system

Abstract

Provide a system. 【Solution means】 Means for detecting a user's selection operation, Means for acquiring content data from a selected information source, Means for transmitting the acquired content data to the main server, Means for analyzing the content data in the main server and extracting the main topics, Means for generating a headline with exaggerated expressions detected and corrected, Means for selecting or generating image data related to the content, Means for displaying the corrected headline and image data to the user, An information processing system including.

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, which is performed by at least one processor, including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In advertisements and articles on the Internet, excessive exaggerated expressions that cause misunderstandings are rampant, and there is a risk that users will make judgments based on inaccurate information. Such exaggerated expressions waste users' time and cause a decrease in the reliability of information. Therefore, there is a need for a technology that eliminates exaggerated expressions and provides accurate information to users.

Means for Solving the Problems

[0005] To address the above challenges, the present invention provides a means for extracting key topics by acquiring content data from user-selected information sources and analyzing it on a main server. Furthermore, it ensures the accuracy of the information by detecting exaggerated expressions and generating corrected headlines. Regarding image data, the system realizes a system that quickly and effectively presents reliable information to the user by selecting or generating relevant images.

[0006] "User selection" refers to the action a user takes to select links or items in order to obtain information.

[0007] "Information source" refers to a place on the internet that provides web pages or articles that users intend to access.

[0008] "Content data" refers to the entire set of data, including text, images, and metadata, obtained from a source.

[0009] The term "main server" refers to the server computer that receives content data and performs analysis processing.

[0010] "Analysis" refers to the process of processing content data and extracting important information from it.

[0011] "Key topics" refer to themes or topics that should be given particular emphasis within the content data.

[0012] "Exaggerated language" refers to language that emphasizes something more than it actually is, potentially misleading users.

[0013] A "revised headline" refers to a title that accurately reflects the content, with exaggerated language removed.

[0014] "Image data" refers to data that includes still images used to provide visual information related to content.

[0015] The "information processing system" refers to an integrated series of processing devices that analyze the acquired data and provide information to the user.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of the data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of the data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of the data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of the data processing device and the headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of the data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of the data processing device and the robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple 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 the emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0017] 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.

[0018] First, the terms used in the following description will be explained. <>

[0019] In the following embodiments, a labeled 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), etc.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a labeled 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.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention provides an information processing system that enables users to accurately understand information on the internet. Specifically, it aims to display accurate headlines and associated image data, free from exaggerated expressions, by acquiring and analyzing content data based on links to web pages and articles selected by the user.

[0038] First, when a user clicks on a link on a webpage, the content data associated with that link is retrieved by the user's device. This data includes text, images, and metadata. The retrieved data is sent to the server, which then receives the content data.

[0039] Next, the server analyzes the content using natural language processing technology. This analysis extracts key topics from the text and detects exaggerations that could mislead users. After detecting exaggerations, it generates corrected headlines based on accurate information and provides them to the user.

[0040] Furthermore, the server uses image analysis technology to select relevant image data. It also generates new images as needed to appropriately complement the information. The resulting headlines and thumbnail images are sent to the terminal, and the user is shown this accurate information.

[0041] For example, if a user clicks on a link on a news site that reads "Shocking! Huge space discovered in the city," the system analyzes the content and generates a more accurate headline such as "New art space opens in the city." This allows the user to properly understand the content and obtain information conveniently. This system is designed to help users avoid misunderstandings on the internet and make informed decisions based on high-quality information.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] A user clicks a link on a web page. The user takes the first step to access information that interests them.

[0045] Step 2:

[0046] The device retrieves content data from the linked URL. The retrieved data includes HTML text, metadata, and associated image data.

[0047] Step 3:

[0048] The terminal sends the acquired content data to the main server. The terminal transmits the data over the network, and the main server prepares to receive it.

[0049] Step 4:

[0050] The server analyzes the received content data. Using a natural language processing module, the server extracts key topics and keywords from the text while detecting exaggerations.

[0051] Step 5:

[0052] The server generates accurate headlines based on extracted information, eliminating exaggerations. It creates user-friendly titles while maintaining content accuracy.

[0053] Step 6:

[0054] The server uses image analysis technology to select appropriate image data or generate new images as needed. This completes the content and prepares it to provide users with visual information.

[0055] Step 7:

[0056] The server sends the generated headline and image data to the terminal. The server then sends the final analysis results back to the terminal, preparing to provide accurate information to the user.

[0057] Step 8:

[0058] The device displays new headlines and thumbnail images to the user. The user can use this to decide whether to read further about information that interests them, based on accurate and reliable information.

[0059] (Example 1)

[0060] 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."

[0061] In recent years, with the increasing volume of information on the internet, users are often misled by exaggerated or inaccurate information. In this situation, there is a need for a system that allows users to quickly obtain accurate and reliable information. However, current systems lack sufficient functionality to automatically correct exaggerated expressions and select or generate appropriate image data related to the content, making it difficult for users to correctly understand the information.

[0062] 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.

[0063] In this invention, the server includes means for detecting user selection operations, means for acquiring digital information from selected information sources, and means for transmitting the acquired digital information to a central device. This enables the user to quickly obtain accurate and unexaggerated information.

[0064] A "user" is the entity that operates the system and makes selections to obtain information.

[0065] A "selection operation" is an action performed by a user to specify a particular source of information.

[0066] An "information source" is a place on the internet where information such as web pages and articles are provided.

[0067] "Digital information" is a general term for all forms of data, including text, images, and metadata, obtained from information sources.

[0068] A "central device" is a computing device that receives and processes acquired digital information.

[0069] "Analysis" is the process of extracting key topics from digital information and is a fundamental process for detecting exaggerations.

[0070] "Main topics" refer to elements that hold central significance within digital information and are important to the user.

[0071] "Exaggeration" refers to words or phrases that are emphasized more than usual and may mislead the recipient of the information.

[0072] A "title" is a short, modified sentence that provides a summary of the information the user will see.

[0073] "Visual data" refers to images and diagrams used to visually supplement the content of information.

[0074] A "natural language processing module" is a program that analyzes digital information to understand human language.

[0075] "Image analysis technology" refers to technologies for evaluating, selecting, and generating visual data.

[0076] This information processing system is primarily composed of users, terminals, and a central device (server). Users select links to web pages and online articles, and their role is to retrieve the digital information on their terminals. This retrieved digital information includes text data, image data, and metadata. This data is transmitted to the central device via the internet.

[0077] The central system first uses a natural language processing module to process the received digital information. This module leverages Python's natural language processing libraries to analyze text data containing key topics. In particular, it uses Python's NLTK and spaCy to understand the semantic structure of the text and detect exaggerations.

[0078] If exaggerated language is detected, the central system uses a generative AI model to correct it and generate an accurate title. Specifically, it utilizes the generative AI model and takes a prompt message such as, "Remove exaggerated language from this text and generate an accurate title," to create an appropriate title.

[0079] Furthermore, the central system uses image analysis technology in conjunction with image data. This allows it to select appropriate visual data to complement the content of the digital information and generate visual elements as needed. The generation of visual elements utilizes methods that leverage generative AI models.

[0080] Finally, the processed, accurate title and selected or generated visual data are sent to the device and displayed to the user. By viewing this information, the user can understand the content based on accurate information without exaggeration.

[0081] This system aims to enable users to obtain information efficiently and accurately on the internet, and is achieved through a combination of a generative AI model and the use of prompt statements.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The user selects a link to be the source of information. The selected link allows the device to retrieve digital information from that source. This digital information includes text data, image data, and metadata. Given a link as input, digital information is generated as output.

[0085] Step 2:

[0086] The terminal transmits the acquired digital information to the server (central device). Transmission takes place via the internet, ensuring the digital information reaches the server quickly and accurately. Here, the input from the terminal is digital information, and the output is the digital information transferred to the server.

[0087] Step 3:

[0088] The server analyzes the received digital information. It uses a natural language processing module to extract the main topics within the text. This process utilizes Python's natural language processing library. The main topics extracted from the text data are obtained as output.

[0089] Step 4:

[0090] The server uses a generative AI model to correct detected exaggerations and generate an accurate title. Specifically, it prompts the generative AI model with the message, "Remove exaggerations from this text and generate an accurate title," and outputs the corrected title.

[0091] Step 5:

[0092] The server uses image analysis technology to select or generate relevant visual data. If necessary, it utilizes a generative AI model to generate new visual elements. This process takes image data or a generation prompt as input and outputs visual data for display to the user.

[0093] Step 6:

[0094] The server sends the corrected title and selected or generated visual data to the terminal. The terminal provides the user with accurate information by displaying the received data. Here, the input is the data from the server, and the output is the accurate information provided to the user.

[0095] (Application Example 1)

[0096] 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."

[0097] Much of the information provided on the internet contains exaggerated language, making it difficult for users to obtain accurate information. Furthermore, exaggeration can lead to users misunderstanding the content, highlighting the need to improve the accuracy of information. In particular, news and article headlines are often exaggerated, making it difficult for users to judge the reliability of the information.

[0098] 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.

[0099] In this invention, the server includes means for detecting user selection operations, means for acquiring information from selected information sources, means for transmitting the acquired information to a central control unit, means for analyzing the information at the central control unit and extracting key topics, means for detecting and correcting exaggerated expressions and generating corrected headlines, means for selecting or generating images related to the information, and means for summarizing the acquired information and generating accurate headlines. This enables the user to obtain accurate and reliable information.

[0100] "User selection" refers to the act of a user choosing a specific source of information on an interface.

[0101] An "information source" refers to the source of data, including web pages and articles, that exist on the internet.

[0102] "Information" refers to digital content, including text, images, and metadata.

[0103] A "central control unit" is a computer server that receives and processes information.

[0104] "Analysis" is the act of analyzing the content of information in detail using natural language processing techniques.

[0105] "Main topics" refer to the most important topics among the analyzed information.

[0106] "Exaggerated expression" refers to a way of expressing information that is excessively exaggerated, making it more impressive than it actually is.

[0107] A "revised headline" is the title of an article that has been rewritten to remove exaggerated language and be based on facts.

[0108] An "image" is a still image or generated visual data displayed to visually complement information.

[0109] A "summary" is a concise compilation of information, a process of extracting the main points and shortening them.

[0110] "Reliability" refers to the quality that demonstrates that information is based on facts and is accurate.

[0111] To implement this invention, a system is constructed using a terminal owned by the user and a server as a central control unit for analyzing the information. The user obtains the necessary information by selecting any information source on the internet. The terminal transmits this information to the server, which analyzes the information using natural language processing technology and extracts the main topics.

[0112] The server detects, removes, and corrects exaggerated expressions in the information. Furthermore, it generates corrected headlines based on the analysis results and selects or generates relevant images. For this purpose, the server utilizes software modules such as spaCy for natural language processing and Transformers for text summarization. Image analysis techniques are also applied to the analysis of visual data.

[0113] The user's device displays a revised headline and a reliable image, allowing the user to make decisions based on accurate and reliable information. For example, if a user selects an article titled "Shocking! Huge Space Discovered in City," the system analyzes the article and provides the user with a more accurate headline such as "New Art Space Opens in City."

[0114] The AI ​​generation model is designed to generate accurate summaries by using the prompt: "Summarize the following English sentence, removing any exaggerations: Shocking! A huge space has been discovered in the city."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user interacts with the device to select a specific information source. Input includes the user's clicks and the selected URL. This action allows the device to retrieve the URL of the selected information source, which triggers the next information gathering process.

[0118] Step 2:

[0119] The device accesses the selected URL and retrieves the HTML data of the webpage. The input is an HTTP request based on the URL, which outputs the webpage data. Specifically, this involves retrieving data over the network using libraries such as the requests library.

[0120] Step 3:

[0121] The device parses the acquired HTML data and extracts the text content. The input is HTML data, and the output is extracted text data. The HTML is parsed using tools like BeautifulSoup, and the text is identified.

[0122] Step 4:

[0123] The terminal sends the extracted text data to the server. The input is text data, and the output is the network transmission to the server. This data serves as the material for the next analysis step.

