient and reliable information while taking the user's emotions into consideration.

[0278] A "reliable source" refers to a trusted source of information, such as a website or database, that provides accurate and verifiable information.

[0279] "Means of collecting data" refers to techniques for obtaining necessary information from the Internet using web scraping techniques, API calls, etc.

[0280] "Means for analyzing data" refers to the technology of analyzing collected data using natural language processing technology and extracting important information.

[0281] "Means for generating a summary of a discussion" refers to a technology that uses natural language processing techniques to extract key sentences from collected data and create a short-form summary.

[0282] "Means for customizing according to the user's emotions" refers to a technology that uses an emotion engine to analyze the user's emotions and adjusts the content and expression of the summary based on the results.

[0283] "Means for providing a summary to a user" refers to technology that displays a customized summary to a user through a device such as a smartphone or tablet.

[0284] An "emotion engine" is a software program that analyzes a user's emotional state and adjusts information based on the analysis results.

[0285] A "generative AI model" is a machine learning model trained on large datasets that generates content tailored to a user's specific needs and emotional state.

[0286] A "prompt sentence" is an instruction sentence that is input to a generative AI model and contains instructions for the model to generate output based on that instruction.

[0287] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and customizes it according to the user's emotions to provide appropriate information to the user. This system aims to provide users with reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0288] Server Roles

[0289] The server first needs to maintain a list of URLs of reliable news sites. The server sends an HTTP request to each news site to retrieve its HTML content. The server uses BeautifulSoup to parse the retrieved HTML content. The server then uses web scraping techniques to extract article links from the parsed HTML content.

[0290] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library and analyzed to obtain the raw data of the article body. This data is then analyzed using natural language processing techniques and divided into sentences. Important sentences are extracted and a summary of about five sentences is generated.

[0291] The generated summary is customized by an emotion engine according to the user's emotional state. The server uses a generative AI model to tailor the summary to a positive tone based on a prompt. For example, a prompt could be, "If the user is feeling stressed, please make the following summary positive."

[0292] Device Role

[0293] The device uses an emotion engine to analyze the user's emotions before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the information to be presented in the most receptive form for the user.

[0294] User Roles

[0295] The user can view the customized summary provided through their device. This summary is customized with the user's feelings in mind, allowing them to receive information in the format that is most receptive to them. If necessary, they can also view detailed information by clicking on the original article link.

[0296] Specific examples

[0297] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0298] The server then recognizes and analyzes the user's emotions in real time and uses a generative AI model to create a prompt. If the user is feeling stressed, the generated summary is changed to a more positive expression. For example, a prompt might be generated that reads, "If the user is feeling stressed, please make the following summary more positive. Summary: Economic news shows that stock prices have fallen sharply."

[0299] The terminal displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0300] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0301] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0302] Step 1:

[0303] A server maintains a list of URLs of news sites from reliable sources. Here, the list of reliable news sites is the input data. The server sends HTTP requests to these URLs to get the HTML content. In this process, the HTTP request is made and the output is the HTML content.

[0304] Step 2:

[0305] The HTML content retrieved by the server is analyzed using BeautifulSoup to extract article links. The input data is the HTML content retrieved in step 1. BeautifulSoup is used to analyze the HTML content and extract article links. The output is a list of news article links.

[0306] Step 3:

[0307] Using the article links collected by the server, the pages to which each link points are analyzed and the article content is saved in text format. The articles are downloaded and analyzed using the Article class of the newspaper library. The input data is the article link, and the output data is the text of the article itself.

[0308] Step 4:

[0309] The server uses natural language processing technology to divide article data into sentences, extract important sentences, and generate a summary. The input data is the article text in text format. Natural language processing technology is used to divide the text into sentences, extract important sentences, and generate a summary of about five sentences. The output data is the summary sentences.

[0310] Step 5:

[0311] The server uses an emotion engine to analyze the user's emotional state. The input data is the user's emotional data. The emotion engine analyzes the user's emotions to understand the user's emotional state. The output data is the result of the user's emotion analysis.

[0312] Step 6:

[0313] The server uses a generative AI model to customize a summary based on the prompt. For example, it creates a prompt such as, "If the user is feeling stressed, please make the following summary positive." The input data are the generated summary and the emotion analysis results. The prompt is input into the generative AI model to obtain a customized summary based on the emotion. The output is the customized summary.

[0314] Step 7:

[0315] The terminal displays the final customized summary to the user. The input data is the customized summary text. The terminal displays this summary text for the user to confirm. The output is the customized summary displayed in a form that the user can visually confirm.

[0316] Step 8:

[0317] The user checks the customized summary provided through the terminal. The input data is the customized summary text displayed on the terminal. The user checks this summary and, if necessary, checks for more detailed information by clicking on the original article link. The output is the detailed information available to the user.

[0318] 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.

[0319] 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.

[0320] 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.

[0321] [Second embodiment]

[0322] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0323] 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.

[0324] 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).

[0325] 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.

[0326] 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.

[0327] 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).

[0328] 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. 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.

[0329] 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.

[0330] 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.

[0331] 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.

[0332] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0333] 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."

[0334] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0335] Server Roles

[0336] The server collects data from designated reliable sources. Specifically, it maintains a list of URLs of reliable news sites and sends HTTP requests to each news site to obtain its HTML content. The server then analyzes the obtained HTML content and extracts article links. This link extraction is performed using web scraping technology.

[0337] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL and parsing the article body as text, resulting in the raw article data.

[0338] The server then analyzes the retrieved article text and uses natural language processing technology to extract key sentences and generate a summary. The text is divided into sentences and the most important sentences are selected. This summary is condensed to about five sentences to help users understand the information efficiently.

[0339] Device Role

[0340] The terminal displays the final summary provided by the server to the user. The server generates a summary and sends it to the terminal in an appropriate format. The terminal receives the summary and displays it on its interface for the user to view.

[0341] User Roles

[0342] Users can check the summary provided through their device, which allows them to efficiently grasp reliable, multifaceted information. If necessary, they can also view detailed information by clicking on the original article link.

[0343] Specific examples

[0344] For example, a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. The server then uses natural language processing techniques to summarize each article and generate a final summary. These summaries are then sent to the device and displayed in a format that the user can view.

[0345] Users can view summaries on their devices and quickly obtain the information they need from the summaries. For example, if a user wants to know about a particular news item, they can simply read the summary to understand the main points. If they need more information, they can click on the provided link to the original article to access the detailed information.

[0346] In this way, the present invention provides a system that enables users to efficiently obtain information from reliable and multifaceted perspectives.

[0347] The processing flow will be explained below.

[0348] Step 1:

[0349] The server maintains a list of URLs for trusted news sites.

[0350] Step 2:

[0351] The server sends an HTTP request to each news site to retrieve its HTML content. For example, it uses requests.get to retrieve the page contents.

[0352] Step 3:

[0353] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0354] Step 4:

[0355] The server processes the collected article links one by one, analyzes the linked pages, and downloads and analyzes the article content. For analysis, it uses the Article class of the newspaper library.

[0356] Step 5:

[0357] The server saves the analyzed article text in text format, thereby accumulating raw text data.

[0358] Step 6:

[0359] The server analyzes the stored article text using a natural language processing tool (e.g., Spacy) and divides it into sentences. The text is analyzed using nlp objects.

[0360] Step 7:

[0361] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0362] Step 8:

[0363] The server collects the summaries it generates and saves them in a single file, such as summary.txt, allowing for centralized management of summary information.

[0364] Step 9:

[0365] The terminal retrieves the summary file from the server and displays it on the interface in a format that the user can view, allowing the user to quickly understand the important information.

[0366] Step 10:

[0367] If users need more information, they can access the original article link provided on their device and view the full text of the original article.

[0368] Example 1

[0369] 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."

[0370] In today's information society, a large amount of information is scattered across the Internet, and there is a need to efficiently collect information from reliable sources, summarize it, and provide it to users. However, manually collecting data from reliable sources, analyzing it, and generating summaries is time-consuming, labor-intensive, and inefficient. Furthermore, generating summaries requires advanced natural language processing technology, and there are currently no easy ways to do this. Therefore, there is a need for a system that can automate the collection, analysis, and summarization of information and make it available efficiently.

[0371] 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.

[0372] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the HTML content of the collected data and extracting article links, means for acquiring article text from the extracted article links and saving it as text, means for generating summaries of the saved article text using natural language processing technology, and means for transmitting the generated summaries to a terminal and providing them to a user. This makes it possible to automate the collection of information from reliable information sources, data analysis, and summary generation, and efficiently provide them to users.

[0373] A "reliable source of information" refers to an information provider or site whose information is guaranteed to be accurate and objective.

[0374] "Data collection methods" refers to the technologies and methods used to automatically obtain the required information from sources on the Internet.

[0375] "HTML Content" refers to content written in HTML, a markup language that defines the structure of web pages.

[0376] "Article Link" means a URL that provides access to a specific article on a web page.

[0377] "Article body" refers to text data that contains the main information of news articles, blog articles, etc.

[0378] "Means of saving as text" refers to the technology or method of saving acquired information in a string format in a file, etc.

[0379] "Natural language processing technology" refers to computer technology for understanding and analyzing human language.

[0380] A "summary generator" refers to a technique or method for extracting important parts from a long text and summarizing them in a shorter form.

[0381] "Device" refers to a device used by a User, such as a computer, smartphone, or tablet.

[0382] "User" refers to any individual or organization that uses the information collection system.

[0383] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0384] Server Roles

[0385] The server is responsible for collecting data from designated reliable sources. Specifically, it maintains a list of URLs for reliable news sites, sends HTTP requests to each news site, and retrieves their HTML content. The HTTP requests are sent using Python's requests library. The retrieved HTML content is then analyzed using BeautifulSoup to extract article links. Web scraping technology is used to extract these links.

[0386] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL, parsing the article body, and saving it as text. This process also uses the BeautifulSoup and requests libraries.

[0387] The server then analyzes the retrieved article text using natural language processing technology, extracts key sentences, and generates a summary. Specifically, it uses natural language processing libraries such as nltk and spaCy to divide the text into sentences and select the most important sentences. This summary is condensed to about five sentences, allowing users to efficiently understand the information.

[0388] Device Role

[0389] The device is responsible for displaying the final summary provided by the server to the user. The summary generated by the server is sent to the device in an appropriate format. For example, the summary information sent in JSON format is received and displayed on the device's web interface. This display is implemented using JavaScript and HTML to present the summary in a user-friendly format.

[0390] User Roles

[0391] Users can efficiently grasp reliable, multifaceted information by checking the summary provided through their device. If necessary, they can also access detailed information by clicking on a link to the original article. Specifically, users read the summary, quickly obtain key information from its contents, and then access the original article as needed.

[0392] Specific examples

[0393] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. It then uses natural language processing technology to summarize each article and generate a final summary. This summary is then sent to the device and displayed in a format that the user can view.

[0394] Users can view summaries on their devices and quickly understand key points. For example, if a user wants to know about a particular piece of news, they can request information from the system using the prompt "Show me the latest news summary." They can then quickly obtain the information they need by reading the summary, and if they need more details, they can click on the provided link to the original article to access the details. In this way, the present invention provides users with a powerful tool for efficiently obtaining and understanding information.

[0395] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0396] Step 1:

[0397] The server collects data from reliable sources. It receives a list of URLs of reliable news sites as input and sends HTTP requests to each news site. Specifically, it uses the requests library to send requests to each URL and retrieve HTML content. The retrieved HTML content is the output.

[0398] Step 2:

[0399] The HTML content retrieved by the server is analyzed and article links are extracted. HTML content is received as input and the HTML is parsed using BeautifulSoup. Links to news articles are extracted from the parsed HTML. The extracted article links are the output. Specifically, using BeautifulSoup< / url:> Search for links contained in tags and collect article links in list format.

[0400] Step 3:

[0401] The server retrieves the body of each article from the extracted article links and saves it in text format. It receives the article links as input, sends an HTTP request to each link again to retrieve the HTML content, extracts the body of the article from the retrieved HTML, converts it to text format, and saves it. The saved article text is obtained as output. Specifically, the article URL is accessed, and the retrieved HTML is analyzed again with BeautifulSoup to extract the main content.

