System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving user setting information; means for filtering specific content based on the user setting information; means for regenerating the filtered content to be provided to a user; and means for transmitting the regenerated content to a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's Internet usage environment, users are often exposed to numerous advertisements and specific content, which can detract from the user experience. In particular, advertisements related to sexual or appearance-related insecurities, as well as articles on politics, religion, and ideology, can be offensive to users. Furthermore, users may be unintentionally placed into specific segmentations, which can hinder privacy and personal freedom of access to information. There is a need to solve these problems and provide an environment in which users can comfortably use the Internet. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: A means for receiving user setting information is provided, allowing the user to specify in advance the types of content they do not want; A means for the server to filter specific content based on this setting information; A means for regenerating the filtered content and providing it to the user; A system is further provided that includes a means for transmitting the regenerated content to the user's terminal; A system is also provided that has a means for receiving the user's desired content settings, analyzing the content of the web page based on the settings, generating and applying filtering rules to enable the user to browse comfortably; A local database for storing user setting information is provided on the terminal, and a means for synchronizing this information with the server is provided, ensuring that the filtering desired by the user is performed.

[0006] "User" refers to an individual or organization that uses this system to view web pages.

[0007] "User setting information" refers to information including the filtering conditions and settings for content desired by the user.

[0008] "Server" refers to a computer system that processes requests received from user terminals and filters and reproduces the required content.

[0009] "Terminal" refers to a device (e.g., a PC, smartphone, or tablet) that a user uses to view a web page.

[0010] "Content" refers to the information and elements displayed on a web page (e.g., advertisements, articles, links).

[0011] "Filtering" refers to the act or process of removing or hiding certain content that a user does not want to see.

[0012] "Regeneration" refers to the process of reconstructing the content of a web page after it has been filtered.

[0013] The term "local database" refers to a data storage area that exists within a user terminal and that stores user setting information.

[0014] "Synchronization" refers to the process of matching data between a user terminal and a server.

[0015] "Filtering rules" refer to the criteria or rules used to filter certain content.

[0016] "Analysis" refers to the process of examining and breaking down the content of a web page in detail to understand its structure and elements.

[0017] "Receiving" refers to the server or terminal acquiring data from the outside. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention is a browser system that filters out unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with the user, the terminal, and the server.

[0040] User Settings

[0041] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, or ideology. The user's selections are stored in a local database on the device and synchronized with the server.

[0042] Access to the web page

[0043] When a user enters a URL into a browser to access a specific web page, the request is sent from the device to the server, which receives the request and retrieves the target web page.

[0044] Content Acquisition and Analysis

[0045] The server analyzes the HTML content of the retrieved web page. This analysis is performed using a generation AI. The generation AI analyzes the tag structure of the HTML document and identifies each element (e.g., advertisement, article link). It also identifies the category of content to be filtered based on user settings.

[0046] Content Filtering

[0047] The server creates a list of content elements to be filtered, and generates filtering rules based on this list. These rules include hiding specific HTML elements and CSS selectors (e.g., display: none;).

[0048] Regenerate and send content

[0049] The server regenerates the content by applying the generated filtering rules, and transmits the regenerated content to the user's terminal.

[0050] User Browsing

[0051] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0052] Specific examples

[0053] For example, consider the case where a user accesses a news site. The user has set the browser to hide political articles. This setting information is sent from the device to the server. The server retrieves the news site's HTML and analyzes it using generative AI. From the analysis results, political articles are identified and filtering rules for those elements are generated. The generated filtering rules (e.g., the political article section { display: none;}) are applied, and the regenerated content is sent to the user. The user's browser displays this filtered page, allowing the user to browse the news site without political articles.

[0054] In this way, users can avoid unwanted content and enjoy a comfortable browsing experience. This system protects users' privacy and allows them to freely access information.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] When a user first launches the browser, they select the categories of content they want to filter from the initial settings screen, such as ads related to sexual complexes or articles related to politics, religion, or ideology. These settings allow users to customize their content experience.

[0058] Step 2:

[0059] The device stores the user-selected setting information in a local database, and simultaneously synchronizes the setting information with the server.

[0060] Step 3:

[0061] A user attempts to access a specific web page in a browser, for example, by entering the URL of a news site.

[0062] Step 4:

[0063] The terminal sends an access request to the server, along with the user's setting information.

[0064] Step 5:

[0065] The server retrieves a corresponding web page based on the received access request, and this web page is subject to filtering.

[0066] Step 6:

[0067] The server then uses generative AI to analyze the HTML content of the retrieved web page, including identifying each element on the page, such as advertisements, articles, and links.

[0068] Step 7:

[0069] The server determines which categories of content to hide based on the filtering criteria selected by the user in the initial settings, such as political articles or sexually insensitive ads.

[0070] Step 8:

[0071] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0072] Step 9:

[0073] The server applies the generated filtering rules to create regenerated content, and during regeneration, unnecessary content is deleted or hidden.

[0074] Step 10:

[0075] The server transmits the regenerated filtered content to the terminal.

[0076] Step 11:

[0077] The device renders the received filtered content as a web page.

[0078] Step 12:

[0079] Users can browse web pages with filtered content, hiding political articles and advertisements related to sexual complexes, providing a comfortable browsing experience.

[0080] Example 1

[0081] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0082] In today's Internet usage, users are frequently confronted with unwanted content. This problem not only significantly impairs the user's browsing experience, but can also cause mental stress and a loss of concentration due to information overload. Furthermore, from the perspective of privacy protection, displaying unwanted advertisements and articles based on a user's interests is problematic. Conventional content filtering methods are unable to provide sophisticated filtering tailored to individual user needs and can only provide general-purpose filtering. Given this background, there is a growing need for a system that achieves more accurate content filtering based on the user's individual settings.

[0083] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0084] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for analyzing the HTML content of the web page using a generative AI model, and means for generating filtering rules based on the analysis. This enables highly accurate filtering based on the needs of each user, protects users from unwanted content, and provides a comfortable and secure internet usage environment.

[0085] "User setting information" is information for a user to specify categories and conditions for filtering specific content.

[0086] A "generative AI model" is an artificial intelligence model used to analyze the HTML content of a web page and generate filtering rules.

[0087] A "filtering rule" is a rule that includes CSS or JavaScript code for hiding specific content based on user preference information.

[0088] "Regenerated content" is the content of a web page that has been reconstructed to be presented to a user after applying filtering rules.

[0089] A "local database" is a database stored in a user's terminal and is used to store user setting information.

[0090] A "prompt sentence" is input text that instructs a generative AI model to perform a specific analysis or generate rules.

[0091] An "HTTP request" is an Internet communication request message sent to a server to retrieve a web page.

[0092] An "HTML document" is a file written in HTML, a markup language for describing the structure of a web page.

[0093] A "CSS rule" is a style rule that specifies the appearance of HTML elements, and includes settings such as "display: none;" to hide certain elements.

[0094] MODE FOR CARRYING OUT THE INVENTION

[0095] This invention relates to a browser system that filters unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with a user, a terminal, and a server. Specific embodiments are described below.

[0096] Retrieving and saving user settings

[0097] When users first launch the browser, they are shown an initial setup screen where they can select the categories of content they want to filter. For example, they can choose to filter out advertisements related to sexual complexes or articles on politics, religion, or ideology. These selections are made to customize the user's desired Internet usage environment. The configuration information is stored in a local database on the device and later synchronized with the server.

[0098] Specifically, local storage such as an SQLite database is used to store user settings, which are synchronized with the server every time the browser is launched and kept up to date.

[0099] Requesting a web page and retrieving its content

[0100] When a user enters a URL into the address bar of a browser to access a specific web page, the request is first sent from the device to the server, which then retrieves the target web page based on this request.

[0101] Specifically, an HTTP client library (e.g., Python's requests library) is used to retrieve the HTML document of the web page, which is then processed within the server for analysis.

[0102] Content analysis and filtering rule generation

[0103] The server analyzes the HTML document of the retrieved web page using a generative AI model. The generative AI model analyzes the tag structure of the HTML document and identifies each element (e.g., advertisements or article links). It also identifies the content category to be filtered based on user settings and generates filtering rules to apply to it.

[0104] Examples of prompts for generative AI models include:

[0105] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0106] Regenerating and sending filtered content

[0107] The server regenerates the web page content by applying the generated filtering rules. The regenerated content is a filtered HTML document that does not contain information that the user does not want. The server then sends this regenerated content to the terminal.

[0108] Specifically, the server inserts the generated CSS rules into the HTML, reconstructs the DOM, and then sends the reconstructed HTML to the terminal as an HTTP response.

[0109] Rendering Filtered Content

[0110] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0111] Specifically, the device's browser engine parses the received HTML document, generates a DOM, applies CSS rules to render the page, and displays the filtered web page to the user.

[0112] In this way, the system achieves highly accurate filtering based on the individual needs of users, providing a comfortable and secure Internet usage environment.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Processing flow

[0115] The program process for this system is divided into the following steps:

[0116] Step 1: Get user configuration information

[0117] When users first launch the browser, they are shown an initial setup screen where they select the categories of content they want to filter, and this selection is stored in a local database on the device and then synchronized with the server.

[0118] Input: User's content filtering settings (e.g. sexual content, politics, religion, etc.)

[0119] Data processing: Save selected setting information to a local database (e.g., SQLite)

[0120] Output: Saved user settings information

[0121] Specific operation: Once the user completes the settings, the browser saves the settings information in a local database and notifies the server that the settings have been changed.

[0122] Step 2: Sending a web page request

[0123] When a user types a specific URL into the address bar of their browser, the request is first sent from the device to the server, which initiates a filtering process based on the user's settings.

[0124] Input: The URL entered by the user

[0125] Data processing: Formatting URL information as an HTTP request

[0126] Output: HTTP request sent to the server

[0127] Specific operation: When you enter a URL in the browser's address bar and press Enter, the device generates an HTTP request and sends it to the server.

[0128] Step 3: Retrieving web page content

[0129] The server retrieves the HTML content of the specified web page based on the received request. It uses an HTTP client library to retrieve the desired web page.

[0130] Input: The URL requested by the user

[0131] Data processing: Convert the URL into an HTTP request and obtain the HTML of the web page.

[0132] Output: The retrieved HTML document

[0133] Specific operation: The server uses Python's requests library to access the URL and retrieve the HTML document.

[0134] Step 4: Analyzing content and generating filtering rules

[0135] The server analyzes the retrieved HTML document using a generative AI model, sends a prompt to the generative AI model, and generates filtering rules.

[0136] Input: HTML document, user settings information

[0137] Data processing: Send prompts to the generative AI model and obtain analysis results

[0138] Output: Generated filtering rules

[0139] Specific operation: The server sends the following prompt to the generation AI model to generate filtering rules:

[0140] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0141] Step 5: Regenerate filtered content

[0142] The server then applies the generated filtering rules to regenerate the content of the web page, resulting in an HTML document that excludes the unwanted content.

[0143] Input: Generated filtering rules, original HTML document

[0144] Data processing: Apply filtering rules to HTML and regenerate content

[0145] Output: Regenerated HTML document

[0146] What happens: The server applies filtering rules to the original HTML and reconstructs the DOM.

[0147] Step 6: Sending filtered content

[0148] The server sends the regenerated filtered content to the terminal, where the user can view it.

[0149] Input: Regenerated HTML document

[0150] Data processing: Formatting the regenerated HTML document as an HTTP response

[0151] Output: HTTP response sent to the device

[0152] Specific operation: The server sends the regenerated HTML document to the terminal as an HTTP response.

[0153] Step 7: Rendering the filtered content

[0154] The device then renders the received filtered content as a web page, allowing the user to view the web page with the unwanted content removed.

[0155] Input: The filtered HTML document received from the server

[0156] Data processing: Parse HTML documents and generate DOM

[0157] Output: Rendered web page

[0158] What happens: The device's browser engine parses the received HTML document, applies CSS rules, and renders the page.

[0159] In this way, the system can achieve highly accurate filtering based on the individual needs of users, providing a comfortable and safe Internet usage environment.

[0160] (Application example 1)

[0161] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0162] In conventional Internet browsing systems, users frequently encounter unwanted content, making it difficult to ensure safe and comfortable web browsing. Furthermore, content filtering is insufficient, especially on mobile devices, significantly impairing the user experience. Therefore, there is a need for a method that can quickly analyze web page content in real time based on user-specified filtering rules and appropriately filter out unwanted content.

[0163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0164] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a URL of a website specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a document object model, means for applying filtering to the constructed document object model based on the user setting information, and means for transmitting the filtered content to the user's terminal for display. This allows the user to enjoy a safe and comfortable web browsing experience with unnecessary content filtered out in real time.

[0165] "User setting information" is information for specifying categories of content that the user does not want.

[0166] "URL" is an abbreviation for Uniform Resource Locator, and is a character string that indicates the address of a web page.

[0167] "HTML content" refers to the HTML documents that make up a web page and the elements contained within them.

[0168] A "server" is a central computer system that provides data over a network.

[0169] The "Document Object Model (DOM)" is a model for representing HTML documents as a hierarchical structure, making it easier to manipulate them programmatically.

[0170] A "filtering rule" is a rule for preventing certain content from being displayed based on conditions specified by the user.

[0171] "Parsing" is the process of reading an HTML document as code and identifying each element.

[0172] "Regeneration" means reconstructing the content of a web page after applying the filtering rules.

[0173] "Local Database" means a database stored on a User's device that is used to store User settings and other important information.

[0174] A "terminal" is a computing device (e.g., smartphone, tablet, computer) that is directly operated by a user.

[0175] This invention is a system for filtering content that a user does not want to view, thereby providing a comfortable and safe Internet usage environment. The basic configuration of the system includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a website URL specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a Document Object Model (DOM), means for applying filtering to the constructed DOM based on the user setting information, and means for transmitting the filtered content to the user's terminal for display.