[0124] Step 5:

[0125] The server analyzes the received text data using natural language processing and extracts the main topics. The input is text data, and topics are identified by analyzing them using tools like spaCy. A list of the main topics is provided as output.

[0126] Step 6:

[0127] The server uses a generative AI model to detect exaggerated expressions and generate corrected headlines. The input consists of a topic list and text data, from which exaggerations are removed. This process results in corrected headlines as output. The prompt used is "Remove exaggerations from the following English text and summarize its content."

[0128] Step 7:

[0129] The server performs image analysis to select or generate relevant images. Input includes text and a topic, and it uses an image database to select appropriate images. Alternatively, it may generate new images, resulting in appropriate image data as output.

[0130] Step 8:

[0131] The server sends the corrected headline and image data to the user's terminal. The input consists of the corrected headline and image data, and the output is the completion of data transfer to the user's terminal. This information is displayed on the user's interface, ensuring accurate information retrieval.

[0132] 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.

[0133] This invention provides an information processing system that incorporates an emotion engine that recognizes user emotions and optimizes information based on those emotions. The system acquires and analyzes content based on links to web pages and articles selected by the user. Furthermore, it aims to improve the user experience by recognizing user emotion data in real time and optimizing the displayed information.

[0134] When a user clicks a link on a web page, the device retrieves content data from that URL. This content data includes HTML, meta information, images, etc. The retrieved content data is sent to the server. Simultaneously, the device's emotion engine recognizes the user's emotions and sends that emotion data to the server.

[0135] The server uses a natural language processing module to analyze content data, extracting key topics and detecting exaggerations. This generates more accurate headlines. Furthermore, based on sentiment data from the sentiment engine, the server optimizes information according to the user's emotions. For example, if the user is excited, the server selects visually appealing, vibrant images. If the user is relaxed, it provides calming images and easy-to-read content.

[0136] For example, if a user clicks on a link with a headline like "Shocking! Major Incident in XX" on a news site, the emotion engine recognizes that the user is surprised. Based on this emotion data, the server displays a revised headline, such as "New Information Released in XX," removing the exaggeration, and selects relevant images. This improvement allows users to receive information that matches their emotions, resulting in a high-quality information experience.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] When a user clicks a link on a web page, the user's selection process begins. The user takes the first step to obtain information that interests them.

[0140] Step 2:

[0141] The device retrieves the content data of the selected URL. This data includes HTML text, meta information, and related media such as images.

[0142] Step 3:

[0143] The device's emotion engine recognizes the user's emotional state in real time. The emotional state is determined using facial recognition and voice tone analysis to capture the user's current psychological state.

[0144] Step 4:

[0145] The device sends the acquired content data and user sentiment data to the main server. This data is used as foundational data for optimizing the information.

[0146] Step 5:

[0147] The server analyzes the received content data. Using natural language processing techniques, it extracts key topics and keywords from the content and detects exaggerations.

[0148] Step 6:

[0149] The server uses sentiment data to analyze the results and adjust the headlines and displayed content to match the user's emotions. For example, if the emotion is positive, a more friendly tone of headline will be used.

[0150] Step 7:

[0151] The server uses image analysis technology to select appropriate image data. Furthermore, by selecting images that match the user's emotions, visually relevant content is provided.

[0152] Step 8:

[0153] The server sends the corrected headline and selected image data to the terminal. This prepares the terminal to display optimized information to the user.

[0154] Step 9:

[0155] The device displays new headlines and image data to the user. The user can then decide whether to read the article in detail based on information that resonates with their emotions.

[0156] (Example 2)

[0157] 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 as the "terminal".

[0158] In recent years, the amount of information available on the internet has continued to increase, making it difficult for users to select the most relevant information from the vast amount available. Furthermore, some information contains exaggerated claims, which can unnecessarily affect users' emotions. This can lead to unpleasant information experiences and potentially cause erroneous decision-making. To address this challenge, it is necessary to provide information that is appropriately optimized based on the user's emotions.

[0159] 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.

[0160] In this invention, the server includes means for analyzing content data using natural language processing and detecting exaggerated expressions, means for recognizing the user's emotions in real time using an emotion recognition device, and means for selecting or generating relevant image data based on the emotion data. This makes it possible to optimize and provide information in a way that is appropriate to the user's emotions.

[0161] A "user" refers to an individual or organization that operates an information system, selects content, or provides sentiment data.

[0162] A "selection operation" refers to an action performed by a user to choose specific content from a source of information.

[0163] "Information source" refers to the source of digital content such as web pages and articles that users choose to access.

[0164] "Content data" refers to datasets such as HTML documents, metadata, and images obtained from information sources.

[0165] An "emotion recognition device" refers to a technology or device that determines a user's emotional state based on data acquired from them.

[0166] The term "main server" refers to the core computer system that analyzes acquired data, generates optimized information, and provides it to users.

[0167] "Natural language processing" refers to computer technology that analyzes digital text and audio data to extract intent and information.

[0168] "Exaggeration" refers to expressions that excessively emphasize or distort facts or information.

[0169] "Emotional data" refers to information that indicates the user's current emotional state.

[0170] "Image data" refers to digital images and related data used to provide visual information displayed to the user.

[0171] To implement this invention, it is necessary to construct an information processing system that acquires content data from a user-selected information source, optimizes that data, and provides it to the user. Specifically, the following system components are required.

[0172] User

[0173] The user selects a link to a specific webpage or article through their device. At this time, the user's emotions are collected in real time by an emotion recognition device.

[0174] terminal

[0175] The device includes a user interface (UI) that detects user selections and software such as a web browser to retrieve content from selected information sources. The device also includes an emotion recognition device that acquires emotion data in real time from the user's facial expressions and voice tone and transmits it to a server.

[0176] server

[0177] The server is the core component, analyzing the acquired content data using natural language processing techniques. This processing includes tokenization, part-of-speech identification, extraction of key topics, and detection of exaggerated language. Furthermore, the server optimizes content based on sentiment data. This includes selecting or generating relevant image data according to the user's emotions. For example, it might select and insert a vibrant image from a picture database.

[0178] As a concrete example, consider a scenario where a user clicks on a surprising headline on a news website. An emotion recognition device detects the user's surprise and sends it to the server. The server then enhances the user's informational experience by providing an optimized, less exaggerated revised headline along with associated image data.

[0179] As an example of a prompt, use the text: "Explain an optimization algorithm that modifies headlines and selects relevant images based on sentiment data when a user is surprised on a news site."

[0180] This system enables the optimization of information while taking user emotions into consideration, allowing users to have a higher quality information experience.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user clicks a link to a specific webpage on their device. This provides the URL of the linked page as input data. The device then uses this URL to send an HTTP request and retrieves the content data (HTML, meta information, images, etc.) of the target webpage. This retrieved content data becomes the input for the next step.

[0184] Step 2:

[0185] An emotion recognition device installed in the terminal analyzes the user's facial expression data and voice tone in real time to acquire emotion data. Input includes the user's facial expressions and voice data, and output is the user's emotional state (e.g., "surprise," "joy"). This emotion data becomes additional data when transmitted to the server.

[0186] Step 3:

[0187] The acquired content data and sentiment data are sent from the terminal to the server. The input for transmission is the content data and sentiment data, and the output is that this data is stored on the server and ready for analysis.

[0188] Step 4:

[0189] The server analyzes incoming content data using natural language processing techniques. The input is content data; during the analysis process, the data is tokenized, parts of speech are identified, and key topics are extracted. Hypocrisy is also detected. The output consists of the analyzed structured data and the detected hyperbolic expressions.

[0190] Step 5:

[0191] The server optimizes information to suit the user's emotions based on the analyzed data and received sentiment data. Inputs include analyzed data and sentiment data, while output includes adjusted and modified headlines and image data that matches the user's emotions. Specifically, it selects relevant images from the database and prepares them for display on the user's screen.

[0192] Step 6:

[0193] The server sends optimized content back to the device, where it is displayed to the user. The input at this point is optimized data, and the output is the screen display received by the user. The device receives the data from the server, renders it appropriately, and improves the user's information experience.

[0194] (Application Example 2)

[0195] 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".

[0196] In modern information processing systems, there is a problem in that information is not sufficiently optimized to respond to user emotions, resulting in a lack of individualized user experience. In particular, when users are in different emotional states, the inability to provide appropriate information or content can lead to decreased user satisfaction.

[0197] 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.

[0198] In this invention, the server includes means for recognizing the user's emotional state using an emotion recognition device, means for optimizing the displayed content based on the recognized emotion data, and means for extracting key themes and correcting exaggerated expressions. This enables the provision of optimal information tailored to the user's emotions.

[0199] A "device for detecting user selection actions" is a technology that detects a user's behavior of selecting specific content from an information source.

[0200] "Information source" refers to the medium, including websites and digital platforms, from which content data is obtained.

[0201] A "device for acquiring content data" is a technology for collecting data from selected information sources.

[0202] A "central server" is a core computing system that collects and analyzes acquired data and provides optimal information.

[0203] A "device for extracting key themes" is a technology for identifying and extracting important topics from analyzed content data.

[0204] A "device that detects and corrects exaggerated expressions and generates corrected headlines" is a technology for identifying and correcting exaggerated expressions within content data.

[0205] "An apparatus for selecting or generating image data related to content" refers to a technology for selecting or creating new visual information related to content data.

[0206] A "device for presenting to the user" refers to technology for visually displaying corrected headlines and image data to the user.

[0207] An "emotion recognition device" is a device that detects and evaluates a user's emotional state in real time.

[0208] A "device for optimizing displayed content" is a technology that adjusts and optimizes the content displayed based on the user's emotions.

[0209] This invention is an information processing system that optimizes content according to the user's emotional state. It begins when the user's terminal detects a selection operation and transmits the acquired content data to a central server. The central server analyzes the obtained content data, extracts the main themes, and corrects exaggerated expressions. This generates appropriate headlines and associated image data.

[0210] Furthermore, a key feature of this system is the inclusion of an emotion recognition device that evaluates the user's emotional state in real time. Based on this emotion data, the server dynamically selects and displays the most appropriate content for the user. The content can provide calming images depending on the user's relaxed state, or stimulating images depending on their excited state.

[0211] The specific technologies used include "OpenCV" and "Microsoft® Azure® Emotion API" for emotion recognition, and "TENSORFLOW®" and "Scikit-learn" for content optimization. This will improve the quality of the user's viewing experience.

[0212] For example, if a user is wearing smart glasses and listening to calming music while strolling through nature, the emotion recognition device will detect a relaxed emotion and provide related calming images and music. On the other hand, if the user is excited while jogging in the city, the emotion recognition device will recommend fast-paced music and energetic images.

[0213] An example of a prompt sentence to input into a generative AI model is, "What content do you recommend for relaxation?" By using such prompt sentences, the system can present the most suitable content in real time.

[0214] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0215] Step 1:

[0216] The device detects the user's selection action. When the user clicks a link to a specific information source, a selection action is made, and the device detects the URL of that source. Using this as input, the device begins collecting relevant content data.

[0217] Step 2:

[0218] The device retrieves content data from the selected information source. Using the detected URL, it downloads content data such as HTML and images from the web. It then prepares this retrieved content data for transmission to the server.

[0219] Step 3:

[0220] The server analyzes the received data. Using a natural language processing module, it analyzes the text within the content and extracts the main themes. This identifies which topics are particularly important and provides input for subsequent processing.

[0221] Step 4:

[0222] The server detects exaggerated language and generates a revised headline. Natural language processing techniques identify exaggerated language within the content and create a new headline that mitigates it. This revised headline is then used in the next step.

[0223] Step 5:

[0224] The server selects or generates image data relevant to the content. Based on the analysis results, it selects the most suitable image from the database or generates a new one. At this stage, it is determined what visual information the user will receive.

[0225] Step 6:

[0226] The emotion recognition device recognizes the user's emotions in real time. Using sensors and cameras attached to the device, it analyzes the user's facial expressions, heart rate, and other data to detect their emotional state. This information becomes input data used in the next step.