[0402] Step 4:

[0403] The server uses natural language processing technology to analyze article text stored on the server, extracting important sentences and generating a summary. It receives the stored article text as input and uses nltk or spaCy to divide the text into sentences. It evaluates the importance of each sentence, selects the most important sentence, and generates a summary of about five sentences. The generated summary is output. Specifically, it uses NLP techniques such as morphological analysis and sentence importance score calculation.

[0404] Step 5:

[0405] The server sends the generated summary to the terminal. It receives the generated summary as input and sends it to the terminal in an appropriate format (e.g., JSON format). As output, it obtains the JSON format summary data that was sent. Specifically, it sends the summary data as an HTTP response.

[0406] Step 6:

[0407] The terminal displays the received summary to the user. It receives the received JSON format summary data as input and displays the summary on a web interface. As output, the displayed summary is provided to the user. Specifically, it formats the summary data using JavaScript and HTML and displays it on the browser.

[0408] Step 7:

[0409] The user reviews the summary through their device and accesses the original article if necessary. The input is the displayed summary, and they obtain the necessary information. The output is the information the user obtained and access to the original article. Specifically, they read the summary to understand the main points, and if they need more details, they click the link to view the original article.

[0410] (Application example 1)

[0411] 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."

[0412] In the current information distribution system, a huge amount of information is generated every day, making it difficult for users to efficiently obtain reliable information. Browsing through many sources and articles takes time, and important information may be overlooked. Furthermore, there is a lack of real-time notifications of important information based on users' areas of interest and quick access to the original detailed information.

[0413] 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.

[0414] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for providing the generated summary to the user, means for notifying the user of important information based on the user's interests in real time, and means for providing a link from the summarized information to the original detailed information. This makes it possible to efficiently collect and summarize reliable information and provide important information based on the user's interests in real time. It also enables quick access to detailed information from the summarized information.

[0415] "Reliable sources" refer to trusted news sites and official websites that provide accurate and objective information.

[0416] "Means of collecting data" refers to the means of obtaining the necessary information from designated sources, such as using web scraping technology.

[0417] "Means for analyzing data" refers to means for analyzing collected text data and extracting important information using natural language processing technology.

[0418] "Means for generating summaries of discussions" refers to means for generating summaries of articles or discussions based on the extracted important information.

[0419] The "means for providing a summary to a user" refers to a means for displaying the generated summary on the user's terminal.

[0420] "Means of notifying users of important information in real time based on their interests" refers to means of collecting important information from reliable sources based on users' areas of interest and keywords, and notifying them in a timely manner.

[0421] "Means for providing links from the summarized information to the original detailed information" refers to means for providing links from the generated summary to the original article or detailed information, allowing users to access the detailed information.

[0422] This invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0423] Server Roles

[0424] The server first collects data from reliable sources. In this process, it uses web scraping technology to obtain the necessary data from the sources. Specifically, it uses BeautifulSoup (Python) to extract HTML content from news sites and collect article links.

[0425] Next, each article is retrieved based on the collected links and its contents are saved in text format. This involves sending an HTTP request and parsing the article's HTML to extract the text. The retrieved article text is then analyzed using natural language processing techniques. Here, techniques such as spaCy (Python) and GPT-3 (OpenAI) are used to extract important sentences and generate summaries.

[0426] The generated summary is sent to the terminal in an appropriate format. The server stores this information in a database and updates it as needed. PostgreSQL is used for the database, improving data management and access efficiency.

[0427] Device Role

[0428] The device displays the summaries provided by the server to the user, provides an appropriate user interface so that the user can view the summaries through a browser or a dedicated smartphone app, and notifies the user of important information in real time from the server based on the user's areas of interest and keywords.

[0429] Furthermore, the summary also provides a link to the original detailed information, allowing users to access the detailed information at their discretion. The interface for this purpose is designed to be easy for users to operate.

[0430] User Roles

[0431] Users can quickly understand important information by checking the summaries provided through their devices. Users can receive important information in real time based on their own interests. For example, when news about "environmental issues" is updated, users will automatically receive a summary and can access the detailed original article from the summary article.

[0432] Specific examples

[0433] For example, a server might collect articles about environmental issues from a news site and generate summaries of the articles. The summaries are generated using prompts such as:

[0434] Example prompt sentence:

[0435] Generate a summary of a news article:

[0436] 1. Load articles collected from trusted news sites.

[0437] 2. Extract the key points from the article and summarize them in about five sentences.

[0438] 3. Return the summary.

[0439] (Article text)

[0440] "..."

[0441] ...

[0442] "

[0443] (summary)

[0444] 1. In this article...

[0445] 2. ...

[0446] This allows users to quickly grasp important information and access detailed information as needed. The system efficiently collects and summarizes reliable information, providing important information based on the user's interests in real time. Furthermore, it enables quick access to detailed information from the summarized information, significantly reducing the burden on users when it comes to obtaining information.

[0447] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0448] Step 1:

[0449] The server retrieves the URLs of news sites from a specified list of reliable sources. Then, it sends an HTTP request to retrieve the HTML content of each news site. It then parses the HTML content using BeautifulSoup (Python) to extract article links. The input is a list of news site URLs, and the output is a list of article links.

[0450] Step 2:

[0451] The server retrieves the content of each article based on the extracted article links. Specifically, it sends an HTTP request to each link again to retrieve the article's HTML, and then uses BeautifulSoup (Python) to extract the article's body text. The input is a list of article links, and the output is the text of each article's body.

[0452] Step 3:

[0453] The server analyzes the retrieved article text using natural language processing technology. For example, it uses spaCy (Python) to divide the article text into sentences and GPT-3 (OpenAI) to extract important sentences. The following sentence is used as an example of a prompt sentence:

[0454] Example prompt sentence:

[0455] Generate a summary of a news article:

[0456] 1. Load articles collected from trusted news sites.

[0457] 2. Extract the key points from the article and summarize them in about five sentences.

[0458] 3. Return the summary.

[0459] (Article text)

[0460] "..."

[0461] ...

[0462] "

[0463] (summary)

[0464] 1. In this article...

[0465] 2. ...

[0466] The input is the text of the article, and the output is a summary of about five sentences.

[0467] Step 4:

[0468] The server saves the generated summary and sends it to the terminal in an appropriate format. During this process, the summary and the link to the original article are stored in a database (PostgreSQL) and sent to the front end to provide a user interface. The input is the summary text and the link to the original article, and the output is the summary displayed on the user terminal.

[0469] Step 5:

[0470] The terminal displays the summary received from the server to the user. The user interface is simple and provides a summary and a link to the original article. The input is the summary text received from the server and the link to the original article, and the output is the display to the user.

[0471] Step 6:

[0472] The device notifies users of important information in real time based on their profile and areas of interest. It receives updates from the server, filters them based on their interests, and sends push notifications to users. The input is the user's interest information and summary text, and the output is the information sent to the user as a push notification.

[0473] Step 7:

[0474] Users can view the summary on their device and, if necessary, click on the link to the original article to access more detailed information. This allows users to efficiently grasp important information and easily view detailed information. The input is the summary and article link displayed on the device, and the output is the information the user obtains.

[0475] 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.

[0476] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and then uses an emotion engine to recognize and analyze the user's emotions, customizing the generated summary to suit the user's emotions. This system aims to provide users with highly reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0477] Server Roles

[0478] The server must first maintain a list of URLs for reliable news sites. The server then sends an HTTP request to each news site to retrieve its HTML content. The retrieved HTML content is then parsed using BeautifulSoup to extract article links. This link extraction is performed using web scraping techniques.

[0479] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library, and the raw article text is obtained by analyzing it. This data is then analyzed using natural language processing techniques, divided into sentences, and key sentences are extracted to generate a summary of about five sentences.

[0480] The generated summary is customized according to the user's emotional state by the emotion engine, which recognizes and analyzes the user's emotions and adjusts the content and expression of the summary based on the analysis results.

[0481] Device Role

[0482] The device analyzes the user's emotions using the emotion engine before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the device to provide the most effective information to the user.

[0483] User Roles

[0484] The user checks the summary provided through their device. This summary is customized to take into account the user's emotions, so the user can receive the information in the format that is most receptive to them. If necessary, they can also view more detailed information by clicking on the link to the original article.

[0485] Specific examples

[0486] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0487] The server then recognizes and analyzes the user's emotions in real time and customizes the summary based on the results of the emotion analysis. For example, if the user is feeling stressed, the server will change the summary content to more positive expressions.

[0488] The device displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0489] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0490] The processing flow will be explained below.

[0491] Step 1:

[0492] The server maintains a list of URLs for reputable news sites that are known to provide trustworthy information.

[0493] Step 2:

[0494] The server sends an HTTP request to each news site to retrieve its HTML content, and uses the requests.get method to retrieve the page data for each site.

[0495] Step 3:

[0496] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0497] Step 4:

[0498] The server processes the extracted article links in order, parses the linked pages, and saves the article content in text format. It uses the Article class from the newspaper library to download and parse the article body.

[0499] Step 5:

[0500] The server saves the downloaded and analyzed article text, and analyzes the text data using natural language processing technology. Specifically, it uses a natural language processing library such as spacy to divide the text into sentences.

[0501] Step 6:

[0502] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0503] Step 7:

[0504] After the server generates the summary, it prepares it for emotion analysis by the emotion engine in the server, which is a software module for recognizing the user's emotional state.

[0505] Step 8:

[0506] To recognize the user's emotions, the device collects the user's voice, text input, or facial expression data, for example, by using a microphone or camera to capture real-time data.

[0507] Step 9:

[0508] The device sends the collected data to an emotion engine, which then analyzes the data to determine the user's emotional state, for example, by identifying stress levels through voice analysis or assessing happiness through facial expression analysis.

[0509] Step 10:

[0510] The server customizes the content and expression of the generated summary based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the summary will be changed to more positive wording.

[0511] Step 11:

[0512] The server sends the customized summary to the terminal, which receives the summary and displays it in a user-viewable format.

[0513] Step 12:

[0514] The user views the customized summary provided through the device, allowing the user to obtain information in a format that takes their emotions into consideration.

[0515] Step 13:

[0516] If the user needs more detailed information, they can access the original article link provided and view the full text of the original article.

[0517] In this way, the present invention is a system that efficiently provides highly reliable, multifaceted information while taking into consideration the feelings of the user.

[0518] Example 2

[0519] 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."

[0520] Conventional information collection and provision systems were able to efficiently collect and analyze highly reliable information. However, they did not provide information according to the user's emotional state, and did not take into account the psychological burden that users experience when receiving information. Therefore, there is a need for optimal information provision according to the user's emotional state.

[0521] 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.

[0522] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for customizing the generated summary according to the emotional state of the user, and means for providing the customized summary to the user, thereby enabling optimal information provision that takes into account the emotional state of the user.

[0523] A "reliable source" is one that has been proven to provide accurate and consistent data with little misinformation or false information.

[0524] "Means of collecting data" refers to technologies and methods that have the ability to extract and collect data from various sources on the Internet.

[0525] "Means of analyzing data" refers to a method of converting collected data into a form that is easy to understand by using certain algorithms or techniques.

[0526] A "means for generating a summary of a discussion" is a technology that extracts important points from collected and analyzed data and provides them in a concise summary.

[0527] "Means for customizing according to the user's emotional state" refers to a method for analyzing the user's current emotions and adjusting the content and format of the information provided based on the analysis results.

[0528] A "means for providing a customized summary" is a technique for displaying or providing a summary to a user that is tailored to take into account the user's emotional state.

[0529] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0530] "Web scraping technology" is a technology that automatically extracts data from websites.

[0531] A "machine learning model" is a system that has an algorithm that learns from data and makes predictions and judgments.

[0532] A "terminal" is a device or equipment through which a user receives information.

[0533] This invention relates to a system that uses advanced information collection, analysis, and customization techniques to provide optimal information to users. This system is realized mainly by three roles: a server, a terminal, and a user.

[0534] Server Roles

[0535] The server first collects data from reliable sources. To do this, it has a pre-defined list of URLs for news sites, etc. The server uses the requests library to send HTTP requests to each news site and obtain the HTML content. It then uses BeautifulSoup to parse the HTML content and extract article links. Using web scraping technology, reliable information can be collected efficiently.

[0536] Next, the server parses the collected article links and uses the newspaper library to save the article content in text format. The article is downloaded using the Article class of this library and parsed to obtain the raw text. Natural language processing (NLP) techniques are then used to split the text into sentences, extract key sentences, and generate summaries. For example, NLP libraries such as spaCy and NLTK are used.

