system

Abstract

We provide the system. [Solution] A means of automatically collecting information from information sources via the Internet communication network, A natural language processing method for analyzing collected information and identifying important elements, Means for generating a summary of information based on identified key elements, A means of delivering the generated summary to the user's terminal, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In recent years, with the development of information technology, businesspersons and information collectors are exposed to a large amount of information every day. However, it is difficult and time-consuming to efficiently collect necessary information from the vast amount of information and understand the key points. In addition, there are not many systems that can perform filtering according to individual information needs, and there is a problem that it is very difficult for users to select the information they actually need. 【Means for Solving the Problems】 【0005】 To solve this problem, the present invention provides a system that automatically collects information from information sources, analyzes the information using natural language processing, and identifies important elements. Furthermore, it generates a summary of the information based on the identified important elements and filters it according to information categories specified individually by the user. In addition, by providing links between the generated summary and the related original information, it creates a highly convenient information gathering environment for the user. 【0006】 The "Internet communication network" is a communication infrastructure that allows computers and devices to connect with each other and send and receive information. 【0007】 An "information source" refers to a website or database that provides content such as news and articles. 【0008】 "Means of automatically collecting information" refers to technologies or processes that obtain up-to-date information from sources without human intervention. 【0009】 "Natural language processing" is a technology that uses computers to understand and analyze human language. 【0010】 "Means for generating information summaries" refers to techniques or methods for extracting important information and presenting it concisely. 【0011】 A "terminal" refers to a device that a user uses to connect to the internet or receive information, such as a smartphone or a personal computer. 【0012】 "Filtering" is the process of selecting information according to specific criteria and providing it in a desirable format. 【0013】 A "link to the original information" is a hyperlink that provides access to detailed information related to the generated summary. [Brief explanation of the drawing] 【0014】 [Figure 1]It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0020】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc. 【0021】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0025】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0026】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0027】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0028】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0029】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0032】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0033】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0034】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0035】 This invention is a system that automatically collects information from information sources, generates summaries, and provides them to users. Specific embodiments of the entire system are described below. 【0036】 The system starts when the server periodically retrieves information from sources via the internet. The information is obtained from reliable news sites and databases using RSS feeds and APIs. The server uses natural language processing techniques to analyze the collected information. Here, the information is analyzed through grammatical and semantic analysis to identify important elements and key phrases within the articles. 【0037】 Following the analysis, the server generates a concise summary based on the identified information. This summary is designed to include the subject matter, key data, and other relevant information, helping users understand the information quickly. 【0038】 The generated summaries are then delivered to the user's device. The device displays the received summaries in a user interface and is designed to allow the user to efficiently access information of interest by filtering them according to category and importance. Users can review the summaries on their device and, if necessary, click on links to access the original information to obtain more details. 【0039】 As a concrete example, if a business person uses this system, their terminal will display summaries of economic news from a specified category every morning. The user reviews these summaries during their commute and clicks on links to the original articles for news that particularly interests them to investigate further. This process allows the user to efficiently gather necessary information within a limited time and use it to aid in business decision-making. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The server collects information from news sites and databases via the internet using RSS feeds and APIs. The collected information is stored in the database. 【0043】 Step 2: 【0044】 The server preprocesses the stored articles, removing unnecessary HTML tags and special characters from the text. The information is then divided into sentences, preparing it for analysis. 【0045】 Step 3: 【0046】 The server analyzes the article using natural language processing techniques. Specifically, this includes a process of extracting nouns from the text and identifying key phrases and important elements. 【0047】 Step 4: 【0048】 The server generates a summary based on the analysis results. The summary reflects the key points and presents the content concisely. 【0049】 Step 5: 【0050】 The server delivers the generated summary to the user's terminal. Information updates and delivery times are managed according to the user's settings. 【0051】 Step 6: 【0052】 The device displays summaries received through the user interface. The display is filtered by category and importance, prioritizing information of interest to the user. 【0053】 Step 7: 【0054】 If a user selects a summary they are interested in and wants to see more details, the device will present a link to the original information, and the user can access the original article by clicking the link. 【0055】 (Example 1) 【0056】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0057】 In today's world, where vast amounts of information exist on the internet, it is difficult for users to efficiently gather, summarize, and understand the information they need. This challenge is particularly pronounced in fields where the quality and quantity of information are increasing, hindering users from making accurate decisions within limited timeframes. 【0058】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0059】 In this invention, the server includes means for automatically collecting data from a data source via a communication network, processing means for analyzing the collected data and identifying key components, and means for inputting prompt sentences to a generating AI model and forming a summary. This enables the user to efficiently collect information and quickly obtain a high-quality summary. 【0060】 A "communication network" is the infrastructure used to send and receive information between multiple devices. 【0061】 A "data source" refers to a place or service that serves as the starting point for generating or providing information. 【0062】 "Data" refers to information that can be expressed as facts, numbers, strings of characters, or in other forms. 【0063】 "Means of collection" refers to the technology or equipment used to collect information according to certain standards or methods. 【0064】 "Means of analysis" refer to techniques for analyzing collected data and understanding its meaning and characteristics. 【0065】 "Generative means" refer to technologies and models for creating new information and data. 【0066】 A "generative AI model" is a model that uses artificial intelligence technology to generate, transform, or optimize data. 【0067】 A "prompt statement" is a command or question that is entered to give instructions to an AI model. 【0068】 "Equipment" refers to devices or equipment that have a specific function. 【0069】 A "summary" is a piece of writing or expression that shortens a large amount of information to convey its essence. 【0070】 A "user" is a person or group that operates or uses this system. 【0071】 This invention is a system for efficiently collecting, analyzing, summarizing, and providing information to users. First, the server connects to multiple data sources on the internet, specifically collecting the latest information periodically through RSS feeds and APIs. In this process, the server uses the Python requests library to retrieve the data. 【0072】 Next, the server uses natural language processing techniques to analyze the collected data. Specifically, it uses Python's nltk and spaCy libraries to analyze the grammatical structure and meaning of the text. This process identifies important elements and key phrases. 【0073】 Based on the analysis results, the server generates a summary using a generative AI model. Specifically, the summary is formed by inputting a prompt such as "Create a summary from the given text" into a generative AI model such as GPT (Generative Pre-trained Transformer). 【0074】 The generated summary is then delivered from the server to the device. The device displays the summary received via a RESTful API in its user interface, using frontend technologies such as React or Vue.js to allow the user to easily review the summary. 【0075】 As a concrete example, suppose a business person uses this system to receive a summary of economic news every morning. They can read the summary during their commute, click on links for news that interests them, and check the details in their browser. 【0076】 An example of a prompt might be: "Collect business-related articles and summarize them concisely. The summary should include the article's subject, key data, and relevant information." 【0077】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0078】 Step 1: 【0079】 The server collects data from specified data sources. This process involves accessing RSS feeds and API endpoints via the internet and retrieving data using the Python requests library. Inputs include data source URLs and API keys, while output is raw data in JSON or XML format. This collected data serves as foundational material for further analysis. 【0080】 Step 2: 【0081】 The server analyzes the collected data. Specifically, it uses Python's natural language processing libraries, nltk and spaCy, to analyze the grammatical structure and meaning of the text data. The input is the raw data obtained in step 1, and the output is analyzed data containing important key phrases and contextual information from the article. This analysis extracts important information from the data. 【0082】 Step 3: 【0083】 The server passes the analyzed data to a generative AI model to generate a summary. Here, a generative AI model such as GPT is used, and a prompt is input to create the summary. Specifically, a prompt such as "Create a summary based on the analyzed data" is input to the AI ​​model. The input consists of the analyzed data and the prompt, and the output is the summarized text. This summary is useful for conveying the essence of information in a short amount of time. 【0084】 Step 4: 【0085】 The server sends the generated summary to the terminal. At this stage, a RESTful API is used to send the summary data, and the terminal is prepared to receive and display it. The input is the generated summary, and the output is the summary text delivered to the user's terminal. This delivery allows the user to easily access the information. 【0086】 Step 5: 【0087】 The terminal displays the received summary in the user interface. Using specific frontend technologies such as React and Vue.js, the summary is provided to the user in a visually easy-to-understand format. The input is the summary received from the server, and the output is a displayed summary in a format viewable by the user. Based on this information, the user can retrieve detailed information as needed. 【0088】 (Application Example 1) 【0089】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0090】 In today's information society, users need to efficiently gather necessary information from a vast amount of data to make informed decisions. However, manually collecting and analyzing information from numerous sources is time-consuming and laborious. Furthermore, financial information, in particular, requires support for users' rapid decision-making, highlighting the high need for systems that summarize and efficiently present information. 【0091】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0092】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the collected information and identifying important elements, means for generating a summary of the information based on the identified important elements, means for delivering and presenting the generated summary to the user's terminal, and means for efficiently summarizing financial information and supporting decision-making. This enables users to quickly and efficiently obtain the necessary information from a vast amount of information and make decisions. 【0093】 The "Internet of Things" is a global computer network used to automatically retrieve data from various sources. 【0094】 An "information source" is a medium or platform that provides reliable information, such as news articles or databases. 【0095】 "Means of automatically collecting information" refers to technical functions that allow a server to acquire information without human intervention. 【0096】 "Natural language processing tools" are algorithms and methods for analyzing the grammar and meaning of collected information and identifying important elements. 【0097】 "Key elements" refer to points or main themes within the information that deserve particular attention. 【0098】 "Means of generating a summary" refers to the process of concisely summarizing the content of information based on identified key elements. 【0099】 A "user's terminal" is a digital device used to receive and display the generated summary. 【0100】 "Financial information" refers to important data and facts related to investments, markets, and economic trends. 【0101】 "Means of supporting decision-making" are functions that provide users with the information they need to make important decisions and help them make choices. 【0102】 The system implementing this invention consists of several main components. The server automatically collects financial information from information sources via the internet communication network. Specifically, it obtains news and economic data using publicly available RSS feeds, dedicated APIs, etc. 【0103】 Next, the server uses a programming language such as Python to execute natural language processing technologies like the Google Cloud Natural Language API. This process performs grammatical and semantic analysis on the collected information to identify key elements. Based on these identified elements, the server generates a summary of the information. This summary generation uses a text summarization algorithm designed to make the content easily understandable to the user. 【0104】 The generated summary is delivered to the user's device using a web framework such as Flask. On the user's device, an application built with a framework such as React Native displays the summary and provides the ability to filter the information as needed. Based on this displayed information, the user can use links to access relevant details and view additional content. 【0105】 As a concrete example, a user selects "Investment information on AI technology" as the category. Based on this query, the server gathers the latest relevant information and generates a summary, which can be reviewed quickly, such as during a morning commute. The generative AI model in this system plays a crucial role in the information summarization process and may use prompts like the following: 【0106】 "Summarize AI-related news and extract the key points." 【0107】 "Please provide a concise summary of information on promising technology companies as investment targets." 【0108】 This allows users to quickly and efficiently access the information they need from a vast amount of data, supporting them in making important decisions such as financial decisions. 【0109】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0110】 Step 1: 【0111】 The server automatically collects financial information from designated sources via the internet. Inputs are RSS feeds or API URLs for information collection, and output is raw data in XML or JSON format. This collection process is performed regularly and is automated. 【0112】 Step 2: 【0113】 The server uses Python to apply natural language processing techniques, such as the Google Cloud Natural Language API, to analyze the grammar and semantics of the collected information. The input is the raw data collected in step 1, and the output is parsed data containing important elements and key phrases. This analysis makes it possible to extract important information and identify relevant elements. 【0114】 Step 3: 【0115】 The server generates a summary of the information based on the identified key elements. This process utilizes a generative AI model and performs summarization using prompts. The input is the parsed data obtained in step 2, and the output is the summarized text. Specifically, the generative AI model is given the prompt "Summarize this text" for processing. 