[0176] First, when a user launches a browser for the first time, they enter user configuration information to specify categories of content they do not want. This user configuration information is then saved in the device's local database and synchronized with the server. When the user accesses a specific website, the device sends the specified URL to the server, which retrieves the corresponding HTML content. The server then uses a library such as BeautifulSoup to analyze the retrieved HTML content and construct a DOM. Filtering rules are applied to the constructed DOM to hide the unwanted content specified by the user.

[0177] After applying the filtering rules, the server regenerates the content of the web page and sends the filtered content to the user's device. The device receives the regenerated content, allowing the user to view it with unnecessary content removed.

[0178] A concrete example is when a user visits a news site. If the user selects to filter "violent content," the server retrieves the HTML of the specified news site, analyzes the DOM to identify violent articles and images, and filters them. Finally, the user is presented with a clean news site with no violent content.

[0179] An example prompt is:

[0180] "Using SafeBrowse, I visited a specific news site. I selected 'Violent Content' as the filtering category. The URL for the news site is 'http: / / example.com / news'. Please explain how SafeBrowse filters this page."

[0181] This invention allows users to enjoy a filtered, safe and comfortable web browsing experience.

[0182] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0183] Step 1:

[0184] The user launches the browser and selects the categories of unwanted content on the initial setup screen. The information entered here is user preference information, which specifies the types of content the user wants to filter while browsing. This preference information is saved in the device's local database and is then synchronized with the server. The entered data is user preference information, and data processing is performed to save it in the local database.

[0185] Step 2:

[0186] When a user accesses a particular website using a browser, the device receives the specified URL. This URL is the address of the website the user wants to visit. The input is the URL entered by the user, and data processing is performed to send this information to the server. The output is a URL request to the server.

[0187] Step 3:

[0188] The server retrieves the HTML content of the website based on the specified URL. Using the above request URL as input, it sends an HTTP request to retrieve the target HTML document. The output is the HTML content.

[0189] Step 4:

[0190] The server parses the retrieved HTML content and constructs a Document Object Model (DOM). The input is the retrieved HTML content, and a library such as BeautifulSoup is used to parse the HTML code and generate a DOM tree. The output is the constructed DOM tree. Specifically, the process converts HTML tags into a tree structure and identifies each element.

[0191] Step 5:

[0192] The server applies filtering to the constructed DOM tree based on user configuration information. The input is the user configuration information and the constructed DOM tree, and it applies user-specified filtering rules (e.g., removing violent content). The output is the filtered DOM tree.

[0193] Step 6:

[0194] The server applies the filtering rules and then recreates the web page content. The input is the filtered DOM tree, and the server recreates the HTML document based on the DOM content. The output is the recreated HTML content.

[0195] Step 7:

[0196] The server sends the regenerated HTML content to the user's terminal. The input is the regenerated HTML content, which is sent to the user's terminal as an HTTP response. The output is the HTML content converted into a format that can be displayed on the user's terminal.

[0197] Step 8:

[0198] The terminal displays the regenerated HTML content it receives. The input is the regenerated HTML content sent from the server, which is rendered in the terminal's browser and displayed to the user. This process allows the user to view a web page with the specified unwanted content filtered out. The output is the filtered web page displayed to the user.

[0199] The above are the processing steps of this system.

[0200] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0201] This invention is a browser system that combines an emotion engine that recognizes the user's emotions. In addition to the basic functions of receiving user settings, filtering, regenerating, and providing specific content, it also has the ability to analyze the user's emotional state in real time and dynamically change filtering rules. This system provides a comfortable Internet usage environment that is tailored to the user's psychological state.

[0202] User Settings

[0203] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, and ideology. This configuration information is stored in a local database by the device and synchronized with the server.

[0204] Access to the web page

[0205] When a user attempts to access a specific web page using a browser, the terminal sends an access request to the server, along with the user setting information.

[0206] Content Acquisition and Analysis

[0207] The server retrieves the target web page based on the received access request and analyzes its HTML content. This analysis is performed using generative AI to identify each element on the page, such as advertisements, articles, and links.

[0208] Emotion recognition by emotion engine

[0209] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes emotions in real time from the user's facial expressions and voice. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice and recognizes their emotional state, such as positive or negative.

[0210] Content Filtering

[0211] The server identifies content elements to be filtered based on user settings and the emotion analysis results of the emotion engine. If the emotion engine recognizes the user's emotion as negative, specific content (e.g., articles or advertisements that may cause stress) will be filtered as well.

[0212] Creating and dynamically changing filtering rules

[0213] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS, and dynamically changes the filtering rules based on the analysis results of the emotion engine.

[0214] Regenerate and send content

[0215] The server applies the generated filtering rules to generate regenerated content and transmits it to the terminal.

[0216] User Browsing

[0217] The device then renders the received filtered content as a web page. The user then browses the web page, which displays content filtered based on real-time emotion recognition and user settings. For example, if the user's emotion is negative, articles or advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[0218] Specific examples

[0219] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0220] This system allows users to have the optimal browsing environment according to their own emotions and preferences.

[0221] The processing flow will be explained below.

[0222] Step 1:

[0223] When a user first launches the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter. This could include, for example, ads related to sexual complexes or articles related to politics, religion, or ideology. This setting allows filtering based on the user's preferences.

[0224] Step 2:

[0225] The device stores the user's selected settings in a local database, which is then synchronized with the server.

[0226] Step 3:

[0227] When a user accesses a specific web page using a browser, the access request is sent from the terminal to the server, which also includes user setting information.

[0228] Step 4:

[0229] The server retrieves the target web page based on the received access request, and the HTML content of this web page is analyzed.

[0230] Step 5:

[0231] The server uses a generation AI to analyze the retrieved HTML content, which identifies each element on the web page, such as advertisements, articles, and links.

[0232] Step 6:

[0233] The device is equipped with an emotion engine that recognizes the user's emotions. The device uses a camera and microphone to analyze the user's facial expressions and voice in real time, and recognizes positive and negative emotional states.

[0234] Step 7:

[0235] The server identifies content elements to be filtered based on user settings and the analysis results of the emotion engine. For example, if the emotion engine recognizes the user's emotion as negative, articles and advertisements that may cause stress are additionally filtered.

[0236] Step 8:

[0237] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0238] Step 9:

[0239] The server applies these filtering rules to regenerate the content of the web page, and the regenerated content has unnecessary elements deleted or hidden.

[0240] Step 10:

[0241] The server transmits the regenerated filtered content to the terminal.

[0242] Step 11:

[0243] The device then renders the received filtered content as a web page, allowing the user to view the web page with the content filtered based on real-time emotion recognition and user settings.

[0244] Step 12:

[0245] For example, if a user visits a news site and the emotion engine recognizes the user's emotion as negative, political articles and articles that may cause stress will be filtered out from the news site, preventing these articles from appearing and allowing the user to enjoy a comfortable and stress-free browsing experience.

[0246] Example 2

[0247] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0248] Existing Internet browser systems provide the ability to filter content based on a user's specific preferences, but they are unable to dynamically change content filtering rules to take into account the user's real-time emotional state, making it difficult for users to obtain an optimal Internet usage environment that reflects their psychological state at any given time.

[0249] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0250] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for using an emotion engine that analyzes the user's emotional state in real time, means for dynamically changing filtering rules based on the emotion analysis results, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal, thereby making it possible to provide an Internet usage environment that corresponds to the user's real-time emotional state.

[0251] "User setting information" is information about the categories of content to be filtered, which is set by the user when the user starts up the Internet browser for the first time.

[0252] "Means for filtering specific content" refers to a function that excludes content that should not be displayed based on user setting information.

[0253] The "emotion engine" is a system that analyzes the user's facial expressions and voice and recognizes the user's emotional state in real time.

[0254] "Means for dynamically changing filtering rules based on emotion analysis results" is a function that changes filtering rules each time according to the emotional state recognized by the emotion engine.

[0255] "Regenerated content" refers to the content of a web page that has been reconstructed after applying filtering rules.

[0256] A "terminal including a storage device" is a user's device that has a storage function for saving data such as user setting information.

[0257] A "server" is a central processing unit that receives a web page access request from a user, retrieves, analyzes, filters, and regenerates the content, and sends the results to a terminal.

[0258] A "storage device for saving user setting information" is a storage mechanism within the device for saving setting information specified by the user.

[0259] "Means for analyzing the content of a web page" refers to the ability to analyze the HTML and other code of a web page and identify each element within the page.

[0260] "Filtering rules" are a set of rules and conditions that determine whether content is displayed or hidden.

[0261] This invention is a system that recognizes a user's emotions and dynamically filters Internet content based on those emotions. This system aims to provide an environment in which users can comfortably use the Internet.

[0262] Specifically, the system includes a means for receiving user setting information, a means for filtering specific content, an emotion engine for analyzing the user's emotional state in real time, a means for dynamically changing filtering rules based on the emotion analysis results, a means for regenerating the filtered content, and a means for transmitting the regenerated content to the user's terminal.

[0263] Hardware and software used

[0264] To implement this system, the following hardware and software are required:

[0265] User device: A computer or smart device equipped with a camera, microphone, and a local database

[0266] Server: a central processing unit for high-performance analysis and data processing

[0267] Emotion Engine: Software that analyzes the user's facial expressions and voice

[0268] Generative AI: The model used to analyze content (e.g., GPT-4)

[0269] Communication protocol: Network communication technology such as HTTP / HTTPS

[0270] System processing overview

[0271] 1. User Settings: When a user launches the browser for the first time, an initial setup screen appears. The user selects the categories of content they do not want to see (e.g., sexual content, politics, religion, etc.). This setting information is stored in a local database on the device and synchronized with the server.

[0272] 2. Accessing a web page: When a user attempts to access a specific web page, an access request is sent from the terminal to the server, along with user setting information.

[0273] 3. Content retrieval and analysis: The server retrieves the HTML content of the web page based on the access request. It uses a generative AI model (e.g., GPT-4) to analyze the HTML content and identify each content element, such as an advertisement, article, or link.

[0274] 4. Emotion recognition using an emotion engine: The emotion engine installed on the device uses the camera and microphone to analyze the user's facial expressions and voice in real time and recognize positive and negative emotional states.

[0275] 5. Content filtering: The server identifies content elements to filter based on user preferences and the analysis results of the emotion engine. If a negative emotional state is detected, certain content (e.g., articles or advertisements that may cause stress) will be additionally filtered.

[0276] 6. Generation and dynamic modification of filtering rules: The server generates filtering rules for the identified content elements. The filtering rules may be dynamically modified based on the analysis results of the emotion engine.

[0277] 7. Regenerate and send content: The server applies the filtering rules and sends the regenerated content to the terminal.

[0278] 8. User browsing: The device renders the filtered content as a web page, and the user browses the web page, with content based on real-time emotion recognition and user preferences.

[0279] Specific examples

[0280] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0281] Prompt Sentence Examples

[0282] Here are some example prompts to input to a generative AI model:

[0283] Please provide a step-by-step description of the process a browser system uses to enforce filtering when user sentiment is negative, starting from saving the user's preferences to finally displaying filtered content to the user.

[0284] This prompt allows the generative AI model to explain each processing step in detail.

[0285] In this way, the present invention can provide an optimal Internet usage environment based on the user's feelings and preferences.

[0286] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0287] Step 1: Enter and save your user settings

[0288] When a user first launches the browser, they are presented with an initial setup screen. They select the categories of content they do not want to view (e.g., sexual content, politics, religion, etc.). This information is stored in a local database on the device and serves as input. The settings are then synchronized with the server and serve as output. For example, if a user chooses to hide the "Politics" category, that setting is stored on the device and sent to the server.

[0289] Step 2: Access the web page

[0290] When a user attempts to access a specific web page, the request is sent from the terminal to the server. The user setting information stored in the terminal's database is also sent here, and this becomes input. The server receives the access request and outputs the URL of the web page and the user setting information.

[0291] Step 3: Acquire and parse content

[0292] Based on the received access request, the server retrieves the HTML content of the specified web page from the Internet. The retrieved HTML content is used as input and analyzed using a generative AI model (e.g., GPT-4). This analysis identifies each element, such as advertisements, articles, and links, and outputs the analysis results. For example, all advertisements and articles on a news site are identified.

[0293] Step 4: Emotion Recognition with the Emotion Engine

[0294] The device is equipped with an emotion engine that recognizes the user's emotions. It uses a camera and microphone to analyze the user's facial expressions and voice in real time and recognizes positive and negative emotional states. The user's facial expressions and voice are input, and the emotion analysis results are output. For example, if the user's facial expression is smiling, it is judged as positive, and if they are frowning, it is judged as negative.

[0295] Step 5: Filtering content

[0296] The server identifies content elements to be filtered based on user settings and the emotion engine's analysis results. User settings and emotion analysis results are input, and a list of content to be filtered is output. For example, if a user hides the "Politics" category and the emotion is negative, certain news articles will be filtered.

[0297] Step 6: Creating and dynamically changing filtering rules

[0298] The server generates filtering rules for the identified content elements. These rules include hiding settings using HTML and CSS. The list of content to be filtered is input, and the filtering rules are output. In addition, the filtering rules may be dynamically changed based on the analysis results of the emotion engine. For example, if the emotion changes to a positive one, the filtered content will be redisplayed.

[0299] Step 7: Regenerate and submit content

[0300] The server applies the generated filtering rules to create regenerated content. The filtering rules and the original HTML content are input, and regenerated HTML content is output. This is then sent to the terminal. For example, content with CSS rules applied to hide specific HTML tags is generated and sent to the terminal.

[0301] Step 8: User Browsing

[0302] The device renders the received filtered content as a web page. The transmitted regenerated content is input and the rendered web page is output. The user then browses the web page, which displays content filtered based on emotion recognition and user settings. For example, if the user is in a negative emotional state, news articles and advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[0303] (Application example 2)

[0304] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0305] In modern content distribution services, many users browse content from various categories, which can often cause psychological stress. In particular, when a user is experiencing negative emotions, content that exacerbates those emotions can make the user's experience even more unpleasant. In such situations, users need to receive content that is appropriately filtered according to their emotions.