[0537] Device Role

[0538] The device has the ability to analyze the user's emotions before displaying the summary provided by the server to the user. Sentiment analysis uses machine learning models such as TensorFlow and PyTorch. It can analyze emotions in real time from the user's camera footage and text input.

[0539] Based on the analysis results, the device customizes the summary sent from the server according to the user's emotional state. For example, if the analysis indicates that the user is feeling stressed, the device will change the summary content to more positive expressions. This reduces the user's psychological burden and enables the provision of optimal information.

[0540] User Roles

[0541] The user can view the summary provided through their device. The summary is customized based on the user's emotional state, allowing them to receive information in the most easily understandable format. If necessary, they can also view detailed information by clicking on a link to the original article.

[0542] Specific examples

[0543] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages of each link and saves the article text in text format. It then uses natural language processing technology to summarize each article in about five sentences. Next, the device analyzes the user's emotional state and, for example, if the user is feeling stressed, changes the summary to more positive expressions. Finally, the device displays the customized summary to the user, allowing the user to efficiently obtain the information they need.

[0544] Prompt Sentence Examples

[0545] Prompt to create a list of news article links:

[0546] "Collect information from the following news sites: News Site A: [URL], News Site B: [URL]."

[0547] Article summary prompt:

[0548] "Using natural language processing techniques, summarize the following article in five sentences: [Text content]"

[0549] User emotion recognition prompts:

[0550] "Analyze the user's current emotions and customize the following summary based on the results: [Summary]"

[0551] As a result, the present invention realizes a system that efficiently provides highly reliable and multifaceted information while taking into consideration the feelings of the user.

[0552] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0553] Step 1:

[0554] The server collects data from reliable sources. Specifically, the server has a pre-defined list of news site URLs and uses the requests library to send HTTP requests to each news site, thereby obtaining HTML content. The input is the list of news site URLs, and the output is the obtained HTML content.

[0555] Step 2:

[0556] The server parses the HTML content and extracts article links. Specifically, the server parses the HTML content and extracts article links using the BeautifulSoup library. This uses web scraping technology. The input is the retrieved HTML content, and the output is a list of extracted article links.

[0557] Step 3:

[0558] The server analyzes the article links, retrieves the article text, and saves it in text format. Specifically, the server uses the Article class of the newspaper library to download and analyze the articles, saving the article text in text format. The input is a list of article links, and the output is the text data of the saved article text.

[0559] Step 4:

[0560] The server uses natural language processing technology to analyze the article text and generate a summary. Specifically, the server uses an NLP library such as spaCy or NLTK to divide the article text into sentences, extract important sentences, and generate a summary of about five sentences. The input is the text data of the article text, and the output is the generated summary.

[0561] Step 5:

[0562] The device analyzes the user's emotions. Specifically, the device uses machine learning models such as TensorFlow and PyTorch to analyze emotions from the user's camera footage and text input. The input is the user's video or text data, and the output is the analyzed emotional state.

[0563] Step 6:

[0564] The device customizes the summary based on the emotion analysis results. Specifically, the device appropriately adjusts the content of the summary provided by the server based on the emotion analysis results obtained by the device. For example, if the user is feeling stressed, the device changes the summary to a more positive expression. The input is the emotion analysis results and the summary provided by the server, and the output is the adjusted summary.

[0565] Step 7:

[0566] The terminal displays the customized summary to the user. Specifically, the terminal displays the tailored summary on the screen for the user to review. The input is the tailored summary, and the output is the screen display for the user to review.

[0567] Specific operation example

[0568] In step 1, the server maintains a list of URLs, such as "https: / / news-site-a.com", and uses the requests library to retrieve the HTML content.

[0569] In step 2, article links such as "https: / / news-site-a.com / article / 123" are extracted from the retrieved HTML content using the BeautifulSoup library.

[0570] In step 3, the linked page is parsed using the newspaper library and the article text is saved in text format.

[0571] In step 4, the spaCy library is used to split the article into sentences, extract the key sentences, and create a five-sentence summary.

[0572] In step 5, the device analyzes the user's video using a machine learning model to determine whether the user is feeling stressed.

[0573] In step 6, negative expressions in the summary are changed to positive ones to adapt to the user's emotional state.

[0574] In step 7, the customized summary is displayed on the device screen for the user to review.

[0575] (Application example 2)

[0576] 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."

[0577] In today's world, many users desire to quickly and efficiently gather reliable information on a daily basis. However, providing this information without regard to the user's emotional state can lead to problems such as stress and information overload. To address this issue, a system that provides information customized to the user's emotional state is required. However, current technology does not provide a system that combines data collection from reliable information sources, summary generation, and emotion-based customization. This makes it difficult to provide information in a format that is optimal for the user.

[0578] The specific processing by the specific 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 collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, and means for customizing the generated summary according to the user's emotions. This makes it possible to provide efficient and reliable information while taking the user's emotions into consideration.

[0579] A "reliable source" refers to a trusted source of information, such as a website or database, that provides accurate and verifiable information.

[0580] "Means of collecting data" refers to techniques for obtaining necessary information from the Internet using web scraping techniques, API calls, etc.

[0581] "Means for analyzing data" refers to the technology of analyzing collected data using natural language processing technology and extracting important information.

[0582] "Means for generating a summary of a discussion" refers to a technology that uses natural language processing techniques to extract key sentences from collected data and create a short-form summary.

[0583] "Means for customizing according to the user's emotions" refers to a technology that uses an emotion engine to analyze the user's emotions and adjusts the content and expression of the summary based on the results.

[0584] "Means for providing a summary to a user" refers to technology that displays a customized summary to a user through a device such as a smartphone or tablet.

[0585] An "emotion engine" is a software program that analyzes a user's emotional state and adjusts information based on the analysis results.

[0586] A "generative AI model" is a machine learning model trained on large datasets that generates content tailored to a user's specific needs and emotional state.

[0587] A "prompt sentence" is an instruction sentence that is input to a generative AI model and contains instructions for the model to generate output based on that instruction.

[0588] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and customizes it according to the user's emotions to provide appropriate information to the user. This system aims to provide users with reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0589] Server Roles

[0590] The server first needs to maintain a list of URLs of reliable news sites. The server sends an HTTP request to each news site to retrieve its HTML content. The server uses BeautifulSoup to parse the retrieved HTML content. The server then uses web scraping techniques to extract article links from the parsed HTML content.

[0591] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library and analyzed to obtain the raw data of the article body. This data is then analyzed using natural language processing techniques and divided into sentences. Important sentences are extracted and a summary of about five sentences is generated.

[0592] The generated summary is customized by an emotion engine according to the user's emotional state. The server uses a generative AI model to tailor the summary to a positive tone based on a prompt. For example, a prompt could be, "If the user is feeling stressed, please make the following summary positive."

[0593] Device Role

[0594] The device uses an emotion engine to analyze the user's emotions before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the information to be presented in the most receptive form for the user.

[0595] User Roles

[0596] The user can view the customized summary provided through their device. This summary is customized with the user's feelings in mind, allowing them to receive information in the format that is most receptive to them. If necessary, they can also view detailed information by clicking on the original article link.

[0597] Specific examples

[0598] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0599] The server then recognizes and analyzes the user's emotions in real time and uses a generative AI model to create a prompt. If the user is feeling stressed, the generated summary is changed to a more positive expression. For example, a prompt might be generated that reads, "If the user is feeling stressed, please make the following summary more positive. Summary: Economic news shows that stock prices have fallen sharply."

[0600] The terminal displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0601] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0602] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0603] Step 1:

[0604] A server maintains a list of URLs of news sites from reliable sources. Here, the list of reliable news sites is the input data. The server sends HTTP requests to these URLs to get the HTML content. In this process, the HTTP request is made and the output is the HTML content.

[0605] Step 2:

[0606] The HTML content retrieved by the server is analyzed using BeautifulSoup to extract article links. The input data is the HTML content retrieved in step 1. BeautifulSoup is used to analyze the HTML content and extract article links. The output is a list of news article links.

[0607] Step 3:

[0608] Using the article links collected by the server, the pages to which each link points are analyzed and the article content is saved in text format. The articles are downloaded and analyzed using the Article class of the newspaper library. The input data is the article link, and the output data is the text of the article itself.

[0609] Step 4:

[0610] The server uses natural language processing technology to divide article data into sentences, extract important sentences, and generate a summary. The input data is the article text in text format. Natural language processing technology is used to divide the text into sentences, extract important sentences, and generate a summary of about five sentences. The output data is the summary sentences.

[0611] Step 5:

[0612] The server uses an emotion engine to analyze the user's emotional state. The input data is the user's emotional data. The emotion engine analyzes the user's emotions to understand the user's emotional state. The output data is the result of the user's emotion analysis.

[0613] Step 6:

[0614] The server uses a generative AI model to customize a summary based on the prompt. For example, it creates a prompt such as, "If the user is feeling stressed, please make the following summary positive." The input data are the generated summary and the emotion analysis results. The prompt is input into the generative AI model to obtain a customized summary based on the emotion. The output is the customized summary.

[0615] Step 7:

[0616] The terminal displays the final customized summary to the user. The input data is the customized summary text. The terminal displays this summary text for the user to confirm. The output is the customized summary displayed in a form that the user can visually confirm.

[0617] Step 8:

[0618] The user checks the customized summary provided through the terminal. The input data is the customized summary text displayed on the terminal. The user checks this summary and, if necessary, checks for more detailed information by clicking on the original article link. The output is the detailed information available to the user.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] [Third embodiment]

[0623] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0624] 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.

[0625] 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).

[0626] 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.

[0627] 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.

[0628] 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).

[0629] 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. 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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."

[0635] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0636] Server Roles

[0637] The server collects data from designated reliable sources. Specifically, it maintains a list of URLs of reliable news sites and sends HTTP requests to each news site to obtain its HTML content. The server then analyzes the obtained HTML content and extracts article links. This link extraction is performed using web scraping technology.

[0638] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL and parsing the article body as text, resulting in the raw article data.

[0639] The server then analyzes the retrieved article text and uses natural language processing technology to extract key sentences and generate a summary. The text is divided into sentences and the most important sentences are selected. This summary is condensed to about five sentences to help users understand the information efficiently.

[0640] Device Role

[0641] The terminal displays the final summary provided by the server to the user. The server generates a summary and sends it to the terminal in an appropriate format. The terminal receives the summary and displays it on its interface for the user to view.

[0642] User Roles

[0643] Users can check the summary provided through their device, which allows them to efficiently grasp reliable, multifaceted information. If necessary, they can also view detailed information by clicking on the original article link.

[0644] Specific examples

[0645] For example, a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. The server then uses natural language processing techniques to summarize each article and generate a final summary. These summaries are then sent to the device and displayed in a format that the user can view.

[0646] Users can view summaries on their devices and quickly obtain the information they need from the summaries. For example, if a user wants to know about a particular news item, they can simply read the summary to understand the main points. If they need more information, they can click on the provided link to the original article to access the detailed information.

[0647] In this way, the present invention provides a system that enables users to efficiently obtain information from reliable and multifaceted perspectives.

[0648] The processing flow will be explained below.

[0649] Step 1:

[0650] The server maintains a list of URLs for trusted news sites.

[0651] Step 2:

[0652] The server sends an HTTP request to each news site to retrieve its HTML content. For example, it uses requests.get to retrieve the page contents.

[0653] Step 3:

[0654] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0655] Step 4:

[0656] The server processes the collected article links one by one, analyzes the linked pages, and downloads and analyzes the article content. For analysis, it uses the Article class of the newspaper library.

[0657] Step 5:

[0658] The server saves the analyzed article text in text format, thereby accumulating raw text data.

[0659] Step 6:

[0660] The server analyzes the stored article text using a natural language processing tool (e.g., Spacy) and divides it into sentences. The text is analyzed using nlp objects.

[0661] Step 7:

[0662] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0663] Step 8:

[0664] The server collects the summaries it generates and saves them in a single file, such as summary.txt, allowing for centralized management of summary information.

[0665] Step 9:

[0666] The terminal retrieves the summary file from the server and displays it on the interface in a format that the user can view, allowing the user to quickly understand the important information.