[0227] Step 7:

[0228] The server optimizes displayed content based on recognized emotion data. It dynamically selects content according to emotions; for example, it provides calming images and music when the user is relaxed, and stimulating content when the user is excited. A generative AI model is used to achieve real-time content optimization. This optimized content is then presented to the user as the final output.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] [Second Embodiment]

[0233] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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".

[0245] This invention provides an information processing system that enables users to accurately understand information on the internet. Specifically, it aims to display accurate headlines and associated image data, free from exaggerated expressions, by acquiring and analyzing content data based on links to web pages and articles selected by the user.

[0246] First, when a user clicks on a link on a webpage, the content data associated with that link is retrieved by the user's device. This data includes text, images, and metadata. The retrieved data is sent to the server, which then receives the content data.

[0247] Next, the server analyzes the content using natural language processing technology. This analysis extracts key topics from the text and detects exaggerations that could mislead users. After detecting exaggerations, it generates corrected headlines based on accurate information and provides them to the user.

[0248] Furthermore, the server uses image analysis technology to select relevant image data. It also generates new images as needed to appropriately complement the information. The resulting headlines and thumbnail images are sent to the terminal, and the user is shown this accurate information.

[0249] For example, if a user clicks on a link on a news site that reads "Shocking! Huge space discovered in the city," the system analyzes the content and generates a more accurate headline such as "New art space opens in the city." This allows the user to properly understand the content and obtain information conveniently. This system is designed to help users avoid misunderstandings on the internet and make informed decisions based on high-quality information.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] A user clicks a link on a web page. The user takes the first step to access information that interests them.

[0253] Step 2:

[0254] The device retrieves content data from the linked URL. The retrieved data includes HTML text, metadata, and associated image data.

[0255] Step 3:

[0256] The terminal sends the acquired content data to the main server. The terminal transmits the data over the network, and the main server prepares to receive it.

[0257] Step 4:

[0258] The server analyzes the received content data. Using a natural language processing module, the server extracts key topics and keywords from the text while detecting exaggerations.

[0259] Step 5:

[0260] The server generates accurate headlines based on extracted information, eliminating exaggerations. It creates user-friendly titles while maintaining content accuracy.

[0261] Step 6:

[0262] The server uses image analysis technology to select appropriate image data or generate new images as needed. This completes the content and prepares it to provide users with visual information.

[0263] Step 7:

[0264] The server sends the generated headline and image data to the terminal. The server then sends the final analysis results back to the terminal, preparing to provide accurate information to the user.

[0265] Step 8:

[0266] The device displays new headlines and thumbnail images to the user. The user can use this to decide whether to read further about information that interests them, based on accurate and reliable information.

[0267] (Example 1)

[0268] 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."

[0269] In recent years, with the increasing volume of information on the internet, users are often misled by exaggerated or inaccurate information. In this situation, there is a need for a system that allows users to quickly obtain accurate and reliable information. However, current systems lack sufficient functionality to automatically correct exaggerated expressions and select or generate appropriate image data related to the content, making it difficult for users to correctly understand the information.

[0270] 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.

[0271] In this invention, the server includes means for detecting user selection operations, means for acquiring digital information from selected information sources, and means for transmitting the acquired digital information to a central device. This enables the user to quickly obtain accurate and unexaggerated information.

[0272] A "user" is the entity that operates the system and makes selections to obtain information.

[0273] A "selection operation" is an action performed by a user to specify a particular source of information.

[0274] An "information source" is a place on the internet where information such as web pages and articles are provided.

[0275] "Digital information" is a general term for all forms of data, including text, images, and meta-information, obtained from information sources.

[0276] "Central device" is a computing device to which the acquired digital information is transmitted and processed.

[0277] "Analysis" is the act of extracting the main topics from digital information and is the underlying process for detecting exaggerated expressions.

[0278] "Main topic" is an element with a central meaning in digital information and refers to content that is important to the user.

[0279] "Exaggerated expression" is an expression that is emphasized more than usual and is a word or phrase that may mislead the recipient of the information.

[0280] "Title" is a short sentence that shows an overview of the information that the user views, generated with modifications.

[0281] "Visual data" refers to images and charts used to visually complement the content of information.

[0282] "Natural language processing module" is a program for analyzing digital information and understanding human language.

[0283] "Image analysis technology" is a technology for evaluating, selecting, and generating visual data.

[0284] This information processing system is mainly configured around the user, the terminal, and the central device (server). The user is responsible for selecting links to web pages or online articles and obtaining the digital information on the terminal. The acquired digital information includes text data, image data, and meta-information. This data is transmitted to the central device through the Internet.

[0285] The central device first uses a natural language processing module to process the received digital information. This module utilizes Python's natural language processing libraries to analyze text data including the main topics. In particular, it uses Python's NLTK and spaCy to understand the semantic structure of sentences and detect exaggerated expressions.

[0286] If an exaggerated expression is detected, the central device uses a generative AI model to make corrections and generate an accurate title. Specifically, it utilizes the generative AI model to input a prompt sentence such as "Please eliminate the exaggerated expressions from this text and generate an accurate title." and create an appropriate title.

[0287] In addition, the central device also uses image analysis technology for image data. Thereby, it selects appropriate visual data to complement the content of the digital information and generates visual elements as needed. For the generation of visual elements, a method utilizing the generative AI model is used.

[0288] Finally, the processed accurate title and the selected or generated visual data are sent to the terminal and displayed to the user. By browsing this information, the user can understand the content based on accurate information without exaggerated expressions.

[0289] This system aims to enable users to obtain information efficiently and accurately on the Internet and is realized by the combination of the generative AI model and the utilization of prompt sentences.

[0290] The flow of specific processing in Example 1 will be described using Figure 11.

[0291] Step 1:

[0292] The user selects a link that serves as an information source. Based on the selected link, the terminal acquires digital information from that information source. This digital information includes text data, image data, and meta information. By providing a link as input, digital information as output is generated.

[0293] Step 2:

[0294] The terminal transmits the acquired digital information to the server (central device). Transmission takes place via the internet, ensuring the digital information reaches the server quickly and accurately. Here, the input from the terminal is digital information, and the output is the digital information transferred to the server.

[0295] Step 3:

[0296] The server analyzes the received digital information. It uses a natural language processing module to extract the main topics within the text. This process utilizes Python's natural language processing library. The main topics extracted from the text data are obtained as output.

[0297] Step 4:

[0298] The server uses a generative AI model to correct detected exaggerations and generate an accurate title. Specifically, it prompts the generative AI model with the message, "Remove exaggerations from this text and generate an accurate title," and outputs the corrected title.

[0299] Step 5:

[0300] The server uses image analysis technology to select or generate relevant visual data. If necessary, it utilizes a generative AI model to generate new visual elements. This process takes image data or a generation prompt as input and outputs visual data for display to the user.

[0301] Step 6:

[0302] The server sends the modified title and the selected or generated visual data to the terminal. The terminal provides accurate information to the user by displaying the received data to the user. Here, the input is the data from the server, and the output is the accurate information provided to the user.

[0303] (Application Example 1)

[0304] 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".

[0305] Since much of the information provided on the Internet contains exaggerated expressions, there is a problem that it is difficult for users to obtain accurate information. In addition, there is a possibility that users may misunderstand the content due to exaggerated expressions, and it is necessary to improve the accuracy of information. In particular, the headlines of news and articles are often exaggerated, and there is a problem that it is difficult for users to judge the reliability of the information.

[0306] 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.

[0307] In this invention, the server includes means for detecting a user's selection operation, means for acquiring information from the selected information source, means for transmitting the acquired information to the central control device, means for analyzing the information by the central control device and extracting the main topic, means for detecting exaggerated expressions and generating a modified title, means for selecting or generating an image related to the information, and means for summarizing the acquired information and generating an accurate title. Thereby, it becomes possible for the user to obtain accurate and reliable information.

[0308] The "user's selection operation" refers to the act of a user selecting a specific information source on the interface.

[0309] The "information source" is a data provider including web pages and articles existing on the Internet.

[0310] "Information" refers to digital content, including text, images, and metadata.

[0311] A "central control unit" is a computer server that receives and processes information.

[0312] "Analysis" is the act of analyzing the content of information in detail using natural language processing techniques.

[0313] "Main topics" refer to the most important topics among the analyzed information.

[0314] "Exaggerated expression" refers to a way of expressing information that is excessively exaggerated, making it more impressive than it actually is.

[0315] A "revised headline" is the title of an article that has been rewritten to remove exaggerated language and be based on facts.

[0316] An "image" is a still image or generated visual data displayed to visually complement information.

[0317] A "summary" is a concise compilation of information, a process of extracting the main points and shortening them.

[0318] "Reliability" refers to the quality that demonstrates that information is based on facts and is accurate.

[0319] To implement this invention, a system is constructed using a terminal owned by the user and a server as a central control unit for analyzing the information. The user obtains the necessary information by selecting any information source on the internet. The terminal transmits this information to the server, which analyzes the information using natural language processing technology and extracts the main topics.

[0320] The server detects, removes, and corrects exaggerated expressions in the information. Furthermore, it generates corrected headlines based on the analysis results and selects or generates relevant images. For this purpose, the server utilizes software modules such as spaCy for natural language processing and Transformers for text summarization. Image analysis techniques are also applied to the analysis of visual data.

[0321] The user's device displays a revised headline and a reliable image, allowing the user to make decisions based on accurate and reliable information. For example, if a user selects an article titled "Shocking! Huge Space Discovered in City," the system analyzes the article and provides the user with a more accurate headline such as "New Art Space Opens in City."

[0322] The AI ​​generation model is designed to generate accurate summaries by using the prompt: "Summarize the following English sentence, removing any exaggerations: Shocking! A huge space has been discovered in the city."

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The user interacts with the device to select a specific information source. Input includes the user's clicks and the selected URL. This action allows the device to retrieve the URL of the selected information source, which triggers the next information gathering process.

[0326] Step 2:

[0327] The device accesses the selected URL and retrieves the HTML data of the webpage. The input is an HTTP request based on the URL, which outputs the webpage data. Specifically, this involves retrieving data over the network using libraries such as the requests library.

[0328] Step 3:

[0329] The device parses the acquired HTML data and extracts the text content. The input is HTML data, and the output is extracted text data. The HTML is parsed using tools like BeautifulSoup, and the text is identified.

[0330] Step 4:

[0331] The terminal sends the extracted text data to the server. The input is text data, and the output is the network transmission to the server. This data serves as the material for the next analysis step.

[0332] Step 5:

[0333] The server analyzes the received text data using natural language processing and extracts the main topics. The input is text data, and topics are identified by analyzing them using tools like spaCy. A list of the main topics is provided as output.

[0334] Step 6:

[0335] The server uses a generative AI model to detect exaggerated expressions and generate corrected headlines. The input consists of a topic list and text data, from which exaggerations are removed. This process results in corrected headlines as output. The prompt used is "Remove exaggerations from the following English text and summarize its content."

[0336] Step 7:

[0337] The server performs image analysis to select or generate relevant images. Input includes text and a topic, and it uses an image database to select appropriate images. Alternatively, it may generate new images, resulting in appropriate image data as output.

[0338] Step 8:

[0339] The server sends the corrected headline and image data to the user's terminal. The input consists of the corrected headline and image data, and the output is the completion of data transfer to the user's terminal. This information is displayed on the user's interface, ensuring accurate information retrieval.

[0340] 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.

[0341] This invention provides an information processing system that incorporates an emotion engine that recognizes user emotions and optimizes information based on those emotions. The system acquires and analyzes content based on links to web pages and articles selected by the user. Furthermore, it aims to improve the user experience by recognizing user emotion data in real time and optimizing the displayed information.

[0342] When a user clicks a link on a web page, the device retrieves content data from that URL. This content data includes HTML, meta information, images, etc. The retrieved content data is sent to the server. Simultaneously, the device's emotion engine recognizes the user's emotions and sends that emotion data to the server.

[0343] The server uses a natural language processing module to analyze content data, extracting key topics and detecting exaggerations. This generates more accurate headlines. Furthermore, based on sentiment data from the sentiment engine, the server optimizes information according to the user's emotions. For example, if the user is excited, the server selects visually appealing, vibrant images. If the user is relaxed, it provides calming images and easy-to-read content.