[0306] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user setting information, means for filtering specific content, emotion recognition means for recognizing the user's emotion in real time, means for dynamically changing the filtering rules based on the emotion analysis result by the emotion recognition means, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal. This enables the user to receive filtered content that is suited to their emotional state in real time.

[0307] "User setting information" is information about the category of content that the user selects on the initial setting screen of a browser or application to display or hide.

[0308] The "content filtering means" is a means having a function of selecting specific content and determining whether to display or hide it based on user setting information.

[0309] The "emotion recognition means" is a means having the function of analyzing the user's emotions in real time from their facial expressions and tone of voice, and recognizing their emotional state.

[0310] The "means for dynamically changing filtering rules" refers to a means having a function for changing in real time the rules for adding or removing content to be filtered based on the emotion analysis results obtained by the emotion recognition means.

[0311] The "content regeneration means" is a means having the function of applying the filtering rules defined above and reconstructing the content to be provided to the user.

[0312] The "content transmitting means" is a means having a function of transmitting the regenerated content to the user's terminal.

[0313] A "local database" is a database that is installed on a user terminal and that saves and temporarily stores user setting information.

[0314] A "server" is a central management system that receives access requests from user terminals, analyzes and filters the content, and provides the regenerated content to the user.

[0315] This invention relates to a system that recognizes a user's emotions in real time and filters content according to the user's psychological state. This system mainly comprises the following elements: a means for receiving user setting information, a means for filtering specific content, an emotion recognition means for recognizing the user's emotions, a means for dynamically changing filtering rules, a means for providing the regenerated content to the user, and a means for transmitting the regenerated content to the user's terminal.

[0316] System configuration and operation

[0317] 1. Receiving user settings information:

[0318] When a user first uses the system, they enter content filtering configuration information, which specifies the categories of content they do not want to see. This configuration information is stored in a local database on the device and synchronized with the server.

[0319] 2. Real-time emotion recognition:

[0320] The device utilizes a built-in camera and microphone to capture the user's facial expressions and voice, and then analyzes emotions in real time using emotion recognition, which is powered by a pre-trained generative AI model.

[0321] 3. Integrating emotion data and user preference information:

[0322] The server dynamically changes the filtering rules based on the received user setting information and real-time emotional states detected by the emotion recognition means. The filtering rules include HTML and CSS settings for hiding specific content.

[0323] 4. Content Acquisition and Analysis:

[0324] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is identified by specific categories. Based on these analysis results, the server generates filtering rules to provide content appropriate to the user.

[0325] 5. Reproducing and Submitting Content:

[0326] The server regenerates the filtered content based on the generated filtering rules and transmits the content to the user's terminal, which then renders the received content and displays it to the user.

[0327] Hardware and software configuration

[0328] The main hardware and software used in this system are as follows:

[0329] Camera and microphone: Captures the user's facial expressions and voice.

[0330] Emotion recognition: Using generative AI models trained using machine learning frameworks such as TensorFlow.

[0331] Server: Acquires content, analyzes it, generates filtering rules, and regenerates content.

[0332] Local Database: A database for storing user configuration information and synchronizing it with the server.

[0333] Specific examples

[0334] For example, if a user is using a video streaming service and has set horror movies to be hidden, and the emotion recognition means analyzes the user's emotion as "sad," the server will filter out not only horror movie content but also movies that may evoke sad emotions. As a result, the user can watch safe and comfortable content that is adapted to their emotional state.

[0335] Prompt Sentence Examples

[0336] "Generate a model that analyzes emotions from a user's facial expressions and voice in real time."

[0337] "Generate an algorithm that dynamically changes filtering rules based on the user's emotional state."

[0338] "Build a system that filters content that may cause stress based on emotion recognition results."

[0339] Such a system allows users to enjoy content that is optimal for their emotional state, providing a stress-free experience.

[0340] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0341] Step 1:

[0342] When a user first uses the system, they enter their user configuration information, select the content categories they do not want to see (e.g., violence, horror, politics), and the information is stored in a local database on the device and synchronized with the server.

[0343] Input: Content category selection by user.

[0344] Output: Saved user settings information.

[0345] Step 2:

[0346] The device uses a built-in camera and microphone to capture the user's facial expressions and voice in real time.

[0347] Input: User's facial expression data, voice data.

[0348] Output: Captured facial and speech data.

[0349] Step 3:

[0350] The device analyzes the captured data using emotion recognition means – for example, a generative AI model using TensorFlow – to recognize the user's emotions in real time.

[0351] Input: Captured facial expression data, audio data.

[0352] Data processing: Sentiment analysis is performed using generative AI models.

[0353] Output: Perceived emotional state (e.g., positive, negative).

[0354] Step 4:

[0355] The device sends the analyzed emotional state to the server, and the server dynamically generates and modifies filtering rules based on the received user settings and emotion recognition results, including HTML and CSS settings to hide specific content (e.g., articles or videos that may cause stress).

[0356] Input: User preference information, perceived emotional state.

[0357] Data processing: Applying algorithms to generate filtering rules.

[0358] Output: The generated filtering rules.

[0359] Step 5:

[0360] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is then identified by specific categories.

[0361] Input: Web page URL, filtering rules.

[0362] Data processing: Analyze web content using a generative AI model and identify it by category.

[0363] Output: Parsed content information.

[0364] Step 6:

[0365] The server then regenerates the parsed content based on the generated filtering rules to create a filtered web page, which involves using HTML and CSS to hide certain elements.

[0366] Input: Parsed content information, filtering rules.

[0367] Data manipulation: Regenerate content by applying HTML and CSS.

[0368] Output: The regenerated filtered web page.

[0369] Step 7:

[0370] The server sends the regenerated web page to the user's device, which renders the received content and displays it to the user.

[0371] Input: The regenerated web page.

[0372] Output: The filtered content that is displayed to the user.

[0373] In this way, filtering adapted to the user's emotional state is performed through a series of steps, providing a stress-free content viewing environment.

[0374] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0375] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0376] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0377] [Second embodiment]

[0378] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0379] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0380] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0381] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0382] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0383] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0384] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0385] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0386] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0387] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0388] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0389] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0390] This invention is a browser system that filters out unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with the user, the terminal, and the server.

[0391] User Settings

[0392] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, or ideology. The user's selections are stored in a local database on the device and synchronized with the server.

[0393] Access to the web page

[0394] When a user enters a URL into a browser to access a specific web page, the request is sent from the device to the server, which receives the request and retrieves the target web page.

[0395] Content Acquisition and Analysis

[0396] The server analyzes the HTML content of the retrieved web page. This analysis is performed using a generation AI. The generation AI analyzes the tag structure of the HTML document and identifies each element (e.g., advertisement, article link). It also identifies the category of content to be filtered based on user settings.

[0397] Content Filtering

[0398] The server creates a list of content elements to be filtered, and generates filtering rules based on this list. These rules include hiding specific HTML elements and CSS selectors (e.g., display: none;).

[0399] Regenerate and send content

[0400] The server regenerates the content by applying the generated filtering rules, and transmits the regenerated content to the user's terminal.

[0401] User Browsing

[0402] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0403] Specific examples

[0404] For example, consider the case where a user accesses a news site. The user has set the browser to hide political articles. This setting information is sent from the device to the server. The server retrieves the news site's HTML and analyzes it using generative AI. From the analysis results, political articles are identified and filtering rules for those elements are generated. The generated filtering rules (e.g., the political article section { display: none;}) are applied, and the regenerated content is sent to the user. The user's browser displays this filtered page, allowing the user to browse the news site without political articles.

[0405] In this way, users can avoid unwanted content and enjoy a comfortable browsing experience. This system protects users' privacy and allows them to freely access information.

[0406] The processing flow will be explained below.

[0407] Step 1:

[0408] When a user first launches the browser, they select the categories of content they want to filter from the initial settings screen, such as ads related to sexual complexes or articles related to politics, religion, or ideology. These settings allow users to customize their content experience.

[0409] Step 2:

[0410] The device stores the user-selected setting information in a local database, and simultaneously synchronizes the setting information with the server.

[0411] Step 3:

[0412] A user attempts to access a specific web page in a browser, for example, by entering the URL of a news site.

[0413] Step 4:

[0414] The terminal sends an access request to the server, along with the user's setting information.

[0415] Step 5:

[0416] The server retrieves a corresponding web page based on the received access request, and this web page is subject to filtering.

[0417] Step 6:

[0418] The server then uses generative AI to analyze the HTML content of the retrieved web page, including identifying each element on the page, such as advertisements, articles, and links.

[0419] Step 7:

[0420] The server determines which categories of content to hide based on the filtering criteria selected by the user in the initial settings, such as political articles or sexually insensitive ads.

[0421] Step 8:

[0422] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0423] Step 9:

[0424] The server applies the generated filtering rules to create regenerated content, and during regeneration, unnecessary content is deleted or hidden.

[0425] Step 10:

[0426] The server transmits the regenerated filtered content to the terminal.

[0427] Step 11:

[0428] The device renders the received filtered content as a web page.

[0429] Step 12:

[0430] Users can browse web pages with filtered content, hiding political articles and advertisements related to sexual complexes, providing a comfortable browsing experience.

[0431] Example 1

[0432] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0433] In today's Internet usage, users are frequently confronted with unwanted content. This problem not only significantly impairs the user's browsing experience, but can also cause mental stress and a loss of concentration due to information overload. Furthermore, from the perspective of privacy protection, displaying unwanted advertisements and articles based on a user's interests is problematic. Conventional content filtering methods are unable to provide sophisticated filtering tailored to individual user needs and can only provide general-purpose filtering. Given this background, there is a growing need for a system that achieves more accurate content filtering based on the user's individual settings.

[0434] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0435] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for analyzing the HTML content of the web page using a generative AI model, and means for generating filtering rules based on the analysis. This enables highly accurate filtering based on the needs of each user, protects users from unwanted content, and provides a comfortable and secure internet usage environment.

[0436] "User setting information" is information for a user to specify categories and conditions for filtering specific content.

[0437] A "generative AI model" is an artificial intelligence model used to analyze the HTML content of a web page and generate filtering rules.

[0438] A "filtering rule" is a rule that includes CSS or JavaScript code for hiding specific content based on user preference information.

[0439] "Regenerated content" is the content of a web page that has been reconstructed to be presented to a user after applying filtering rules.

[0440] A "local database" is a database stored in a user's terminal and is used to store user setting information.

[0441] A "prompt sentence" is input text that instructs a generative AI model to perform a specific analysis or generate rules.

[0442] An "HTTP request" is an Internet communication request message sent to a server to retrieve a web page.

[0443] An "HTML document" is a file written in HTML, a markup language for describing the structure of a web page.

[0444] A "CSS rule" is a style rule that specifies the appearance of HTML elements, and includes settings such as "display: none;" to hide certain elements.

[0445] MODE FOR CARRYING OUT THE INVENTION

[0446] This invention relates to a browser system that filters unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with a user, a terminal, and a server. Specific embodiments are described below.

[0447] Retrieving and saving user settings

[0448] When users first launch the browser, they are shown an initial setup screen where they can select the categories of content they want to filter. For example, they can choose to filter out advertisements related to sexual complexes or articles on politics, religion, or ideology. These selections are made to customize the user's desired Internet usage environment. The configuration information is stored in a local database on the device and later synchronized with the server.

[0449] Specifically, local storage such as an SQLite database is used to store user settings, which are synchronized with the server every time the browser is launched and kept up to date.

[0450] Requesting a web page and retrieving its content

[0451] When a user enters a URL into the address bar of a browser to access a specific web page, the request is first sent from the device to the server, which then retrieves the target web page based on this request.

[0452] Specifically, an HTTP client library (e.g., Python's requests library) is used to retrieve the HTML document of the web page, which is then processed within the server for analysis.

[0453] Content analysis and filtering rule generation

[0454] The server analyzes the HTML document of the retrieved web page using a generative AI model. The generative AI model analyzes the tag structure of the HTML document and identifies each element (e.g., advertisements or article links). It also identifies the content category to be filtered based on user settings and generates filtering rules to apply to it.

[0455] Examples of prompts for generative AI models include:

[0456] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0457] Regenerating and sending filtered content

[0458] The server regenerates the web page content by applying the generated filtering rules. The regenerated content is a filtered HTML document that does not contain information that the user does not want. The server then sends this regenerated content to the terminal.

[0459] Specifically, the server inserts the generated CSS rules into the HTML, reconstructs the DOM, and then sends the reconstructed HTML to the terminal as an HTTP response.

[0460] Rendering Filtered Content

[0461] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0462] Specifically, the device's browser engine parses the received HTML document, generates a DOM, applies CSS rules to render the page, and displays the filtered web page to the user.

[0463] In this way, the system achieves highly accurate filtering based on the individual needs of users, providing a comfortable and secure Internet usage environment.

[0464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0465] Processing flow

[0466] The program process for this system is divided into the following steps:

[0467] Step 1: Get user configuration information

[0468] When users first launch the browser, they are shown an initial setup screen where they select the categories of content they want to filter, and this selection is stored in a local database on the device and then synchronized with the server.

[0469] Input: User's content filtering settings (e.g. sexual content, politics, religion, etc.)

[0470] Data processing: Save selected setting information to a local database (e.g., SQLite)

[0471] Output: Saved user settings information

[0472] Specific operation: Once the user completes the settings, the browser saves the settings information in a local database and notifies the server that the settings have been changed.

[0473] Step 2: Sending a web page request

[0474] When a user types a specific URL into the address bar of their browser, the request is first sent from the device to the server, which initiates a filtering process based on the user's settings.

[0475] Input: The URL entered by the user

[0476] Data processing: Formatting URL information as an HTTP request

[0477] Output: HTTP request sent to the server

[0478] Specific operation: When you enter a URL in the browser's address bar and press Enter, the device generates an HTTP request and sends it to the server.

[0479] Step 3: Retrieving web page content

[0480] The server retrieves the HTML content of the specified web page based on the received request. It uses an HTTP client library to retrieve the desired web page.