[0667] Step 10:

[0668] If users need more information, they can access the original article link provided on their device and view the full text of the original article.

[0669] Example 1

[0670] 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."

[0671] In today's information society, a large amount of information is scattered across the Internet, and there is a need to efficiently collect information from reliable sources, summarize it, and provide it to users. However, manually collecting data from reliable sources, analyzing it, and generating summaries is time-consuming, labor-intensive, and inefficient. Furthermore, generating summaries requires advanced natural language processing technology, and there are currently no easy ways to do this. Therefore, there is a need for a system that can automate the collection, analysis, and summarization of information and make it available efficiently.

[0672] 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.

[0673] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the HTML content of the collected data and extracting article links, means for acquiring article text from the extracted article links and saving it as text, means for generating summaries of the saved article text using natural language processing technology, and means for transmitting the generated summaries to a terminal and providing them to a user. This makes it possible to automate the collection of information from reliable information sources, data analysis, and summary generation, and efficiently provide them to users.

[0674] A "reliable source of information" refers to an information provider or site whose information is guaranteed to be accurate and objective.

[0675] "Data collection methods" refers to the technologies and methods used to automatically obtain the required information from sources on the Internet.

[0676] "HTML Content" refers to content written in HTML, a markup language that defines the structure of web pages.

[0677] "Article Link" means a URL that provides access to a specific article on a web page.

[0678] "Article body" refers to text data that contains the main information of news articles, blog articles, etc.

[0679] "Means of saving as text" refers to the technology or method of saving acquired information in a string format in a file, etc.

[0680] "Natural language processing technology" refers to computer technology for understanding and analyzing human language.

[0681] A "summary generator" refers to a technique or method for extracting important parts from a long text and summarizing them in a shorter form.

[0682] "Device" refers to a device used by a User, such as a computer, smartphone, or tablet.

[0683] "User" refers to any individual or organization that uses the information collection system.

[0684] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0685] Server Roles

[0686] The server is responsible for collecting data from designated reliable sources. Specifically, it maintains a list of URLs for reliable news sites, sends HTTP requests to each news site, and retrieves their HTML content. The HTTP requests are sent using Python's requests library. The retrieved HTML content is then analyzed using BeautifulSoup to extract article links. Web scraping technology is used to extract these links.

[0687] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL, parsing the article body, and saving it as text. This process also uses the BeautifulSoup and requests libraries.

[0688] The server then analyzes the retrieved article text using natural language processing technology, extracts key sentences, and generates a summary. Specifically, it uses natural language processing libraries such as nltk and spaCy to divide the text into sentences and select the most important sentences. This summary is condensed to about five sentences, allowing users to efficiently understand the information.

[0689] Device Role

[0690] The device is responsible for displaying the final summary provided by the server to the user. The summary generated by the server is sent to the device in an appropriate format. For example, the summary information sent in JSON format is received and displayed on the device's web interface. This display is implemented using JavaScript and HTML to present the summary in a user-friendly format.

[0691] User Roles

[0692] Users can efficiently grasp reliable, multifaceted information by checking the summary provided through their device. If necessary, they can also access detailed information by clicking on a link to the original article. Specifically, users read the summary, quickly obtain key information from its contents, and then access the original article as needed.

[0693] Specific examples

[0694] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. It then uses natural language processing technology to summarize each article and generate a final summary. This summary is then sent to the device and displayed in a format that the user can view.

[0695] Users can view summaries on their devices and quickly understand key points. For example, if a user wants to know about a particular piece of news, they can request information from the system using the prompt "Show me the latest news summary." They can then quickly obtain the information they need by reading the summary, and if they need more details, they can click on the provided link to the original article to access the details. In this way, the present invention provides users with a powerful tool for efficiently obtaining and understanding information.

[0696] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0697] Step 1:

[0698] The server collects data from reliable sources. It receives a list of URLs of reliable news sites as input and sends HTTP requests to each news site. Specifically, it uses the requests library to send requests to each URL and retrieve HTML content. The retrieved HTML content is the output.

[0699] Step 2:

[0700] The HTML content retrieved by the server is analyzed and article links are extracted. HTML content is received as input and the HTML is parsed using BeautifulSoup. Links to news articles are extracted from the parsed HTML. The extracted article links are the output. Specifically, using BeautifulSoup< / url:> Search for links contained in tags and collect article links in list format.

[0701] Step 3:

[0702] The server retrieves the body of each article from the extracted article links and saves it in text format. It receives the article links as input, sends an HTTP request to each link again to retrieve the HTML content, extracts the body of the article from the retrieved HTML, converts it to text format, and saves it. The saved article text is obtained as output. Specifically, the article URL is accessed, and the retrieved HTML is analyzed again with BeautifulSoup to extract the main content.

[0703] Step 4:

[0704] The server uses natural language processing technology to analyze article text stored on the server, extracting important sentences and generating a summary. It receives the stored article text as input and uses nltk or spaCy to divide the text into sentences. It evaluates the importance of each sentence, selects the most important sentence, and generates a summary of about five sentences. The generated summary is output. Specifically, it uses NLP techniques such as morphological analysis and sentence importance score calculation.

[0705] Step 5:

[0706] The server sends the generated summary to the terminal. It receives the generated summary as input and sends it to the terminal in an appropriate format (e.g., JSON format). As output, it obtains the JSON format summary data that was sent. Specifically, it sends the summary data as an HTTP response.

[0707] Step 6:

[0708] The terminal displays the received summary to the user. It receives the received JSON format summary data as input and displays the summary on a web interface. As output, the displayed summary is provided to the user. Specifically, it formats the summary data using JavaScript and HTML and displays it on the browser.

[0709] Step 7:

[0710] The user reviews the summary through their device and accesses the original article if necessary. The input is the displayed summary, and they obtain the necessary information. The output is the information the user obtained and access to the original article. Specifically, they read the summary to understand the main points, and if they need more details, they click the link to view the original article.

[0711] (Application example 1)

[0712] 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."

[0713] In the current information distribution system, a huge amount of information is generated every day, making it difficult for users to efficiently obtain reliable information. Browsing through many sources and articles takes time, and important information may be overlooked. Furthermore, there is a lack of real-time notifications of important information based on users' areas of interest and quick access to the original detailed information.

[0714] 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.

[0715] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for providing the generated summary to the user, means for notifying the user of important information based on the user's interests in real time, and means for providing a link from the summarized information to the original detailed information. This makes it possible to efficiently collect and summarize reliable information and provide important information based on the user's interests in real time. It also enables quick access to detailed information from the summarized information.

[0716] "Reliable sources" refer to trusted news sites and official websites that provide accurate and objective information.

[0717] "Means of collecting data" refers to the means of obtaining the necessary information from designated sources, such as using web scraping technology.

[0718] "Means for analyzing data" refers to means for analyzing collected text data and extracting important information using natural language processing technology.

[0719] "Means for generating summaries of discussions" refers to means for generating summaries of articles or discussions based on the extracted important information.

[0720] The "means for providing a summary to a user" refers to a means for displaying the generated summary on the user's terminal.

[0721] "Means of notifying users of important information in real time based on their interests" refers to means of collecting important information from reliable sources based on users' areas of interest and keywords, and notifying them in a timely manner.

[0722] "Means for providing links from the summarized information to the original detailed information" refers to means for providing links from the generated summary to the original article or detailed information, allowing users to access the detailed information.

[0723] This invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0724] Server Roles

[0725] The server first collects data from reliable sources. In this process, it uses web scraping technology to obtain the necessary data from the sources. Specifically, it uses BeautifulSoup (Python) to extract HTML content from news sites and collect article links.

[0726] Next, each article is retrieved based on the collected links and its contents are saved in text format. This involves sending an HTTP request and parsing the article's HTML to extract the text. The retrieved article text is then analyzed using natural language processing techniques. Here, techniques such as spaCy (Python) and GPT-3 (OpenAI) are used to extract important sentences and generate summaries.

[0727] The generated summary is sent to the terminal in an appropriate format. The server stores this information in a database and updates it as needed. PostgreSQL is used for the database, improving data management and access efficiency.

[0728] Device Role

[0729] The device displays the summaries provided by the server to the user, provides an appropriate user interface so that the user can view the summaries through a browser or a dedicated smartphone app, and notifies the user of important information in real time from the server based on the user's areas of interest and keywords.

[0730] Furthermore, the summary also provides a link to the original detailed information, allowing users to access the detailed information at their discretion. The interface for this purpose is designed to be easy for users to operate.

[0731] User Roles

[0732] Users can quickly understand important information by checking the summaries provided through their devices. Users can receive important information in real time based on their own interests. For example, when news about "environmental issues" is updated, users will automatically receive a summary and can access the detailed original article from the summary article.

[0733] Specific examples

[0734] For example, a server might collect articles about environmental issues from a news site and generate summaries of the articles. The summaries are generated using prompts such as:

[0735] Example prompt sentence:

[0736] Generate a summary of a news article:

[0737] 1. Load articles collected from trusted news sites.

[0738] 2. Extract the key points from the article and summarize them in about five sentences.

[0739] 3. Return the summary.

[0740] (Article text)

[0741] "..."

[0742] ...

[0743] "

[0744] (summary)

[0745] 1. In this article...

[0746] 2. ...

[0747] This allows users to quickly grasp important information and access detailed information as needed. The system efficiently collects and summarizes reliable information, providing important information based on the user's interests in real time. Furthermore, it enables quick access to detailed information from the summarized information, significantly reducing the burden on users when it comes to obtaining information.

[0748] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0749] Step 1:

[0750] The server retrieves the URLs of news sites from a specified list of reliable sources. Then, it sends an HTTP request to retrieve the HTML content of each news site. It then parses the HTML content using BeautifulSoup (Python) to extract article links. The input is a list of news site URLs, and the output is a list of article links.

[0751] Step 2:

[0752] The server retrieves the content of each article based on the extracted article links. Specifically, it sends an HTTP request to each link again to retrieve the article's HTML, and then uses BeautifulSoup (Python) to extract the article's body text. The input is a list of article links, and the output is the text of each article's body.

[0753] Step 3:

[0754] The server analyzes the retrieved article text using natural language processing technology. For example, it uses spaCy (Python) to divide the article text into sentences and GPT-3 (OpenAI) to extract important sentences. The following sentence is used as an example of a prompt sentence:

[0755] Example prompt sentence:

[0756] Generate a summary of a news article:

[0757] 1. Load articles collected from trusted news sites.

[0758] 2. Extract the key points from the article and summarize them in about five sentences.

[0759] 3. Return the summary.

[0760] (Article text)

[0761] "..."

[0762] ...

[0763] "

[0764] (summary)

[0765] 1. In this article...

[0766] 2. ...

[0767] The input is the text of the article, and the output is a summary of about five sentences.

[0768] Step 4:

[0769] The server saves the generated summary and sends it to the terminal in an appropriate format. During this process, the summary and the link to the original article are stored in a database (PostgreSQL) and sent to the front end to provide a user interface. The input is the summary text and the link to the original article, and the output is the summary displayed on the user terminal.

[0770] Step 5:

[0771] The terminal displays the summary received from the server to the user. The user interface is simple and provides a summary and a link to the original article. The input is the summary text received from the server and the link to the original article, and the output is the display to the user.

[0772] Step 6:

[0773] The device notifies users of important information in real time based on their profile and areas of interest. It receives updates from the server, filters them based on their interests, and sends push notifications to users. The input is the user's interest information and summary text, and the output is the information sent to the user as a push notification.

[0774] Step 7:

[0775] Users can view the summary on their device and, if necessary, click on the link to the original article to access more detailed information. This allows users to efficiently grasp important information and easily view detailed information. The input is the summary and article link displayed on the device, and the output is the information the user obtains.

[0776] 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.

[0777] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and then uses an emotion engine to recognize and analyze the user's emotions, customizing the generated summary to suit the user's emotions. This system aims to provide users with highly reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0778] Server Roles

[0779] The server must first maintain a list of URLs for reliable news sites. The server then sends an HTTP request to each news site to retrieve its HTML content. The retrieved HTML content is then parsed using BeautifulSoup to extract article links. This link extraction is performed using web scraping techniques.

[0780] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library, and the raw article text is obtained by analyzing it. This data is then analyzed using natural language processing techniques, divided into sentences, and key sentences are extracted to generate a summary of about five sentences.