【0116】 Step 4: 【0117】 The server uses a web framework such as Flask to deliver the generated summary to the user's terminal. The input is the summary text generated in step 3, and the output is the data delivered to the terminal. The server sends the data using the appropriate encoding. 【0118】 Step 5: 【0119】 The device displays received summaries in a user interface and provides the ability to filter information according to category and importance. The input is summary text delivered from the server, and the output is a visualized information display for the user. An interface using React Native or similar technologies runs on the device. This allows users to quickly evaluate the necessary information and utilize links to obtain more detailed information. 【0120】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0121】 This invention is a system that automatically collects information from information sources, analyzes and summarizes the information using natural language processing, and further optimizes information delivery by recognizing the user's emotions. Specific embodiments of this system are described below. 【0122】 The server retrieves information from news sites and databases via the internet and stores it in the database. This ensures that the necessary information is always up-to-date. The server then uses natural language processing technology to analyze the retrieved information. The analysis involves understanding the grammar and meaning of the articles and identifying key points. 【0123】 Next, the server uses an emotion engine to recognize the user's emotional state. This emotion recognition infers the user's emotional response from real-time input on the user's device and helps adjust the information provided. 【0124】 Based on the user's emotions recognized by the emotion engine, the server adjusts the content of the summaries. For example, if the server detects that the user is stressed, it prioritizes providing summaries containing relaxing news or positive content. Conversely, if the server determines that the user is receptive to the information they are seeking, it includes more relevant details. These adjustments provide a more personalized user experience by delivering information that takes the user's emotions into consideration. 【0125】 As a concrete example, consider a scenario where a user uses this system during their morning commute. The user's device receives the latest news summaries and, through the emotion engine, recognizes that the user is expressing frustration with morning traffic. In this case, the server responds by displaying summaries that include positive news and interesting topics, thereby improving the user's mood and supporting a more comfortable information-gathering experience. 【0126】 Thus, this invention interactively and dynamically improves how information is received through information provision based on user emotions. 【0127】 The following describes the processing flow. 【0128】 Step 1: 【0129】 The server collects information from news sites and databases via the internet. This information is retrieved via RSS feeds and APIs and stored in a database. 【0130】 Step 2: 【0131】 The server preprocesses the collected information, preparing it to remove unnecessary HTML tags and special characters from the text. The information is divided into sentences and prepared for analysis. 【0132】 Step 3: 【0133】 The server uses natural language processing to analyze the pre-processed information. This analysis identifies important elements and key phrases from the article and extracts data to construct a summary. 【0134】 Step 4: 【0135】 The device utilizes an emotion engine to recognize the user's current emotional state based on data collected in real time from the user's input device. 【0136】 Step 5: 【0137】 The server receives output from the emotion engine and adjusts the content and focus of the summary according to the recognized user's emotions. For example, if the user is seeking relaxation, it will select and include relaxing news in the summary. 【0138】 Step 6: 【0139】 The server generates a refined summary and delivers it to the user's device, including links to the relevant original information. 【0140】 Step 7: 【0141】 The device displays summaries received by the user. The display is filtered based on category and importance, making it easier for the user to access information of interest. 【0142】 Step 8: 【0143】 Users can review the displayed summary and, if they wish to learn more, select the link to the original information provided by their device to retrieve the details. 【0144】 (Example 2) 【0145】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0146】 While systems already exist that collect information from news and databases and generate summaries, they alone cannot provide sufficiently personalized information to users. In particular, when information is provided without considering the user's emotional state, the information may not align with the user's interests or feelings. As a result, there is a problem of decreased user satisfaction. 【0147】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0148】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the information and identifying important elements, sentiment analysis means for recognizing the user's emotional state, and means for adjusting the information summary based on the recognized emotions. This enables the provision of personalized information based on the user's emotions. 【0149】 The "Internet communication network" refers to the network infrastructure used to send and receive digital data globally. 【0150】 "Information source" refers to a primary source that provides specific information, such as a news website or a database. 【0151】 "Means of automatically collecting information" refers to methods of obtaining data through programs without user intervention. 【0152】 "Natural language processing" refers to technologies that enable computers to understand and analyze human language. 【0153】 "Important elements" refer to data or points that deserve special attention during the information analysis process. 【0154】 "Methods for generating summaries" refer to methods for extracting essential information from a large amount of data and expressing it in a concise form. 【0155】 "User's emotional state" refers to the user's psychological state as obtained using emotion analysis. 【0156】 "Emotion analysis methods" refer to technologies that identify emotions from a user's facial expressions, voice, and other similar information. 【0157】 "Means of adjustment" refers to methods for changing the content or expression of information according to specific conditions. 【0158】 "Terminal" refers to a device used for displaying and operating information, and includes smartphones, personal computers, and other similar devices. 【0159】 This invention is a system that collects information via an internet communication network and analyzes it using natural language processing. By recognizing the user's emotions and optimizing the information provided based on those emotions, it delivers a personalized experience. 【0160】 The server is built using Python or Java (registered trademark) and automatically collects information from news sites and databases. It uses the Python requests library to make HTTP requests for information collection. The collected data is then analyzed using BeautifulSoup or Scrapy, and the results are stored in a database on the server. MySQL (registered trademark) and PostgreSQL are commonly used as databases. 【0161】 The server performs natural language processing (NLP) and uses libraries such as NLTK and spaCy to identify important elements of the information. Furthermore, techniques such as TF-IDF and the BERT model are used to improve the accuracy of summarizing key points. 【0162】 In parallel, the device recognizes the user's emotional state. This involves using the device's camera and microphone to capture facial expressions and voice tone in real time. Affectiva and emotion analysis APIs are used to analyze the user's current emotions (e.g., stress or relaxation). 【0163】 Consider an example where a user uses this system during their morning commute. The server collects the latest news and sends an analyzed summary to the user's device. If the device detects through sentiment analysis that the user is frustrated with traffic, the server provides a corresponding positive news summary. This improves the user's mood and allows them to receive information more comfortably. 【0164】 An example of a prompt using a generative AI model is: "Create a news summary to provide to a user who is feeling stressed during their morning commute." This prompt allows for the rapid delivery of information tailored to the user's situation. 【0165】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0166】 Step 1: 【0167】 The server collects information from news sites and databases. In this process, the server uses the Python requests library to send HTTP requests and retrieve HTML data from web pages. The input is the URL of the news site, and the output is the retrieved HTML data. Specifically, it accesses a specified list of URLs at regular intervals and caches the content. 【0168】 Step 2: 【0169】 The server analyzes the collected information. The server uses BeautifulSoup or Scrapy to parse the HTML data and extract important elements such as news titles and body text. In this case, the input is the HTML data obtained in step 1, and the output is structured text data. Specifically, it searches the DOM tree and extracts the necessary text nodes. 【0170】 Step 3: 【0171】 The server uses natural language processing techniques to analyze the extracted data. The server uses NLTK and spaCy to tag parts of speech and analyze the grammatical structure of the analyzed text. The input is the structured text obtained in step 2, and the output is data including grammatical structure. Specifically, a topic model of the text is constructed in preparation for summary generation. 【0172】 Step 4: 【0173】 The server generates a summary. The server uses TF-IDF and BERT models to extract important elements from the analyzed data and create a summary. The input is text data containing the grammatical structure obtained in step 3, and the output is the summarized text. Specifically, it calculates importance scores and selects the sentence with the highest score. 【0174】 Step 5: 【0175】 The device performs emotion recognition. The user's device uses its camera and microphone to collect the user's facial expressions and voice, and uses an emotion analysis API to determine emotions in real time. The input is the user's facial expressions and voice data, and the output is data on their emotional state. Specifically, the facial expression analysis software scans the user's facial expressions in real time and calculates their stress level. 【0176】 Step 6: 【0177】 The server adjusts the summary based on sentiment data. The server uses a generative AI model to provide information that takes sentiment data into account. The input is the summary generated in step 4 and the sentiment data obtained in step 5, and the output is the adjusted summary. Specifically, it changes the tone and level of detail of the information according to the user's emotional state. 【0178】 Step 7: 【0179】 The server delivers the adjusted summary to the user's device. The final input is the adjusted summary obtained in step 6, and the output is that it is displayed on the device. Specifically, the summary is sent to the device via the appropriate API, and the user is notified. 【0180】 (Application Example 2) 【0181】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0182】 In modern society, there is a demand for information that takes into account the emotional state of individual users. However, conventional systems lack the ability to optimize information based on user emotions, resulting in inefficient information delivery. In particular, there is a need for a system that can provide appropriate information to users who are experiencing stress or frustration. 【0183】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0184】 In this invention, the server includes means for automatically collecting information from a data source via the internet, means for processing the collected information and extracting important elements, means for generating an information summary based on the extracted important elements, means for recognizing the user's emotions and adjusting the summary according to their emotional state, and means for providing the user with the emotionally adjusted summary. This makes it possible to optimize information provision according to the user's unique emotional state. 【0185】 The "Internet" is an information and communication network in which computer networks are interconnected, and it is a technology that makes it possible to access information sources around the world. 【0186】 A "data source" is a place or system where information is stored, and serves as the starting point for information gathering. 【0187】 "Means of automatically collecting information" refers to methods or devices in which a program or device acquires and stores data without human intervention. 【0188】 "Linguistic analysis methods" refer to the process of understanding natural language using machines, and are technologies that analyze the structure of text and extract meaning. 【0189】 "Extracting key elements" is the process or task of identifying the parts of information that are deemed to have high value. 【0190】 "Means for generating information summaries" refers to methods or functions for organizing large amounts of information into a concise form and extracting and expressing only the essential points. 【0191】 "Recognizing a user's emotions" is the process of understanding their emotional state based on their facial expressions and behavior. 【0192】 "An emotion analysis method that adjusts summaries according to emotional states" is a technology that appropriately modifies the content of the information to be provided based on the recognized emotional state. 【0193】 "Means for providing users with emotion-based adjusted summaries" refers to a device or method for editing and presenting information that matches the user's emotions. 【0194】 The system implementing this invention enables the provision of information tailored to the user's emotional state in a consumer robot. The server automatically collects information from data sources via the internet. Information collection includes the use of cloud services via the robot's Wi-Fi communication function. After information collection, the server processes the collected information using language analysis means and extracts important elements. This analysis uses natural language processing software such as the Google Cloud Natural Language API. 【0195】 Next, the user's terminal, i.e., a consumer robot, uses emotion recognition sensors and cameras to analyze the user's facial expressions and voice to recognize their emotional state. This emotion analysis utilizes the Microsoft® Azure® Emotion API. After the user's emotional state is recognized, the server adjusts the summary content accordingly and generates emotion-based information. 【0196】 Ultimately, the server provides the user with a refined summary. The terminal displays the information on its screen or communicates it verbally through its speaker. For example, consider a scenario where a user speaks to a robot before leaving for work in the morning and requests to know the weather and news for the day. If the user's facial expression shows signs of fatigue, the system prioritizes presenting positive, uplifting news and helpful information. 【0197】 To enhance user interaction using a generative AI model, the following message is used as an example of a prompt: 【0198】 "How are you feeling today? We'll bring you news and information that might lift your spirits, even just a little. Tell us what you've been interested in lately." 【0199】 In this way, users can receive emotionally sensitive information in their daily lives. 【0200】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0201】 Step 1: 【0202】 The server collects information from news sites and databases via the internet. In this step, the collected information is entered into the server and stored in the database. The server regularly updates the information using the latest information retrieval algorithms, ensuring that it is always up-to-date. 【0203】 Step 2: 【0204】 The server analyzes the collected information using a natural language processing engine. The input is the news data collected in the previous step. The server uses the Google Cloud Natural Language API to analyze the grammar and semantics and identify important elements. As output, the server obtains element extraction results to pass on to the summarization generation process. 【0205】 Step 3: 【0206】 The device uses an emotion recognition sensor to recognize the user's emotions in real time. The input consists of the user's facial expressions and voice data. The device processes this data using the Microsoft Azure Emotion API and outputs the user's current emotional state. This output is used in a later step to optimize the information provided. 【0207】 Step 4: 【0208】 The server uses a summarization generation mechanism to generate a summary of the information based on the analyzed data. The input is a list of key elements obtained in step 2. The generated summary is output to the server as a basis for adjustment, taking into account the user's emotional state. 【0209】 Step 5: 【0210】 The server adjusts the summary generated based on the user's emotional state. The inputs are the emotional data from step 3 and the summary content from step 4. The server uses an emotional analysis algorithm to select the appropriate information from the summary and outputs it as the most suitable content for the user. 【0211】 Step 6: 【0212】 The terminal provides the user with an adjusted summary. The input is the adjusted summary received from the server. The terminal interacts with the user using prompts and conveys information visually or audibly. The output provides the user with emotionally sensitive information. 