[0344] For example, if a user clicks on a link with a headline like "Shocking! Major Incident in XX" on a news site, the emotion engine recognizes that the user is surprised. Based on this emotion data, the server displays a revised headline, such as "New Information Released in XX," removing the exaggeration, and selects relevant images. This improvement allows users to receive information that matches their emotions, resulting in a high-quality information experience.

[0345] The following describes the processing flow.

[0346] Step 1:

[0347] When a user clicks a link on a web page, the user's selection process begins. The user takes the first step to obtain information that interests them.

[0348] Step 2:

[0349] The device retrieves the content data of the selected URL. This data includes HTML text, meta information, and related media such as images.

[0350] Step 3:

[0351] The device's emotion engine recognizes the user's emotional state in real time. The emotional state is determined using facial recognition and voice tone analysis to capture the user's current psychological state.

[0352] Step 4:

[0353] The device sends the acquired content data and user sentiment data to the main server. This data is used as foundational data for optimizing the information.

[0354] Step 5:

[0355] The server analyzes the received content data. Using natural language processing techniques, it extracts key topics and keywords from the content and detects exaggerations.

[0356] Step 6:

[0357] The server uses sentiment data to analyze the results and adjust the headlines and displayed content to match the user's emotions. For example, if the emotion is positive, a more friendly tone of headline will be used.

[0358] Step 7:

[0359] The server uses image analysis technology to select appropriate image data. Furthermore, by selecting images that match the user's emotions, visually relevant content is provided.

[0360] Step 8:

[0361] The server sends the corrected headline and selected image data to the terminal. This prepares the terminal to display optimized information to the user.

[0362] Step 9:

[0363] The device displays new headlines and image data to the user. The user can then decide whether to read the article in detail based on information that resonates with their emotions.

[0364] (Example 2)

[0365] 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".

[0366] In recent years, the amount of information available on the internet has continued to increase, making it difficult for users to select the most relevant information from the vast amount available. Furthermore, some information contains exaggerated claims, which can unnecessarily affect users' emotions. This can lead to unpleasant information experiences and potentially cause erroneous decision-making. To address this challenge, it is necessary to provide information that is appropriately optimized based on the user's emotions.

[0367] 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.

[0368] In this invention, the server includes means for analyzing content data using natural language processing and detecting exaggerated expressions, means for recognizing the user's emotions in real time using an emotion recognition device, and means for selecting or generating relevant image data based on the emotion data. This makes it possible to optimize and provide information in a way that is appropriate to the user's emotions.

[0369] A "user" refers to an individual or organization that operates an information system, selects content, or provides sentiment data.

[0370] A "selection operation" refers to an action performed by a user to choose specific content from a source of information.

[0371] "Information source" refers to the source of digital content such as web pages and articles that users choose to access.

[0372] "Content data" refers to datasets such as HTML documents, metadata, and images obtained from information sources.

[0373] An "emotion recognition device" refers to a technology or device that determines a user's emotional state based on data acquired from them.

[0374] The term "main server" refers to the core computer system that analyzes acquired data, generates optimized information, and provides it to users.

[0375] "Natural language processing" refers to computer technology that analyzes digital text and audio data to extract intent and information.

[0376] "Exaggeration" refers to expressions that excessively emphasize or distort facts or information.

[0377] "Emotional data" refers to information that indicates the user's current emotional state.

[0378] "Image data" refers to digital images and related data used to provide visual information displayed to the user.

[0379] To implement this invention, it is necessary to construct an information processing system that acquires content data from a user-selected information source, optimizes that data, and provides it to the user. Specifically, the following system components are required.

[0380] User

[0381] The user selects a link to a specific webpage or article through their device. At this time, the user's emotions are collected in real time by an emotion recognition device.

[0382] terminal

[0383] The device includes a user interface (UI) that detects user selections and software such as a web browser to retrieve content from selected information sources. The device also includes an emotion recognition device that acquires emotion data in real time from the user's facial expressions and voice tone and transmits it to a server.

[0384] server

[0385] The server is the core component, analyzing the acquired content data using natural language processing techniques. This processing includes tokenization, part-of-speech identification, extraction of key topics, and detection of exaggerated language. Furthermore, the server optimizes content based on sentiment data. This includes selecting or generating relevant image data according to the user's emotions. For example, it might select and insert a vibrant image from a picture database.

[0386] As a concrete example, consider a scenario where a user clicks on a surprising headline on a news website. An emotion recognition device detects the user's surprise and sends it to the server. The server then enhances the user's informational experience by providing an optimized, less exaggerated revised headline along with associated image data.

[0387] As an example of a prompt, use the text: "Explain an optimization algorithm that modifies headlines and selects relevant images based on sentiment data when a user is surprised on a news site."

[0388] This system enables the optimization of information while taking user emotions into consideration, allowing users to have a higher quality information experience.

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] The user clicks a link to a specific webpage on their device. This provides the URL of the linked page as input data. The device then uses this URL to send an HTTP request and retrieves the content data (HTML, meta information, images, etc.) of the target webpage. This retrieved content data becomes the input for the next step.

[0392] Step 2:

[0393] An emotion recognition device installed in the terminal analyzes the user's facial expression data and voice tone in real time to acquire emotion data. Input includes the user's facial expressions and voice data, and output is the user's emotional state (e.g., "surprise," "joy"). This emotion data becomes additional data when transmitted to the server.

[0394] Step 3:

[0395] The acquired content data and sentiment data are sent from the terminal to the server. The input for transmission is the content data and sentiment data, and the output is that this data is stored on the server and ready for analysis.

[0396] Step 4:

[0397] The server analyzes incoming content data using natural language processing techniques. The input is content data; during the analysis process, the data is tokenized, parts of speech are identified, and key topics are extracted. Hypocrisy is also detected. The output consists of the analyzed structured data and the detected hyperbolic expressions.

[0398] Step 5:

[0399] The server optimizes information to suit the user's emotions based on the analyzed data and received sentiment data. Inputs include analyzed data and sentiment data, while output includes adjusted and modified headlines and image data that matches the user's emotions. Specifically, it selects relevant images from the database and prepares them for display on the user's screen.

[0400] Step 6:

[0401] The server sends optimized content back to the device, where it is displayed to the user. The input at this point is optimized data, and the output is the screen display received by the user. The device receives the data from the server, renders it appropriately, and improves the user's information experience.

[0402] (Application Example 2)

[0403] 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."

[0404] In modern information processing systems, there is a problem in that information is not sufficiently optimized to respond to user emotions, resulting in a lack of individualized user experience. In particular, when users are in different emotional states, the inability to provide appropriate information or content can lead to decreased user satisfaction.

[0405] 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.

[0406] In this invention, the server includes means for recognizing the user's emotional state using an emotion recognition device, means for optimizing the displayed content based on the recognized emotion data, and means for extracting key themes and correcting exaggerated expressions. This enables the provision of optimal information tailored to the user's emotions.

[0407] A "device for detecting user selection actions" is a technology that detects a user's behavior of selecting specific content from an information source.

[0408] "Information source" refers to the medium, including websites and digital platforms, from which content data is obtained.

[0409] A "device for acquiring content data" is a technology for collecting data from selected information sources.

[0410] A "central server" is a core computing system that collects and analyzes acquired data and provides optimal information.

[0411] A "device for extracting key themes" is a technology for identifying and extracting important topics from analyzed content data.

[0412] A "device that detects and corrects exaggerated expressions and generates corrected headlines" is a technology for identifying and correcting exaggerated expressions within content data.

[0413] "An apparatus for selecting or generating image data related to content" refers to a technology for selecting or creating new visual information related to content data.

[0414] A "device for presenting to the user" refers to technology for visually displaying corrected headlines and image data to the user.

[0415] An "emotion recognition device" is a device that detects and evaluates a user's emotional state in real time.

[0416] A "device for optimizing displayed content" is a technology that adjusts and optimizes the content displayed based on the user's emotions.

[0417] This invention is an information processing system that optimizes content according to the user's emotional state. It begins when the user's terminal detects a selection operation and transmits the acquired content data to a central server. The central server analyzes the obtained content data, extracts the main themes, and corrects exaggerated expressions. This generates appropriate headlines and associated image data.

[0418] Furthermore, a key feature of this system is the inclusion of an emotion recognition device that evaluates the user's emotional state in real time. Based on this emotion data, the server dynamically selects and displays the most appropriate content for the user. The content can provide calming images depending on the user's relaxed state, or stimulating images depending on their excited state.

[0419] The specific technologies used include OpenCV and Microsoft Azure Emotion API for emotion recognition, and TensorFlow and Scikit-learn for content optimization. This will improve the quality of the user's viewing experience.

[0420] For example, if a user is wearing smart glasses and listening to calming music while strolling through nature, the emotion recognition device will detect a relaxed emotion and provide related calming images and music. On the other hand, if the user is excited while jogging in the city, the emotion recognition device will recommend fast-paced music and energetic images.

[0421] An example of a prompt sentence to input into a generative AI model is, "What content do you recommend for relaxation?" By using such prompt sentences, the system can present the most suitable content in real time.

[0422] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0423] Step 1:

[0424] The device detects the user's selection action. When the user clicks a link to a specific information source, a selection action is made, and the device detects the URL of that source. Using this as input, the device begins collecting relevant content data.

[0425] Step 2:

[0426] The device retrieves content data from the selected information source. Using the detected URL, it downloads content data such as HTML and images from the web. It then prepares this retrieved content data for transmission to the server.

[0427] Step 3:

[0428] The server analyzes the received data. Using a natural language processing module, it analyzes the text within the content and extracts the main themes. This identifies which topics are particularly important and provides input for subsequent processing.

[0429] Step 4:

[0430] The server detects exaggerated language and generates a revised headline. Natural language processing techniques identify exaggerated language within the content and create a new headline that mitigates it. This revised headline is then used in the next step.

[0431] Step 5:

[0432] The server selects or generates image data relevant to the content. Based on the analysis results, it selects the most suitable image from the database or generates a new one. At this stage, it is determined what visual information the user will receive.

[0433] Step 6:

[0434] The emotion recognition device recognizes the user's emotions in real time. Using sensors and cameras attached to the device, it analyzes the user's facial expressions, heart rate, and other data to detect their emotional state. This information becomes input data used in the next step.

[0435] Step 7:

[0436] The server optimizes displayed content based on recognized emotion data. It dynamically selects content according to emotions; for example, it provides calming images and music when the user is relaxed, and stimulating content when the user is excited. A generative AI model is used to achieve real-time content optimization. This optimized content is then presented to the user as the final output.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Third Embodiment]

[0441] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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".

[0453] This invention provides an information processing system that enables users to accurately understand information on the internet. Specifically, it aims to display accurate headlines and associated image data, free from exaggerated expressions, by acquiring and analyzing content data based on links to web pages and articles selected by the user.

[0454] First, when a user clicks on a link on a webpage, the content data associated with that link is retrieved by the user's device. This data includes text, images, and metadata. The retrieved data is sent to the server, which then receives the content data.

[0455] Next, the server analyzes the content using natural language processing technology. This analysis extracts key topics from the text and detects exaggerations that could mislead users. After detecting exaggerations, it generates corrected headlines based on accurate information and provides them to the user.

[0456] Furthermore, the server uses image analysis technology to select relevant image data. It also generates new images as needed to appropriately complement the information. The resulting headlines and thumbnail images are sent to the terminal, and the user is shown this accurate information.

[0457] For example, if a user clicks on a link on a news site that reads "Shocking! Huge space discovered in the city," the system analyzes the content and generates a more accurate headline such as "New art space opens in the city." This allows the user to properly understand the content and obtain information conveniently. This system is designed to help users avoid misunderstandings on the internet and make informed decisions based on high-quality information.

[0458] The following describes the processing flow.

[0459] Step 1:

[0460] A user clicks a link on a web page. The user takes the first step to access information that interests them.