[0781] The generated summary is customized according to the user's emotional state by the emotion engine, which recognizes and analyzes the user's emotions and adjusts the content and expression of the summary based on the analysis results.

[0782] Device Role

[0783] The device analyzes the user's emotions using the emotion engine before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the device to provide the most effective information to the user.

[0784] User Roles

[0785] The user checks the summary provided through their device. This summary is customized to take into account the user's emotions, so the user can receive the information in the format that is most receptive to them. If necessary, they can also view more detailed information by clicking on the link to the original article.

[0786] Specific examples

[0787] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0788] The server then recognizes and analyzes the user's emotions in real time and customizes the summary based on the results of the emotion analysis. For example, if the user is feeling stressed, the server will change the summary content to more positive expressions.

[0789] The device displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0790] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0791] The processing flow will be explained below.

[0792] Step 1:

[0793] The server maintains a list of URLs for reputable news sites that are known to provide trustworthy information.

[0794] Step 2:

[0795] The server sends an HTTP request to each news site to retrieve its HTML content, and uses the requests.get method to retrieve the page data for each site.

[0796] Step 3:

[0797] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0798] Step 4:

[0799] The server processes the extracted article links in order, parses the linked pages, and saves the article content in text format. It uses the Article class from the newspaper library to download and parse the article body.

[0800] Step 5:

[0801] The server saves the downloaded and analyzed article text, and analyzes the text data using natural language processing technology. Specifically, it uses a natural language processing library such as spacy to divide the text into sentences.

[0802] Step 6:

[0803] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0804] Step 7:

[0805] After the server generates the summary, it prepares it for emotion analysis by the emotion engine in the server, which is a software module for recognizing the user's emotional state.

[0806] Step 8:

[0807] To recognize the user's emotions, the device collects the user's voice, text input, or facial expression data, for example, by using a microphone or camera to capture real-time data.

[0808] Step 9:

[0809] The device sends the collected data to an emotion engine, which then analyzes the data to determine the user's emotional state, for example, by identifying stress levels through voice analysis or assessing happiness through facial expression analysis.

[0810] Step 10:

[0811] The server customizes the content and expression of the generated summary based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the summary will be changed to more positive wording.

[0812] Step 11:

[0813] The server sends the customized summary to the terminal, which receives the summary and displays it in a user-viewable format.

[0814] Step 12:

[0815] The user views the customized summary provided through the device, allowing the user to obtain information in a format that takes their emotions into consideration.

[0816] Step 13:

[0817] If the user needs more detailed information, they can access the original article link provided and view the full text of the original article.

[0818] In this way, the present invention is a system that efficiently provides highly reliable, multifaceted information while taking into consideration the feelings of the user.

[0819] Example 2

[0820] 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."

[0821] Conventional information collection and provision systems were able to efficiently collect and analyze highly reliable information. However, they did not provide information according to the user's emotional state, and did not take into account the psychological burden that users experience when receiving information. Therefore, there is a need for optimal information provision according to the user's emotional state.

[0822] 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.

[0823] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for customizing the generated summary according to the emotional state of the user, and means for providing the customized summary to the user, thereby enabling optimal information provision that takes into account the emotional state of the user.

[0824] A "reliable source" is one that has been proven to provide accurate and consistent data with little misinformation or false information.

[0825] "Means of collecting data" refers to technologies and methods that have the ability to extract and collect data from various sources on the Internet.

[0826] "Means of analyzing data" refers to a method of converting collected data into a form that is easy to understand by using certain algorithms or techniques.

[0827] A "means for generating a summary of a discussion" is a technology that extracts important points from collected and analyzed data and provides them in a concise summary.

[0828] "Means for customizing according to the user's emotional state" refers to a method for analyzing the user's current emotions and adjusting the content and format of the information provided based on the analysis results.

[0829] A "means for providing a customized summary" is a technique for displaying or providing a summary to a user that is tailored to take into account the user's emotional state.

[0830] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0831] "Web scraping technology" is a technology that automatically extracts data from websites.

[0832] A "machine learning model" is a system that has an algorithm that learns from data and makes predictions and judgments.

[0833] A "terminal" is a device or equipment through which a user receives information.

[0834] This invention relates to a system that uses advanced information collection, analysis, and customization techniques to provide optimal information to users. This system is realized mainly by three roles: a server, a terminal, and a user.

[0835] Server Roles

[0836] The server first collects data from reliable sources. To do this, it has a pre-defined list of URLs for news sites, etc. The server uses the requests library to send HTTP requests to each news site and obtain the HTML content. It then uses BeautifulSoup to parse the HTML content and extract article links. Using web scraping technology, reliable information can be collected efficiently.

[0837] Next, the server parses the collected article links and uses the newspaper library to save the article content in text format. The article is downloaded using the Article class of this library and parsed to obtain the raw text. Natural language processing (NLP) techniques are then used to split the text into sentences, extract key sentences, and generate summaries. For example, NLP libraries such as spaCy and NLTK are used.

[0838] Device Role

[0839] The device has the ability to analyze the user's emotions before displaying the summary provided by the server to the user. Sentiment analysis uses machine learning models such as TensorFlow and PyTorch. It can analyze emotions in real time from the user's camera footage and text input.

[0840] Based on the analysis results, the device customizes the summary sent from the server according to the user's emotional state. For example, if the analysis indicates that the user is feeling stressed, the device will change the summary content to more positive expressions. This reduces the user's psychological burden and enables the provision of optimal information.

[0841] User Roles

[0842] The user can view the summary provided through their device. The summary is customized based on the user's emotional state, allowing them to receive information in the most easily understandable format. If necessary, they can also view detailed information by clicking on a link to the original article.

[0843] Specific examples

[0844] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages of each link and saves the article text in text format. It then uses natural language processing technology to summarize each article in about five sentences. Next, the device analyzes the user's emotional state and, for example, if the user is feeling stressed, changes the summary to more positive expressions. Finally, the device displays the customized summary to the user, allowing the user to efficiently obtain the information they need.

[0845] Prompt Sentence Examples

[0846] Prompt to create a list of news article links:

[0847] "Collect information from the following news sites: News Site A: [URL], News Site B: [URL]."

[0848] Article summary prompt:

[0849] "Using natural language processing techniques, summarize the following article in five sentences: [Text content]"

[0850] User emotion recognition prompts:

[0851] "Analyze the user's current emotions and customize the following summary based on the results: [Summary]"

[0852] As a result, the present invention realizes a system that efficiently provides highly reliable and multifaceted information while taking into consideration the feelings of the user.

[0853] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0854] Step 1:

[0855] The server collects data from reliable sources. Specifically, the server has a pre-defined list of news site URLs and uses the requests library to send HTTP requests to each news site, thereby obtaining HTML content. The input is the list of news site URLs, and the output is the obtained HTML content.

[0856] Step 2:

[0857] The server parses the HTML content and extracts article links. Specifically, the server parses the HTML content and extracts article links using the BeautifulSoup library. This uses web scraping technology. The input is the retrieved HTML content, and the output is a list of extracted article links.

[0858] Step 3:

[0859] The server analyzes the article links, retrieves the article text, and saves it in text format. Specifically, the server uses the Article class of the newspaper library to download and analyze the articles, saving the article text in text format. The input is a list of article links, and the output is the text data of the saved article text.

[0860] Step 4:

[0861] The server uses natural language processing technology to analyze the article text and generate a summary. Specifically, the server uses an NLP library such as spaCy or NLTK to divide the article text into sentences, extract important sentences, and generate a summary of about five sentences. The input is the text data of the article text, and the output is the generated summary.

[0862] Step 5:

[0863] The device analyzes the user's emotions. Specifically, the device uses machine learning models such as TensorFlow and PyTorch to analyze emotions from the user's camera footage and text input. The input is the user's video or text data, and the output is the analyzed emotional state.

[0864] Step 6:

[0865] The device customizes the summary based on the emotion analysis results. Specifically, the device appropriately adjusts the content of the summary provided by the server based on the emotion analysis results obtained by the device. For example, if the user is feeling stressed, the device changes the summary to a more positive expression. The input is the emotion analysis results and the summary provided by the server, and the output is the adjusted summary.

[0866] Step 7:

[0867] The terminal displays the customized summary to the user. Specifically, the terminal displays the tailored summary on the screen for the user to review. The input is the tailored summary, and the output is the screen display for the user to review.

[0868] Specific operation example

[0869] In step 1, the server maintains a list of URLs, such as "https: / / news-site-a.com", and uses the requests library to retrieve the HTML content.

[0870] In step 2, article links such as "https: / / news-site-a.com / article / 123" are extracted from the retrieved HTML content using the BeautifulSoup library.

[0871] In step 3, the linked page is parsed using the newspaper library and the article text is saved in text format.

[0872] In step 4, the spaCy library is used to split the article into sentences, extract the key sentences, and create a five-sentence summary.

[0873] In step 5, the device analyzes the user's video using a machine learning model to determine whether the user is feeling stressed.

[0874] In step 6, negative expressions in the summary are changed to positive ones to adapt to the user's emotional state.

[0875] In step 7, the customized summary is displayed on the device screen for the user to review.

[0876] (Application example 2)

[0877] 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."

[0878] In today's world, many users desire to quickly and efficiently gather reliable information on a daily basis. However, providing this information without regard to the user's emotional state can lead to problems such as stress and information overload. To address this issue, a system that provides information customized to the user's emotional state is required. However, current technology does not provide a system that combines data collection from reliable information sources, summary generation, and emotion-based customization. This makes it difficult to provide information in a format that is optimal for the user.

[0879] The specific processing by the specific 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 collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, and means for customizing the generated summary according to the user's emotions. This makes it possible to provide efficient and reliable information while taking the user's emotions into consideration.

[0880] A "reliable source" refers to a trusted source of information, such as a website or database, that provides accurate and verifiable information.

[0881] "Means of collecting data" refers to techniques for obtaining necessary information from the Internet using web scraping techniques, API calls, etc.

[0882] "Means for analyzing data" refers to the technology of analyzing collected data using natural language processing technology and extracting important information.

[0883] "Means for generating a summary of a discussion" refers to a technology that uses natural language processing techniques to extract key sentences from collected data and create a short-form summary.

[0884] "Means for customizing according to the user's emotions" refers to a technology that uses an emotion engine to analyze the user's emotions and adjusts the content and expression of the summary based on the results.

[0885] "Means for providing a summary to a user" refers to technology that displays a customized summary to a user through a device such as a smartphone or tablet.

[0886] An "emotion engine" is a software program that analyzes a user's emotional state and adjusts information based on the analysis results.

[0887] A "generative AI model" is a machine learning model trained on large datasets that generates content tailored to a user's specific needs and emotional state.

[0888] A "prompt sentence" is an instruction sentence that is input to a generative AI model and contains instructions for the model to generate output based on that instruction.

[0889] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and customizes it according to the user's emotions to provide appropriate information to the user. This system aims to provide users with reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[0890] Server Roles

[0891] The server first needs to maintain a list of URLs of reliable news sites. The server sends an HTTP request to each news site to retrieve its HTML content. The server uses BeautifulSoup to parse the retrieved HTML content. The server then uses web scraping techniques to extract article links from the parsed HTML content.

[0892] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library and analyzed to obtain the raw data of the article body. This data is then analyzed using natural language processing techniques and divided into sentences. Important sentences are extracted and a summary of about five sentences is generated.

[0893] The generated summary is customized by an emotion engine according to the user's emotional state. The server uses a generative AI model to tailor the summary to a positive tone based on a prompt. For example, a prompt could be, "If the user is feeling stressed, please make the following summary positive."

[0894] Device Role

[0895] The device uses an emotion engine to analyze the user's emotions before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the information to be presented in the most receptive form for the user.

[0896] User Roles

[0897] The user can view the customized summary provided through their device. This summary is customized with the user's feelings in mind, allowing them to receive information in the format that is most receptive to them. If necessary, they can also view detailed information by clicking on the original article link.

[0898] Specific examples

[0899] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[0900] The server then recognizes and analyzes the user's emotions in real time and uses a generative AI model to create a prompt. If the user is feeling stressed, the generated summary is changed to a more positive expression. For example, a prompt might be generated that reads, "If the user is feeling stressed, please make the following summary more positive. Summary: Economic news shows that stock prices have fallen sharply."