[0481] Input: The URL requested by the user

[0482] Data processing: Convert the URL into an HTTP request and obtain the HTML of the web page.

[0483] Output: The retrieved HTML document

[0484] Specific operation: The server uses Python's requests library to access the URL and retrieve the HTML document.

[0485] Step 4: Analyzing content and generating filtering rules

[0486] The server analyzes the retrieved HTML document using a generative AI model, sends a prompt to the generative AI model, and generates filtering rules.

[0487] Input: HTML document, user settings information

[0488] Data processing: Send prompts to the generative AI model and obtain analysis results

[0489] Output: Generated filtering rules

[0490] Specific operation: The server sends the following prompt to the generation AI model to generate filtering rules:

[0491] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0492] Step 5: Regenerate filtered content

[0493] The server then applies the generated filtering rules to regenerate the content of the web page, resulting in an HTML document that excludes the unwanted content.

[0494] Input: Generated filtering rules, original HTML document

[0495] Data processing: Apply filtering rules to HTML and regenerate content

[0496] Output: Regenerated HTML document

[0497] What happens: The server applies filtering rules to the original HTML and reconstructs the DOM.

[0498] Step 6: Sending filtered content

[0499] The server sends the regenerated filtered content to the terminal, where the user can view it.

[0500] Input: Regenerated HTML document

[0501] Data processing: Formatting the regenerated HTML document as an HTTP response

[0502] Output: HTTP response sent to the device

[0503] Specific operation: The server sends the regenerated HTML document to the terminal as an HTTP response.

[0504] Step 7: Rendering the Filtered Content

[0505] The device then renders the received filtered content as a web page, allowing the user to view the web page with the unwanted content removed.

[0506] Input: The filtered HTML document received from the server

[0507] Data processing: Parse HTML documents and generate DOM

[0508] Output: Rendered web page

[0509] What happens: The device's browser engine parses the received HTML document, applies CSS rules, and renders the page.

[0510] In this way, the system can achieve highly accurate filtering based on the individual needs of users, providing a comfortable and safe Internet usage environment.

[0511] (Application example 1)

[0512] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0513] In conventional Internet browsing systems, users frequently encounter unwanted content, making it difficult to ensure safe and comfortable web browsing. Furthermore, content filtering is insufficient, especially on mobile devices, significantly impairing the user experience. Therefore, there is a need for a method that can quickly analyze web page content in real time based on user-specified filtering rules and appropriately filter out unwanted content.

[0514] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0515] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a URL of a website specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a document object model, means for applying filtering to the constructed document object model based on the user setting information, and means for transmitting the filtered content to the user's terminal for display. This allows the user to enjoy a safe and comfortable web browsing experience with unnecessary content filtered out in real time.

[0516] "User setting information" is information for specifying categories of content that the user does not want.

[0517] "URL" is an abbreviation for Uniform Resource Locator, and is a character string that indicates the address of a web page.

[0518] "HTML content" refers to the HTML documents that make up a web page and the elements contained within them.

[0519] A "server" is a central computer system that provides data over a network.

[0520] The "Document Object Model (DOM)" is a model for representing HTML documents as a hierarchical structure, making it easier to manipulate them programmatically.

[0521] A "filtering rule" is a rule for preventing certain content from being displayed based on conditions specified by the user.

[0522] "Parsing" is the process of reading an HTML document as code and identifying each element.

[0523] "Regeneration" means reconstructing the content of a web page after applying the filtering rules.

[0524] "Local Database" means a database stored on a User's device that is used to store User settings and other important information.

[0525] A "terminal" is a computing device (e.g., smartphone, tablet, computer) that is directly operated by a user.

[0526] This invention is a system for filtering content that a user does not want to view, thereby providing a comfortable and safe Internet usage environment. The basic configuration of the system includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a website URL specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a Document Object Model (DOM), means for applying filtering to the constructed DOM based on the user setting information, and means for transmitting the filtered content to the user's terminal for display.

[0527] First, when a user launches a browser for the first time, they enter user configuration information to specify categories of content they do not want. This user configuration information is then saved in the device's local database and synchronized with the server. When the user accesses a specific website, the device sends the specified URL to the server, which retrieves the corresponding HTML content. The server then uses a library such as BeautifulSoup to analyze the retrieved HTML content and construct a DOM. Filtering rules are applied to the constructed DOM to hide the unwanted content specified by the user.

[0528] After applying the filtering rules, the server regenerates the content of the web page and sends the filtered content to the user's device. The device receives the regenerated content, allowing the user to view it with unnecessary content removed.

[0529] A concrete example is when a user visits a news site. If the user selects to filter "violent content," the server retrieves the HTML of the specified news site, analyzes the DOM to identify violent articles and images, and filters them. Finally, the user is presented with a clean news site with no violent content.

[0530] An example prompt is:

[0531] "Using SafeBrowse, I visited a specific news site. I selected 'Violent Content' as the filtering category. The URL for the news site is 'http: / / example.com / news'. Please explain how SafeBrowse filters this page."

[0532] This invention allows users to enjoy a filtered, safe and comfortable web browsing experience.

[0533] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0534] Step 1:

[0535] The user launches the browser and selects the categories of unwanted content on the initial setup screen. The information entered here is user preference information, which specifies the types of content the user wants to filter while browsing. This preference information is saved in the device's local database and is then synchronized with the server. The entered data is user preference information, and data processing is performed to save it in the local database.

[0536] Step 2:

[0537] When a user accesses a particular website using a browser, the device receives the specified URL. This URL is the address of the website the user wants to visit. The input is the URL entered by the user, and data processing is performed to send this information to the server. The output is a URL request to the server.

[0538] Step 3:

[0539] The server retrieves the HTML content of the website based on the specified URL. Using the above request URL as input, it sends an HTTP request to retrieve the target HTML document. The output is the HTML content.

[0540] Step 4:

[0541] The server parses the retrieved HTML content and constructs a Document Object Model (DOM). The input is the retrieved HTML content, and a library such as BeautifulSoup is used to parse the HTML code and generate a DOM tree. The output is the constructed DOM tree. Specifically, the process converts HTML tags into a tree structure and identifies each element.

[0542] Step 5:

[0543] The server applies filtering to the constructed DOM tree based on user configuration information. The input is the user configuration information and the constructed DOM tree, and it applies user-specified filtering rules (e.g., removing violent content). The output is the filtered DOM tree.

[0544] Step 6:

[0545] The server applies the filtering rules and then recreates the web page content. The input is the filtered DOM tree, and the server recreates the HTML document based on the DOM content. The output is the recreated HTML content.

[0546] Step 7:

[0547] The server sends the regenerated HTML content to the user's terminal. The input is the regenerated HTML content, which is sent to the user's terminal as an HTTP response. The output is the HTML content converted into a format that can be displayed on the user's terminal.

[0548] Step 8:

[0549] The terminal displays the regenerated HTML content it receives. The input is the regenerated HTML content sent from the server, which is rendered in the terminal's browser and displayed to the user. This process allows the user to view a web page with the specified unwanted content filtered out. The output is the filtered web page displayed to the user.

[0550] The above are the processing steps of this system.

[0551] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0552] This invention is a browser system that combines an emotion engine that recognizes the user's emotions. In addition to the basic functions of receiving user settings, filtering, regenerating, and providing specific content, it also has the ability to analyze the user's emotional state in real time and dynamically change filtering rules. This system provides a comfortable Internet usage environment that is tailored to the user's psychological state.

[0553] User Settings

[0554] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, and ideology. This configuration information is stored in a local database by the device and synchronized with the server.

[0555] Access to the web page

[0556] When a user attempts to access a specific web page using a browser, the terminal sends an access request to the server, along with the user setting information.

[0557] Content Acquisition and Analysis

[0558] The server retrieves the target web page based on the received access request and analyzes its HTML content. This analysis is performed using generative AI to identify each element on the page, such as advertisements, articles, and links.

[0559] Emotion recognition by emotion engine

[0560] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes emotions in real time from the user's facial expressions and voice. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice and recognizes their emotional state, such as positive or negative.

[0561] Content Filtering

[0562] The server identifies content elements to be filtered based on user settings and the emotion analysis results of the emotion engine. If the emotion engine recognizes the user's emotion as negative, specific content (e.g., articles or advertisements that may cause stress) will be filtered as additional content.

[0563] Creating and dynamically changing filtering rules

[0564] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS, and dynamically changes the filtering rules based on the analysis results of the emotion engine.

[0565] Regenerate and send content

[0566] The server applies the generated filtering rules to generate regenerated content and transmits it to the terminal.

[0567] User Browsing

[0568] The device then renders the received filtered content as a web page. The user then browses the web page, which displays content filtered based on real-time emotion recognition and user settings. For example, if the user's emotion is negative, articles or advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[0569] Specific examples

[0570] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0571] This system allows users to have the optimal browsing environment according to their own emotions and preferences.

[0572] The processing flow will be explained below.

[0573] Step 1:

[0574] When a user first launches the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter. This could include, for example, ads related to sexual complexes or articles related to politics, religion, or ideology. This setting allows filtering based on the user's preferences.

[0575] Step 2:

[0576] The device stores the user's selected settings in a local database, which is then synchronized with the server.

[0577] Step 3:

[0578] When a user accesses a specific web page using a browser, the access request is sent from the terminal to the server, which also includes user setting information.

[0579] Step 4:

[0580] The server retrieves the target web page based on the received access request, and the HTML content of this web page is analyzed.

[0581] Step 5:

[0582] The server uses a generation AI to analyze the retrieved HTML content, which identifies each element on the web page, such as advertisements, articles, and links.

[0583] Step 6:

[0584] The device is equipped with an emotion engine that recognizes the user's emotions. The device uses a camera and microphone to analyze the user's facial expressions and voice in real time, and recognizes positive and negative emotional states.

[0585] Step 7:

[0586] The server identifies content elements to be filtered based on user settings and the analysis results of the emotion engine. For example, if the emotion engine recognizes the user's emotion as negative, articles and advertisements that may cause stress are additionally filtered.

[0587] Step 8:

[0588] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0589] Step 9:

[0590] The server applies these filtering rules to regenerate the content of the web page, and the regenerated content has unnecessary elements deleted or hidden.

[0591] Step 10:

[0592] The server transmits the regenerated filtered content to the terminal.

[0593] Step 11:

[0594] The device then renders the received filtered content as a web page, allowing the user to view the web page with the content filtered based on real-time emotion recognition and user settings.

[0595] Step 12:

[0596] For example, if a user visits a news site and the emotion engine recognizes the user's emotion as negative, political articles and articles that may cause stress will be filtered out from the news site, preventing these articles from appearing and allowing the user to enjoy a comfortable and stress-free browsing experience.

[0597] Example 2

[0598] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0599] Existing Internet browser systems provide the ability to filter content based on a user's specific preferences, but they are unable to dynamically change content filtering rules to take into account the user's real-time emotional state, making it difficult for users to obtain an optimal Internet usage environment that reflects their psychological state at any given time.

[0600] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0601] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for using an emotion engine that analyzes the user's emotional state in real time, means for dynamically changing filtering rules based on the emotion analysis results, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal, thereby making it possible to provide an Internet usage environment that corresponds to the user's real-time emotional state.

[0602] "User setting information" is information about the categories of content to be filtered, which is set by the user when the user starts up the Internet browser for the first time.

[0603] "Means for filtering specific content" refers to a function that excludes content that should not be displayed based on user setting information.

[0604] The "emotion engine" is a system that analyzes the user's facial expressions and voice and recognizes the user's emotional state in real time.

[0605] "Means for dynamically changing filtering rules based on emotion analysis results" is a function that changes filtering rules each time according to the emotional state recognized by the emotion engine.

[0606] "Regenerated content" refers to the content of a web page that has been reconstructed after applying filtering rules.

[0607] A "terminal including a storage device" is a user's device that has a storage function for saving data such as user setting information.

[0608] A "server" is a central processing unit that receives a web page access request from a user, retrieves, analyzes, filters, and regenerates the content, and sends the results to a terminal.

[0609] A "storage device for saving user setting information" is a storage mechanism within the device for saving setting information specified by the user.

[0610] "Means for analyzing the content of a web page" refers to the ability to analyze the HTML and other code of a web page and identify each element within the page.

[0611] "Filtering rules" are a set of rules and conditions that determine whether content is displayed or hidden.

[0612] This invention is a system that recognizes a user's emotions and dynamically filters Internet content based on those emotions. This system aims to provide an environment in which users can comfortably use the Internet.

[0613] Specifically, the system includes a means for receiving user setting information, a means for filtering specific content, an emotion engine for analyzing the user's emotional state in real time, a means for dynamically changing filtering rules based on the emotion analysis results, a means for regenerating the filtered content, and a means for transmitting the regenerated content to the user's terminal.

[0614] Hardware and software used

[0615] To implement this system, the following hardware and software are required:

[0616] User device: A computer or smart device equipped with a camera, microphone, and a local database

[0617] Server: a central processing unit for high-performance analysis and data processing

[0618] Emotion Engine: Software that analyzes the user's facial expressions and voice

[0619] Generative AI: The model used to analyze content (e.g., GPT-4)

[0620] Communication protocol: Network communication technology such as HTTP / HTTPS

[0621] System processing overview

[0622] 1. User Settings: When a user launches the browser for the first time, an initial setup screen appears. The user selects the categories of content they do not want to see (e.g., sexual content, politics, religion, etc.). This setting information is stored in a local database on the device and synchronized with the server.

[0623] 2. Accessing a web page: When a user attempts to access a specific web page, an access request is sent from the terminal to the server, along with user setting information.

[0624] 3. Content retrieval and analysis: The server retrieves the HTML content of the web page based on the access request. It uses a generative AI model (e.g., GPT-4) to analyze the HTML content and identify each content element, such as an advertisement, article, or link.

[0625] 4. Emotion recognition using an emotion engine: The emotion engine installed on the device uses the camera and microphone to analyze the user's facial expressions and voice in real time and recognize positive and negative emotional states.