【0213】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0214】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0215】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0216】 [Second Embodiment] 【0217】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0218】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0219】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0220】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0221】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0222】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0223】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0224】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0225】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0226】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0227】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0228】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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". 【0229】 This invention is a system that automatically collects information from information sources, generates summaries, and provides them to users. Specific embodiments of the entire system are described below. 【0230】 The system starts when the server periodically retrieves information from sources via the internet. The information is obtained from reliable news sites and databases using RSS feeds and APIs. The server uses natural language processing techniques to analyze the collected information. Here, the information is analyzed through grammatical and semantic analysis to identify important elements and key phrases within the articles. 【0231】 Following the analysis, the server generates a concise summary based on the identified information. This summary is designed to include the subject matter, key data, and other relevant information, helping users understand the information quickly. 【0232】 The generated summaries are then delivered to the user's device. The device displays the received summaries in a user interface and is designed to allow the user to efficiently access information of interest by filtering them according to category and importance. Users can review the summaries on their device and, if necessary, click on links to access the original information to obtain more details. 【0233】 As a concrete example, if a business person uses this system, their terminal will display summaries of economic news from a specified category every morning. The user reviews these summaries during their commute and clicks on links to the original articles for news that particularly interests them to investigate further. This process allows the user to efficiently gather necessary information within a limited time and use it to aid in business decision-making. 【0234】 The following describes the processing flow. 【0235】 Step 1: 【0236】 The server collects information from news sites and databases via the internet using RSS feeds and APIs. The collected information is stored in the database. 【0237】 Step 2: 【0238】 The server preprocesses the stored articles, removing unnecessary HTML tags and special characters from the text. The information is then divided into sentences, preparing it for analysis. 【0239】 Step 3: 【0240】 The server analyzes the article using natural language processing techniques. Specifically, this includes a process of extracting nouns from the text and identifying key phrases and important elements. 【0241】 Step 4: 【0242】 The server generates a summary based on the analysis results. The summary reflects the key points and presents the content concisely. 【0243】 Step 5: 【0244】 The server delivers the generated summary to the user's terminal. Information updates and delivery times are managed according to the user's settings. 【0245】 Step 6: 【0246】 The device displays summaries received through the user interface. The display is filtered by category and importance, prioritizing information of interest to the user. 【0247】 Step 7: 【0248】 If a user selects a summary they are interested in and wants to see more details, the device will present a link to the original information, and the user can access the original article by clicking the link. 【0249】 (Example 1) 【0250】 Next, we will describe Example 1. 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." 【0251】 In today's world, where vast amounts of information exist on the internet, it is difficult for users to efficiently gather, summarize, and understand the information they need. This challenge is particularly pronounced in fields where the quality and quantity of information are increasing, hindering users from making accurate decisions within limited timeframes. 【0252】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0253】 In this invention, the server includes means for automatically collecting data from a data source via a communication network, processing means for analyzing the collected data and identifying key components, and means for inputting prompt sentences to a generating AI model and forming a summary. This enables the user to efficiently collect information and quickly obtain a high-quality summary. 【0254】 A "communication network" is the infrastructure used to send and receive information between multiple devices. 【0255】 A "data source" refers to a place or service that serves as the starting point for generating or providing information. 【0256】 "Data" refers to information that can be expressed as facts, numbers, strings of characters, or in other forms. 【0257】 "Means of collection" refers to the technology or equipment used to collect information according to certain standards or methods. 【0258】 "Means of analysis" refer to techniques for analyzing collected data and understanding its meaning and characteristics. 【0259】 "Generative means" refer to technologies and models for creating new information and data. 【0260】 A "generative AI model" is a model that uses artificial intelligence technology to generate, transform, or optimize data. 【0261】 A "prompt statement" is a command or question that is entered to give instructions to an AI model. 【0262】 "Equipment" refers to devices or equipment that have a specific function. 【0263】 A "summary" is a piece of writing or expression that shortens a large amount of information to convey its essence. 【0264】 A "user" is a person or group that operates or uses this system. 【0265】 This invention is a system for efficiently collecting, analyzing, summarizing, and providing information to users. First, the server connects to multiple data sources on the internet, specifically collecting the latest information periodically through RSS feeds and APIs. In this process, the server uses the Python requests library to retrieve the data. 【0266】 Next, the server uses natural language processing techniques to analyze the collected data. Specifically, it uses Python's nltk and spaCy libraries to analyze the grammatical structure and meaning of the text. This process identifies important elements and key phrases. 【0267】 Based on the analysis results, the server generates a summary using a generative AI model. Specifically, the summary is formed by inputting a prompt such as "Create a summary from the given text" into a generative AI model such as GPT (Generative Pre-trained Transformer). 【0268】 The generated summary is then delivered from the server to the device. The device displays the summary received via a RESTful API in its user interface, using frontend technologies such as React or Vue.js to allow the user to easily review the summary. 【0269】 As a concrete example, suppose a business person uses this system to receive a summary of economic news every morning. They can read the summary during their commute, click on links for news that interests them, and check the details in their browser. 【0270】 An example of a prompt might be: "Collect business-related articles and summarize them concisely. The summary should include the article's subject, key data, and relevant information." 【0271】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0272】 Step 1: 【0273】 The server collects data from specified data sources. This process involves accessing RSS feeds and API endpoints via the internet and retrieving data using the Python requests library. Inputs include data source URLs and API keys, while output is raw data in JSON or XML format. This collected data serves as foundational material for further analysis. 【0274】 Step 2: 【0275】 The server analyzes the collected data. Specifically, it uses Python's natural language processing libraries, nltk and spaCy, to analyze the grammatical structure and meaning of the text data. The input is the raw data obtained in step 1, and the output is analyzed data containing important key phrases and contextual information from the article. This analysis extracts important information from the data. 【0276】 Step 3: 【0277】 The server passes the analyzed data to a generative AI model to generate a summary. Here, a generative AI model such as GPT is used, and a prompt is input to create the summary. Specifically, a prompt such as "Create a summary based on the analyzed data" is input to the AI ​​model. The input consists of the analyzed data and the prompt, and the output is the summarized text. This summary is useful for conveying the essence of information in a short amount of time. 【0278】 Step 4: 【0279】 The server sends the generated summary to the terminal. At this stage, the RESTful API is used to send the summary data, and the terminal is prepared to receive and display it. The input is the generated summary, and the output is the summary text distributed to the user terminal. With this distribution, the user can easily check the information. 【0280】 Step 5: 【0281】 The terminal displays the received summary on the user interface. As a specific front-end technology, React or Vue.js is used to provide the summary to the user in a visually understandable form. The input is the summary received from the server, and the output is the displayed summary in a form that can be viewed by the user. Based on this information, the user can obtain detailed information as needed. 【0282】 (Application Example 1) 【0283】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0284】 In modern information-based society, users need to efficiently collect the necessary information from a vast amount of information and make decisions. However, manually collecting and analyzing information from many information sources requires time and effort. In particular, information related to finance is required to support users' rapid decision-making, and there is a high need for a system that summarizes and efficiently presents information. 【0285】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0286】 In this invention, the server includes means for automatically collecting information from an information source via an Internet communication network, natural language processing means for analyzing the collected information to identify important elements, means for generating a summary of the information based on the identified important elements, means for distributing and presenting the generated summary to the user's terminal, and means for efficiently summarizing financial-related information to support decision-making. As a result, the user can quickly and efficiently obtain the necessary information from a vast amount of information and make judgments. 【0287】 The "Internet communication network" is a global computer network used to automatically acquire data from an information source. 【0288】 The "information source" is a medium or platform that provides reliable information such as news and databases. 【0289】 The "means for automatically collecting information" is a technical function for the server to acquire information without human intervention. 【0290】 The "natural language processing means" is an algorithm or method for analyzing the grammar and meaning of the collected information to identify important elements. 【0291】 The "important elements" refer to the points or main themes that should be particularly noted in the information. 【0292】 The "means for generating a summary" is a process of concisely summarizing the content of the information based on the identified important elements. 【0293】 The "user's terminal" is a digital device for receiving and displaying the generated summary. 【0294】 The "financial-related information" is important data and facts related to investments, markets, economic trends, etc. 【0295】 "Means of supporting decision-making" are functions that provide users with the information they need to make important decisions and help them make choices. 【0296】 The system implementing this invention consists of several main components. The server automatically collects financial information from information sources via the internet communication network. Specifically, it obtains news and economic data using publicly available RSS feeds, dedicated APIs, etc. 【0297】 Next, the server uses a programming language such as Python to execute natural language processing technologies like the Google Cloud Natural Language API. This process performs grammatical and semantic analysis on the collected information to identify key elements. Based on these identified elements, the server generates a summary of the information. This summary generation uses a text summarization algorithm designed to make the content easily understandable to the user. 【0298】 The generated summary is delivered to the user's device using a web framework such as Flask. On the user's device, an application built with a framework such as React Native displays the summary and provides the ability to filter the information as needed. Based on this displayed information, the user can use links to access relevant details and view additional content. 【0299】 As a concrete example, a user selects "Investment information on AI technology" as the category. Based on this query, the server gathers the latest relevant information and generates a summary, which can be reviewed quickly, such as during a morning commute. The generative AI model in this system plays a crucial role in the information summarization process and may use prompts like the following: 【0300】 "Summarize AI-related news and extract the key points." 【0301】 Please briefly summarize the information of promising technology companies as investment targets. 【0302】 This enables users to quickly and efficiently access the necessary information from a vast amount of information, thus supporting important decision-making such as in finance. 【0303】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0304】 Step 1: 【0305】 The server automatically collects financial-related information from a predetermined information source via the Internet communication network. The input is an RSS feed or an API URL for information collection, and the output is raw data in XML or JSON format. This collection operation is performed regularly and is automated. 【0306】 Step 2: 【0307】 The server applies natural language processing technologies such as the Google Cloud Natural Language API using Python to analyze the grammar and meaning of the collected information. The input is the raw data collected in Step 1, and the output is the analyzed data containing important elements and key phrases. This analysis makes it possible to extract important information and identify related elements. 【0308】 Step 3: 【0309】 The server generates a summary of the information based on the identified important elements. In this process, a generative AI model is utilized to perform a summarization process using a prompt sentence. The input is the analyzed data obtained in Step 2, and the output is the summarized text. Specifically, a prompt sentence "Please summarize this text" is given to the generative AI model for processing. 【0310】 Step 4: 【0311】 The server uses a web framework such as Flask to deliver the generated summary to the user's terminal. The input is the summary text generated in step 3, and the output is the data delivered to the terminal. The server sends the data using the appropriate encoding. 【0312】 Step 5: 【0313】 The device displays received summaries in a user interface and provides the ability to filter information according to category and importance. The input is summary text delivered from the server, and the output is a visualized information display for the user. An interface using React Native or similar technologies runs on the device. This allows users to quickly evaluate the necessary information and utilize links to obtain more detailed information. 【0314】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0315】 This invention is a system that automatically collects information from information sources, analyzes and summarizes the information using natural language processing, and further optimizes information delivery by recognizing the user's emotions. Specific embodiments of this system are described below. 【0316】 The server retrieves information from news sites and databases via the internet and stores it in the database. This ensures that the necessary information is always up-to-date. The server then uses natural language processing technology to analyze the retrieved information. The analysis involves understanding the grammar and meaning of the articles and identifying key points. 【0317】 Next, the server uses an emotion engine to recognize the user's emotional state. This emotion recognition infers the user's emotional response from real-time input on the user's device and helps adjust the information provided. 【0318】 Based on the user's emotions recognized by the emotion engine, the server adjusts the content of the summaries. For example, if the server detects that the user is stressed, it prioritizes providing summaries containing relaxing news or positive content. Conversely, if the server determines that the user is receptive to the information they are seeking, it includes more relevant details. These adjustments provide a more personalized user experience by delivering information that takes the user's emotions into consideration. 