[0901] The terminal displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[0902] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[0903] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0904] Step 1:

[0905] A server maintains a list of URLs of news sites from reliable sources. Here, the list of reliable news sites is the input data. The server sends HTTP requests to these URLs to get the HTML content. In this process, the HTTP request is made and the output is the HTML content.

[0906] Step 2:

[0907] The HTML content retrieved by the server is analyzed using BeautifulSoup to extract article links. The input data is the HTML content retrieved in step 1. BeautifulSoup is used to analyze the HTML content and extract article links. The output is a list of news article links.

[0908] Step 3:

[0909] Using the article links collected by the server, the pages to which each link points are analyzed and the article content is saved in text format. The articles are downloaded and analyzed using the Article class of the newspaper library. The input data is the article link, and the output data is the text of the article itself.

[0910] Step 4:

[0911] The server uses natural language processing technology to divide article data into sentences, extract important sentences, and generate a summary. The input data is the article text in text format. Natural language processing technology is used to divide the text into sentences, extract important sentences, and generate a summary of about five sentences. The output data is the summary sentences.

[0912] Step 5:

[0913] The server uses an emotion engine to analyze the user's emotional state. The input data is the user's emotional data. The emotion engine analyzes the user's emotions to understand the user's emotional state. The output data is the result of the user's emotion analysis.

[0914] Step 6:

[0915] The server uses a generative AI model to customize a summary based on the prompt. For example, it creates a prompt such as, "If the user is feeling stressed, please make the following summary positive." The input data are the generated summary and the emotion analysis results. The prompt is input into the generative AI model to obtain a customized summary based on the emotion. The output is the customized summary.

[0916] Step 7:

[0917] The terminal displays the final customized summary to the user. The input data is the customized summary text. The terminal displays this summary text for the user to confirm. The output is the customized summary displayed in a form that the user can visually confirm.

[0918] Step 8:

[0919] The user checks the customized summary provided through the terminal. The input data is the customized summary text displayed on the terminal. The user checks this summary and, if necessary, checks for more detailed information by clicking on the original article link. The output is the detailed information available to the user.

[0920] 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.

[0921] 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.

[0922] 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.

[0923] [Fourth embodiment]

[0924] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0925] 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.

[0926] 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).

[0927] 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.

[0928] 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.

[0929] 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).

[0930] 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. 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.

[0931] 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.

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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.

[0936] 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."

[0937] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0938] Server Roles

[0939] The server collects data from designated reliable sources. Specifically, it maintains a list of URLs of reliable news sites and sends HTTP requests to each news site to obtain its HTML content. The server then analyzes the obtained HTML content and extracts article links. This link extraction is performed using web scraping technology.

[0940] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL and parsing the article body as text, resulting in the raw article data.

[0941] The server then analyzes the retrieved article text and uses natural language processing technology to extract key sentences and generate a summary. The text is divided into sentences and the most important sentences are selected. This summary is condensed to about five sentences to help users understand the information efficiently.

[0942] Device Role

[0943] The terminal displays the final summary provided by the server to the user. The server generates a summary and sends it to the terminal in an appropriate format. The terminal receives the summary and displays it on its interface for the user to view.

[0944] User Roles

[0945] Users can check the summary provided through their device, which allows them to efficiently grasp reliable, multifaceted information. If necessary, they can also view detailed information by clicking on the original article link.

[0946] Specific examples

[0947] For example, a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. The server then uses natural language processing techniques to summarize each article and generate a final summary. These summaries are then sent to the device and displayed in a format that the user can view.

[0948] Users can view summaries on their devices and quickly obtain the information they need from the summaries. For example, if a user wants to know about a particular news item, they can simply read the summary to understand the main points. If they need more information, they can click on the provided link to the original article to access the detailed information.

[0949] In this way, the present invention provides a system that enables users to efficiently obtain information from reliable and multifaceted perspectives.

[0950] The processing flow will be explained below.

[0951] Step 1:

[0952] The server maintains a list of URLs for trusted news sites.

[0953] Step 2:

[0954] The server sends an HTTP request to each news site to retrieve its HTML content. For example, it uses requests.get to retrieve the page contents.

[0955] Step 3:

[0956] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[0957] Step 4:

[0958] The server processes the collected article links one by one, analyzes the linked pages, and downloads and analyzes the article content. For analysis, it uses the Article class of the newspaper library.

[0959] Step 5:

[0960] The server saves the analyzed article text in text format, thereby accumulating raw text data.

[0961] Step 6:

[0962] The server analyzes the stored article text using a natural language processing tool (e.g., Spacy) and divides it into sentences. The text is analyzed using nlp objects.

[0963] Step 7:

[0964] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[0965] Step 8:

[0966] The server collects the summaries it generates and saves them in a single file, such as summary.txt, allowing for centralized management of summary information.

[0967] Step 9:

[0968] The terminal retrieves the summary file from the server and displays it on the interface in a format that the user can view, allowing the user to quickly understand the important information.

[0969] Step 10:

[0970] If users need more information, they can access the original article link provided on their device and view the full text of the original article.

[0971] Example 1

[0972] 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."

[0973] In today's information society, a large amount of information is scattered across the Internet, and there is a need to efficiently collect information from reliable sources, summarize it, and provide it to users. However, manually collecting data from reliable sources, analyzing it, and generating summaries is time-consuming, labor-intensive, and inefficient. Furthermore, generating summaries requires advanced natural language processing technology, and there are currently no easy ways to do this. Therefore, there is a need for a system that can automate the collection, analysis, and summarization of information and make it available efficiently.

[0974] 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.

[0975] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the HTML content of the collected data and extracting article links, means for acquiring article text from the extracted article links and saving it as text, means for generating summaries of the saved article text using natural language processing technology, and means for transmitting the generated summaries to a terminal and providing them to a user. This makes it possible to automate the collection of information from reliable information sources, data analysis, and summary generation, and efficiently provide them to users.

[0976] A "reliable source of information" refers to an information provider or site whose information is guaranteed to be accurate and objective.

[0977] "Data collection methods" refers to the technologies and methods used to automatically obtain the required information from sources on the Internet.

[0978] "HTML Content" refers to content written in HTML, a markup language that defines the structure of web pages.

[0979] "Article Link" means a URL that provides access to a specific article on a web page.

[0980] "Article body" refers to text data that contains the main information of news articles, blog articles, etc.

[0981] "Means of saving as text" refers to the technology or method of saving acquired information in a string format in a file, etc.

[0982] "Natural language processing technology" refers to computer technology for understanding and analyzing human language.

[0983] A "summary generator" refers to a technique or method for extracting important parts from a long text and summarizing them in a shorter form.

[0984] "Device" refers to a device used by a User, such as a computer, smartphone, or tablet.

[0985] "User" refers to any individual or organization that uses the information collection system.

[0986] The present invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[0987] Server Roles

[0988] The server is responsible for collecting data from designated reliable sources. Specifically, it maintains a list of URLs for reliable news sites, sends HTTP requests to each news site, and retrieves their HTML content. The HTTP requests are sent using Python's requests library. The retrieved HTML content is then analyzed using BeautifulSoup to extract article links. Web scraping technology is used to extract these links.

[0989] The server then retrieves each article using the collected article links and saves the article content in text format. This process involves downloading the article content from its URL, parsing the article body, and saving it as text. This process also uses the BeautifulSoup and requests libraries.

[0990] The server then analyzes the retrieved article text using natural language processing technology, extracts key sentences, and generates a summary. Specifically, it uses natural language processing libraries such as nltk and spaCy to divide the text into sentences and select the most important sentences. This summary is condensed to about five sentences, allowing users to efficiently understand the information.

[0991] Device Role

[0992] The device is responsible for displaying the final summary provided by the server to the user. The summary generated by the server is sent to the device in an appropriate format. For example, the summary information sent in JSON format is received and displayed on the device's web interface. This display is implemented using JavaScript and HTML to present the summary in a user-friendly format.

[0993] User Roles

[0994] Users can efficiently grasp reliable, multifaceted information by checking the summary provided through their device. If necessary, they can also access detailed information by clicking on a link to the original article. Specifically, users read the summary, quickly obtain key information from its contents, and then access the original article as needed.

[0995] Specific examples

[0996] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes these links, downloads the article text from each article link, and saves it in text format. It then uses natural language processing technology to summarize each article and generate a final summary. This summary is then sent to the device and displayed in a format that the user can view.

[0997] Users can view summaries on their devices and quickly understand key points. For example, if a user wants to know about a particular piece of news, they can request information from the system using the prompt "Show me the latest news summary." They can then quickly obtain the information they need by reading the summary, and if they need more details, they can click on the provided link to the original article to access the details. In this way, the present invention provides users with a powerful tool for efficiently obtaining and understanding information.

[0998] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0999] Step 1:

[1000] The server collects data from reliable sources. It receives a list of URLs of reliable news sites as input and sends HTTP requests to each news site. Specifically, it uses the requests library to send requests to each URL and retrieve HTML content. The retrieved HTML content is the output.

[1001] Step 2:

[1002] The HTML content retrieved by the server is analyzed and article links are extracted. HTML content is received as input and the HTML is parsed using BeautifulSoup. Links to news articles are extracted from the parsed HTML. The extracted article links are the output. Specifically, using BeautifulSoup< / url:> Search for links contained in tags and collect article links in list format.

[1003] Step 3:

[1004] The server retrieves the body of each article from the extracted article links and saves it in text format. It receives the article links as input, sends an HTTP request to each link again to retrieve the HTML content, extracts the body of the article from the retrieved HTML, converts it to text format, and saves it. The saved article text is obtained as output. Specifically, the article URL is accessed, and the retrieved HTML is analyzed again with BeautifulSoup to extract the main content.

[1005] Step 4:

[1006] The server uses natural language processing technology to analyze article text stored on the server, extracting important sentences and generating a summary. It receives the stored article text as input and uses nltk or spaCy to divide the text into sentences. It evaluates the importance of each sentence, selects the most important sentence, and generates a summary of about five sentences. The generated summary is output. Specifically, it uses NLP techniques such as morphological analysis and sentence importance score calculation.

[1007] Step 5:

[1008] The server sends the generated summary to the terminal. It receives the generated summary as input and sends it to the terminal in an appropriate format (e.g., JSON format). As output, it obtains the JSON format summary data that was sent. Specifically, it sends the summary data as an HTTP response.

[1009] Step 6:

[1010] The terminal displays the received summary to the user. It receives the received JSON format summary data as input and displays the summary on a web interface. As output, the displayed summary is provided to the user. Specifically, it formats the summary data using JavaScript and HTML and displays it on the browser.

[1011] Step 7:

[1012] The user reviews the summary through their device and accesses the original article if necessary. The input is the displayed summary, and they obtain the necessary information. The output is the information the user obtained and access to the original article. Specifically, they read the summary to understand the main points, and if they need more details, they click the link to view the original article.

[1013] (Application example 1)

[1014] 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."

[1015] In the current information distribution system, a huge amount of information is generated every day, making it difficult for users to efficiently obtain reliable information. Browsing through many sources and articles takes time, and important information may be overlooked. Furthermore, there is a lack of real-time notifications of important information based on users' areas of interest and quick access to the original detailed information.

[1016] 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.

[1017] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for providing the generated summary to the user, means for notifying the user of important information based on the user's interests in real time, and means for providing a link from the summarized information to the original detailed information. This makes it possible to efficiently collect and summarize reliable information and provide important information based on the user's interests in real time. It also enables quick access to detailed information from the summarized information.

[1018] "Reliable sources" refer to trusted news sites and official websites that provide accurate and objective information.

[1019] "Means of collecting data" refers to the means of obtaining the necessary information from designated sources, such as using web scraping technology.

[1020] "Means for analyzing data" refers to means for analyzing collected text data and extracting important information using natural language processing technology.

[1021] "Means for generating summaries of discussions" refers to means for generating summaries of articles or discussions based on the extracted important information.

[1022] The "means for providing a summary to a user" refers to a means for displaying the generated summary on the user's terminal.

[1023] "Means of notifying users of important information in real time based on their interests" refers to means of collecting important information from reliable sources based on users' areas of interest and keywords, and notifying them in a timely manner.

[1024] "Means for providing links from the summarized information to the original detailed information" refers to means for providing links from the generated summary to the original article or detailed information, allowing users to access the detailed information.