[0626] 5. Content filtering: The server identifies content elements to filter based on user preferences and the analysis results of the emotion engine. If a negative emotional state is detected, certain content (e.g., articles or advertisements that may cause stress) will be additionally filtered.

[0627] 6. Generation and dynamic modification of filtering rules: The server generates filtering rules for the identified content elements. The filtering rules may be dynamically modified based on the analysis results of the emotion engine.

[0628] 7. Regenerate and send content: The server applies the filtering rules and sends the regenerated content to the terminal.

[0629] 8. User browsing: The device renders the filtered content as a web page, and the user browses the web page, with content based on real-time emotion recognition and user preferences.

[0630] Specific examples

[0631] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0632] Prompt Sentence Examples

[0633] Here are some example prompts to input to a generative AI model:

[0634] Please provide a step-by-step description of the process a browser system uses to enforce filtering when user sentiment is negative, starting from saving the user's preferences to finally displaying filtered content to the user.

[0635] This prompt allows the generative AI model to explain each processing step in detail.

[0636] In this way, the present invention can provide an optimal Internet usage environment based on the user's feelings and preferences.

[0637] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0638] Step 1: Enter and save your user settings

[0639] When a user first launches the browser, they are presented with an initial setup screen. They select the categories of content they do not want to view (e.g., sexual content, politics, religion, etc.). This information is stored in a local database on the device and serves as input. The settings are then synchronized with the server and serve as output. For example, if a user chooses to hide the "Politics" category, that setting is stored on the device and sent to the server.

[0640] Step 2: Access the web page

[0641] When a user attempts to access a specific web page, the request is sent from the terminal to the server. The user setting information stored in the terminal's database is also sent here, and this becomes input. The server receives the access request and outputs the URL of the web page and the user setting information.

[0642] Step 3: Acquire and parse content

[0643] Based on the received access request, the server retrieves the HTML content of the specified web page from the Internet. The retrieved HTML content is used as input and analyzed using a generative AI model (e.g., GPT-4). This analysis identifies each element, such as advertisements, articles, and links, and outputs the analysis results. For example, all advertisements and articles on a news site are identified.

[0644] Step 4: Emotion Recognition with the Emotion Engine

[0645] The device is equipped with an emotion engine that recognizes the user's emotions. It uses a camera and microphone to analyze the user's facial expressions and voice in real time and recognizes positive and negative emotional states. The user's facial expressions and voice are input, and the emotion analysis results are output. For example, if the user's facial expression is smiling, it is judged as positive, and if they are frowning, it is judged as negative.

[0646] Step 5: Filtering content

[0647] The server identifies content elements to be filtered based on user settings and the emotion engine's analysis results. User settings and emotion analysis results are input, and a list of content to be filtered is output. For example, if a user hides the "Politics" category and the emotion is negative, certain news articles will be filtered.

[0648] Step 6: Creating and dynamically changing filtering rules

[0649] The server generates filtering rules for the identified content elements. These rules include hiding settings using HTML and CSS. The list of content to be filtered is input, and the filtering rules are output. In addition, the filtering rules may be dynamically changed based on the analysis results of the emotion engine. For example, if the emotion changes to a positive one, the filtered content will be redisplayed.

[0650] Step 7: Regenerate and submit content

[0651] The server applies the generated filtering rules to create regenerated content. The filtering rules and the original HTML content are input, and regenerated HTML content is output. This is then sent to the terminal. For example, content with CSS rules applied to hide specific HTML tags is generated and sent to the terminal.

[0652] Step 8: User Browsing

[0653] The device renders the received filtered content as a web page. The transmitted regenerated content is input and the rendered web page is output. The user then browses the web page, which displays content filtered based on emotion recognition and user settings. For example, if the user is in a negative emotional state, news articles and advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[0654] (Application example 2)

[0655] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0656] In modern content distribution services, many users browse content from various categories, which can often cause psychological stress. In particular, when a user is experiencing negative emotions, content that exacerbates those emotions can make the user's experience even more unpleasant. In such situations, users need to receive content that is appropriately filtered according to their emotions.

[0657] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user setting information, means for filtering specific content, emotion recognition means for recognizing the user's emotion in real time, means for dynamically changing the filtering rules based on the emotion analysis result by the emotion recognition means, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal. This enables the user to receive filtered content that is suited to their emotional state in real time.

[0658] "User setting information" is information about the category of content that the user selects on the initial setting screen of a browser or application to display or hide.

[0659] The "content filtering means" is a means having a function of selecting specific content and determining whether to display or hide it based on user setting information.

[0660] The "emotion recognition means" is a means having the function of analyzing the user's emotions in real time from their facial expressions and tone of voice, and recognizing their emotional state.

[0661] The "means for dynamically changing filtering rules" refers to a means having a function for changing in real time the rules for adding or removing content to be filtered based on the emotion analysis results obtained by the emotion recognition means.

[0662] The "content regeneration means" is a means having the function of applying the filtering rules defined above and reconstructing the content to be provided to the user.

[0663] The "content transmitting means" is a means having a function of transmitting the regenerated content to the user's terminal.

[0664] A "local database" is a database that is installed on a user terminal and that saves and temporarily stores user setting information.

[0665] A "server" is a central management system that receives access requests from user terminals, analyzes and filters the content, and provides the regenerated content to the user.

[0666] This invention relates to a system that recognizes a user's emotions in real time and filters content according to the user's psychological state. This system mainly comprises the following elements: a means for receiving user setting information, a means for filtering specific content, an emotion recognition means for recognizing the user's emotions, a means for dynamically changing filtering rules, a means for providing the regenerated content to the user, and a means for transmitting the regenerated content to the user's terminal.

[0667] System configuration and operation

[0668] 1. Receiving user settings information:

[0669] When a user first uses the system, they enter content filtering configuration information, which specifies the categories of content they do not want to see. This configuration information is stored in a local database on the device and synchronized with the server.

[0670] 2. Real-time emotion recognition:

[0671] The device utilizes a built-in camera and microphone to capture the user's facial expressions and voice, and then analyzes emotions in real time using emotion recognition, which is powered by a pre-trained generative AI model.

[0672] 3. Integrating emotion data and user preference information:

[0673] The server dynamically changes the filtering rules based on the received user setting information and real-time emotional states detected by the emotion recognition means. The filtering rules include HTML and CSS settings for hiding specific content.

[0674] 4. Content Acquisition and Analysis:

[0675] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is identified by specific categories. Based on these analysis results, the server generates filtering rules to provide content appropriate to the user.

[0676] 5. Reproducing and Submitting Content:

[0677] The server regenerates the filtered content based on the generated filtering rules and transmits the content to the user's terminal, which then renders the received content and displays it to the user.

[0678] Hardware and software configuration

[0679] The main hardware and software used in this system are as follows:

[0680] Camera and microphone: Captures the user's facial expressions and voice.

[0681] Emotion recognition: Using generative AI models trained using machine learning frameworks such as TensorFlow.

[0682] Server: Acquires content, analyzes it, generates filtering rules, and regenerates content.

[0683] Local Database: A database for storing user configuration information and synchronizing it with the server.

[0684] Specific examples

[0685] For example, if a user is using a video streaming service and has set horror movies to be hidden, and the emotion recognition means analyzes the user's emotion as "sad," the server will filter out not only horror movie content but also movies that may evoke sad emotions. As a result, the user can watch safe and comfortable content that is adapted to their emotional state.

[0686] Prompt Sentence Examples

[0687] "Generate a model that analyzes emotions from a user's facial expressions and voice in real time."

[0688] "Generate an algorithm that dynamically changes filtering rules based on the user's emotional state."

[0689] "Build a system that filters content that may cause stress based on emotion recognition results."

[0690] Such a system allows users to enjoy content that is optimal for their emotional state, providing a stress-free experience.

[0691] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0692] Step 1:

[0693] When a user first uses the system, they enter their user configuration information, select the content categories they do not want to see (e.g., violence, horror, politics), and the information is stored in a local database on the device and synchronized with the server.

[0694] Input: Content category selection by user.

[0695] Output: Saved user settings information.

[0696] Step 2:

[0697] The device uses a built-in camera and microphone to capture the user's facial expressions and voice in real time.

[0698] Input: User's facial expression data, voice data.

[0699] Output: Captured facial and speech data.

[0700] Step 3:

[0701] The device analyzes the captured data using emotion recognition means – for example, a generative AI model using TensorFlow – to recognize the user's emotions in real time.

[0702] Input: Captured facial expression data, audio data.

[0703] Data processing: Sentiment analysis is performed using generative AI models.

[0704] Output: Perceived emotional state (e.g., positive, negative).

[0705] Step 4:

[0706] The device sends the analyzed emotional state to the server, and the server dynamically generates and modifies filtering rules based on the received user settings and emotion recognition results, including HTML and CSS settings to hide specific content (e.g., articles or videos that may cause stress).

[0707] Input: User preference information, perceived emotional state.

[0708] Data processing: Applying algorithms to generate filtering rules.

[0709] Output: The generated filtering rules.

[0710] Step 5:

[0711] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is then identified by specific categories.

[0712] Input: Web page URL, filtering rules.

[0713] Data processing: Analyze web content using a generative AI model and identify it by category.

[0714] Output: Parsed content information.

[0715] Step 6:

[0716] The server then regenerates the parsed content based on the generated filtering rules to create a filtered web page, which involves using HTML and CSS to hide certain elements.

[0717] Input: Parsed content information, filtering rules.

[0718] Data manipulation: Regenerate content by applying HTML and CSS.

[0719] Output: The regenerated filtered web page.

[0720] Step 7:

[0721] The server sends the regenerated web page to the user's device, which renders the received content and displays it to the user.

[0722] Input: The regenerated web page.

[0723] Output: The filtered content that is displayed to the user.

[0724] In this way, filtering adapted to the user's emotional state is performed through a series of steps, providing a stress-free content viewing environment.

[0725] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0726] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0727] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0728] [Third embodiment]

[0729] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0730] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0731] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0732] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0733] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0734] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0735] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0736] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0737] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0738] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0739] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0740] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0741] This invention is a browser system that filters out unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with the user, the terminal, and the server.

[0742] User Settings

[0743] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, or ideology. The user's selections are stored in a local database on the device and synchronized with the server.

[0744] Access to the web page

[0745] When a user enters a URL into a browser to access a specific web page, the request is sent from the device to the server, which receives the request and retrieves the target web page.

[0746] Content Acquisition and Analysis

[0747] The server analyzes the HTML content of the retrieved web page. This analysis is performed using a generation AI. The generation AI analyzes the tag structure of the HTML document and identifies each element (e.g., advertisement, article link). It also identifies the category of content to be filtered based on user settings.

[0748] Content Filtering

[0749] The server creates a list of content elements to be filtered, and generates filtering rules based on this list. These rules include hiding specific HTML elements and CSS selectors (e.g., display: none;).

[0750] Regenerate and send content

[0751] The server regenerates the content by applying the generated filtering rules, and transmits the regenerated content to the user's terminal.

[0752] User Browsing

[0753] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0754] Specific examples

[0755] For example, consider the case where a user accesses a news site. The user has set the browser to hide political articles. This setting information is sent from the device to the server. The server retrieves the news site's HTML and analyzes it using generative AI. From the analysis results, political articles are identified and filtering rules for those elements are generated. The generated filtering rules (e.g., the political article section { display: none;}) are applied, and the regenerated content is sent to the user. The user's browser displays this filtered page, allowing the user to browse the news site without political articles.

[0756] In this way, users can avoid unwanted content and enjoy a comfortable browsing experience. This system protects users' privacy and allows them to freely access information.

[0757] The processing flow will be explained below.

[0758] Step 1:

[0759] When a user first launches the browser, they select the categories of content they want to filter from the initial settings screen, such as ads related to sexual complexes or articles related to politics, religion, or ideology. These settings allow users to customize their content experience.

[0760] Step 2:

[0761] The device stores the user-selected setting information in a local database, and simultaneously synchronizes the setting information with the server.

[0762] Step 3:

[0763] A user attempts to access a specific web page in a browser, for example, by entering the URL of a news site.

[0764] Step 4:

[0765] The terminal sends an access request to the server, along with the user's setting information.

[0766] Step 5:

[0767] The server retrieves a corresponding web page based on the received access request, and this web page is subject to filtering.

[0768] Step 6:

[0769] The server then uses generative AI to analyze the HTML content of the retrieved web page, including identifying each element on the page, such as advertisements, articles, and links.

[0770] Step 7:

[0771] The server determines which categories of content to hide based on the filtering criteria selected by the user in the initial settings, such as political articles or sexually insensitive ads.

[0772] Step 8:

[0773] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0774] Step 9:

[0775] The server applies the generated filtering rules to create regenerated content, and during regeneration, unnecessary content is deleted or hidden.

[0776] Step 10:

[0777] The server transmits the regenerated filtered content to the terminal.

[0778] Step 11:

[0779] The device renders the received filtered content as a web page.

[0780] Step 12:

[0781] Users can browse web pages with filtered content, hiding political articles and advertisements related to sexual complexes, providing a comfortable browsing experience.

[0782] Example 1

[0783] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0784] In today's Internet usage, users are frequently confronted with unwanted content. This problem not only significantly impairs the user's browsing experience, but can also cause mental stress and a loss of concentration due to information overload. Furthermore, from the perspective of privacy protection, displaying unwanted advertisements and articles based on a user's interests is problematic. Conventional content filtering methods are unable to provide sophisticated filtering tailored to individual user needs and can only provide general-purpose filtering. Given this background, there is a growing need for a system that achieves more accurate content filtering based on the user's individual settings.

[0785] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0786] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for analyzing the HTML content of the web page using a generative AI model, and means for generating filtering rules based on the analysis. This enables highly accurate filtering based on the needs of each user, protects users from unwanted content, and provides a comfortable and secure internet usage environment.

[0787] "User setting information" is information for a user to specify categories and conditions for filtering specific content.

[0788] A "generative AI model" is an artificial intelligence model used to analyze the HTML content of a web page and generate filtering rules.