【0319】 As a concrete example, consider a scenario where a user uses this system during their morning commute. The user's device receives the latest news summaries and, through the emotion engine, recognizes that the user is expressing frustration with morning traffic. In this case, the server responds by displaying summaries that include positive news and interesting topics, thereby improving the user's mood and supporting a more comfortable information-gathering experience. 【0320】 Thus, this invention interactively and dynamically improves how information is received through information provision based on user emotions. 【0321】 The following describes the processing flow. 【0322】 Step 1: 【0323】 The server collects information from news sites and databases via the internet. This information is retrieved via RSS feeds and APIs and stored in a database. 【0324】 Step 2: 【0325】 The server preprocesses the collected information, preparing it to remove unnecessary HTML tags and special characters from the text. The information is divided into sentences and prepared for analysis. 【0326】 Step 3: 【0327】 The server uses natural language processing to analyze the pre-processed information. This analysis identifies important elements and key phrases from the article and extracts data to construct a summary. 【0328】 Step 4: 【0329】 The device utilizes an emotion engine to recognize the user's current emotional state based on data collected in real time from the user's input device. 【0330】 Step 5: 【0331】 The server receives output from the emotion engine and adjusts the content and focus of the summary according to the recognized user's emotions. For example, if the user is seeking relaxation, it will select and include relaxing news in the summary. 【0332】 Step 6: 【0333】 The server generates a refined summary and delivers it to the user's device, including links to the relevant original information. 【0334】 Step 7: 【0335】 The device displays summaries received by the user. The display is filtered based on category and importance, making it easier for the user to access information of interest. 【0336】 Step 8: 【0337】 Users can review the displayed summary and, if they wish to learn more, select the link to the original information provided by their device to retrieve the details. 【0338】 (Example 2) 【0339】 Next, we will describe Example 2. 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". 【0340】 While systems already exist that collect information from news and databases and generate summaries, they alone cannot provide sufficiently personalized information to users. In particular, when information is provided without considering the user's emotional state, the information may not align with the user's interests or feelings. As a result, there is a problem of decreased user satisfaction. 【0341】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0342】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the information and identifying important elements, sentiment analysis means for recognizing the user's emotional state, and means for adjusting the information summary based on the recognized emotions. This enables the provision of personalized information based on the user's emotions. 【0343】 The "Internet communication network" refers to the network infrastructure used to send and receive digital data globally. 【0344】 "Information source" refers to a primary source that provides specific information, such as a news website or a database. 【0345】 "Means of automatically collecting information" refers to methods of obtaining data through programs without user intervention. 【0346】 "Natural language processing" refers to technologies that enable computers to understand and analyze human language. 【0347】 "Important elements" refer to data or points that deserve special attention during the information analysis process. 【0348】 "Methods for generating summaries" refer to methods for extracting essential information from a large amount of data and expressing it in a concise form. 【0349】 "User's emotional state" refers to the user's psychological state as obtained using emotion analysis. 【0350】 "Emotion analysis methods" refer to technologies that identify emotions from a user's facial expressions, voice, and other similar information. 【0351】 "Means of adjustment" refers to methods for changing the content or expression of information according to specific conditions. 【0352】 "Terminal" refers to a device used for displaying and operating information, and includes smartphones, personal computers, and other similar devices. 【0353】 This invention is a system that collects information via an internet communication network and analyzes it using natural language processing. By recognizing the user's emotions and optimizing the information provided based on those emotions, it delivers a personalized experience. 【0354】 The server is built using Python or Java and automatically collects information from news sites and databases. It uses the Python requests library to make HTTP requests for data collection. The collected data is then analyzed using BeautifulSoup or Scrapy, and the results are stored in a database on the server. MySQL and PostgreSQL are commonly used databases. 【0355】 The server performs natural language processing (NLP) and uses libraries such as NLTK and spaCy to identify important elements of the information. Furthermore, techniques such as TF-IDF and the BERT model are used to improve the accuracy of summarizing key points. 【0356】 In parallel, the device recognizes the user's emotional state. This involves using the device's camera and microphone to capture facial expressions and voice tone in real time. Affectiva and emotion analysis APIs are used to analyze the user's current emotions (e.g., stress or relaxation). 【0357】 Consider an example where a user uses this system during their morning commute. The server collects the latest news and sends an analyzed summary to the user's device. If the device detects through sentiment analysis that the user is frustrated with traffic, the server provides a corresponding positive news summary. This improves the user's mood and allows them to receive information more comfortably. 【0358】 An example of a prompt using a generative AI model is: "Create a news summary to provide to a user who is feeling stressed during their morning commute." This prompt allows for the rapid delivery of information tailored to the user's situation. 【0359】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0360】 Step 1: 【0361】 The server collects information from news sites and databases. In this process, the server uses the Python requests library to send HTTP requests and retrieve HTML data from web pages. The input is the URL of the news site, and the output is the retrieved HTML data. Specifically, it accesses a specified list of URLs at regular intervals and caches the content. 【0362】 Step 2: 【0363】 The server analyzes the collected information. The server uses BeautifulSoup or Scrapy to parse the HTML data and extract important elements such as news titles and body text. In this case, the input is the HTML data obtained in step 1, and the output is structured text data. Specifically, it searches the DOM tree and extracts the necessary text nodes. 【0364】 Step 3: 【0365】 The server uses natural language processing techniques to analyze the extracted data. The server uses NLTK and spaCy to tag parts of speech and analyze the grammatical structure of the analyzed text. The input is the structured text obtained in step 2, and the output is data including grammatical structure. Specifically, a topic model of the text is constructed in preparation for summary generation. 【0366】 Step 4: 【0367】 The server generates a summary. The server uses TF-IDF and BERT models to extract important elements from the analyzed data and create a summary. The input is text data containing the grammatical structure obtained in step 3, and the output is the summarized text. Specifically, it calculates importance scores and selects the sentence with the highest score. 【0368】 Step 5: 【0369】 The device performs emotion recognition. The user's device uses its camera and microphone to collect the user's facial expressions and voice, and uses an emotion analysis API to determine emotions in real time. The input is the user's facial expressions and voice data, and the output is data on their emotional state. Specifically, the facial expression analysis software scans the user's facial expressions in real time and calculates their stress level. 【0370】 Step 6: 【0371】 The server adjusts the summary based on sentiment data. The server uses a generative AI model to provide information that takes sentiment data into account. The input is the summary generated in step 4 and the sentiment data obtained in step 5, and the output is the adjusted summary. Specifically, it changes the tone and level of detail of the information according to the user's emotional state. 【0372】 Step 7: 【0373】 The server delivers the adjusted summary to the user's device. The final input is the adjusted summary obtained in step 6, and the output is that it is displayed on the device. Specifically, the summary is sent to the device via the appropriate API, and the user is notified. 【0374】 (Application Example 2) 【0375】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0376】 In modern society, there is a demand for information that takes into account the emotional state of individual users. However, conventional systems lack the ability to optimize information based on user emotions, resulting in inefficient information delivery. In particular, there is a need for a system that can provide appropriate information to users who are experiencing stress or frustration. 【0377】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0378】 In this invention, the server includes means for automatically collecting information from a data source via the internet, means for processing the collected information and extracting important elements, means for generating an information summary based on the extracted important elements, means for recognizing the user's emotions and adjusting the summary according to their emotional state, and means for providing the user with the emotionally adjusted summary. This makes it possible to optimize information provision according to the user's unique emotional state. 【0379】 The "Internet" is an information and communication network in which computer networks are interconnected, and it is a technology that makes it possible to access information sources around the world. 【0380】 A "data source" is a place or system where information is stored, and serves as the starting point for information gathering. 【0381】 "Means of automatically collecting information" refers to methods or devices in which a program or device acquires and stores data without human intervention. 【0382】 "Linguistic analysis methods" refer to the process of understanding natural language using machines, and are technologies that analyze the structure of text and extract meaning. 【0383】 "Extracting key elements" is the process or task of identifying the parts of information that are deemed to have high value. 【0384】 "Means for generating information summaries" refers to methods or functions for organizing large amounts of information into a concise form and extracting and expressing only the essential points. 【0385】 "Recognizing a user's emotions" is the process of understanding their emotional state based on their facial expressions and behavior. 【0386】 "An emotion analysis method that adjusts summaries according to emotional states" is a technology that appropriately modifies the content of the information to be provided based on the recognized emotional state. 【0387】 "Means for providing users with emotion-based adjusted summaries" refers to a device or method for editing and presenting information that matches the user's emotions. 【0388】 The system implementing this invention enables the provision of information tailored to the user's emotional state in a consumer robot. The server automatically collects information from data sources via the internet. Information collection includes the use of cloud services via the robot's Wi-Fi communication function. After information collection, the server processes the collected information using language analysis means and extracts important elements. This analysis uses natural language processing software such as the Google Cloud Natural Language API. 【0389】 Next, the user's device, i.e., a consumer robot, uses emotion recognition sensors and cameras to analyze the user's facial expressions and voice to recognize their emotional state. The Microsoft Azure Emotion API is used for this emotion analysis. After the user's emotional state is recognized, the server adjusts the summary content according to that state and generates emotion-based information. 【0390】 Ultimately, the server provides the user with a refined summary. The terminal displays the information on its screen or communicates it verbally through its speaker. For example, consider a scenario where a user speaks to a robot before leaving for work in the morning and requests to know the weather and news for the day. If the user's facial expression shows signs of fatigue, the system prioritizes presenting positive, uplifting news and helpful information. 【0391】 To enhance user interaction using a generative AI model, the following message is used as an example of a prompt: 【0392】 "How are you feeling today? We'll bring you news and information that might lift your spirits, even just a little. Tell us what you've been interested in lately." 【0393】 In this way, users can receive emotionally sensitive information in their daily lives. 【0394】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0395】 Step 1: 【0396】 The server collects information from news sites and databases via the internet. In this step, the collected information is entered into the server and stored in the database. The server regularly updates the information using the latest information retrieval algorithms, ensuring that it is always up-to-date. 【0397】 Step 2: 【0398】 The server analyzes the collected information using a natural language processing engine. The input is the news data collected in the previous step. The server uses the Google Cloud Natural Language API to analyze the grammar and semantics and identify important elements. As output, the server obtains element extraction results to pass on to the summarization generation process. 【0399】 Step 3: 【0400】 The device uses an emotion recognition sensor to recognize the user's emotions in real time. The input consists of the user's facial expressions and voice data. The device processes this data using the Microsoft Azure Emotion API and outputs the user's current emotional state. This output is used in a later step to optimize the information provided. 【0401】 Step 4: 【0402】 The server uses a summarization generation mechanism to generate a summary of the information based on the analyzed data. The input is a list of key elements obtained in step 2. The generated summary is output to the server as a basis for adjustment, taking into account the user's emotional state. 【0403】 Step 5: 【0404】 The server adjusts the summary generated based on the user's emotional state. The inputs are the emotional data from step 3 and the summary content from step 4. The server uses an emotional analysis algorithm to select the appropriate information from the summary and outputs it as the most suitable content for the user. 【0405】 Step 6: 【0406】 The terminal provides the user with an adjusted summary. The input is the adjusted summary received from the server. The terminal interacts with the user using prompts and conveys information visually or audibly. The output provides the user with emotionally sensitive information. 【0407】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0408】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0409】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0410】 [Third Embodiment] 【0411】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0412】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0413】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0414】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0415】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0416】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0417】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0418】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0419】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0420】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0421】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0422】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0423】 This invention is a system that automatically collects information from information sources, generates summaries, and provides them to users. Specific embodiments of the entire system are described below. 【0424】 The system starts when the server periodically retrieves information from sources via the internet. The information is obtained from reliable news sites and databases using RSS feeds and APIs. The server uses natural language processing techniques to analyze the collected information. Here, the information is analyzed through grammatical and semantic analysis to identify important elements and key phrases within the articles. 【0425】 Following the analysis, the server generates a concise summary based on the identified information. This summary is designed to include the subject matter, key data, and other relevant information, helping users understand the information quickly. 