[0461] Step 2:

[0462] The device retrieves content data from the linked URL. The retrieved data includes HTML text, metadata, and associated image data.

[0463] Step 3:

[0464] The terminal sends the acquired content data to the main server. The terminal transmits the data over the network, and the main server prepares to receive it.

[0465] Step 4:

[0466] The server analyzes the received content data. Using a natural language processing module, the server extracts key topics and keywords from the text while detecting exaggerations.

[0467] Step 5:

[0468] The server generates accurate headlines based on extracted information, eliminating exaggerations. It creates user-friendly titles while maintaining content accuracy.

[0469] Step 6:

[0470] The server uses image analysis technology to select appropriate image data or generate new images as needed. This completes the content and prepares it to provide users with visual information.

[0471] Step 7:

[0472] The server sends the generated headline and image data to the terminal. The server then sends the final analysis results back to the terminal, preparing to provide accurate information to the user.

[0473] Step 8:

[0474] The device displays new headlines and thumbnail images to the user. The user can use this to decide whether to read further about information that interests them, based on accurate and reliable information.

[0475] (Example 1)

[0476] 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."

[0477] In recent years, with the increasing volume of information on the internet, users are often misled by exaggerated or inaccurate information. In this situation, there is a need for a system that allows users to quickly obtain accurate and reliable information. However, current systems lack sufficient functionality to automatically correct exaggerated expressions and select or generate appropriate image data related to the content, making it difficult for users to correctly understand the information.

[0478] 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.

[0479] In this invention, the server includes means for detecting user selection operations, means for acquiring digital information from selected information sources, and means for transmitting the acquired digital information to a central device. This enables the user to quickly obtain accurate and unexaggerated information.

[0480] A "user" is the entity that operates the system and makes selections to obtain information.

[0481] A "selection operation" is an action performed by a user to specify a particular source of information.

[0482] An "information source" is a place on the internet where information such as web pages and articles are provided.

[0483] "Digital information" is a general term for all forms of data, including text, images, and metadata, obtained from information sources.

[0484] A "central device" is a computing device that receives and processes acquired digital information.

[0485] "Analysis" is the process of extracting key topics from digital information and is a fundamental process for detecting exaggerations.

[0486] "Main topics" refer to elements that hold central significance within digital information and are important to the user.

[0487] "Exaggeration" refers to words or phrases that are emphasized more than usual and may mislead the recipient of the information.

[0488] A "title" is a short, modified sentence that provides a summary of the information the user will see.

[0489] "Visual data" refers to images and diagrams used to visually supplement the content of information.

[0490] A "natural language processing module" is a program that analyzes digital information to understand human language.

[0491] "Image analysis technology" refers to technologies for evaluating, selecting, and generating visual data.

[0492] This information processing system is primarily composed of users, terminals, and a central device (server). Users select links to web pages and online articles, and their role is to retrieve the digital information on their terminals. This retrieved digital information includes text data, image data, and metadata. This data is transmitted to the central device via the internet.

[0493] The central system first uses a natural language processing module to process the received digital information. This module leverages Python's natural language processing libraries to analyze text data containing key topics. In particular, it uses Python's NLTK and spaCy to understand the semantic structure of the text and detect exaggerations.

[0494] If exaggerated language is detected, the central system uses a generative AI model to correct it and generate an accurate title. Specifically, it utilizes the generative AI model and takes a prompt message such as, "Remove exaggerated language from this text and generate an accurate title," to create an appropriate title.

[0495] Furthermore, the central system uses image analysis technology in conjunction with image data. This allows it to select appropriate visual data to complement the content of the digital information and generate visual elements as needed. The generation of visual elements utilizes methods that leverage generative AI models.

[0496] Finally, the processed, accurate title and selected or generated visual data are sent to the device and displayed to the user. By viewing this information, the user can understand the content based on accurate information without exaggeration.

[0497] This system aims to enable users to obtain information efficiently and accurately on the internet, and is achieved through a combination of a generative AI model and the use of prompt statements.

[0498] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0499] Step 1:

[0500] The user selects a link to be the source of information. The selected link allows the device to retrieve digital information from that source. This digital information includes text data, image data, and metadata. Given a link as input, digital information is generated as output.

[0501] Step 2:

[0502] The terminal transmits the acquired digital information to the server (central device). Transmission takes place via the internet, ensuring the digital information reaches the server quickly and accurately. Here, the input from the terminal is digital information, and the output is the digital information transferred to the server.

[0503] Step 3:

[0504] The server analyzes the received digital information. It uses a natural language processing module to extract the main topics within the text. This process utilizes Python's natural language processing library. The main topics extracted from the text data are obtained as output.

[0505] Step 4:

[0506] The server uses a generative AI model to correct detected exaggerations and generate an accurate title. Specifically, it prompts the generative AI model with the message, "Remove exaggerations from this text and generate an accurate title," and outputs the corrected title.

[0507] Step 5:

[0508] The server uses image analysis technology to select or generate relevant visual data. If necessary, it utilizes a generative AI model to generate new visual elements. This process takes image data or a generation prompt as input and outputs visual data for display to the user.

[0509] Step 6:

[0510] The server sends the corrected title and selected or generated visual data to the terminal. The terminal provides the user with accurate information by displaying the received data. Here, the input is the data from the server, and the output is the accurate information provided to the user.

[0511] (Application Example 1)

[0512] 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."

[0513] Much of the information provided on the internet contains exaggerated language, making it difficult for users to obtain accurate information. Furthermore, exaggeration can lead to users misunderstanding the content, highlighting the need to improve the accuracy of information. In particular, news and article headlines are often exaggerated, making it difficult for users to judge the reliability of the information.

[0514] 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.

[0515] In this invention, the server includes means for detecting user selection operations, means for acquiring information from selected information sources, means for transmitting the acquired information to a central control unit, means for analyzing the information at the central control unit and extracting key topics, means for detecting and correcting exaggerated expressions and generating corrected headlines, means for selecting or generating images related to the information, and means for summarizing the acquired information and generating accurate headlines. This enables the user to obtain accurate and reliable information.

[0516] "User selection" refers to the act of a user choosing a specific source of information on an interface.

[0517] An "information source" refers to the source of data, including web pages and articles, that exist on the internet.

[0518] "Information" refers to digital content, including text, images, and metadata.

[0519] A "central control unit" is a computer server that receives and processes information.

[0520] "Analysis" is the act of analyzing the content of information in detail using natural language processing techniques.

[0521] "Main topics" refer to the most important topics among the analyzed information.

[0522] "Exaggerated expression" refers to a way of expressing information that is excessively exaggerated, making it more impressive than it actually is.

[0523] A "revised headline" is the title of an article that has been rewritten to remove exaggerated language and be based on facts.

[0524] An "image" is a still image or generated visual data displayed to visually complement information.

[0525] A "summary" is a concise compilation of information, a process of extracting the main points and shortening them.

[0526] "Reliability" refers to the quality that demonstrates that information is based on facts and is accurate.

[0527] To implement this invention, a system is constructed using a terminal owned by the user and a server as a central control unit for analyzing the information. The user obtains the necessary information by selecting any information source on the internet. The terminal transmits this information to the server, which analyzes the information using natural language processing technology and extracts the main topics.

[0528] The server detects, removes, and corrects exaggerated expressions in the information. Furthermore, it generates corrected headlines based on the analysis results and selects or generates relevant images. For this purpose, the server utilizes software modules such as spaCy for natural language processing and Transformers for text summarization. Image analysis techniques are also applied to the analysis of visual data.

[0529] The user's device displays a revised headline and a reliable image, allowing the user to make decisions based on accurate and reliable information. For example, if a user selects an article titled "Shocking! Huge Space Discovered in City," the system analyzes the article and provides the user with a more accurate headline such as "New Art Space Opens in City."

[0530] The AI ​​generation model is designed to generate accurate summaries by using the prompt: "Summarize the following English sentence, removing any exaggerations: Shocking! A huge space has been discovered in the city."

[0531] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0532] Step 1:

[0533] The user interacts with the device to select a specific information source. Input includes the user's clicks and the selected URL. This action allows the device to retrieve the URL of the selected information source, which triggers the next information gathering process.

[0534] Step 2:

[0535] The device accesses the selected URL and retrieves the HTML data of the webpage. The input is an HTTP request based on the URL, which outputs the webpage data. Specifically, this involves retrieving data over the network using libraries such as the requests library.

[0536] Step 3:

[0537] The device parses the acquired HTML data and extracts the text content. The input is HTML data, and the output is extracted text data. The HTML is parsed using tools like BeautifulSoup, and the text is identified.

[0538] Step 4:

[0539] The terminal sends the extracted text data to the server. The input is text data, and the output is the network transmission to the server. This data serves as the material for the next analysis step.

[0540] Step 5:

[0541] The server analyzes the received text data using natural language processing and extracts the main topics. The input is text data, and topics are identified by analyzing them using tools like spaCy. A list of the main topics is provided as output.

[0542] Step 6:

[0543] The server uses a generative AI model to detect exaggerated expressions and generate corrected headlines. The input consists of a topic list and text data, from which exaggerations are removed. This process results in corrected headlines as output. The prompt used is "Remove exaggerations from the following English text and summarize its content."

[0544] Step 7:

[0545] The server performs image analysis to select or generate relevant images. Input includes text and a topic, and it uses an image database to select appropriate images. Alternatively, it may generate new images, resulting in appropriate image data as output.

[0546] Step 8:

[0547] The server sends the corrected headline and image data to the user's terminal. The input consists of the corrected headline and image data, and the output is the completion of data transfer to the user's terminal. This information is displayed on the user's interface, ensuring accurate information retrieval.

[0548] 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.

[0549] This invention provides an information processing system that incorporates an emotion engine that recognizes user emotions and optimizes information based on those emotions. The system acquires and analyzes content based on links to web pages and articles selected by the user. Furthermore, it aims to improve the user experience by recognizing user emotion data in real time and optimizing the displayed information.

[0550] When a user clicks a link on a web page, the device retrieves content data from that URL. This content data includes HTML, meta information, images, etc. The retrieved content data is sent to the server. Simultaneously, the device's emotion engine recognizes the user's emotions and sends that emotion data to the server.

[0551] The server uses a natural language processing module to analyze content data, extracting key topics and detecting exaggerations. This generates more accurate headlines. Furthermore, based on sentiment data from the sentiment engine, the server optimizes information according to the user's emotions. For example, if the user is excited, the server selects visually appealing, vibrant images. If the user is relaxed, it provides calming images and easy-to-read content.

[0552] For example, if a user clicks on a link with a headline like "Shocking! Major Incident in XX" on a news site, the emotion engine recognizes that the user is surprised. Based on this emotion data, the server displays a revised headline, such as "New Information Released in XX," removing the exaggeration, and selects relevant images. This improvement allows users to receive information that matches their emotions, resulting in a high-quality information experience.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] When a user clicks a link on a web page, the user's selection process begins. The user takes the first step to obtain information that interests them.

[0556] Step 2:

[0557] The device retrieves the content data of the selected URL. This data includes HTML text, meta information, and related media such as images.

[0558] Step 3:

[0559] The device's emotion engine recognizes the user's emotional state in real time. The emotional state is determined using facial recognition and voice tone analysis to capture the user's current psychological state.

[0560] Step 4:

[0561] The device sends the acquired content data and user sentiment data to the main server. This data is used as foundational data for optimizing the information.

[0562] Step 5:

[0563] The server analyzes the received content data. Using natural language processing techniques, it extracts key topics and keywords from the content and detects exaggerations.

[0564] Step 6:

[0565] The server uses sentiment data to analyze the results and adjust the headlines and displayed content to match the user's emotions. For example, if the emotion is positive, a more friendly tone of headline will be used.

[0566] Step 7:

[0567] The server uses image analysis technology to select appropriate image data. Furthermore, by selecting images that match the user's emotions, visually relevant content is provided.

[0568] Step 8:

[0569] The server sends the corrected headline and selected image data to the terminal. This prepares the terminal to display optimized information to the user.

[0570] Step 9:

[0571] The device displays new headlines and image data to the user. The user can then decide whether to read the article in detail based on information that resonates with their emotions.