[0789] A "filtering rule" is a rule that includes CSS or JavaScript code for hiding specific content based on user preference information.

[0790] "Regenerated content" is the content of a web page that has been reconstructed to be presented to a user after applying filtering rules.

[0791] A "local database" is a database stored in a user's terminal and is used to store user setting information.

[0792] A "prompt sentence" is input text that instructs a generative AI model to perform a specific analysis or generate rules.

[0793] An "HTTP request" is an Internet communication request message sent to a server to retrieve a web page.

[0794] An "HTML document" is a file written in HTML, a markup language for describing the structure of a web page.

[0795] A "CSS rule" is a style rule that specifies the appearance of HTML elements, and includes settings such as "display: none;" to hide certain elements.

[0796] MODE FOR CARRYING OUT THE INVENTION

[0797] This invention relates to a browser system that filters unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with a user, a terminal, and a server. Specific embodiments are described below.

[0798] Retrieving and saving user settings

[0799] When users first launch the browser, they are shown an initial setup screen where they can select the categories of content they want to filter. For example, they can choose to filter out advertisements related to sexual complexes or articles on politics, religion, or ideology. These selections are made to customize the user's desired Internet usage environment. The configuration information is stored in a local database on the device and later synchronized with the server.

[0800] Specifically, local storage such as an SQLite database is used to store user settings, which are synchronized with the server every time the browser is launched and kept up to date.

[0801] Requesting a web page and retrieving its content

[0802] When a user enters a URL into the address bar of a browser to access a specific web page, the request is first sent from the device to the server, which then retrieves the target web page based on this request.

[0803] Specifically, an HTTP client library (e.g., Python's requests library) is used to retrieve the HTML document of the web page, which is then processed within the server for analysis.

[0804] Content analysis and filtering rule generation

[0805] The server analyzes the HTML document of the retrieved web page using a generative AI model. The generative AI model analyzes the tag structure of the HTML document and identifies each element (e.g., advertisements or article links). It also identifies the content category to be filtered based on user settings and generates filtering rules to apply to it.

[0806] Examples of prompts for generative AI models include:

[0807] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0808] Regenerating and sending filtered content

[0809] The server regenerates the web page content by applying the generated filtering rules. The regenerated content is a filtered HTML document that does not contain information that the user does not want. The server then sends this regenerated content to the terminal.

[0810] Specifically, the server inserts the generated CSS rules into the HTML, reconstructs the DOM, and then sends the reconstructed HTML to the terminal as an HTTP response.

[0811] Rendering Filtered Content

[0812] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[0813] Specifically, the device's browser engine parses the received HTML document, generates a DOM, applies CSS rules to render the page, and displays the filtered web page to the user.

[0814] In this way, the system achieves highly accurate filtering based on the individual needs of users, providing a comfortable and secure Internet usage environment.

[0815] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0816] Processing flow

[0817] The program process for this system is divided into the following steps:

[0818] Step 1: Get user configuration information

[0819] When users first launch the browser, they are shown an initial setup screen where they select the categories of content they want to filter, and this selection is stored in a local database on the device and then synchronized with the server.

[0820] Input: User's content filtering settings (e.g. sexual content, politics, religion, etc.)

[0821] Data processing: Save selected setting information to a local database (e.g., SQLite)

[0822] Output: Saved user settings information

[0823] Specific operation: Once the user completes the settings, the browser saves the settings information in a local database and notifies the server that the settings have been changed.

[0824] Step 2: Sending a web page request

[0825] When a user types a specific URL into the address bar of their browser, the request is first sent from the device to the server, which initiates a filtering process based on the user's settings.

[0826] Input: The URL entered by the user

[0827] Data processing: Formatting URL information as an HTTP request

[0828] Output: HTTP request sent to the server

[0829] Specific operation: When you enter a URL in the browser's address bar and press Enter, the device generates an HTTP request and sends it to the server.

[0830] Step 3: Retrieving web page content

[0831] The server retrieves the HTML content of the specified web page based on the received request. It uses an HTTP client library to retrieve the desired web page.

[0832] Input: The URL requested by the user

[0833] Data processing: Convert the URL into an HTTP request and obtain the HTML of the web page.

[0834] Output: The retrieved HTML document

[0835] Specific operation: The server uses Python's requests library to access the URL and retrieve the HTML document.

[0836] Step 4: Analyzing content and generating filtering rules

[0837] The server analyzes the retrieved HTML document using a generative AI model, sends a prompt to the generative AI model, and generates filtering rules.

[0838] Input: HTML document, user settings information

[0839] Data processing: Send prompts to the generative AI model and obtain analysis results

[0840] Output: Generated filtering rules

[0841] Specific operation: The server sends the following prompt to the generation AI model to generate filtering rules:

[0842] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[0843] Step 5: Regenerate filtered content

[0844] The server then applies the generated filtering rules to regenerate the content of the web page, resulting in an HTML document that excludes the unwanted content.

[0845] Input: Generated filtering rules, original HTML document

[0846] Data processing: Apply filtering rules to HTML and regenerate content

[0847] Output: Regenerated HTML document

[0848] What happens: The server applies filtering rules to the original HTML and reconstructs the DOM.

[0849] Step 6: Sending filtered content

[0850] The server sends the regenerated filtered content to the terminal, where the user can view it.

[0851] Input: Regenerated HTML document

[0852] Data processing: Formatting the regenerated HTML document as an HTTP response

[0853] Output: HTTP response sent to the device

[0854] Specific operation: The server sends the regenerated HTML document to the terminal as an HTTP response.

[0855] Step 7: Rendering the filtered content

[0856] The device then renders the received filtered content as a web page, allowing the user to view the web page with the unwanted content removed.

[0857] Input: The filtered HTML document received from the server

[0858] Data processing: Parse HTML documents and generate DOM

[0859] Output: Rendered web page

[0860] What happens: The device's browser engine parses the received HTML document, applies CSS rules, and renders the page.

[0861] In this way, the system can achieve highly accurate filtering based on the individual needs of users, providing a comfortable and safe Internet usage environment.

[0862] (Application example 1)

[0863] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0864] In conventional Internet browsing systems, users frequently encounter unwanted content, making it difficult to ensure safe and comfortable web browsing. Furthermore, content filtering is insufficient, especially on mobile devices, significantly impairing the user experience. Therefore, there is a need for a method that can quickly analyze web page content in real time based on user-specified filtering rules and appropriately filter out unwanted content.

[0865] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0866] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a URL of a website specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a document object model, means for applying filtering to the constructed document object model based on the user setting information, and means for transmitting the filtered content to the user's terminal for display. This allows the user to enjoy a safe and comfortable web browsing experience with unnecessary content filtered out in real time.

[0867] "User setting information" is information for specifying categories of content that the user does not want.

[0868] "URL" is an abbreviation for Uniform Resource Locator, and is a character string that indicates the address of a web page.

[0869] "HTML content" refers to the HTML documents that make up a web page and the elements contained within them.

[0870] A "server" is a central computer system that provides data over a network.

[0871] The "Document Object Model (DOM)" is a model for representing HTML documents as a hierarchical structure, making it easier to manipulate them programmatically.

[0872] A "filtering rule" is a rule for preventing certain content from being displayed based on conditions specified by the user.

[0873] "Parsing" is the process of reading an HTML document as code and identifying each element.

[0874] "Regeneration" means reconstructing the content of a web page after applying the filtering rules.

[0875] "Local Database" means a database stored on a User's device that is used to store User settings and other important information.

[0876] A "terminal" is a computing device (e.g., smartphone, tablet, computer) that is directly operated by a user.

[0877] This invention is a system for filtering content that a user does not want to view, thereby providing a comfortable and safe Internet usage environment. The basic configuration of the system includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a website URL specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a Document Object Model (DOM), means for applying filtering to the constructed DOM based on the user setting information, and means for transmitting the filtered content to the user's terminal for display.

[0878] First, when a user launches a browser for the first time, they enter user configuration information to specify categories of content they do not want. This user configuration information is then saved in the device's local database and synchronized with the server. When the user accesses a specific website, the device sends the specified URL to the server, which retrieves the corresponding HTML content. The server then uses a library such as BeautifulSoup to analyze the retrieved HTML content and construct a DOM. Filtering rules are applied to the constructed DOM to hide the unwanted content specified by the user.

[0879] After applying the filtering rules, the server regenerates the content of the web page and sends the filtered content to the user's device. The device receives the regenerated content, allowing the user to view it with unnecessary content removed.

[0880] A concrete example is when a user visits a news site. If the user selects to filter "violent content," the server retrieves the HTML of the specified news site, analyzes the DOM to identify violent articles and images, and filters them. Finally, the user is presented with a clean news site with no violent content.

[0881] An example prompt is:

[0882] "Using SafeBrowse, I visited a specific news site. I selected 'Violent Content' as the filtering category. The URL for the news site is 'http: / / example.com / news'. Please explain how SafeBrowse filters this page."

[0883] This invention allows users to enjoy a filtered, safe and comfortable web browsing experience.

[0884] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0885] Step 1:

[0886] The user launches the browser and selects the categories of unwanted content on the initial setup screen. The information entered here is user preference information, which specifies the types of content the user wants to filter while browsing. This preference information is saved in the device's local database and is then synchronized with the server. The entered data is user preference information, and data processing is performed to save it in the local database.

[0887] Step 2:

[0888] When a user accesses a particular website using a browser, the device receives the specified URL. This URL is the address of the website the user wants to visit. The input is the URL entered by the user, and data processing is performed to send this information to the server. The output is a URL request to the server.

[0889] Step 3:

[0890] The server retrieves the HTML content of the website based on the specified URL. Using the above request URL as input, it sends an HTTP request to retrieve the target HTML document. The output is the HTML content.

[0891] Step 4:

[0892] The server parses the retrieved HTML content and constructs a Document Object Model (DOM). The input is the retrieved HTML content, and a library such as BeautifulSoup is used to parse the HTML code and generate a DOM tree. The output is the constructed DOM tree. Specifically, the process converts HTML tags into a tree structure and identifies each element.

[0893] Step 5:

[0894] The server applies filtering to the constructed DOM tree based on user configuration information. The input is the user configuration information and the constructed DOM tree, and it applies user-specified filtering rules (e.g., removing violent content). The output is the filtered DOM tree.

[0895] Step 6:

[0896] The server applies the filtering rules and then recreates the web page content. The input is the filtered DOM tree, and the server recreates the HTML document based on the DOM content. The output is the recreated HTML content.

[0897] Step 7:

[0898] The server sends the regenerated HTML content to the user's terminal. The input is the regenerated HTML content, which is sent to the user's terminal as an HTTP response. The output is the HTML content converted into a format that can be displayed on the user's terminal.

[0899] Step 8:

[0900] The terminal displays the regenerated HTML content it receives. The input is the regenerated HTML content sent from the server, which is rendered in the terminal's browser and displayed to the user. This process allows the user to view a web page with the specified unwanted content filtered out. The output is the filtered web page displayed to the user.

[0901] The above are the processing steps of this system.

[0902] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0903] This invention is a browser system that combines an emotion engine that recognizes the user's emotions. In addition to the basic functions of receiving user settings, filtering, regenerating, and providing specific content, it also has the ability to analyze the user's emotional state in real time and dynamically change filtering rules. This system provides a comfortable Internet usage environment that is tailored to the user's psychological state.

[0904] User Settings

[0905] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, and ideology. This configuration information is stored in a local database by the device and synchronized with the server.

[0906] Access to the web page

[0907] When a user attempts to access a specific web page using a browser, the terminal sends an access request to the server, along with the user setting information.

[0908] Content Acquisition and Analysis

[0909] The server retrieves the target web page based on the received access request and analyzes its HTML content. This analysis is performed using generative AI to identify each element on the page, such as advertisements, articles, and links.

[0910] Emotion recognition by emotion engine

[0911] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes emotions in real time from the user's facial expressions and voice. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice and recognizes their emotional state, such as positive or negative.

[0912] Content Filtering

[0913] The server identifies content elements to be filtered based on user settings and the emotion analysis results of the emotion engine. If the emotion engine recognizes the user's emotion as negative, specific content (e.g., articles or advertisements that may cause stress) will be filtered as additional content.

[0914] Creating and dynamically changing filtering rules

[0915] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS, and dynamically changes the filtering rules based on the analysis results of the emotion engine.

[0916] Regenerate and send content

[0917] The server applies the generated filtering rules to generate regenerated content and transmits it to the terminal.

[0918] User Browsing

[0919] The device then renders the received filtered content as a web page. The user then browses the web page, which displays content filtered based on real-time emotion recognition and user settings. For example, if the user's emotion is negative, articles or advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[0920] Specific examples

[0921] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0922] This system allows users to have the optimal browsing environment according to their own emotions and preferences.

[0923] The processing flow will be explained below.

[0924] Step 1:

[0925] When a user first launches the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter. This could include, for example, ads related to sexual complexes or articles related to politics, religion, or ideology. This setting allows filtering based on the user's preferences.

[0926] Step 2:

[0927] The device stores the user's selected settings in a local database, which is then synchronized with the server.

[0928] Step 3:

[0929] When a user accesses a specific web page using a browser, the access request is sent from the terminal to the server, which also includes user setting information.

[0930] Step 4:

[0931] The server retrieves the target web page based on the received access request, and the HTML content of this web page is analyzed.

[0932] Step 5:

[0933] The server uses a generation AI to analyze the retrieved HTML content, which identifies each element on the web page, such as advertisements, articles, and links.

[0934] Step 6:

[0935] The device is equipped with an emotion engine that recognizes the user's emotions. The device uses a camera and microphone to analyze the user's facial expressions and voice in real time, and recognizes positive and negative emotional states.

[0936] Step 7:

[0937] The server identifies content elements to be filtered based on user settings and the analysis results of the emotion engine. For example, if the emotion engine recognizes the user's emotion as negative, articles and advertisements that may cause stress are additionally filtered.