【0426】 The generated summaries are then delivered to the user's device. The device displays the received summaries in a user interface and is designed to allow the user to efficiently access information of interest by filtering them according to category and importance. Users can review the summaries on their device and, if necessary, click on links to access the original information to obtain more details. 【0427】 As a concrete example, if a business person uses this system, their terminal will display summaries of economic news from a specified category every morning. The user reviews these summaries during their commute and clicks on links to the original articles for news that particularly interests them to investigate further. This process allows the user to efficiently gather necessary information within a limited time and use it to aid in business decision-making. 【0428】 The following describes the processing flow. 【0429】 Step 1: 【0430】 The server collects information from news sites and databases via the internet using RSS feeds and APIs. The collected information is stored in the database. 【0431】 Step 2: 【0432】 The server preprocesses the stored articles, removing unnecessary HTML tags and special characters from the text. The information is then divided into sentences, preparing it for analysis. 【0433】 Step 3: 【0434】 The server analyzes the article using natural language processing techniques. Specifically, this includes a process of extracting nouns from the text and identifying key phrases and important elements. 【0435】 Step 4: 【0436】 The server generates a summary based on the analysis results. The summary reflects the key points and presents the content concisely. 【0437】 Step 5: 【0438】 The server delivers the generated summary to the user's terminal. Information updates and delivery times are managed according to the user's settings. 【0439】 Step 6: 【0440】 The device displays summaries received through the user interface. The display is filtered by category and importance, prioritizing information of interest to the user. 【0441】 Step 7: 【0442】 If a user selects a summary they are interested in and wants to see more details, the device will present a link to the original information, and the user can access the original article by clicking the link. 【0443】 (Example 1) 【0444】 Next, we will describe Example 1. 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." 【0445】 In today's world, where vast amounts of information exist on the internet, it is difficult for users to efficiently gather, summarize, and understand the information they need. This challenge is particularly pronounced in fields where the quality and quantity of information are increasing, hindering users from making accurate decisions within limited timeframes. 【0446】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0447】 In this invention, the server includes means for automatically collecting data from a data source via a communication network, processing means for analyzing the collected data and identifying key components, and means for inputting prompt sentences to a generating AI model and forming a summary. This enables the user to efficiently collect information and quickly obtain a high-quality summary. 【0448】 A "communication network" is the infrastructure used to send and receive information between multiple devices. 【0449】 A "data source" refers to a place or service that serves as the starting point for generating or providing information. 【0450】 "Data" refers to information that can be expressed as facts, numbers, strings of characters, or in other forms. 【0451】 "Means of collection" refers to the technology or equipment used to collect information according to certain standards or methods. 【0452】 "Means of analysis" refer to techniques for analyzing collected data and understanding its meaning and characteristics. 【0453】 "Generative means" refer to technologies and models for creating new information and data. 【0454】 A "generative AI model" is a model that uses artificial intelligence technology to generate, transform, or optimize data. 【0455】 A "prompt statement" is a command or question that is entered to give instructions to an AI model. 【0456】 "Equipment" refers to devices or equipment that have a specific function. 【0457】 A "summary" is a piece of writing or expression that shortens a large amount of information to convey its essence. 【0458】 A "user" is a person or group that operates or uses this system. 【0459】 This invention is a system for efficiently collecting, analyzing, summarizing, and providing information to users. First, the server connects to multiple data sources on the internet, specifically collecting the latest information periodically through RSS feeds and APIs. In this process, the server uses the Python requests library to retrieve the data. 【0460】 Next, the server uses natural language processing techniques to analyze the collected data. Specifically, it uses Python's nltk and spaCy libraries to analyze the grammatical structure and meaning of the text. This process identifies important elements and key phrases. 【0461】 Based on the analysis results, the server generates a summary using a generative AI model. Specifically, the summary is formed by inputting a prompt such as "Create a summary from the given text" into a generative AI model such as GPT (Generative Pre-trained Transformer). 【0462】 The generated summary is then delivered from the server to the device. The device displays the summary received via a RESTful API in its user interface, using frontend technologies such as React or Vue.js to allow the user to easily review the summary. 【0463】 As a concrete example, suppose a business person uses this system to receive a summary of economic news every morning. They can read the summary during their commute, click on links for news that interests them, and check the details in their browser. 【0464】 An example of a prompt might be: "Collect business-related articles and summarize them concisely. The summary should include the article's subject, key data, and relevant information." 【0465】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0466】 Step 1: 【0467】 The server collects data from specified data sources. This process involves accessing RSS feeds and API endpoints via the internet and retrieving data using the Python requests library. Inputs include data source URLs and API keys, while output is raw data in JSON or XML format. This collected data serves as foundational material for further analysis. 【0468】 Step 2: 【0469】 The server analyzes the collected data. Specifically, it uses Python's natural language processing libraries, nltk and spaCy, to analyze the grammatical structure and meaning of the text data. The input is the raw data obtained in step 1, and the output is analyzed data containing important key phrases and contextual information from the article. This analysis extracts important information from the data. 【0470】 Step 3: 【0471】 The server passes the analyzed data to a generative AI model to generate a summary. Here, a generative AI model such as GPT is used, and a prompt is input to create the summary. Specifically, a prompt such as "Create a summary based on the analyzed data" is input to the AI ​​model. The input consists of the analyzed data and the prompt, and the output is the summarized text. This summary is useful for conveying the essence of information in a short amount of time. 【0472】 Step 4: 【0473】 The server sends the generated summary to the terminal. At this stage, a RESTful API is used to send the summary data, and the terminal is prepared to receive and display it. The input is the generated summary, and the output is the summary text delivered to the user's terminal. This delivery allows the user to easily access the information. 【0474】 Step 5: 【0475】 The terminal displays the received summary in the user interface. Using specific frontend technologies such as React and Vue.js, the summary is provided to the user in a visually easy-to-understand format. The input is the summary received from the server, and the output is a displayed summary in a format viewable by the user. Based on this information, the user can retrieve detailed information as needed. 【0476】 (Application Example 1) 【0477】 Next, we will explain Application Example 1. In the following explanation, 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." 【0478】 In today's information society, users need to efficiently gather necessary information from a vast amount of data to make informed decisions. However, manually collecting and analyzing information from numerous sources is time-consuming and laborious. Furthermore, financial information, in particular, requires support for users' rapid decision-making, highlighting the high need for systems that summarize and efficiently present information. 【0479】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0480】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the collected information and identifying important elements, means for generating a summary of the information based on the identified important elements, means for delivering and presenting the generated summary to the user's terminal, and means for efficiently summarizing financial information and supporting decision-making. This enables users to quickly and efficiently obtain the necessary information from a vast amount of information and make decisions. 【0481】 The "Internet of Things" is a global computer network used to automatically retrieve data from various sources. 【0482】 An "information source" is a medium or platform that provides reliable information, such as news articles or databases. 【0483】 "Means of automatically collecting information" refers to technical functions that allow a server to acquire information without human intervention. 【0484】 "Natural language processing tools" are algorithms and methods for analyzing the grammar and meaning of collected information and identifying important elements. 【0485】 "Key elements" refer to points or main themes within the information that deserve particular attention. 【0486】 "Means of generating a summary" refers to the process of concisely summarizing the content of information based on identified key elements. 【0487】 A "user's terminal" is a digital device used to receive and display the generated summary. 【0488】 "Financial information" refers to important data and facts related to investments, markets, and economic trends. 【0489】 "Means of supporting decision-making" are functions that provide users with the information they need to make important decisions and help them make choices. 【0490】 The system implementing this invention consists of several main components. The server automatically collects financial information from information sources via the internet communication network. Specifically, it obtains news and economic data using publicly available RSS feeds, dedicated APIs, etc. 【0491】 Next, the server uses a programming language such as Python to execute natural language processing technologies like the Google Cloud Natural Language API. This process performs grammatical and semantic analysis on the collected information to identify key elements. Based on these identified elements, the server generates a summary of the information. This summary generation uses a text summarization algorithm designed to make the content easily understandable to the user. 【0492】 The generated summary is delivered to the user's device using a web framework such as Flask. On the user's device, an application built with a framework such as React Native displays the summary and provides the ability to filter the information as needed. Based on this displayed information, the user can use links to access relevant details and view additional content. 【0493】 As a concrete example, a user selects "Investment information on AI technology" as the category. Based on this query, the server gathers the latest relevant information and generates a summary, which can be reviewed quickly, such as during a morning commute. The generative AI model in this system plays a crucial role in the information summarization process and may use prompts like the following: 【0494】 "Summarize AI-related news and extract the key points." 【0495】 "Please provide a concise summary of information on promising technology companies as investment targets." 【0496】 This allows users to quickly and efficiently access the information they need from a vast amount of data, supporting them in making important decisions such as financial decisions. 【0497】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0498】 Step 1: 【0499】 The server automatically collects financial information from designated sources via the internet. Inputs are RSS feeds or API URLs for information collection, and output is raw data in XML or JSON format. This collection process is performed regularly and is automated. 【0500】 Step 2: 【0501】 The server uses Python to apply natural language processing techniques, such as the Google Cloud Natural Language API, to analyze the grammar and semantics of the collected information. The input is the raw data collected in step 1, and the output is parsed data containing important elements and key phrases. This analysis makes it possible to extract important information and identify relevant elements. 【0502】 Step 3: 【0503】 The server generates a summary of the information based on the identified key elements. This process utilizes a generative AI model and performs summarization using prompts. The input is the parsed data obtained in step 2, and the output is the summarized text. Specifically, the generative AI model is given the prompt "Summarize this text" for processing. 【0504】 Step 4: 【0505】 The server uses a web framework such as Flask to deliver the generated summary to the user's terminal. The input is the summary text generated in step 3, and the output is the data delivered to the terminal. The server sends the data using the appropriate encoding. 【0506】 Step 5: 【0507】 The device displays received summaries in a user interface and provides the ability to filter information according to category and importance. The input is summary text delivered from the server, and the output is a visualized information display for the user. An interface using React Native or similar technologies runs on the device. This allows users to quickly evaluate the necessary information and utilize links to obtain more detailed information. 【0508】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0509】 This invention is a system that automatically collects information from information sources, analyzes and summarizes the information using natural language processing, and further optimizes information delivery by recognizing the user's emotions. Specific embodiments of this system are described below. 【0510】 The server retrieves information from news sites and databases via the internet and stores it in the database. This ensures that the necessary information is always up-to-date. The server then uses natural language processing technology to analyze the retrieved information. The analysis involves understanding the grammar and meaning of the articles and identifying key points. 【0511】 Next, the server uses an emotion engine to recognize the user's emotional state. This emotion recognition infers the user's emotional response from real-time input on the user's device and helps adjust the information provided. 【0512】 Based on the user's emotions recognized by the emotion engine, the server adjusts the content of the summaries. For example, if the server detects that the user is stressed, it prioritizes providing summaries containing relaxing news or positive content. Conversely, if the server determines that the user is receptive to the information they are seeking, it includes more relevant details. These adjustments provide a more personalized user experience by delivering information that takes the user's emotions into consideration. 【0513】 As a concrete example, consider a scenario where a user uses this system during their morning commute. The user's device receives the latest news summaries and, through the emotion engine, recognizes that the user is expressing frustration with morning traffic. In this case, the server responds by displaying summaries that include positive news and interesting topics, thereby improving the user's mood and supporting a more comfortable information-gathering experience. 【0514】 Thus, this invention interactively and dynamically improves how information is received through information provision based on user emotions. 【0515】 The following describes the processing flow. 【0516】 Step 1: 【0517】 The server collects information from news sites and databases via the internet. This information is retrieved via RSS feeds and APIs and stored in a database. 【0518】 Step 2: 【0519】 The server preprocesses the collected information, preparing it to remove unnecessary HTML tags and special characters from the text. The information is divided into sentences and prepared for analysis. 【0520】 Step 3: 【0521】 The server uses natural language processing to analyze the pre-processed information. This analysis identifies important elements and key phrases from the article and extracts data to construct a summary. 【0522】 Step 4: 【0523】 The device utilizes an emotion engine to recognize the user's current emotional state based on data collected in real time from the user's input device. 【0524】 Step 5: 【0525】 The server receives output from the emotion engine and adjusts the content and focus of the summary according to the recognized user's emotions. For example, if the user is seeking relaxation, it will select and include relaxing news in the summary. 【0526】 Step 6: 【0527】 The server generates a refined summary and delivers it to the user's device, including links to the relevant original information. 【0528】 Step 7: 【0529】 The device displays summaries received by the user. The display is filtered based on category and importance, making it easier for the user to access information of interest. 