[0572] (Example 2)

[0573] 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."

[0574] In recent years, the amount of information available on the internet has continued to increase, making it difficult for users to select the most relevant information from the vast amount available. Furthermore, some information contains exaggerated claims, which can unnecessarily affect users' emotions. This can lead to unpleasant information experiences and potentially cause erroneous decision-making. To address this challenge, it is necessary to provide information that is appropriately optimized based on the user's emotions.

[0575] 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.

[0576] In this invention, the server includes means for analyzing content data using natural language processing and detecting exaggerated expressions, means for recognizing the user's emotions in real time using an emotion recognition device, and means for selecting or generating relevant image data based on the emotion data. This makes it possible to optimize and provide information in a way that is appropriate to the user's emotions.

[0577] A "user" refers to an individual or organization that operates an information system, selects content, or provides sentiment data.

[0578] A "selection operation" refers to an action performed by a user to choose specific content from a source of information.

[0579] "Information source" refers to the source of digital content such as web pages and articles that users choose to access.

[0580] "Content data" refers to datasets such as HTML documents, metadata, and images obtained from information sources.

[0581] An "emotion recognition device" refers to a technology or device that determines a user's emotional state based on data acquired from them.

[0582] The term "main server" refers to the core computer system that analyzes acquired data, generates optimized information, and provides it to users.

[0583] "Natural language processing" refers to computer technology that analyzes digital text and audio data to extract intent and information.

[0584] "Exaggeration" refers to expressions that excessively emphasize or distort facts or information.

[0585] "Emotional data" refers to information that indicates the user's current emotional state.

[0586] "Image data" refers to digital images and related data used to provide visual information displayed to the user.

[0587] To implement this invention, it is necessary to construct an information processing system that acquires content data from a user-selected information source, optimizes that data, and provides it to the user. Specifically, the following system components are required.

[0588] User

[0589] The user selects a link to a specific webpage or article through their device. At this time, the user's emotions are collected in real time by an emotion recognition device.

[0590] terminal

[0591] The device includes a user interface (UI) that detects user selections and software such as a web browser to retrieve content from selected information sources. The device also includes an emotion recognition device that acquires emotion data in real time from the user's facial expressions and voice tone and transmits it to a server.

[0592] server

[0593] The server is the core component, analyzing the acquired content data using natural language processing techniques. This processing includes tokenization, part-of-speech identification, extraction of key topics, and detection of exaggerated language. Furthermore, the server optimizes content based on sentiment data. This includes selecting or generating relevant image data according to the user's emotions. For example, it might select and insert a vibrant image from a picture database.

[0594] As a concrete example, consider a scenario where a user clicks on a surprising headline on a news website. An emotion recognition device detects the user's surprise and sends it to the server. The server then enhances the user's informational experience by providing an optimized, less exaggerated revised headline along with associated image data.

[0595] As an example of a prompt, use the text: "Explain an optimization algorithm that modifies headlines and selects relevant images based on sentiment data when a user is surprised on a news site."

[0596] This system enables the optimization of information while taking user emotions into consideration, allowing users to have a higher quality information experience.

[0597] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0598] Step 1:

[0599] The user clicks a link to a specific webpage on their device. This provides the URL of the linked page as input data. The device then uses this URL to send an HTTP request and retrieves the content data (HTML, meta information, images, etc.) of the target webpage. This retrieved content data becomes the input for the next step.

[0600] Step 2:

[0601] An emotion recognition device installed in the terminal analyzes the user's facial expression data and voice tone in real time to acquire emotion data. Input includes the user's facial expressions and voice data, and output is the user's emotional state (e.g., "surprise," "joy"). This emotion data becomes additional data when transmitted to the server.

[0602] Step 3:

[0603] The acquired content data and sentiment data are sent from the terminal to the server. The input for transmission is the content data and sentiment data, and the output is that this data is stored on the server and ready for analysis.

[0604] Step 4:

[0605] The server analyzes incoming content data using natural language processing techniques. The input is content data; during the analysis process, the data is tokenized, parts of speech are identified, and key topics are extracted. Hypocrisy is also detected. The output consists of the analyzed structured data and the detected hyperbolic expressions.

[0606] Step 5:

[0607] The server optimizes information to suit the user's emotions based on the analyzed data and received sentiment data. Inputs include analyzed data and sentiment data, while output includes adjusted and modified headlines and image data that matches the user's emotions. Specifically, it selects relevant images from the database and prepares them for display on the user's screen.

[0608] Step 6:

[0609] The server sends optimized content back to the device, where it is displayed to the user. The input at this point is optimized data, and the output is the screen display received by the user. The device receives the data from the server, renders it appropriately, and improves the user's information experience.

[0610] (Application Example 2)

[0611] 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."

[0612] In modern information processing systems, there is a problem in that information is not sufficiently optimized to respond to user emotions, resulting in a lack of individualized user experience. In particular, when users are in different emotional states, the inability to provide appropriate information or content can lead to decreased user satisfaction.

[0613] 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.

[0614] In this invention, the server includes means for recognizing the user's emotional state using an emotion recognition device, means for optimizing the displayed content based on the recognized emotion data, and means for extracting key themes and correcting exaggerated expressions. This enables the provision of optimal information tailored to the user's emotions.

[0615] A "device for detecting user selection actions" is a technology that detects a user's behavior of selecting specific content from an information source.

[0616] "Information source" refers to the medium, including websites and digital platforms, from which content data is obtained.

[0617] A "device for acquiring content data" is a technology for collecting data from selected information sources.

[0618] A "central server" is a core computing system that collects and analyzes acquired data and provides optimal information.

[0619] A "device for extracting key themes" is a technology for identifying and extracting important topics from analyzed content data.

[0620] A "device that detects and corrects exaggerated expressions and generates corrected headlines" is a technology for identifying and correcting exaggerated expressions within content data.

[0621] "An apparatus for selecting or generating image data related to content" refers to a technology for selecting or creating new visual information related to content data.

[0622] A "device for presenting to the user" refers to technology for visually displaying corrected headlines and image data to the user.

[0623] An "emotion recognition device" is a device that detects and evaluates a user's emotional state in real time.

[0624] A "device for optimizing displayed content" is a technology that adjusts and optimizes the content displayed based on the user's emotions.

[0625] This invention is an information processing system that optimizes content according to the user's emotional state. It begins when the user's terminal detects a selection operation and transmits the acquired content data to a central server. The central server analyzes the obtained content data, extracts the main themes, and corrects exaggerated expressions. This generates appropriate headlines and associated image data.

[0626] Furthermore, a key feature of this system is the inclusion of an emotion recognition device that evaluates the user's emotional state in real time. Based on this emotion data, the server dynamically selects and displays the most appropriate content for the user. The content can provide calming images depending on the user's relaxed state, or stimulating images depending on their excited state.

[0627] The specific technologies used include OpenCV and Microsoft Azure Emotion API for emotion recognition, and TensorFlow and Scikit-learn for content optimization. This will improve the quality of the user's viewing experience.

[0628] For example, if a user is wearing smart glasses and listening to calming music while strolling through nature, the emotion recognition device will detect a relaxed emotion and provide related calming images and music. On the other hand, if the user is excited while jogging in the city, the emotion recognition device will recommend fast-paced music and energetic images.

[0629] An example of a prompt sentence to input into a generative AI model is, "What content do you recommend for relaxation?" By using such prompt sentences, the system can present the most suitable content in real time.

[0630] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0631] Step 1:

[0632] The device detects the user's selection action. When the user clicks a link to a specific information source, a selection action is made, and the device detects the URL of that source. Using this as input, the device begins collecting relevant content data.

[0633] Step 2:

[0634] The device retrieves content data from the selected information source. Using the detected URL, it downloads content data such as HTML and images from the web. It then prepares this retrieved content data for transmission to the server.

[0635] Step 3:

[0636] The server analyzes the received data. Using a natural language processing module, it analyzes the text within the content and extracts the main themes. This identifies which topics are particularly important and provides input for subsequent processing.

[0637] Step 4:

[0638] The server detects exaggerated language and generates a revised headline. Natural language processing techniques identify exaggerated language within the content and create a new headline that mitigates it. This revised headline is then used in the next step.

[0639] Step 5:

[0640] The server selects or generates image data relevant to the content. Based on the analysis results, it selects the most suitable image from the database or generates a new one. At this stage, it is determined what visual information the user will receive.

[0641] Step 6:

[0642] The emotion recognition device recognizes the user's emotions in real time. Using sensors and cameras attached to the device, it analyzes the user's facial expressions, heart rate, and other data to detect their emotional state. This information becomes input data used in the next step.

[0643] Step 7:

[0644] The server optimizes displayed content based on recognized emotion data. It dynamically selects content according to emotions; for example, it provides calming images and music when the user is relaxed, and stimulating content when the user is excited. A generative AI model is used to achieve real-time content optimization. This optimized content is then presented to the user as the final output.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] [Fourth Embodiment]

[0649] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0650] 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.

[0651] 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).

[0652] 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.

[0653] 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.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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".

[0662] This invention provides an information processing system that enables users to accurately understand information on the internet. Specifically, it aims to display accurate headlines and associated image data, free from exaggerated expressions, by acquiring and analyzing content data based on links to web pages and articles selected by the user.

[0663] First, when a user clicks on a link on a webpage, the content data associated with that link is retrieved by the user's device. This data includes text, images, and metadata. The retrieved data is sent to the server, which then receives the content data.

[0664] Next, the server analyzes the content using natural language processing technology. This analysis extracts key topics from the text and detects exaggerations that could mislead users. After detecting exaggerations, it generates corrected headlines based on accurate information and provides them to the user.

[0665] Furthermore, the server uses image analysis technology to select relevant image data. It also generates new images as needed to appropriately complement the information. The resulting headlines and thumbnail images are sent to the terminal, and the user is shown this accurate information.

[0666] For example, if a user clicks on a link on a news site that reads "Shocking! Huge space discovered in the city," the system analyzes the content and generates a more accurate headline such as "New art space opens in the city." This allows the user to properly understand the content and obtain information conveniently. This system is designed to help users avoid misunderstandings on the internet and make informed decisions based on high-quality information.

[0667] The following describes the processing flow.

[0668] Step 1:

[0669] A user clicks a link on a web page. The user takes the first step to access information that interests them.

[0670] Step 2:

[0671] The device retrieves content data from the linked URL. The retrieved data includes HTML text, metadata, and associated image data.

[0672] Step 3:

[0673] The terminal sends the acquired content data to the main server. The terminal transmits the data over the network, and the main server prepares to receive it.

[0674] Step 4:

[0675] The server analyzes the received content data. Using a natural language processing module, the server extracts key topics and keywords from the text while detecting exaggerations.

[0676] Step 5:

[0677] The server generates accurate headlines based on extracted information, eliminating exaggerations. It creates user-friendly titles while maintaining content accuracy.

[0678] Step 6:

[0679] The server uses image analysis technology to select appropriate image data or generate new images as needed. This completes the content and prepares it to provide users with visual information.

[0680] Step 7:

[0681] The server sends the generated headline and image data to the terminal. The server then sends the final analysis results back to the terminal, preparing to provide accurate information to the user.

[0682] Step 8:

[0683] The device displays new headlines and thumbnail images to the user. The user can use this to decide whether to read further about information that interests them, based on accurate and reliable information.

[0684] (Example 1)

[0685] 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".

[0686] In recent years, with the increasing volume of information on the internet, users are often misled by exaggerated or inaccurate information. In this situation, there is a need for a system that allows users to quickly obtain accurate and reliable information. However, current systems lack sufficient functionality to automatically correct exaggerated expressions and select or generate appropriate image data related to the content, making it difficult for users to correctly understand the information.

[0687] 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.

[0688] In this invention, the server includes means for detecting user selection operations, means for acquiring digital information from selected information sources, and means for transmitting the acquired digital information to a central device. This enables the user to quickly obtain accurate and unexaggerated information.

[0689] A "user" is the entity that operates the system and makes selections to obtain information.