[0938] Step 8:

[0939] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[0940] Step 9:

[0941] The server applies these filtering rules to regenerate the content of the web page, and the regenerated content has unnecessary elements deleted or hidden.

[0942] Step 10:

[0943] The server transmits the regenerated filtered content to the terminal.

[0944] Step 11:

[0945] The device then renders the received filtered content as a web page, allowing the user to view the web page with the content filtered based on real-time emotion recognition and user settings.

[0946] Step 12:

[0947] For example, if a user visits a news site and the emotion engine recognizes the user's emotion as negative, political articles and articles that may cause stress will be filtered out from the news site, preventing these articles from appearing and allowing the user to enjoy a comfortable and stress-free browsing experience.

[0948] Example 2

[0949] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0950] Existing Internet browser systems provide the ability to filter content based on a user's specific preferences, but they are unable to dynamically change content filtering rules to take into account the user's real-time emotional state, making it difficult for users to obtain an optimal Internet usage environment that reflects their psychological state at any given time.

[0951] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0952] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for using an emotion engine that analyzes the user's emotional state in real time, means for dynamically changing filtering rules based on the emotion analysis results, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal, thereby making it possible to provide an Internet usage environment that corresponds to the user's real-time emotional state.

[0953] "User setting information" is information about the categories of content to be filtered, which is set by the user when the user starts up the Internet browser for the first time.

[0954] "Means for filtering specific content" refers to a function that excludes content that should not be displayed based on user setting information.

[0955] The "emotion engine" is a system that analyzes the user's facial expressions and voice and recognizes the user's emotional state in real time.

[0956] "Means for dynamically changing filtering rules based on emotion analysis results" is a function that changes filtering rules each time according to the emotional state recognized by the emotion engine.

[0957] "Regenerated content" refers to the content of a web page that has been reconstructed after applying filtering rules.

[0958] A "terminal including a storage device" is a user's device that has a storage function for saving data such as user setting information.

[0959] A "server" is a central processing unit that receives a web page access request from a user, retrieves, analyzes, filters, and regenerates the content, and sends the results to a terminal.

[0960] A "storage device for saving user setting information" is a storage mechanism within the device for saving setting information specified by the user.

[0961] "Means for analyzing the content of a web page" refers to the ability to analyze the HTML and other code of a web page and identify each element within the page.

[0962] "Filtering rules" are a set of rules and conditions that determine whether content is displayed or hidden.

[0963] This invention is a system that recognizes a user's emotions and dynamically filters Internet content based on those emotions. This system aims to provide an environment in which users can comfortably use the Internet.

[0964] Specifically, the system includes a means for receiving user setting information, a means for filtering specific content, an emotion engine for analyzing the user's emotional state in real time, a means for dynamically changing filtering rules based on the emotion analysis results, a means for regenerating the filtered content, and a means for transmitting the regenerated content to the user's terminal.

[0965] Hardware and software used

[0966] To implement this system, the following hardware and software are required:

[0967] User device: A computer or smart device equipped with a camera, microphone, and a local database

[0968] Server: a central processing unit for high-performance analysis and data processing

[0969] Emotion Engine: Software that analyzes the user's facial expressions and voice

[0970] Generative AI: The model used to analyze content (e.g., GPT-4)

[0971] Communication protocol: Network communication technology such as HTTP / HTTPS

[0972] System processing overview

[0973] 1. User Settings: When a user launches the browser for the first time, an initial setup screen appears. The user selects the categories of content they do not want to see (e.g., sexual content, politics, religion, etc.). This setting information is stored in a local database on the device and synchronized with the server.

[0974] 2. Accessing a web page: When a user attempts to access a specific web page, an access request is sent from the terminal to the server, along with user setting information.

[0975] 3. Content retrieval and analysis: The server retrieves the HTML content of the web page based on the access request. It uses a generative AI model (e.g., GPT-4) to analyze the HTML content and identify each content element, such as an advertisement, article, or link.

[0976] 4. Emotion recognition using an emotion engine: The emotion engine installed on the device uses the camera and microphone to analyze the user's facial expressions and voice in real time and recognize positive and negative emotional states.

[0977] 5. Content filtering: The server identifies content elements to filter based on user preferences and the analysis results of the emotion engine. If a negative emotional state is detected, certain content (e.g., articles or advertisements that may cause stress) will be additionally filtered.

[0978] 6. Generating and dynamically changing filtering rules: The server generates filtering rules for the identified content elements. The filtering rules may be dynamically changed based on the analysis results of the emotion engine.

[0979] 7. Regenerate and send content: The server applies the filtering rules and sends the regenerated content to the terminal.

[0980] 8. User browsing: The device renders the filtered content as a web page, and the user browses the web page, with content based on real-time emotion recognition and user preferences.

[0981] Specific examples

[0982] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[0983] Prompt Sentence Examples

[0984] Here are some example prompts to input to a generative AI model:

[0985] Please provide a step-by-step description of the process a browser system uses to enforce filtering when user sentiment is negative, starting from saving the user's preferences to finally displaying filtered content to the user.

[0986] This prompt allows the generative AI model to explain each processing step in detail.

[0987] In this way, the present invention can provide an optimal Internet usage environment based on the user's feelings and preferences.

[0988] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0989] Step 1: Enter and save your user settings

[0990] When a user first launches the browser, they are presented with an initial setup screen. They select the categories of content they do not want to view (e.g., sexual content, politics, religion, etc.). This information is stored in a local database on the device and serves as input. The settings are then synchronized with the server and serve as output. For example, if a user chooses to hide the "Politics" category, that setting is stored on the device and sent to the server.

[0991] Step 2: Access the web page

[0992] When a user attempts to access a specific web page, the request is sent from the terminal to the server. The user setting information stored in the terminal's database is also sent here, and this becomes input. The server receives the access request and outputs the URL of the web page and the user setting information.

[0993] Step 3: Acquire and parse content

[0994] Based on the received access request, the server retrieves the HTML content of the specified web page from the Internet. The retrieved HTML content is used as input and analyzed using a generative AI model (e.g., GPT-4). This analysis identifies each element, such as advertisements, articles, and links, and outputs the analysis results. For example, all advertisements and articles on a news site are identified.

[0995] Step 4: Emotion Recognition with the Emotion Engine

[0996] The device is equipped with an emotion engine that recognizes the user's emotions. It uses a camera and microphone to analyze the user's facial expressions and voice in real time and recognizes positive and negative emotional states. The user's facial expressions and voice are input, and the emotion analysis results are output. For example, if the user's facial expression is smiling, it is judged as positive, and if they are frowning, it is judged as negative.

[0997] Step 5: Filtering content

[0998] The server identifies content elements to be filtered based on user settings and the emotion engine's analysis results. User settings and emotion analysis results are input, and a list of content to be filtered is output. For example, if a user hides the "Politics" category and the emotion is negative, certain news articles will be filtered.

[0999] Step 6: Creating and dynamically changing filtering rules

[1000] The server generates filtering rules for the identified content elements. These rules include hiding settings using HTML and CSS. The list of content to be filtered is input, and the filtering rules are output. In addition, the filtering rules may be dynamically changed based on the analysis results of the emotion engine. For example, if the emotion changes to a positive one, the filtered content will be redisplayed.

[1001] Step 7: Regenerate and submit content

[1002] The server applies the generated filtering rules to create regenerated content. The filtering rules and the original HTML content are input, and regenerated HTML content is output. This is then sent to the terminal. For example, content with CSS rules applied to hide specific HTML tags is generated and sent to the terminal.

[1003] Step 8: User Browsing

[1004] The device renders the received filtered content as a web page. The transmitted regenerated content is input and the rendered web page is output. The user then browses the web page, which displays content filtered based on emotion recognition and user settings. For example, if the user is in a negative emotional state, news articles and advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[1005] (Application example 2)

[1006] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1007] In modern content distribution services, many users browse content from various categories, which can often cause psychological stress. In particular, when a user is experiencing negative emotions, content that exacerbates those emotions can make the user's experience even more unpleasant. In such situations, users need to receive content that is appropriately filtered according to their emotions.

[1008] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user setting information, means for filtering specific content, emotion recognition means for recognizing the user's emotion in real time, means for dynamically changing the filtering rules based on the emotion analysis result by the emotion recognition means, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal. This enables the user to receive filtered content that is suited to their emotional state in real time.

[1009] "User setting information" is information about the category of content that the user selects on the initial setting screen of a browser or application to display or hide.

[1010] The "content filtering means" is a means having a function of selecting specific content and determining whether to display or hide it based on user setting information.

[1011] The "emotion recognition means" is a means having the function of analyzing the user's emotions in real time from their facial expressions and tone of voice, and recognizing their emotional state.

[1012] The "means for dynamically changing filtering rules" refers to means having a function for changing in real time the rules for adding or removing content to be filtered based on the emotion analysis results obtained by the emotion recognition means.

[1013] The "content regeneration means" is a means having the function of applying the filtering rules defined above and reconstructing the content to be provided to the user.

[1014] The "content transmitting means" is a means having a function of transmitting the regenerated content to the user's terminal.

[1015] A "local database" is a database that is installed on a user terminal and that saves and temporarily stores user setting information.

[1016] A "server" is a central management system that receives access requests from user terminals, analyzes and filters the content, and provides the regenerated content to the user.

[1017] This invention relates to a system that recognizes a user's emotions in real time and filters content according to the user's psychological state. This system mainly comprises the following elements: a means for receiving user setting information, a means for filtering specific content, an emotion recognition means for recognizing the user's emotions, a means for dynamically changing filtering rules, a means for providing the regenerated content to the user, and a means for transmitting the regenerated content to the user's terminal.

[1018] System configuration and operation

[1019] 1. Receiving user settings information:

[1020] When a user first uses the system, they enter content filtering configuration information, which specifies the categories of content they do not want to see. This configuration information is stored in a local database on the device and synchronized with the server.

[1021] 2. Real-time emotion recognition:

[1022] The device utilizes a built-in camera and microphone to capture the user's facial expressions and voice, and then analyzes emotions in real time using emotion recognition, which is powered by a pre-trained generative AI model.

[1023] 3. Integrating emotion data and user preference information:

[1024] The server dynamically changes the filtering rules based on the received user setting information and real-time emotional states detected by the emotion recognition means. The filtering rules include HTML and CSS settings for hiding specific content.

[1025] 4. Content Acquisition and Analysis:

[1026] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is identified by specific categories. Based on these analysis results, the server generates filtering rules to provide content appropriate to the user.

[1027] 5. Reproducing and Submitting Content:

[1028] The server regenerates the filtered content based on the generated filtering rules and transmits the content to the user's terminal, which then renders the received content and displays it to the user.

[1029] Hardware and software configuration

[1030] The main hardware and software used in this system are as follows:

[1031] Camera and microphone: Captures the user's facial expressions and voice.

[1032] Emotion recognition: Using generative AI models trained using machine learning frameworks such as TensorFlow.

[1033] Server: Acquires content, analyzes it, generates filtering rules, and regenerates content.

[1034] Local Database: A database for storing user configuration information and synchronizing it with the server.

[1035] Specific examples

[1036] For example, if a user is using a video streaming service and has set horror movies to be hidden, and the emotion recognition means analyzes the user's emotion as "sad," the server will filter out not only horror movie content but also movies that may evoke sad emotions. As a result, the user can watch safe and comfortable content that is adapted to their emotional state.

[1037] Prompt Sentence Examples

[1038] "Generate a model that analyzes emotions from a user's facial expressions and voice in real time."

[1039] "Generate an algorithm that dynamically changes filtering rules based on the user's emotional state."

[1040] "Build a system that filters content that may cause stress based on emotion recognition results."

[1041] Such a system allows users to enjoy content that is optimal for their emotional state, providing a stress-free experience.

[1042] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1043] Step 1:

[1044] When a user first uses the system, they enter their user configuration information, select the content categories they do not want to see (e.g., violence, horror, politics), and the information is stored in a local database on the device and synchronized with the server.

[1045] Input: Content category selection by user.

[1046] Output: Saved user settings information.

[1047] Step 2:

[1048] The device uses a built-in camera and microphone to capture the user's facial expressions and voice in real time.

[1049] Input: User's facial expression data, voice data.

[1050] Output: Captured facial and speech data.

[1051] Step 3:

[1052] The device analyzes the captured data using emotion recognition means – for example, a generative AI model using TensorFlow – to recognize the user's emotions in real time.

[1053] Input: Captured facial expression data, audio data.

[1054] Data processing: Sentiment analysis is performed using generative AI models.

[1055] Output: Perceived emotional state (e.g., positive, negative).

[1056] Step 4:

[1057] The device sends the analyzed emotional state to the server, and the server dynamically generates and modifies filtering rules based on the received user settings and emotion recognition results, including HTML and CSS settings to hide specific content (e.g., articles or videos that may cause stress).

[1058] Input: User preference information, perceived emotional state.

[1059] Data processing: Applying algorithms to generate filtering rules.

[1060] Output: The generated filtering rules.

[1061] Step 5:

[1062] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is then identified by specific categories.

[1063] Input: Web page URL, filtering rules.

[1064] Data processing: Analyze web content using a generative AI model and identify it by category.

[1065] Output: Parsed content information.

[1066] Step 6:

[1067] The server then regenerates the parsed content based on the generated filtering rules to create a filtered web page, which involves using HTML and CSS to hide certain elements.

[1068] Input: Parsed content information, filtering rules.

[1069] Data manipulation: Regenerate content by applying HTML and CSS.

[1070] Output: The regenerated filtered web page.

[1071] Step 7:

[1072] The server sends the regenerated web page to the user's device, which renders the received content and displays it to the user.

[1073] Input: The regenerated web page.

[1074] Output: The filtered content that is displayed to the user.

[1075] In this way, filtering adapted to the user's emotional state is performed through a series of steps, providing a stress-free content viewing environment.

[1076] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1077] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1078] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1079] [Fourth embodiment]

[1080] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1081] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1082] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1083] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1084] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1085] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1086] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1087] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1088] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1089] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1090] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1091] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1092] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1093] This invention is a browser system that filters out unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with the user, the terminal, and the server.