[1025] This invention relates to a system that collects data from reliable information sources, analyzes the data, generates a summary of the discussion, and provides it to users. This system functions in unison with a server, terminals, and users.

[1026] Server Roles

[1027] The server first collects data from reliable sources. In this process, it uses web scraping technology to obtain the necessary data from the sources. Specifically, it uses BeautifulSoup (Python) to extract HTML content from news sites and collect article links.

[1028] Next, each article is retrieved based on the collected links and its contents are saved in text format. This involves sending an HTTP request and parsing the article's HTML to extract the text. The retrieved article text is then analyzed using natural language processing techniques. Here, techniques such as spaCy (Python) and GPT-3 (OpenAI) are used to extract important sentences and generate summaries.

[1029] The generated summary is sent to the terminal in an appropriate format. The server stores this information in a database and updates it as needed. PostgreSQL is used for the database, improving data management and access efficiency.

[1030] Device Role

[1031] The device displays the summaries provided by the server to the user, provides an appropriate user interface so that the user can view the summaries through a browser or a dedicated smartphone app, and notifies the user of important information in real time from the server based on the user's areas of interest and keywords.

[1032] Furthermore, the summary also provides a link to the original detailed information, allowing users to access the detailed information at their discretion. The interface for this purpose is designed to be easy for users to operate.

[1033] User Roles

[1034] Users can quickly understand important information by checking the summaries provided through their devices. Users can receive important information in real time based on their own interests. For example, when news about "environmental issues" is updated, users will automatically receive a summary and can access the detailed original article from the summary article.

[1035] Specific examples

[1036] For example, a server might collect articles about environmental issues from a news site and generate summaries of the articles. The summaries are generated using prompts such as:

[1037] Example prompt sentence:

[1038] Generate a summary of a news article:

[1039] 1. Load articles collected from trusted news sites.

[1040] 2. Extract the key points from the article and summarize them in about five sentences.

[1041] 3. Return the summary.

[1042] (Article text)

[1043] "..."

[1044] ...

[1045] "

[1046] (summary)

[1047] 1. In this article...

[1048] 2. ...

[1049] This allows users to quickly grasp important information and access detailed information as needed. The system efficiently collects and summarizes reliable information, providing important information based on the user's interests in real time. Furthermore, it enables quick access to detailed information from the summarized information, significantly reducing the burden on users when it comes to obtaining information.

[1050] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1051] Step 1:

[1052] The server retrieves the URLs of news sites from a specified list of reliable sources. Then, it sends an HTTP request to retrieve the HTML content of each news site. It then parses the HTML content using BeautifulSoup (Python) to extract article links. The input is a list of news site URLs, and the output is a list of article links.

[1053] Step 2:

[1054] The server retrieves the content of each article based on the extracted article links. Specifically, it sends an HTTP request to each link again to retrieve the article's HTML, and then uses BeautifulSoup (Python) to extract the article's body text. The input is a list of article links, and the output is the text of each article's body.

[1055] Step 3:

[1056] The server analyzes the retrieved article text using natural language processing technology. For example, it uses spaCy (Python) to divide the article text into sentences and GPT-3 (OpenAI) to extract important sentences. The following sentence is used as an example of a prompt sentence:

[1057] Example prompt sentence:

[1058] Generate a summary of a news article:

[1059] 1. Load articles collected from trusted news sites.

[1060] 2. Extract the key points from the article and summarize them in about five sentences.

[1061] 3. Return the summary.

[1062] (Article text)

[1063] "..."

[1064] ...

[1065] "

[1066] (summary)

[1067] 1. In this article...

[1068] 2. ...

[1069] The input is the text of the article, and the output is a summary of about five sentences.

[1070] Step 4:

[1071] The server saves the generated summary and sends it to the terminal in an appropriate format. During this process, the summary and the link to the original article are stored in a database (PostgreSQL) and sent to the front end to provide a user interface. The input is the summary text and the link to the original article, and the output is the summary displayed on the user terminal.

[1072] Step 5:

[1073] The terminal displays the summary received from the server to the user. The user interface is simple and provides a summary and a link to the original article. The input is the summary text received from the server and the link to the original article, and the output is the display to the user.

[1074] Step 6:

[1075] The device notifies users of important information in real time based on their profile and areas of interest. It receives updates from the server, filters them based on their interests, and sends push notifications to users. The input is the user's interest information and summary text, and the output is the information sent to the user as a push notification.

[1076] Step 7:

[1077] Users can view the summary on their device and, if necessary, click on the link to the original article to access more detailed information. This allows users to efficiently grasp important information and easily view detailed information. The input is the summary and article link displayed on the device, and the output is the information the user obtains.

[1078] 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.

[1079] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and then uses an emotion engine to recognize and analyze the user's emotions, customizing the generated summary to suit the user's emotions. This system aims to provide users with highly reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[1080] Server Roles

[1081] The server must first maintain a list of URLs for reliable news sites. The server then sends an HTTP request to each news site to retrieve its HTML content. The retrieved HTML content is then parsed using BeautifulSoup to extract article links. This link extraction is performed using web scraping techniques.

[1082] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library, and the raw article text is obtained by analyzing it. This data is then analyzed using natural language processing techniques, divided into sentences, and key sentences are extracted to generate a summary of about five sentences.

[1083] The generated summary is customized according to the user's emotional state by the emotion engine, which recognizes and analyzes the user's emotions and adjusts the content and expression of the summary based on the analysis results.

[1084] Device Role

[1085] The device analyzes the user's emotions using the emotion engine before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the device to provide the most effective information to the user.

[1086] User Roles

[1087] The user checks the summary provided through their device. This summary is customized to take into account the user's emotions, so the user can receive the information in the format that is most receptive to them. If necessary, they can also view more detailed information by clicking on the link to the original article.

[1088] Specific examples

[1089] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[1090] The server then recognizes and analyzes the user's emotions in real time and customizes the summary based on the results of the emotion analysis. For example, if the user is feeling stressed, the server will change the summary content to more positive expressions.

[1091] The device displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[1092] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[1093] The processing flow will be explained below.

[1094] Step 1:

[1095] The server maintains a list of URLs for reputable news sites that are known to provide trustworthy information.

[1096] Step 2:

[1097] The server sends an HTTP request to each news site to retrieve its HTML content, and uses the requests.get method to retrieve the page data for each site.

[1098] Step 3:

[1099] The server uses BeautifulSoup to parse the HTML content and extract the article links. Specifically, it uses the soup.find_all('a') method to collect the article URLs.

[1100] Step 4:

[1101] The server processes the extracted article links in order, parses the linked pages, and saves the article content in text format. It uses the Article class from the newspaper library to download and parse the article body.

[1102] Step 5:

[1103] The server saves the downloaded and analyzed article text, and analyzes the text data using natural language processing technology. Specifically, it uses a natural language processing library such as spacy to divide the text into sentences.

[1104] Step 6:

[1105] The server extracts important sentences from the analyzed text and generates a summary of about five sentences, allowing users to efficiently grasp the main information.

[1106] Step 7:

[1107] After the server generates the summary, it prepares it for emotion analysis by the emotion engine in the server, which is a software module for recognizing the user's emotional state.

[1108] Step 8:

[1109] To recognize the user's emotions, the device collects the user's voice, text input, or facial expression data, for example, by using a microphone or camera to capture real-time data.

[1110] Step 9:

[1111] The device sends the collected data to an emotion engine, which then analyzes the data to determine the user's emotional state, for example, by identifying stress levels through voice analysis or assessing happiness through facial expression analysis.

[1112] Step 10:

[1113] The server customizes the content and expression of the generated summary based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the summary will be changed to more positive wording.

[1114] Step 11:

[1115] The server sends the customized summary to the terminal, which receives the summary and displays it in a user-viewable format.

[1116] Step 12:

[1117] The user views the customized summary provided through the device, allowing the user to obtain information in a format that takes their emotions into consideration.

[1118] Step 13:

[1119] If the user needs more detailed information, they can access the original article link provided and view the full text of the original article.

[1120] In this way, the present invention is a system that efficiently provides highly reliable, multifaceted information while taking into consideration the feelings of the user.

[1121] Example 2

[1122] 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."

[1123] Conventional information collection and provision systems were able to efficiently collect and analyze highly reliable information. However, they did not provide information according to the user's emotional state, and did not take into account the psychological burden that users experience when receiving information. Therefore, there is a need for optimal information provision according to the user's emotional state.

[1124] 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.

[1125] In this invention, the server includes means for collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, means for customizing the generated summary according to the emotional state of the user, and means for providing the customized summary to the user, thereby enabling optimal information provision that takes into account the emotional state of the user.

[1126] A "reliable source" is one that has been proven to provide accurate and consistent data with little misinformation or false information.

[1127] "Means of collecting data" refers to technologies and methods that have the ability to extract and collect data from various sources on the Internet.

[1128] "Means of analyzing data" refers to a method of converting collected data into a form that is easy to understand by using certain algorithms or techniques.

[1129] A "means for generating a summary of a discussion" is a technology that extracts important points from collected and analyzed data and provides them in a concise summary.

[1130] "Means for customizing according to the user's emotional state" refers to a method for analyzing the user's current emotions and adjusting the content and format of the information provided based on the analysis results.

[1131] A "means for providing a customized summary" is a technique for displaying or providing a summary to a user that is tailored to take into account the user's emotional state.

[1132] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1133] "Web scraping technology" is a technology that automatically extracts data from websites.

[1134] A "machine learning model" is a system that has an algorithm that learns from data and makes predictions and judgments.

[1135] A "terminal" is a device or equipment through which a user receives information.

[1136] This invention relates to a system that uses advanced information collection, analysis, and customization techniques to provide optimal information to users. This system is realized mainly by three roles: a server, a terminal, and a user.

[1137] Server Roles

[1138] The server first collects data from reliable sources. To do this, it has a pre-defined list of URLs for news sites, etc. The server uses the requests library to send HTTP requests to each news site and obtain the HTML content. It then uses BeautifulSoup to parse the HTML content and extract article links. Using web scraping technology, reliable information can be collected efficiently.

[1139] Next, the server parses the collected article links and uses the newspaper library to save the article content in text format. The article is downloaded using the Article class of this library and parsed to obtain the raw text. Natural language processing (NLP) techniques are then used to split the text into sentences, extract key sentences, and generate summaries. For example, NLP libraries such as spaCy and NLTK are used.

[1140] Device Role

[1141] The device has the ability to analyze the user's emotions before displaying the summary provided by the server to the user. Sentiment analysis uses machine learning models such as TensorFlow and PyTorch. It can analyze emotions in real time from the user's camera footage and text input.

[1142] Based on the analysis results, the device customizes the summary sent from the server according to the user's emotional state. For example, if the analysis indicates that the user is feeling stressed, the device will change the summary content to more positive expressions. This reduces the user's psychological burden and enables the provision of optimal information.

[1143] User Roles

[1144] The user can view the summary provided through their device. The summary is customized based on the user's emotional state, allowing them to receive information in the most easily understandable format. If necessary, they can also view detailed information by clicking on a link to the original article.

[1145] Specific examples

[1146] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages of each link and saves the article text in text format. It then uses natural language processing technology to summarize each article in about five sentences. Next, the device analyzes the user's emotional state and, for example, if the user is feeling stressed, changes the summary to more positive expressions. Finally, the device displays the customized summary to the user, allowing the user to efficiently obtain the information they need.

[1147] Prompt Sentence Examples

[1148] Prompt to create a list of news article links:

[1149] "Collect information from the following news sites: News Site A: [URL], News Site B: [URL]."

[1150] Article summary prompt:

[1151] "Using natural language processing techniques, summarize the following article in five sentences: [Text content]"

[1152] User emotion recognition prompts:

[1153] "Analyze the user's current emotions and customize the following summary based on the results: [Summary]"

[1154] As a result, the present invention realizes a system that efficiently provides highly reliable and multifaceted information while taking into consideration the feelings of the user.

[1155] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1156] Step 1:

[1157] The server collects data from reliable sources. Specifically, the server has a pre-defined list of news site URLs and uses the requests library to send HTTP requests to each news site, thereby obtaining HTML content. The input is the list of news site URLs, and the output is the obtained HTML content.