【0530】 Step 8: 【0531】 Users can review the displayed summary and, if they wish to learn more, select the link to the original information provided by their device to retrieve the details. 【0532】 (Example 2) 【0533】 Next, we will describe Example 2. 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." 【0534】 While systems already exist that collect information from news and databases and generate summaries, they alone cannot provide sufficiently personalized information to users. In particular, when information is provided without considering the user's emotional state, the information may not align with the user's interests or feelings. As a result, there is a problem of decreased user satisfaction. 【0535】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0536】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the information and identifying important elements, sentiment analysis means for recognizing the user's emotional state, and means for adjusting the information summary based on the recognized emotions. This enables the provision of personalized information based on the user's emotions. 【0537】 The "Internet communication network" refers to the network infrastructure used to send and receive digital data globally. 【0538】 "Information source" refers to a primary source that provides specific information, such as a news website or a database. 【0539】 "Means of automatically collecting information" refers to methods of obtaining data through programs without user intervention. 【0540】 "Natural language processing" refers to technologies that enable computers to understand and analyze human language. 【0541】 "Important elements" refer to data or points that deserve special attention during the information analysis process. 【0542】 "Methods for generating summaries" refer to methods for extracting essential information from a large amount of data and expressing it in a concise form. 【0543】 "User's emotional state" refers to the user's psychological state as obtained using emotion analysis. 【0544】 "Emotion analysis methods" refer to technologies that identify emotions from a user's facial expressions, voice, and other similar information. 【0545】 "Means of adjustment" refers to methods for changing the content or expression of information according to specific conditions. 【0546】 "Terminal" refers to a device used for displaying and operating information, and includes smartphones, personal computers, and other similar devices. 【0547】 This invention is a system that collects information via an internet communication network and analyzes it using natural language processing. By recognizing the user's emotions and optimizing the information provided based on those emotions, it delivers a personalized experience. 【0548】 The server is built using Python or Java and automatically collects information from news sites and databases. It uses the Python requests library to make HTTP requests for data collection. The collected data is then analyzed using BeautifulSoup or Scrapy, and the results are stored in a database on the server. MySQL and PostgreSQL are commonly used databases. 【0549】 The server performs natural language processing (NLP) and uses libraries such as NLTK and spaCy to identify important elements of the information. Furthermore, techniques such as TF-IDF and the BERT model are used to improve the accuracy of summarizing key points. 【0550】 In parallel, the device recognizes the user's emotional state. This involves using the device's camera and microphone to capture facial expressions and voice tone in real time. Affectiva and emotion analysis APIs are used to analyze the user's current emotions (e.g., stress or relaxation). 【0551】 Consider an example where a user uses this system during their morning commute. The server collects the latest news and sends an analyzed summary to the user's device. If the device detects through sentiment analysis that the user is frustrated with traffic, the server provides a corresponding positive news summary. This improves the user's mood and allows them to receive information more comfortably. 【0552】 An example of a prompt using a generative AI model is: "Create a news summary to provide to a user who is feeling stressed during their morning commute." This prompt allows for the rapid delivery of information tailored to the user's situation. 【0553】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0554】 Step 1: 【0555】 The server collects information from news sites and databases. In this process, the server uses the Python requests library to send HTTP requests and retrieve HTML data from web pages. The input is the URL of the news site, and the output is the retrieved HTML data. Specifically, it accesses a specified list of URLs at regular intervals and caches the content. 【0556】 Step 2: 【0557】 The server analyzes the collected information. The server uses BeautifulSoup or Scrapy to parse the HTML data and extract important elements such as news titles and body text. In this case, the input is the HTML data obtained in step 1, and the output is structured text data. Specifically, it searches the DOM tree and extracts the necessary text nodes. 【0558】 Step 3: 【0559】 The server uses natural language processing techniques to analyze the extracted data. The server uses NLTK and spaCy to tag parts of speech and analyze the grammatical structure of the analyzed text. The input is the structured text obtained in step 2, and the output is data including grammatical structure. Specifically, a topic model of the text is constructed in preparation for summary generation. 【0560】 Step 4: 【0561】 The server generates a summary. The server uses TF-IDF and BERT models to extract important elements from the analyzed data and create a summary. The input is text data containing the grammatical structure obtained in step 3, and the output is the summarized text. Specifically, it calculates importance scores and selects the sentence with the highest score. 【0562】 Step 5: 【0563】 The device performs emotion recognition. The user's device uses its camera and microphone to collect the user's facial expressions and voice, and uses an emotion analysis API to determine emotions in real time. The input is the user's facial expressions and voice data, and the output is data on their emotional state. Specifically, the facial expression analysis software scans the user's facial expressions in real time and calculates their stress level. 【0564】 Step 6: 【0565】 The server adjusts the summary based on sentiment data. The server uses a generative AI model to provide information that takes sentiment data into account. The input is the summary generated in step 4 and the sentiment data obtained in step 5, and the output is the adjusted summary. Specifically, it changes the tone and level of detail of the information according to the user's emotional state. 【0566】 Step 7: 【0567】 The server delivers the adjusted summary to the user's device. The final input is the adjusted summary obtained in step 6, and the output is that it is displayed on the device. Specifically, the summary is sent to the device via the appropriate API, and the user is notified. 【0568】 (Application Example 2) 【0569】 Next, we will explain application example 2. In the following explanation, 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." 【0570】 In modern society, there is a demand for information that takes into account the emotional state of individual users. However, conventional systems lack the ability to optimize information based on user emotions, resulting in inefficient information delivery. In particular, there is a need for a system that can provide appropriate information to users who are experiencing stress or frustration. 【0571】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0572】 In this invention, the server includes means for automatically collecting information from a data source via the internet, means for processing the collected information and extracting important elements, means for generating an information summary based on the extracted important elements, means for recognizing the user's emotions and adjusting the summary according to their emotional state, and means for providing the user with the emotionally adjusted summary. This makes it possible to optimize information provision according to the user's unique emotional state. 【0573】 The "Internet" is an information and communication network in which computer networks are interconnected, and it is a technology that makes it possible to access information sources around the world. 【0574】 A "data source" is a place or system where information is stored, and serves as the starting point for information gathering. 【0575】 "Means of automatically collecting information" refers to methods or devices in which a program or device acquires and stores data without human intervention. 【0576】 "Linguistic analysis methods" refer to the process of understanding natural language using machines, and are technologies that analyze the structure of text and extract meaning. 【0577】 "Extracting key elements" is the process or task of identifying the parts of information that are deemed to have high value. 【0578】 "Means for generating information summaries" refers to methods or functions for organizing large amounts of information into a concise form and extracting and expressing only the essential points. 【0579】 "Recognizing a user's emotions" is the process of understanding their emotional state based on their facial expressions and behavior. 【0580】 "An emotion analysis method that adjusts summaries according to emotional states" is a technology that appropriately modifies the content of the information to be provided based on the recognized emotional state. 【0581】 "Means for providing users with emotion-based adjusted summaries" refers to a device or method for editing and presenting information that matches the user's emotions. 【0582】 The system implementing this invention enables the provision of information tailored to the user's emotional state in a consumer robot. The server automatically collects information from data sources via the internet. Information collection includes the use of cloud services via the robot's Wi-Fi communication function. After information collection, the server processes the collected information using language analysis means and extracts important elements. This analysis uses natural language processing software such as the Google Cloud Natural Language API. 【0583】 Next, the user's device, i.e., a consumer robot, uses emotion recognition sensors and cameras to analyze the user's facial expressions and voice to recognize their emotional state. The Microsoft Azure Emotion API is used for this emotion analysis. After the user's emotional state is recognized, the server adjusts the summary content according to that state and generates emotion-based information. 【0584】 Ultimately, the server provides the user with a refined summary. The terminal displays the information on its screen or communicates it verbally through its speaker. For example, consider a scenario where a user speaks to a robot before leaving for work in the morning and requests to know the weather and news for the day. If the user's facial expression shows signs of fatigue, the system prioritizes presenting positive, uplifting news and helpful information. 【0585】 To enhance user interaction using a generative AI model, the following message is used as an example of a prompt: 【0586】 "How are you feeling today? We'll bring you news and information that might lift your spirits, even just a little. Tell us what you've been interested in lately." 【0587】 In this way, users can receive emotionally sensitive information in their daily lives. 【0588】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0589】 Step 1: 【0590】 The server collects information from news sites and databases via the internet. In this step, the collected information is entered into the server and stored in the database. The server regularly updates the information using the latest information retrieval algorithms, ensuring that it is always up-to-date. 【0591】 Step 2: 【0592】 The server analyzes the collected information using a natural language processing engine. The input is the news data collected in the previous step. The server uses the Google Cloud Natural Language API to analyze the grammar and semantics and identify important elements. As output, the server obtains element extraction results to pass on to the summarization generation process. 【0593】 Step 3: 【0594】 The device uses an emotion recognition sensor to recognize the user's emotions in real time. The input consists of the user's facial expressions and voice data. The device processes this data using the Microsoft Azure Emotion API and outputs the user's current emotional state. This output is used in a later step to optimize the information provided. 【0595】 Step 4: 【0596】 The server uses a summarization generation mechanism to generate a summary of the information based on the analyzed data. The input is a list of key elements obtained in step 2. The generated summary is output to the server as a basis for adjustment, taking into account the user's emotional state. 【0597】 Step 5: 【0598】 The server adjusts the summary generated based on the user's emotional state. The inputs are the emotional data from step 3 and the summary content from step 4. The server uses an emotional analysis algorithm to select the appropriate information from the summary and outputs it as the most suitable content for the user. 【0599】 Step 6: 【0600】 The terminal provides the user with an adjusted summary. The input is the adjusted summary received from the server. The terminal interacts with the user using prompts and conveys information visually or audibly. The output provides the user with emotionally sensitive information. 【0601】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0602】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0603】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0604】 [Fourth Embodiment] 【0605】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0606】 As shown in Figure 7, the 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. 【0607】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0608】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0609】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0610】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0611】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0612】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0613】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0614】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0615】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0616】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0617】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0618】 This invention is a system that automatically collects information from information sources, generates summaries, and provides them to users. Specific embodiments of the entire system are described below. 【0619】 The system starts when the server periodically retrieves information from sources via the internet. The information is obtained from reliable news sites and databases using RSS feeds and APIs. The server uses natural language processing techniques to analyze the collected information. Here, the information is analyzed through grammatical and semantic analysis to identify important elements and key phrases within the articles. 【0620】 Following the analysis, the server generates a concise summary based on the identified information. This summary is designed to include the subject matter, key data, and other relevant information, helping users understand the information quickly. 【0621】 The generated summaries are then delivered to the user's device. The device displays the received summaries in a user interface and is designed to allow the user to efficiently access information of interest by filtering them according to category and importance. Users can review the summaries on their device and, if necessary, click on links to access the original information to obtain more details. 【0622】 As a concrete example, if a business person uses this system, their terminal will display summaries of economic news from a specified category every morning. The user reviews these summaries during their commute and clicks on links to the original articles for news that particularly interests them to investigate further. This process allows the user to efficiently gather necessary information within a limited time and use it to aid in business decision-making. 【0623】 The following describes the processing flow. 【0624】 Step 1: 【0625】 The server collects information from news sites and databases via the internet using RSS feeds and APIs. The collected information is stored in the database. 【0626】 Step 2: 【0627】 The server preprocesses the stored articles, removing unnecessary HTML tags and special characters from the text. The information is then divided into sentences, preparing it for analysis. 【0628】 Step 3: 【0629】 The server analyzes the article using natural language processing techniques. Specifically, this includes a process of extracting nouns from the text and identifying key phrases and important elements. 【0630】 Step 4: 【0631】 The server generates a summary based on the analysis results. The summary reflects the key points and presents the content concisely. 【0632】 Step 5: 【0633】 The server delivers the generated summary to the user's terminal. Information updates and delivery times are managed according to the user's settings. 【0634】 Step 6: 【0635】 The device displays summaries received through the user interface. The display is filtered by category and importance, prioritizing information of interest to the user. 【0636】 Step 7: 【0637】 If a user selects a summary they are interested in and wants to see more details, the device will present a link to the original information, and the user can access the original article by clicking the link. 