[0690] A "selection operation" is an action performed by a user to specify a particular source of information.

[0691] An "information source" is a place on the internet where information such as web pages and articles are provided.

[0692] "Digital information" is a general term for all forms of data, including text, images, and metadata, obtained from information sources.

[0693] A "central device" is a computing device that receives and processes acquired digital information.

[0694] "Analysis" is the process of extracting key topics from digital information and is a fundamental process for detecting exaggerations.

[0695] "Main topics" refer to elements that hold central significance within digital information and are important to the user.

[0696] "Exaggeration" refers to words or phrases that are emphasized more than usual and may mislead the recipient of the information.

[0697] A "title" is a short, modified sentence that provides a summary of the information the user will see.

[0698] "Visual data" refers to images and diagrams used to visually supplement the content of information.

[0699] A "natural language processing module" is a program that analyzes digital information to understand human language.

[0700] "Image analysis technology" refers to technologies for evaluating, selecting, and generating visual data.

[0701] This information processing system is primarily composed of users, terminals, and a central device (server). Users select links to web pages and online articles, and their role is to retrieve the digital information on their terminals. This retrieved digital information includes text data, image data, and metadata. This data is transmitted to the central device via the internet.

[0702] The central system first uses a natural language processing module to process the received digital information. This module leverages Python's natural language processing libraries to analyze text data containing key topics. In particular, it uses Python's NLTK and spaCy to understand the semantic structure of the text and detect exaggerations.

[0703] If exaggerated language is detected, the central system uses a generative AI model to correct it and generate an accurate title. Specifically, it utilizes the generative AI model and takes a prompt message such as, "Remove exaggerated language from this text and generate an accurate title," to create an appropriate title.

[0704] Furthermore, the central system uses image analysis technology in conjunction with image data. This allows it to select appropriate visual data to complement the content of the digital information and generate visual elements as needed. The generation of visual elements utilizes methods that leverage generative AI models.

[0705] Finally, the processed, accurate title and selected or generated visual data are sent to the device and displayed to the user. By viewing this information, the user can understand the content based on accurate information without exaggeration.

[0706] This system aims to enable users to obtain information efficiently and accurately on the internet, and is achieved through a combination of a generative AI model and the use of prompt statements.

[0707] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0708] Step 1:

[0709] The user selects a link to be the source of information. The selected link allows the device to retrieve digital information from that source. This digital information includes text data, image data, and metadata. Given a link as input, digital information is generated as output.

[0710] Step 2:

[0711] The terminal transmits the acquired digital information to the server (central device). Transmission takes place via the internet, ensuring the digital information reaches the server quickly and accurately. Here, the input from the terminal is digital information, and the output is the digital information transferred to the server.

[0712] Step 3:

[0713] The server analyzes the received digital information. It uses a natural language processing module to extract the main topics within the text. This process utilizes Python's natural language processing library. The main topics extracted from the text data are obtained as output.

[0714] Step 4:

[0715] The server uses a generative AI model to correct detected exaggerations and generate an accurate title. Specifically, it prompts the generative AI model with the message, "Remove exaggerations from this text and generate an accurate title," and outputs the corrected title.

[0716] Step 5:

[0717] The server uses image analysis technology to select or generate relevant visual data. If necessary, it utilizes a generative AI model to generate new visual elements. This process takes image data or a generation prompt as input and outputs visual data for display to the user.

[0718] Step 6:

[0719] The server sends the corrected title and selected or generated visual data to the terminal. The terminal provides the user with accurate information by displaying the received data. Here, the input is the data from the server, and the output is the accurate information provided to the user.

[0720] (Application Example 1)

[0721] 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".

[0722] Much of the information provided on the internet contains exaggerated language, making it difficult for users to obtain accurate information. Furthermore, exaggeration can lead to users misunderstanding the content, highlighting the need to improve the accuracy of information. In particular, news and article headlines are often exaggerated, making it difficult for users to judge the reliability of the information.

[0723] 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.

[0724] In this invention, the server includes means for detecting user selection operations, means for acquiring information from selected information sources, means for transmitting the acquired information to a central control unit, means for analyzing the information at the central control unit and extracting key topics, means for detecting and correcting exaggerated expressions and generating corrected headlines, means for selecting or generating images related to the information, and means for summarizing the acquired information and generating accurate headlines. This enables the user to obtain accurate and reliable information.

[0725] "User selection" refers to the act of a user choosing a specific source of information on an interface.

[0726] An "information source" refers to the source of data, including web pages and articles, that exist on the internet.

[0727] "Information" refers to digital content, including text, images, and metadata.

[0728] A "central control unit" is a computer server that receives and processes information.

[0729] "Analysis" is the act of analyzing the content of information in detail using natural language processing techniques.

[0730] "Main topics" refer to the most important topics among the analyzed information.

[0731] "Exaggerated expression" refers to a way of expressing information that is excessively exaggerated, making it more impressive than it actually is.

[0732] A "revised headline" is the title of an article that has been rewritten to remove exaggerated language and be based on facts.

[0733] An "image" is a still image or generated visual data displayed to visually complement information.

[0734] A "summary" is a concise compilation of information, a process of extracting the main points and shortening them.

[0735] "Reliability" refers to the quality that demonstrates that information is based on facts and is accurate.

[0736] To implement this invention, a system is constructed using a terminal owned by the user and a server as a central control unit for analyzing the information. The user obtains the necessary information by selecting any information source on the internet. The terminal transmits this information to the server, which analyzes the information using natural language processing technology and extracts the main topics.

[0737] The server detects, removes, and corrects exaggerated expressions in the information. Furthermore, it generates corrected headlines based on the analysis results and selects or generates relevant images. For this purpose, the server utilizes software modules such as spaCy for natural language processing and Transformers for text summarization. Image analysis techniques are also applied to the analysis of visual data.

[0738] The user's device displays a revised headline and a reliable image, allowing the user to make decisions based on accurate and reliable information. For example, if a user selects an article titled "Shocking! Huge Space Discovered in City," the system analyzes the article and provides the user with a more accurate headline such as "New Art Space Opens in City."

[0739] The AI ​​generation model is designed to generate accurate summaries by using the prompt: "Summarize the following English sentence, removing any exaggerations: Shocking! A huge space has been discovered in the city."

[0740] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0741] Step 1:

[0742] The user interacts with the device to select a specific information source. Input includes the user's clicks and the selected URL. This action allows the device to retrieve the URL of the selected information source, which triggers the next information gathering process.

[0743] Step 2:

[0744] The device accesses the selected URL and retrieves the HTML data of the webpage. The input is an HTTP request based on the URL, which outputs the webpage data. Specifically, this involves retrieving data over the network using libraries such as the requests library.

[0745] Step 3:

[0746] The device parses the acquired HTML data and extracts the text content. The input is HTML data, and the output is extracted text data. The HTML is parsed using tools like BeautifulSoup, and the text is identified.

[0747] Step 4:

[0748] The terminal sends the extracted text data to the server. The input is text data, and the output is the network transmission to the server. This data serves as the material for the next analysis step.

[0749] Step 5:

[0750] The server analyzes the received text data using natural language processing and extracts the main topics. The input is text data, and topics are identified by analyzing them using tools like spaCy. A list of the main topics is provided as output.

[0751] Step 6:

[0752] The server uses a generative AI model to detect exaggerated expressions and generate corrected headlines. The input consists of a topic list and text data, from which exaggerations are removed. This process results in corrected headlines as output. The prompt used is "Remove exaggerations from the following English text and summarize its content."

[0753] Step 7:

[0754] The server performs image analysis to select or generate relevant images. Input includes text and a topic, and it uses an image database to select appropriate images. Alternatively, it may generate new images, resulting in appropriate image data as output.

[0755] Step 8:

[0756] The server sends the corrected headline and image data to the user's terminal. The input consists of the corrected headline and image data, and the output is the completion of data transfer to the user's terminal. This information is displayed on the user's interface, ensuring accurate information retrieval.

[0757] 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.

[0758] This invention provides an information processing system that incorporates an emotion engine that recognizes user emotions and optimizes information based on those emotions. The system acquires and analyzes content based on links to web pages and articles selected by the user. Furthermore, it aims to improve the user experience by recognizing user emotion data in real time and optimizing the displayed information.

[0759] When a user clicks a link on a web page, the device retrieves content data from that URL. This content data includes HTML, meta information, images, etc. The retrieved content data is sent to the server. Simultaneously, the device's emotion engine recognizes the user's emotions and sends that emotion data to the server.

[0760] The server uses a natural language processing module to analyze content data, extracting key topics and detecting exaggerations. This generates more accurate headlines. Furthermore, based on sentiment data from the sentiment engine, the server optimizes information according to the user's emotions. For example, if the user is excited, the server selects visually appealing, vibrant images. If the user is relaxed, it provides calming images and easy-to-read content.

[0761] For example, if a user clicks on a link with a headline like "Shocking! Major Incident in XX" on a news site, the emotion engine recognizes that the user is surprised. Based on this emotion data, the server displays a revised headline, such as "New Information Released in XX," removing the exaggeration, and selects relevant images. This improvement allows users to receive information that matches their emotions, resulting in a high-quality information experience.

[0762] The following describes the processing flow.

[0763] Step 1:

[0764] When a user clicks a link on a web page, the user's selection process begins. The user takes the first step to obtain information that interests them.

[0765] Step 2:

[0766] The device retrieves the content data of the selected URL. This data includes HTML text, meta information, and related media such as images.

[0767] Step 3:

[0768] The device's emotion engine recognizes the user's emotional state in real time. The emotional state is determined using facial recognition and voice tone analysis to capture the user's current psychological state.

[0769] Step 4:

[0770] The device sends the acquired content data and user sentiment data to the main server. This data is used as foundational data for optimizing the information.

[0771] Step 5:

[0772] The server analyzes the received content data. Using natural language processing techniques, it extracts key topics and keywords from the content and detects exaggerations.

[0773] Step 6:

[0774] The server uses sentiment data to analyze the results and adjust the headlines and displayed content to match the user's emotions. For example, if the emotion is positive, a more friendly tone of headline will be used.

[0775] Step 7:

[0776] The server uses image analysis technology to select appropriate image data. Furthermore, by selecting images that match the user's emotions, visually relevant content is provided.

[0777] Step 8:

[0778] The server sends the corrected headline and selected image data to the terminal. This prepares the terminal to display optimized information to the user.

[0779] Step 9:

[0780] The device displays new headlines and image data to the user. The user can then decide whether to read the article in detail based on information that resonates with their emotions.

[0781] (Example 2)

[0782] 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".

[0783] In recent years, the amount of information available on the internet has continued to increase, making it difficult for users to select the most relevant information from the vast amount available. Furthermore, some information contains exaggerated claims, which can unnecessarily affect users' emotions. This can lead to unpleasant information experiences and potentially cause erroneous decision-making. To address this challenge, it is necessary to provide information that is appropriately optimized based on the user's emotions.

[0784] 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.

[0785] In this invention, the server includes means for analyzing content data using natural language processing and detecting exaggerated expressions, means for recognizing the user's emotions in real time using an emotion recognition device, and means for selecting or generating relevant image data based on the emotion data. This makes it possible to optimize and provide information in a way that is appropriate to the user's emotions.

[0786] A "user" refers to an individual or organization that operates an information system, selects content, or provides sentiment data.

[0787] A "selection operation" refers to an action performed by a user to choose specific content from a source of information.

[0788] "Information source" refers to the source of digital content such as web pages and articles that users choose to access.

[0789] "Content data" refers to datasets such as HTML documents, metadata, and images obtained from information sources.

[0790] An "emotion recognition device" refers to a technology or device that determines a user's emotional state based on data acquired from them.

[0791] The term "main server" refers to the core computer system that analyzes acquired data, generates optimized information, and provides it to users.

[0792] "Natural language processing" refers to computer technology that analyzes digital text and audio data to extract intent and information.

[0793] "Exaggeration" refers to expressions that excessively emphasize or distort facts or information.

[0794] "Emotional data" refers to information that indicates the user's current emotional state.

[0795] "Image data" refers to digital images and related data used to provide visual information displayed to the user.