[1158] Step 2:

[1159] The server parses the HTML content and extracts article links. Specifically, the server parses the HTML content and extracts article links using the BeautifulSoup library. This uses web scraping technology. The input is the retrieved HTML content, and the output is a list of extracted article links.

[1160] Step 3:

[1161] The server analyzes the article links, retrieves the article text, and saves it in text format. Specifically, the server uses the Article class of the newspaper library to download and analyze the articles, saving the article text in text format. The input is a list of article links, and the output is the text data of the saved article text.

[1162] Step 4:

[1163] The server uses natural language processing technology to analyze the article text and generate a summary. Specifically, the server uses an NLP library such as spaCy or NLTK to divide the article text into sentences, extract important sentences, and generate a summary of about five sentences. The input is the text data of the article text, and the output is the generated summary.

[1164] Step 5:

[1165] The device analyzes the user's emotions. Specifically, the device uses machine learning models such as TensorFlow and PyTorch to analyze emotions from the user's camera footage and text input. The input is the user's video or text data, and the output is the analyzed emotional state.

[1166] Step 6:

[1167] The device customizes the summary based on the emotion analysis results. Specifically, the device appropriately adjusts the content of the summary provided by the server based on the emotion analysis results obtained by the device. For example, if the user is feeling stressed, the device changes the summary to a more positive expression. The input is the emotion analysis results and the summary provided by the server, and the output is the adjusted summary.

[1168] Step 7:

[1169] The terminal displays the customized summary to the user. Specifically, the terminal displays the tailored summary on the screen for the user to review. The input is the tailored summary, and the output is the screen display for the user to review.

[1170] Specific operation example

[1171] In step 1, the server maintains a list of URLs, such as "https: / / news-site-a.com", and uses the requests library to retrieve the HTML content.

[1172] In step 2, article links such as "https: / / news-site-a.com / article / 123" are extracted from the retrieved HTML content using the BeautifulSoup library.

[1173] In step 3, the linked page is parsed using the newspaper library and the article text is saved in text format.

[1174] In step 4, the spaCy library is used to split the article into sentences, extract the key sentences, and create a five-sentence summary.

[1175] In step 5, the device analyzes the user's video using a machine learning model to determine whether the user is feeling stressed.

[1176] In step 6, negative expressions in the summary are changed to positive ones to adapt to the user's emotional state.

[1177] In step 7, the customized summary is displayed on the device screen for the user to review.

[1178] (Application example 2)

[1179] 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."

[1180] In today's world, many users desire to quickly and efficiently gather reliable information on a daily basis. However, providing this information without regard to the user's emotional state can lead to problems such as stress and information overload. To address this issue, a system that provides information customized to the user's emotional state is required. However, current technology does not provide a system that combines data collection from reliable information sources, summary generation, and emotion-based customization. This makes it difficult to provide information in a format that is optimal for the user.

[1181] The specific processing by the specific 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 collecting data from reliable information sources, means for analyzing the collected data to generate a summary of the discussion, and means for customizing the generated summary according to the user's emotions. This makes it possible to provide efficient and reliable information while taking the user's emotions into consideration.

[1182] A "reliable source" refers to a trusted source of information, such as a website or database, that provides accurate and verifiable information.

[1183] "Means of collecting data" refers to techniques for obtaining necessary information from the Internet using web scraping techniques, API calls, etc.

[1184] "Means for analyzing data" refers to the technology of analyzing collected data using natural language processing technology and extracting important information.

[1185] "Means for generating a summary of a discussion" refers to a technology that uses natural language processing techniques to extract key sentences from collected data and create a short-form summary.

[1186] "Means for customizing according to the user's emotions" refers to a technology that uses an emotion engine to analyze the user's emotions and adjusts the content and expression of the summary based on the results.

[1187] "Means for providing a summary to a user" refers to technology that displays a customized summary to a user through a device such as a smartphone or tablet.

[1188] An "emotion engine" is a software program that analyzes a user's emotional state and adjusts information based on the analysis results.

[1189] A "generative AI model" is a machine learning model trained on large datasets that generates content tailored to a user's specific needs and emotional state.

[1190] A "prompt sentence" is an instruction sentence that is input to a generative AI model and contains instructions for the model to generate output based on that instruction.

[1191] This invention relates to a system that collects data from reliable information sources, analyzes the data to generate a summary of the discussion, and customizes it according to the user's emotions to provide appropriate information to the user. This system aims to provide users with reliable, multifaceted information efficiently, with the server, terminals, and users functioning as a single unit.

[1192] Server Roles

[1193] The server first needs to maintain a list of URLs of reliable news sites. The server sends an HTTP request to each news site to retrieve its HTML content. The server uses BeautifulSoup to parse the retrieved HTML content. The server then uses web scraping techniques to extract article links from the parsed HTML content.

[1194] Next, the server uses the collected article links to analyze the linked pages and save the article contents in text format. The article is downloaded using the Article class of the newspaper library and analyzed to obtain the raw data of the article body. This data is then analyzed using natural language processing techniques and divided into sentences. Important sentences are extracted and a summary of about five sentences is generated.

[1195] The generated summary is customized by an emotion engine according to the user's emotional state. The server uses a generative AI model to tailor the summary to a positive tone based on a prompt. For example, a prompt could be, "If the user is feeling stressed, please make the following summary positive."

[1196] Device Role

[1197] The device uses an emotion engine to analyze the user's emotions before displaying the final summary provided by the server to the user. Once the analysis results are obtained, the content and format of the summary are modified according to the user's emotional state. This process allows the information to be presented in the most receptive form for the user.

[1198] User Roles

[1199] The user can view the customized summary provided through their device. This summary is customized with the user's feelings in mind, allowing them to receive information in the format that is most receptive to them. If necessary, they can also view detailed information by clicking on the original article link.

[1200] Specific examples

[1201] For example, suppose a server collects article links from "News Site A" and "News Site B." The server analyzes the pages to which each link points, saves the article text in text format, and then uses natural language processing technology to summarize each article in about five sentences.

[1202] The server then recognizes and analyzes the user's emotions in real time and uses a generative AI model to create a prompt. If the user is feeling stressed, the generated summary is changed to a more positive expression. For example, a prompt might be generated that reads, "If the user is feeling stressed, please make the following summary more positive. Summary: Economic news shows that stock prices have fallen sharply."

[1203] The terminal displays the final customized summary to the user, allowing the user to efficiently obtain the information they need. If the user needs more detailed information, they can click on the original article link to view the full article content.

[1204] Thus, the present invention implements a system that efficiently provides highly reliable and multifaceted information while taking into consideration the user's feelings.

[1205] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1206] Step 1:

[1207] A server maintains a list of URLs of news sites from reliable sources. Here, the list of reliable news sites is the input data. The server sends HTTP requests to these URLs to get the HTML content. In this process, the HTTP request is made and the output is the HTML content.

[1208] Step 2:

[1209] The HTML content retrieved by the server is analyzed using BeautifulSoup to extract article links. The input data is the HTML content retrieved in step 1. BeautifulSoup is used to analyze the HTML content and extract article links. The output is a list of news article links.

[1210] Step 3:

[1211] Using the article links collected by the server, the pages to which each link points are analyzed and the article content is saved in text format. The articles are downloaded and analyzed using the Article class of the newspaper library. The input data is the article link, and the output data is the text of the article itself.

[1212] Step 4:

[1213] The server uses natural language processing technology to divide article data into sentences, extract important sentences, and generate a summary. The input data is the article text in text format. Natural language processing technology is used to divide the text into sentences, extract important sentences, and generate a summary of about five sentences. The output data is the summary sentences.

[1214] Step 5:

[1215] The server uses an emotion engine to analyze the user's emotional state. The input data is the user's emotional data. The emotion engine analyzes the user's emotions to understand the user's emotional state. The output data is the result of the user's emotion analysis.

[1216] Step 6:

[1217] The server uses a generative AI model to customize a summary based on the prompt. For example, it creates a prompt such as, "If the user is feeling stressed, please make the following summary positive." The input data are the generated summary and the emotion analysis results. The prompt is input into the generative AI model to obtain a customized summary based on the emotion. The output is the customized summary.

[1218] Step 7:

[1219] The terminal displays the final customized summary to the user. The input data is the customized summary text. The terminal displays this summary text for the user to confirm. The output is the customized summary displayed in a form that the user can visually confirm.

[1220] Step 8:

[1221] The user checks the customized summary provided through the terminal. The input data is the customized summary text displayed on the terminal. The user checks this summary and, if necessary, checks for more detailed information by clicking on the original article link. The output is the detailed information available to the user.

[1222] 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.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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).

[1229] 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.

[1230] 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."

[1231] 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.

[1232] 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).

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] 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.

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] The following is further disclosed regarding the above embodiment.

[1244] (Claim 1)

[1245] A means of collecting data from reliable sources;

[1246] a means of analyzing the collected data to generate a summary of the discussion;

[1247] means for providing the generated summary to a user;

[1248] A system including:

[1249] (Claim 2)

[1250] 10. The system of claim 1, wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

[1251] (Claim 3)

[1252] 10. The system of claim 1, wherein the system collects data from the information source using web scraping technology.

[1253] "Example 1"

[1254] (Claim 1)

[1255] A means of collecting data from reliable sources;

[1256] A means of analyzing the HTML content of the collected data and extracting article links;

[1257] A means to extract the article text from the extracted article link and save it as text;

[1258] A means for generating summaries of the stored article texts using natural language processing technology;

[1259] means for transmitting the generated summary to a terminal and providing it to a user;

[1260] A system including:

[1261] (Claim 2)

[1262] 10. The system of claim 1, wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

[1263] (Claim 3)

[1264] 10. The system of claim 1, wherein the system collects data from the information source using web scraping technology.

[1265] "Application Example 1"

[1266] (Claim 1)

[1267] A means of collecting data from reliable sources;

[1268] a means of analyzing the collected data to generate a summary of the discussion;

[1269] means for providing the generated summary to a user;

[1270] A way to notify users of important information in real time based on their interests;

[1271] a means of providing a link from the summarized information to the original detailed information;

[1272] A system including:

[1273] (Claim 2)

[1274] 10. The system of claim 1, wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

[1275] (Claim 3)

[1276] 10. The system of claim 1, wherein the system collects data from the information source using web scraping technology.

[1277] "Example 2: Combining Emotion Engines"

[1278] (Claim 1)

[1279] A means of collecting data from reliable sources;

[1280] a means of analyzing the collected data to generate a summary of the discussion;

[1281] means for customizing the generated summary according to the emotional state of the user;

[1282] means for providing a customized summary to a user;

[1283] A system including:

[1284] (Claim 2)

[1285] 10. The system of claim 1, wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

[1286] (Claim 3)

[1287] 10. The system of claim 1, wherein the system collects data from the information source using web scraping technology.

[1288] (Claim 4)

[1289] 10. The system of claim 1, further comprising means for analyzing user sentiment and customizing the summary based on the analysis.

[1290] (Claim 5)

[1291] 5. The system of claim 4, wherein the sentiment analysis uses a machine learning model.

[1292] (Claim 6)

[1293] 10. The system of claim 1, further comprising a terminal that displays the customized summary.

[1294] "Application example 2 when combining emotion engines"

[1295] (Claim 1)

[1296] A means of collecting data from reliable sources;

[1297] a means of analyzing the collected data to generate a summary of the discussion;

[1298] a means for customizing the generated summary according to the user's emotions;

[1299] means for providing the generated customized summary to a user;

[1300] A system including:

[1301] (Claim 2)

[1302] 10. The system of claim 1, wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

[1303] (Claim 3)

[1304] 10. The system of claim 1, wherein the system collects data from the information source using web scraping technology.

[1305] (Claim 4)

[1306] 2. The system according to claim 1, wherein the system analyzes the user's emotions using an emotion engine and adjusts the content and expression of the summary based on the analysis results.

[1307] (Claim 5)

[1308] The system of claim 4, wherein the system uses a generative AI model to generate prompt sentences that take into account the user's emotions and customize the content of the summary. [Explanation of symbols]

[1309] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:>

Claims

1. A means of collecting data from reliable sources; a means of analyzing the collected data to generate a summary of the discussion; means for providing the generated summary to a user; A system including:

2. The system of claim 1 , wherein the system analyzes the data using natural language processing techniques, extracts important sentences, and generates a summary.

3. The system of claim 1 , wherein the data is collected from the information source using web scraping technology.

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