【0638】 (Example 1) 【0639】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0640】 In today's world, where vast amounts of information exist on the internet, it is difficult for users to efficiently gather, summarize, and understand the information they need. This challenge is particularly pronounced in fields where the quality and quantity of information are increasing, hindering users from making accurate decisions within limited timeframes. 【0641】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0642】 In this invention, the server includes means for automatically collecting data from a data source via a communication network, processing means for analyzing the collected data and identifying key components, and means for inputting prompt sentences to a generating AI model and forming a summary. This enables the user to efficiently collect information and quickly obtain a high-quality summary. 【0643】 A "communication network" is the infrastructure used to send and receive information between multiple devices. 【0644】 A "data source" refers to a place or service that serves as the starting point for generating or providing information. 【0645】 "Data" refers to information that can be expressed as facts, numbers, strings of characters, or in other forms. 【0646】 "Means of collection" refers to the technology or equipment used to collect information according to certain standards or methods. 【0647】 "Means of analysis" refer to techniques for analyzing collected data and understanding its meaning and characteristics. 【0648】 "Generative means" refer to technologies and models for creating new information and data. 【0649】 A "generative AI model" is a model that uses artificial intelligence technology to generate, transform, or optimize data. 【0650】 A "prompt statement" is a command or question that is entered to give instructions to an AI model. 【0651】 "Equipment" refers to devices or equipment that have a specific function. 【0652】 A "summary" is a piece of writing or expression that shortens a large amount of information to convey its essence. 【0653】 A "user" is a person or group that operates or uses this system. 【0654】 This invention is a system for efficiently collecting, analyzing, summarizing, and providing information to users. First, the server connects to multiple data sources on the internet, specifically collecting the latest information periodically through RSS feeds and APIs. In this process, the server uses the Python requests library to retrieve the data. 【0655】 Next, the server uses natural language processing techniques to analyze the collected data. Specifically, it uses Python's nltk and spaCy libraries to analyze the grammatical structure and meaning of the text. This process identifies important elements and key phrases. 【0656】 Based on the analysis results, the server generates a summary using a generative AI model. Specifically, the summary is formed by inputting a prompt such as "Create a summary from the given text" into a generative AI model such as GPT (Generative Pre-trained Transformer). 【0657】 The generated summary is then delivered from the server to the device. The device displays the summary received via a RESTful API in its user interface, using frontend technologies such as React or Vue.js to allow the user to easily review the summary. 【0658】 As a concrete example, suppose a business person uses this system to receive a summary of economic news every morning. They can read the summary during their commute, click on links for news that interests them, and check the details in their browser. 【0659】 An example of a prompt might be: "Collect business-related articles and summarize them concisely. The summary should include the article's subject, key data, and relevant information." 【0660】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0661】 Step 1: 【0662】 The server collects data from specified data sources. This process involves accessing RSS feeds and API endpoints via the internet and retrieving data using the Python requests library. Inputs include data source URLs and API keys, while output is raw data in JSON or XML format. This collected data serves as foundational material for further analysis. 【0663】 Step 2: 【0664】 The server analyzes the collected data. Specifically, it uses Python's natural language processing libraries, nltk and spaCy, to analyze the grammatical structure and meaning of the text data. The input is the raw data obtained in step 1, and the output is analyzed data containing important key phrases and contextual information from the article. This analysis extracts important information from the data. 【0665】 Step 3: 【0666】 The server passes the analyzed data to a generative AI model to generate a summary. Here, a generative AI model such as GPT is used, and a prompt is input to create the summary. Specifically, a prompt such as "Create a summary based on the analyzed data" is input to the AI ​​model. The input consists of the analyzed data and the prompt, and the output is the summarized text. This summary is useful for conveying the essence of information in a short amount of time. 【0667】 Step 4: 【0668】 The server sends the generated summary to the terminal. At this stage, a RESTful API is used to send the summary data, and the terminal is prepared to receive and display it. The input is the generated summary, and the output is the summary text delivered to the user's terminal. This delivery allows the user to easily access the information. 【0669】 Step 5: 【0670】 The terminal displays the received summary in the user interface. Using specific frontend technologies such as React and Vue.js, the summary is provided to the user in a visually easy-to-understand format. The input is the summary received from the server, and the output is a displayed summary in a format viewable by the user. Based on this information, the user can retrieve detailed information as needed. 【0671】 (Application Example 1) 【0672】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0673】 In today's information society, users need to efficiently gather necessary information from a vast amount of data to make informed decisions. However, manually collecting and analyzing information from numerous sources is time-consuming and laborious. Furthermore, financial information, in particular, requires support for users' rapid decision-making, highlighting the high need for systems that summarize and efficiently present information. 【0674】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0675】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the collected information and identifying important elements, means for generating a summary of the information based on the identified important elements, means for delivering and presenting the generated summary to the user's terminal, and means for efficiently summarizing financial information and supporting decision-making. This enables users to quickly and efficiently obtain the necessary information from a vast amount of information and make decisions. 【0676】 The "Internet of Things" is a global computer network used to automatically retrieve data from various sources. 【0677】 An "information source" is a medium or platform that provides reliable information, such as news articles or databases. 【0678】 "Means of automatically collecting information" refers to technical functions that allow a server to acquire information without human intervention. 【0679】 "Natural language processing tools" are algorithms and methods for analyzing the grammar and meaning of collected information and identifying important elements. 【0680】 "Key elements" refer to points or main themes within the information that deserve particular attention. 【0681】 "Means of generating a summary" refers to the process of concisely summarizing the content of information based on identified key elements. 【0682】 A "user's terminal" is a digital device used to receive and display the generated summary. 【0683】 "Financial information" refers to important data and facts related to investments, markets, and economic trends. 【0684】 "Means of supporting decision-making" are functions that provide users with the information they need to make important decisions and help them make choices. 【0685】 The system implementing this invention consists of several main components. The server automatically collects financial information from information sources via the internet communication network. Specifically, it obtains news and economic data using publicly available RSS feeds, dedicated APIs, etc. 【0686】 Next, the server uses a programming language such as Python to execute natural language processing technologies like the Google Cloud Natural Language API. This process performs grammatical and semantic analysis on the collected information to identify key elements. Based on these identified elements, the server generates a summary of the information. This summary generation uses a text summarization algorithm designed to make the content easily understandable to the user. 【0687】 The generated summary is delivered to the user's device using a web framework such as Flask. On the user's device, an application built with a framework such as React Native displays the summary and provides the ability to filter the information as needed. Based on this displayed information, the user can use links to access relevant details and view additional content. 【0688】 As a concrete example, a user selects "Investment information on AI technology" as the category. Based on this query, the server gathers the latest relevant information and generates a summary, which can be reviewed quickly, such as during a morning commute. The generative AI model in this system plays a crucial role in the information summarization process and may use prompts like the following: 【0689】 "Summarize AI-related news and extract the key points." 【0690】 "Please provide a concise summary of information on promising technology companies as investment targets." 【0691】 This allows users to quickly and efficiently access the information they need from a vast amount of data, supporting them in making important decisions such as financial decisions. 【0692】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0693】 Step 1: 【0694】 The server automatically collects financial information from designated sources via the internet. Inputs are RSS feeds or API URLs for information collection, and output is raw data in XML or JSON format. This collection process is performed regularly and is automated. 【0695】 Step 2: 【0696】 The server uses Python to apply natural language processing techniques, such as the Google Cloud Natural Language API, to analyze the grammar and semantics of the collected information. The input is the raw data collected in step 1, and the output is parsed data containing important elements and key phrases. This analysis makes it possible to extract important information and identify relevant elements. 【0697】 Step 3: 【0698】 The server generates a summary of the information based on the identified key elements. This process utilizes a generative AI model and performs summarization using prompts. The input is the parsed data obtained in step 2, and the output is the summarized text. Specifically, the generative AI model is given the prompt "Summarize this text" for processing. 【0699】 Step 4: 【0700】 The server uses a web framework such as Flask to deliver the generated summary to the user's terminal. The input is the summary text generated in step 3, and the output is the data delivered to the terminal. The server sends the data using the appropriate encoding. 【0701】 Step 5: 【0702】 The device displays received summaries in a user interface and provides the ability to filter information according to category and importance. The input is summary text delivered from the server, and the output is a visualized information display for the user. An interface using React Native or similar technologies runs on the device. This allows users to quickly evaluate the necessary information and utilize links to obtain more detailed information. 【0703】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0704】 This invention is a system that automatically collects information from information sources, analyzes and summarizes the information using natural language processing, and further optimizes information delivery by recognizing the user's emotions. Specific embodiments of this system are described below. 【0705】 The server retrieves information from news sites and databases via the internet and stores it in the database. This ensures that the necessary information is always up-to-date. The server then uses natural language processing technology to analyze the retrieved information. The analysis involves understanding the grammar and meaning of the articles and identifying key points. 【0706】 Next, the server uses an emotion engine to recognize the user's emotional state. This emotion recognition infers the user's emotional response from real-time input on the user's device and helps adjust the information provided. 【0707】 Based on the user's emotions recognized by the emotion engine, the server adjusts the content of the summaries. For example, if the server detects that the user is stressed, it prioritizes providing summaries containing relaxing news or positive content. Conversely, if the server determines that the user is receptive to the information they are seeking, it includes more relevant details. These adjustments provide a more personalized user experience by delivering information that takes the user's emotions into consideration. 【0708】 As a concrete example, consider a scenario where a user uses this system during their morning commute. The user's device receives the latest news summaries and, through the emotion engine, recognizes that the user is expressing frustration with morning traffic. In this case, the server responds by displaying summaries that include positive news and interesting topics, thereby improving the user's mood and supporting a more comfortable information-gathering experience. 【0709】 Thus, this invention interactively and dynamically improves how information is received through information provision based on user emotions. 【0710】 The following describes the processing flow. 【0711】 Step 1: 【0712】 The server collects information from news sites and databases via the internet. This information is retrieved via RSS feeds and APIs and stored in a database. 【0713】 Step 2: 【0714】 The server preprocesses the collected information, preparing it to remove unnecessary HTML tags and special characters from the text. The information is divided into sentences and prepared for analysis. 【0715】 Step 3: 【0716】 The server uses natural language processing to analyze the pre-processed information. This analysis identifies important elements and key phrases from the article and extracts data to construct a summary. 【0717】 Step 4: 【0718】 The device utilizes an emotion engine to recognize the user's current emotional state based on data collected in real time from the user's input device. 【0719】 Step 5: 【0720】 The server receives output from the emotion engine and adjusts the content and focus of the summary according to the recognized user's emotions. For example, if the user is seeking relaxation, it will select and include relaxing news in the summary. 【0721】 Step 6: 【0722】 The server generates a refined summary and delivers it to the user's device, including links to the relevant original information. 【0723】 Step 7: 【0724】 The device displays summaries received by the user. The display is filtered based on category and importance, making it easier for the user to access information of interest. 【0725】 Step 8: 【0726】 Users can review the displayed summary and, if they wish to learn more, select the link to the original information provided by their device to retrieve the details. 【0727】 (Example 2) 【0728】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0729】 While systems already exist that collect information from news and databases and generate summaries, they alone cannot provide sufficiently personalized information to users. In particular, when information is provided without considering the user's emotional state, the information may not align with the user's interests or feelings. As a result, there is a problem of decreased user satisfaction. 【0730】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0731】 In this invention, the server includes means for automatically collecting information from information sources via an internet communication network, natural language processing means for analyzing the information and identifying important elements, sentiment analysis means for recognizing the user's emotional state, and means for adjusting the information summary based on the recognized emotions. This enables the provision of personalized information based on the user's emotions. 【0732】 The "Internet communication network" refers to the network infrastructure used to send and receive digital data globally. 【0733】 "Information source" refers to a primary source that provides specific information, such as a news website or a database. 【0734】 "Means of automatically collecting information" refers to methods of obtaining data through programs without user intervention. 【0735】 "Natural language processing" refers to technologies that enable computers to understand and analyze human language. 【0736】 "Important elements" refer to data or points that deserve special attention during the information analysis process. 【0737】 "Methods for generating summaries" refer to methods for extracting essential information from a large amount of data and expressing it in a concise form. 【0738】 "User's emotional state" refers to the user's psychological state as obtained using emotion analysis. 【0739】 "Emotion analysis methods" refer to technologies that identify emotions from a user's facial expressions, voice, and other similar information. 【0740】 "Means of adjustment" refers to methods for changing the content or expression of information according to specific conditions. 