[0796] To implement this invention, it is necessary to construct an information processing system that acquires content data from a user-selected information source, optimizes that data, and provides it to the user. Specifically, the following system components are required.

[0797] User

[0798] The user selects a link to a specific webpage or article through their device. At this time, the user's emotions are collected in real time by an emotion recognition device.

[0799] terminal

[0800] The device includes a user interface (UI) that detects user selections and software such as a web browser to retrieve content from selected information sources. The device also includes an emotion recognition device that acquires emotion data in real time from the user's facial expressions and voice tone and transmits it to a server.

[0801] server

[0802] The server is the core component, analyzing the acquired content data using natural language processing techniques. This processing includes tokenization, part-of-speech identification, extraction of key topics, and detection of exaggerated language. Furthermore, the server optimizes content based on sentiment data. This includes selecting or generating relevant image data according to the user's emotions. For example, it might select and insert a vibrant image from a picture database.

[0803] As a concrete example, consider a scenario where a user clicks on a surprising headline on a news website. An emotion recognition device detects the user's surprise and sends it to the server. The server then enhances the user's informational experience by providing an optimized, less exaggerated revised headline along with associated image data.

[0804] As an example of a prompt, use the text: "Explain an optimization algorithm that modifies headlines and selects relevant images based on sentiment data when a user is surprised on a news site."

[0805] This system enables the optimization of information while taking user emotions into consideration, allowing users to have a higher quality information experience.

[0806] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0807] Step 1:

[0808] The user clicks a link to a specific webpage on their device. This provides the URL of the linked page as input data. The device then uses this URL to send an HTTP request and retrieves the content data (HTML, meta information, images, etc.) of the target webpage. This retrieved content data becomes the input for the next step.

[0809] Step 2:

[0810] An emotion recognition device installed in the terminal analyzes the user's facial expression data and voice tone in real time to acquire emotion data. Input includes the user's facial expressions and voice data, and output is the user's emotional state (e.g., "surprise," "joy"). This emotion data becomes additional data when transmitted to the server.

[0811] Step 3:

[0812] The acquired content data and sentiment data are sent from the terminal to the server. The input for transmission is the content data and sentiment data, and the output is that this data is stored on the server and ready for analysis.

[0813] Step 4:

[0814] The server analyzes incoming content data using natural language processing techniques. The input is content data; during the analysis process, the data is tokenized, parts of speech are identified, and key topics are extracted. Hypocrisy is also detected. The output consists of the analyzed structured data and the detected hyperbolic expressions.

[0815] Step 5:

[0816] The server optimizes information to suit the user's emotions based on the analyzed data and received sentiment data. Inputs include analyzed data and sentiment data, while output includes adjusted and modified headlines and image data that matches the user's emotions. Specifically, it selects relevant images from the database and prepares them for display on the user's screen.

[0817] Step 6:

[0818] The server sends optimized content back to the device, where it is displayed to the user. The input at this point is optimized data, and the output is the screen display received by the user. The device receives the data from the server, renders it appropriately, and improves the user's information experience.

[0819] (Application Example 2)

[0820] 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".

[0821] In modern information processing systems, there is a problem in that information is not sufficiently optimized to respond to user emotions, resulting in a lack of individualized user experience. In particular, when users are in different emotional states, the inability to provide appropriate information or content can lead to decreased user satisfaction.

[0822] 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.

[0823] In this invention, the server includes means for recognizing the user's emotional state using an emotion recognition device, means for optimizing the displayed content based on the recognized emotion data, and means for extracting key themes and correcting exaggerated expressions. This enables the provision of optimal information tailored to the user's emotions.

[0824] A "device for detecting user selection actions" is a technology that detects a user's behavior of selecting specific content from an information source.

[0825] "Information source" refers to the medium, including websites and digital platforms, from which content data is obtained.

[0826] A "device for acquiring content data" is a technology for collecting data from selected information sources.

[0827] A "central server" is a core computing system that collects and analyzes acquired data and provides optimal information.

[0828] A "device for extracting key themes" is a technology for identifying and extracting important topics from analyzed content data.

[0829] A "device that detects and corrects exaggerated expressions and generates corrected headlines" is a technology for identifying and correcting exaggerated expressions within content data.

[0830] "An apparatus for selecting or generating image data related to content" refers to a technology for selecting or creating new visual information related to content data.

[0831] A "device for presenting to the user" refers to technology for visually displaying corrected headlines and image data to the user.

[0832] An "emotion recognition device" is a device that detects and evaluates a user's emotional state in real time.

[0833] A "device for optimizing displayed content" is a technology that adjusts and optimizes the content displayed based on the user's emotions.

[0834] This invention is an information processing system that optimizes content according to the user's emotional state. It begins when the user's terminal detects a selection operation and transmits the acquired content data to a central server. The central server analyzes the obtained content data, extracts the main themes, and corrects exaggerated expressions. This generates appropriate headlines and associated image data.

[0835] Furthermore, a key feature of this system is the inclusion of an emotion recognition device that evaluates the user's emotional state in real time. Based on this emotion data, the server dynamically selects and displays the most appropriate content for the user. The content can provide calming images depending on the user's relaxed state, or stimulating images depending on their excited state.

[0836] The specific technologies used include OpenCV and Microsoft Azure Emotion API for emotion recognition, and TensorFlow and Scikit-learn for content optimization. This will improve the quality of the user's viewing experience.

[0837] For example, if a user is wearing smart glasses and listening to calming music while strolling through nature, the emotion recognition device will detect a relaxed emotion and provide related calming images and music. On the other hand, if the user is excited while jogging in the city, the emotion recognition device will recommend fast-paced music and energetic images.

[0838] An example of a prompt sentence to input into a generative AI model is, "What content do you recommend for relaxation?" By using such prompt sentences, the system can present the most suitable content in real time.

[0839] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0840] Step 1:

[0841] The device detects the user's selection action. When the user clicks a link to a specific information source, a selection action is made, and the device detects the URL of that source. Using this as input, the device begins collecting relevant content data.

[0842] Step 2:

[0843] The device retrieves content data from the selected information source. Using the detected URL, it downloads content data such as HTML and images from the web. It then prepares this retrieved content data for transmission to the server.

[0844] Step 3:

[0845] The server analyzes the received data. Using a natural language processing module, it analyzes the text within the content and extracts the main themes. This identifies which topics are particularly important and provides input for subsequent processing.

[0846] Step 4:

[0847] The server detects exaggerated language and generates a revised headline. Natural language processing techniques identify exaggerated language within the content and create a new headline that mitigates it. This revised headline is then used in the next step.

[0848] Step 5:

[0849] The server selects or generates image data relevant to the content. Based on the analysis results, it selects the most suitable image from the database or generates a new one. At this stage, it is determined what visual information the user will receive.

[0850] Step 6:

[0851] The emotion recognition device recognizes the user's emotions in real time. Using sensors and cameras attached to the device, it analyzes the user's facial expressions, heart rate, and other data to detect their emotional state. This information becomes input data used in the next step.

[0852] Step 7:

[0853] The server optimizes displayed content based on recognized emotion data. It dynamically selects content according to emotions; for example, it provides calming images and music when the user is relaxed, and stimulating content when the user is excited. A generative AI model is used to achieve real-time content optimization. This optimized content is then presented to the user as the final output.

[0854] 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.

[0855] 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.

[0856] 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 robot 414.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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."

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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 to be incorporated by reference.

[0875] The following is further disclosed regarding the embodiments described above.

[0876] (Claim 1)

[0877] A means of detecting user selection operations,

[0878] Means for obtaining content data from selected information sources,

[0879] A means for transmitting acquired content data to the main server,

[0880] A method for analyzing content data on the main server and extracting key topics,

[0881] A means for detecting and correcting exaggerated expressions to generate headlines,

[0882] Means for selecting or generating image data related to content,

[0883] A means of displaying the corrected headline and image data to the user,

[0884] An information processing system that includes this.

[0885] (Claim 2)

[0886] The information processing system according to claim 1, wherein the main server uses a natural language processing module to detect exaggerated expressions from analyzed content data.

[0887] (Claim 3)

[0888] The information processing system according to claim 1, which evaluates or generates image data to be displayed to the user using image analysis technology.

[0889] "Example 1"

[0890] (Claim 1)

[0891] A means of detecting user selection operations,

[0892] Means for obtaining digital information from selected sources,

[0893] A means for transmitting acquired digital information to a central device,

[0894] A means of analyzing digital information with a central device and extracting key topics,

[0895] A means for detecting and correcting exaggerated expressions to generate a title,

[0896] Means for selecting or generating visual data related to digital information,

[0897] A means of displaying the corrected title and visual data to the user,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, wherein the central device uses a natural language processing module to detect exaggerated expressions from analyzed digital information.

[0901] (Claim 3)

[0902] The system according to claim 1, which evaluates or generates visual data to be displayed to the user using image analysis technology.

[0903] "Application Example 1"

[0904] (Claim 1)

[0905] A means of detecting user selection operations,

[0906] Means of obtaining information from selected sources,

[0907] A means for transmitting acquired information to a central control unit,

[0908] A means for analyzing information in a central control unit and extracting key topics,

[0909] A means for detecting and correcting exaggerated expressions to generate headlines,

[0910] Means for selecting or generating images related to information,

[0911] A means of displaying the revised headline and image to the user,

[0912] A means of summarizing acquired information and generating accurate headlines,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, wherein a central control unit uses a natural language processing module to detect exaggerated expressions from the analyzed information.

[0916] (Claim 3)

[0917] The system according to claim 1, which evaluates or generates images to be displayed to the user using image analysis technology.

[0918] "Example 2 of combining an emotion engine"

[0919] (Claim 1)

[0920] A means of detecting user selection operations,

[0921] Means for obtaining content data from selected information sources,

[0922] A means of recognizing the user's emotions in real time using an emotion recognition device installed in the terminal,

[0923] A means for transmitting acquired content data and emotion data to the main server,

[0924] A method for analyzing content data using natural language processing on the main server and extracting key topics,

[0925] A means for detecting and correcting exaggerated expressions to generate headlines,

[0926] Means for selecting or generating image data related to content based on sentiment data,

[0927] A means for displaying the revised headline and selected or generated image data to the user,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, wherein the main server uses a natural language processing module to detect exaggerated expressions from the analyzed content data and corrects the headline based on sentiment data.

[0931] (Claim 3)

[0932] The system according to claim 1, which determines image data to be displayed to the user based on sentiment data and evaluates or generates it using image analysis technology.

[0933] "Application example 2 when combining with an emotional engine"

[0934] (Claim 1)

[0935] A device for detecting user selection operations,

[0936] A device that acquires content data from selected information sources,

[0937] A device that transmits the acquired data to a central server,

[0938] A device that analyzes content data on a central server and extracts the main themes,

[0939] A device that detects and corrects exaggerated language to generate headlines,

[0940] A device for selecting or generating image data related to the content,

[0941] A device that presents the corrected headline and image data to the user,

[0942] A device that recognizes the user's emotional state using an emotion recognition device,

[0943] A device that optimizes displayed content based on recognized emotion data,

[0944] A system that includes this.

[0945] (Claim 2)

[0946] The system according to claim 1, wherein a central server uses a natural language processing module to detect exaggerated expressions from analyzed content data.

[0947] (Claim 3)

[0948] The system according to claim 1, which evaluates or generates image data to be presented to the user using image analysis technology and dynamically selects it according to the user's emotional state. [Explanation of Symbols]

[0949] 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

1. A means for detecting user selection operations, Means for obtaining content data from selected information sources, A means for transmitting acquired content data to the main server, A method for analyzing content data on the main server and extracting key topics, A means for detecting and correcting exaggerated expressions to generate headlines, Means for selecting or generating image data related to content, A means of displaying the corrected headline and image data to the user, An information processing system that includes this.

2. The information processing system according to claim 1, wherein the main server uses a natural language processing module to detect exaggerated expressions from the analyzed content data.

3. The information processing system according to claim 1, which evaluates or generates image data to be displayed to the user using image analysis technology.

Images