【0741】 "Terminal" refers to a device used for displaying and operating information, and includes smartphones, personal computers, and other similar devices. 【0742】 This invention is a system that collects information via an internet communication network and analyzes it using natural language processing. By recognizing the user's emotions and optimizing the information provided based on those emotions, it delivers a personalized experience. 【0743】 The server is built using Python or Java and automatically collects information from news sites and databases. It uses the Python requests library to make HTTP requests for data collection. The collected data is then analyzed using BeautifulSoup or Scrapy, and the results are stored in a database on the server. MySQL and PostgreSQL are commonly used databases. 【0744】 The server performs natural language processing (NLP) and uses libraries such as NLTK and spaCy to identify important elements of the information. Furthermore, techniques such as TF-IDF and the BERT model are used to improve the accuracy of summarizing key points. 【0745】 In parallel, the device recognizes the user's emotional state. This involves using the device's camera and microphone to capture facial expressions and voice tone in real time. Affectiva and emotion analysis APIs are used to analyze the user's current emotions (e.g., stress or relaxation). 【0746】 Consider an example where a user uses this system during their morning commute. The server collects the latest news and sends an analyzed summary to the user's device. If the device detects through sentiment analysis that the user is frustrated with traffic, the server provides a corresponding positive news summary. This improves the user's mood and allows them to receive information more comfortably. 【0747】 An example of a prompt using a generative AI model is: "Create a news summary to provide to a user who is feeling stressed during their morning commute." This prompt allows for the rapid delivery of information tailored to the user's situation. 【0748】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0749】 Step 1: 【0750】 The server collects information from news sites and databases. In this process, the server uses the Python requests library to send HTTP requests and retrieve HTML data from web pages. The input is the URL of the news site, and the output is the retrieved HTML data. Specifically, it accesses a specified list of URLs at regular intervals and caches the content. 【0751】 Step 2: 【0752】 The server analyzes the collected information. The server uses BeautifulSoup or Scrapy to parse the HTML data and extract important elements such as news titles and body text. In this case, the input is the HTML data obtained in step 1, and the output is structured text data. Specifically, it searches the DOM tree and extracts the necessary text nodes. 【0753】 Step 3: 【0754】 The server uses natural language processing techniques to analyze the extracted data. The server uses NLTK and spaCy to tag parts of speech and analyze the grammatical structure of the analyzed text. The input is the structured text obtained in step 2, and the output is data including grammatical structure. Specifically, a topic model of the text is constructed in preparation for summary generation. 【0755】 Step 4: 【0756】 The server generates a summary. The server uses TF-IDF and BERT models to extract important elements from the analyzed data and create a summary. The input is text data containing the grammatical structure obtained in step 3, and the output is the summarized text. Specifically, it calculates importance scores and selects the sentence with the highest score. 【0757】 Step 5: 【0758】 The device performs emotion recognition. The user's device uses its camera and microphone to collect the user's facial expressions and voice, and uses an emotion analysis API to determine emotions in real time. The input is the user's facial expressions and voice data, and the output is data on their emotional state. Specifically, the facial expression analysis software scans the user's facial expressions in real time and calculates their stress level. 【0759】 Step 6: 【0760】 The server adjusts the summary based on sentiment data. The server uses a generative AI model to provide information that takes sentiment data into account. The input is the summary generated in step 4 and the sentiment data obtained in step 5, and the output is the adjusted summary. Specifically, it changes the tone and level of detail of the information according to the user's emotional state. 【0761】 Step 7: 【0762】 The server delivers the adjusted summary to the user's device. The final input is the adjusted summary obtained in step 6, and the output is that it is displayed on the device. Specifically, the summary is sent to the device via the appropriate API, and the user is notified. 【0763】 (Application Example 2) 【0764】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0765】 In modern society, there is a demand for information that takes into account the emotional state of individual users. However, conventional systems lack the ability to optimize information based on user emotions, resulting in inefficient information delivery. In particular, there is a need for a system that can provide appropriate information to users who are experiencing stress or frustration. 【0766】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0767】 In this invention, the server includes means for automatically collecting information from a data source via the internet, means for processing the collected information and extracting important elements, means for generating an information summary based on the extracted important elements, means for recognizing the user's emotions and adjusting the summary according to their emotional state, and means for providing the user with the emotionally adjusted summary. This makes it possible to optimize information provision according to the user's unique emotional state. 【0768】 The "Internet" is an information and communication network in which computer networks are interconnected, and it is a technology that makes it possible to access information sources around the world. 【0769】 A "data source" is a place or system where information is stored, and serves as the starting point for information gathering. 【0770】 "Means of automatically collecting information" refers to methods or devices in which a program or device acquires and stores data without human intervention. 【0771】 "Linguistic analysis methods" refer to the process of understanding natural language using machines, and are technologies that analyze the structure of text and extract meaning. 【0772】 "Extracting key elements" is the process or task of identifying the parts of information that are deemed to have high value. 【0773】 "Means for generating information summaries" refers to methods or functions for organizing large amounts of information into a concise form and extracting and expressing only the essential points. 【0774】 "Recognizing a user's emotions" is the process of understanding their emotional state based on their facial expressions and behavior. 【0775】 "An emotion analysis method that adjusts summaries according to emotional states" is a technology that appropriately modifies the content of the information to be provided based on the recognized emotional state. 【0776】 "Means for providing users with emotion-based adjusted summaries" refers to a device or method for editing and presenting information that matches the user's emotions. 【0777】 The system implementing this invention enables the provision of information tailored to the user's emotional state in a consumer robot. The server automatically collects information from data sources via the internet. Information collection includes the use of cloud services via the robot's Wi-Fi communication function. After information collection, the server processes the collected information using language analysis means and extracts important elements. This analysis uses natural language processing software such as the Google Cloud Natural Language API. 【0778】 Next, the user's device, i.e., a consumer robot, uses emotion recognition sensors and cameras to analyze the user's facial expressions and voice to recognize their emotional state. The Microsoft Azure Emotion API is used for this emotion analysis. After the user's emotional state is recognized, the server adjusts the summary content according to that state and generates emotion-based information. 【0779】 Ultimately, the server provides the user with a refined summary. The terminal displays the information on its screen or communicates it verbally through its speaker. For example, consider a scenario where a user speaks to a robot before leaving for work in the morning and requests to know the weather and news for the day. If the user's facial expression shows signs of fatigue, the system prioritizes presenting positive, uplifting news and helpful information. 【0780】 To enhance user interaction using a generative AI model, the following message is used as an example of a prompt: 【0781】 "How are you feeling today? We'll bring you news and information that might lift your spirits, even just a little. Tell us what you've been interested in lately." 【0782】 In this way, users can receive emotionally sensitive information in their daily lives. 【0783】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0784】 Step 1: 【0785】 The server collects information from news sites and databases via the internet. In this step, the collected information is entered into the server and stored in the database. The server regularly updates the information using the latest information retrieval algorithms, ensuring that it is always up-to-date. 【0786】 Step 2: 【0787】 The server analyzes the collected information using a natural language processing engine. The input is the news data collected in the previous step. The server uses the Google Cloud Natural Language API to analyze the grammar and semantics and identify important elements. As output, the server obtains element extraction results to pass on to the summarization generation process. 【0788】 Step 3: 【0789】 The device uses an emotion recognition sensor to recognize the user's emotions in real time. The input consists of the user's facial expressions and voice data. The device processes this data using the Microsoft Azure Emotion API and outputs the user's current emotional state. This output is used in a later step to optimize the information provided. 【0790】 Step 4: 【0791】 The server uses a summarization generation mechanism to generate a summary of the information based on the analyzed data. The input is a list of key elements obtained in step 2. The generated summary is output to the server as a basis for adjustment, taking into account the user's emotional state. 【0792】 Step 5: 【0793】 The server adjusts the summary generated based on the user's emotional state. The inputs are the emotional data from step 3 and the summary content from step 4. The server uses an emotional analysis algorithm to select the appropriate information from the summary and outputs it as the most suitable content for the user. 【0794】 Step 6: 【0795】 The terminal provides the user with an adjusted summary. The input is the adjusted summary received from the server. The terminal interacts with the user using prompts and conveys information visually or audibly. The output provides the user with emotionally sensitive information. 【0796】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0797】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0798】 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0799】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0800】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0801】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0802】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0803】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0804】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0805】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0806】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0807】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0808】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0809】 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. 【0810】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0811】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0812】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0813】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0814】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0815】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0816】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0817】 The following is further disclosed regarding the embodiments described above. 【0818】 (Claim 1) 【0819】 A means of automatically collecting information from information sources via the Internet communication network, 【0820】 A natural language processing method for analyzing collected information and identifying important elements, 【0821】 Means for generating a summary of information based on identified key elements, 【0822】 A means of delivering the generated summary to the user's terminal, 【0823】 A system that includes this. 【0824】 (Claim 2) 【0825】 The system according to claim 1, which filters information based on categories of information specified by the user and generates a summary. 【0826】 (Claim 3) 【0827】 The system according to claim 1, which provides a link to the original information related to the generated summary. 【0828】 "Example 1" 【0829】 (Claim 1) 【0830】 A means of automatically collecting data from a data source via a communication network, 【0831】 Processing means for analyzing collected data and identifying critical components, 【0832】 A generation means for generating a data summary based on identified critical components, 【0833】 A means for inputting prompt sentences into a generative AI model and forming a summary, 【0834】 A means of delivering the generated summary to the user's device, 【0835】 A system that includes this. 【0836】 (Claim 2) 【0837】 The system according to claim 1, which filters data and generates a summary based on a data classification specified by the user. 【0838】 (Claim 3) 【0839】 The system according to claim 1, which provides a reference link to the original data related to the generated summary. 【0840】 "Application Example 1" 【0841】 (Claim 1) 【0842】 A means of automatically collecting information from information sources via the Internet communication network, 【0843】 A natural language processing method for analyzing collected information and identifying important elements, 【0844】 Means for generating a summary of information based on identified key elements, 【0845】 A means of delivering and presenting a generated summary to the user's device, 【0846】 A means to efficiently summarize financial information and support decision-making, 【0847】 A system that includes this. 【0848】 (Claim 2) 【0849】 The system according to claim 1, which filters information based on categories of information specified by the user and generates a summary. 【0850】 (Claim 3) 【0851】 The system according to claim 1, which provides a link to the original information related to the generated summary. 【0852】 "Example 2 of combining an emotion engine" 【0853】 (Claim 1) 【0854】 A means of automatically collecting information from information sources via the Internet communication network, 【0855】 A natural language processing method for analyzing collected information and identifying important elements, 【0856】 Means for generating a summary of information based on identified key elements, 【0857】 An emotion analysis method for recognizing the emotional state of the user, 【0858】 A means of adjusting the summarization of information based on recognized emotions, 【0859】 A means of delivering the generated summary to the user's device, 【0860】 A system that includes this. 【0861】 (Claim 2) 【0862】 The system according to claim 1, which filters information based on categories of information specified by the user and generates a summary. 【0863】 (Claim 3) 【0864】 The system according to claim 1, which provides a link to the original information related to the generated summary. 【0865】 "Application example 2 when combining with an emotional engine" 【0866】 (Claim 1) 【0867】 A means of automatically collecting information from data sources via the internet, 【0868】 A language analysis tool for processing collected information and extracting important elements, 【0869】 A means for generating a summary of information based on the extracted key elements, 【0870】 A sentiment analysis means that recognizes the user's emotions and adjusts the summary according to the emotional state, 【0871】 A means of providing users with an emotionally adjusted summary, 【0872】 A system that includes this. 【0873】 (Claim 2) 【0874】 The system according to claim 1, which sorts information based on the type of information selected by the user and generates an emotionally sensitive summary. 【0875】 (Claim 3) 【0876】 The system according to claim 1, which provides reference links to the source information related to the generated summary and enhances the user experience based on sentiment recognition. [Explanation of Symbols] 【0877】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means of automatically collecting information from information sources via the Internet communication network, A natural language processing method for analyzing collected information and identifying important elements, Means for generating a summary of information based on identified key elements, A means of delivering the generated summary to the user's terminal, A system that includes this. [Claim 2] The system according to claim 1, which filters information based on categories of information specified by the user and generates a summary. [Claim 3] The system according to claim 1, which provides a link to the original information related to the generated summary.

Images