[1094] User Settings

[1095] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, or ideology. The user's selections are stored in a local database on the device and synchronized with the server.

[1096] Access to the web page

[1097] When a user enters a URL into a browser to access a specific web page, the request is sent from the device to the server, which receives the request and retrieves the target web page.

[1098] Content Acquisition and Analysis

[1099] The server analyzes the HTML content of the retrieved web page. This analysis is performed using a generation AI. The generation AI analyzes the tag structure of the HTML document and identifies each element (e.g., advertisement, article link). It also identifies the category of content to be filtered based on user settings.

[1100] Content Filtering

[1101] The server creates a list of content elements to be filtered, and generates filtering rules based on this list. These rules include hiding specific HTML elements and CSS selectors (e.g., display: none;).

[1102] Regenerate and send content

[1103] The server regenerates the content by applying the generated filtering rules, and transmits the regenerated content to the user's terminal.

[1104] User Browsing

[1105] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[1106] Specific examples

[1107] For example, consider the case where a user accesses a news site. The user has set the browser to hide political articles. This setting information is sent from the device to the server. The server retrieves the news site's HTML and analyzes it using generative AI. From the analysis results, political articles are identified and filtering rules for those elements are generated. The generated filtering rules (e.g., the political article section { display: none;}) are applied, and the regenerated content is sent to the user. The user's browser displays this filtered page, allowing the user to browse the news site without political articles.

[1108] In this way, users can avoid unwanted content and enjoy a comfortable browsing experience. This system protects users' privacy and allows them to freely access information.

[1109] The processing flow will be explained below.

[1110] Step 1:

[1111] When a user first launches the browser, they select the categories of content they want to filter from the initial settings screen, such as ads related to sexual complexes or articles related to politics, religion, or ideology. These settings allow users to customize their content experience.

[1112] Step 2:

[1113] The device stores the user-selected setting information in a local database, and simultaneously synchronizes the setting information with the server.

[1114] Step 3:

[1115] A user attempts to access a specific web page in a browser, for example, by entering the URL of a news site.

[1116] Step 4:

[1117] The terminal sends an access request to the server, along with the user's setting information.

[1118] Step 5:

[1119] The server retrieves a corresponding web page based on the received access request, and this web page is subject to filtering.

[1120] Step 6:

[1121] The server then uses generative AI to analyze the HTML content of the retrieved web page, including identifying each element on the page, such as advertisements, articles, and links.

[1122] Step 7:

[1123] The server determines which categories of content to hide based on the filtering criteria selected by the user in the initial settings, such as political articles or sexually insensitive ads.

[1124] Step 8:

[1125] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[1126] Step 9:

[1127] The server applies the generated filtering rules to create regenerated content, and during regeneration, unnecessary content is deleted or hidden.

[1128] Step 10:

[1129] The server transmits the regenerated filtered content to the terminal.

[1130] Step 11:

[1131] The device renders the received filtered content as a web page.

[1132] Step 12:

[1133] Users can browse web pages with filtered content, hiding political articles and advertisements related to sexual complexes, providing a comfortable browsing experience.

[1134] Example 1

[1135] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1136] In today's Internet usage, users are frequently confronted with unwanted content. This problem not only significantly impairs the user's browsing experience, but can also cause mental stress and a loss of concentration due to information overload. Furthermore, from the perspective of privacy protection, displaying unwanted advertisements and articles based on a user's interests is problematic. Conventional content filtering methods are unable to provide sophisticated filtering tailored to individual user needs and can only provide general-purpose filtering. Given this background, there is a growing need for a system that achieves more accurate content filtering based on the user's individual settings.

[1137] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1138] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for analyzing the HTML content of the web page using a generative AI model, and means for generating filtering rules based on the analysis. This enables highly accurate filtering based on the needs of each user, protects users from unwanted content, and provides a comfortable and secure internet usage environment.

[1139] "User setting information" is information for a user to specify categories and conditions for filtering specific content.

[1140] A "generative AI model" is an artificial intelligence model used to analyze the HTML content of a web page and generate filtering rules.

[1141] A "filtering rule" is a rule that includes CSS or JavaScript code for hiding specific content based on user preference information.

[1142] "Regenerated content" is the content of a web page that has been reconstructed to be presented to a user after applying filtering rules.

[1143] A "local database" is a database stored in a user's terminal and is used to store user setting information.

[1144] A "prompt sentence" is input text that instructs a generative AI model to perform a specific analysis or generate rules.

[1145] An "HTTP request" is an Internet communication request message sent to a server to retrieve a web page.

[1146] An "HTML document" is a file written in HTML, a markup language for describing the structure of a web page.

[1147] A "CSS rule" is a style rule that specifies the appearance of HTML elements, and includes settings such as "display: none;" to hide certain elements.

[1148] MODE FOR CARRYING OUT THE INVENTION

[1149] This invention relates to a browser system that filters unwanted content and provides a comfortable Internet usage environment. This system operates in cooperation with a user, a terminal, and a server. Specific embodiments are described below.

[1150] Retrieving and saving user settings

[1151] When users first launch the browser, they are shown an initial setup screen where they can select the categories of content they want to filter. For example, they can choose to filter out advertisements related to sexual complexes or articles on politics, religion, or ideology. These selections are made to customize the user's desired Internet usage environment. The configuration information is stored in a local database on the device and later synchronized with the server.

[1152] Specifically, local storage such as an SQLite database is used to store user settings, which are synchronized with the server every time the browser is launched and kept up to date.

[1153] Requesting a web page and retrieving its content

[1154] When a user enters a URL into the address bar of a browser to access a specific web page, the request is first sent from the device to the server, which then retrieves the target web page based on this request.

[1155] Specifically, an HTTP client library (e.g., Python's requests library) is used to retrieve the HTML document of the web page, which is then processed within the server for analysis.

[1156] Content analysis and filtering rule generation

[1157] The server analyzes the HTML document of the retrieved web page using a generative AI model. The generative AI model analyzes the tag structure of the HTML document and identifies each element (e.g., advertisements or article links). It also identifies the content category to be filtered based on user settings and generates filtering rules to apply to it.

[1158] Examples of prompts for generative AI models include:

[1159] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[1160] Regenerating and sending filtered content

[1161] The server regenerates the web page content by applying the generated filtering rules. The regenerated content is a filtered HTML document that does not contain information that the user does not want. The server then sends this regenerated content to the terminal.

[1162] Specifically, the server inserts the generated CSS rules into the HTML, reconstructs the DOM, and then sends the reconstructed HTML to the terminal as an HTTP response.

[1163] Rendering Filtered Content

[1164] The device then renders the received filtered content as a web page, allowing the user to enjoy a comfortable browsing experience that is filtered based on their preferences.

[1165] Specifically, the device's browser engine parses the received HTML document, generates a DOM, applies CSS rules to render the page, and displays the filtered web page to the user.

[1166] In this way, the system achieves highly accurate filtering based on the individual needs of users, providing a comfortable and secure Internet usage environment.

[1167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1168] Processing flow

[1169] The program process for this system is divided into the following steps:

[1170] Step 1: Get user configuration information

[1171] When users first launch the browser, they are shown an initial setup screen where they select the categories of content they want to filter, and this selection is stored in a local database on the device and then synchronized with the server.

[1172] Input: User's content filtering settings (e.g. sexual content, politics, religion, etc.)

[1173] Data processing: Save selected setting information to a local database (e.g., SQLite)

[1174] Output: Saved user settings information

[1175] Specific operation: Once the user completes the settings, the browser saves the settings information in a local database and notifies the server that the settings have been changed.

[1176] Step 2: Sending a web page request

[1177] When a user types a specific URL into the address bar of their browser, the request is first sent from the device to the server, which initiates a filtering process based on the user's settings.

[1178] Input: The URL entered by the user

[1179] Data processing: Formatting URL information as an HTTP request

[1180] Output: HTTP request sent to the server

[1181] Specific operation: When you enter a URL in the browser's address bar and press Enter, the device generates an HTTP request and sends it to the server.

[1182] Step 3: Retrieving web page content

[1183] The server retrieves the HTML content of the specified web page based on the received request. It uses an HTTP client library to retrieve the desired web page.

[1184] Input: The URL requested by the user

[1185] Data processing: Convert the URL into an HTTP request and obtain the HTML of the web page.

[1186] Output: The retrieved HTML document

[1187] Specific operation: The server uses Python's requests library to access the URL and retrieve the HTML document.

[1188] Step 4: Analyzing content and generating filtering rules

[1189] The server analyzes the retrieved HTML document using a generative AI model, sends a prompt to the generative AI model, and generates filtering rules.

[1190] Input: HTML document, user settings information

[1191] Data processing: Send prompts to the generative AI model and obtain analysis results

[1192] Output: Generated filtering rules

[1193] Specific operation: The server sends the following prompt to the generation AI model to generate filtering rules:

[1194] Parse an HTML document and identify elements that fall into the following categories: sexual content, politics, religion, and ideology. Generate CSS rules that apply "display: none;" to the identified elements.

[1195] Step 5: Regenerate filtered content

[1196] The server then applies the generated filtering rules to regenerate the content of the web page, resulting in an HTML document that excludes the unwanted content.

[1197] Input: Generated filtering rules, original HTML document

[1198] Data processing: Apply filtering rules to HTML and regenerate content

[1199] Output: Regenerated HTML document

[1200] What happens: The server applies filtering rules to the original HTML and reconstructs the DOM.

[1201] Step 6: Sending filtered content

[1202] The server sends the regenerated filtered content to the terminal, where the user can view it.

[1203] Input: Regenerated HTML document

[1204] Data processing: Formatting the regenerated HTML document as an HTTP response

[1205] Output: HTTP response sent to the device

[1206] Specific operation: The server sends the regenerated HTML document to the terminal as an HTTP response.

[1207] Step 7: Rendering the filtered content

[1208] The device then renders the received filtered content as a web page, allowing the user to view the web page with the unwanted content removed.

[1209] Input: The filtered HTML document received from the server

[1210] Data processing: Parse HTML documents and generate DOM

[1211] Output: Rendered web page

[1212] What happens: The device's browser engine parses the received HTML document, applies CSS rules, and renders the page.

[1213] In this way, the system can achieve highly accurate filtering based on the individual needs of users, providing a comfortable and safe Internet usage environment.

[1214] (Application example 1)

[1215] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1216] In conventional Internet browsing systems, users frequently encounter unwanted content, making it difficult to ensure safe and comfortable web browsing. Furthermore, content filtering is insufficient, especially on mobile devices, significantly impairing the user experience. Therefore, there is a need for a method that can quickly analyze web page content in real time based on user-specified filtering rules and appropriately filter out unwanted content.

[1217] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1218] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a URL of a website specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a document object model, means for applying filtering to the constructed document object model based on the user setting information, and means for transmitting the filtered content to the user's terminal for display. This allows the user to enjoy a safe and comfortable web browsing experience with unnecessary content filtered out in real time.

[1219] "User setting information" is information for specifying categories of content that the user does not want.

[1220] "URL" is an abbreviation for Uniform Resource Locator, and is a character string that indicates the address of a web page.

[1221] "HTML content" refers to the HTML documents that make up a web page and the elements contained within them.

[1222] A "server" is a central computer system that provides data over a network.

[1223] The "Document Object Model (DOM)" is a model for representing HTML documents as a hierarchical structure, making it easier to manipulate them programmatically.

[1224] A "filtering rule" is a rule for preventing certain content from being displayed based on conditions specified by the user.

[1225] "Parsing" is the process of reading an HTML document as code and identifying each element.

[1226] "Regeneration" means reconstructing the content of a web page after applying the filtering rules.

[1227] "Local Database" means a database stored on a User's device that is used to store User settings and other important information.

[1228] A "terminal" is a computing device (e.g., smartphone, tablet, computer) that is directly operated by a user.

[1229] This invention is a system for filtering content that a user does not want to view, thereby providing a comfortable and safe Internet usage environment. The basic configuration of the system includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for regenerating the filtered content to provide it to the user, means for transmitting the regenerated content to the user's terminal, means for receiving a website URL specified by the user and acquiring HTML content, means for analyzing the acquired HTML content and constructing a Document Object Model (DOM), means for applying filtering to the constructed DOM based on the user setting information, and means for transmitting the filtered content to the user's terminal for display.

[1230] First, when a user launches a browser for the first time, they enter user configuration information to specify categories of content they do not want. This user configuration information is then saved in the device's local database and synchronized with the server. When the user accesses a specific website, the device sends the specified URL to the server, which retrieves the corresponding HTML content. The server then uses a library such as BeautifulSoup to analyze the retrieved HTML content and construct a DOM. Filtering rules are applied to the constructed DOM to hide the unwanted content specified by the user.

[1231] After applying the filtering rules, the server regenerates the content of the web page and sends the filtered content to the user's device. The device receives the regenerated content, allowing the user to view it with unnecessary content removed.

[1232] A concrete example is when a user visits a news site. If the user selects to filter "violent content," the server retrieves the HTML of the specified news site, analyzes the DOM to identify violent articles and images, and filters them. Finally, the user is presented with a clean news site with no violent content.

[1233] An example prompt is:

[1234] "Using SafeBrowse, I visited a specific news site. I selected 'Violent Content' as the filtering category. The URL for the news site is 'http: / / example.com / news'. Please explain how SafeBrowse filters this page."

[1235] This invention allows users to enjoy a filtered, safe and comfortable web browsing experience.

[1236] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1237] Step 1:

[1238] The user launches the browser and selects the categories of unwanted content on the initial setup screen. The information entered here is user preference information, which specifies the types of content the user wants to filter while browsing. This preference information is saved in the device's local database and is then synchronized with the server. The entered data is user preference information, and data processing is performed to save it in the local database.

[1239] Step 2:

[1240] When a user accesses a particular website using a browser, the device receives the specified URL. This URL is the address of the website the user wants to visit. The input is the URL entered by the user, and data processing is performed to send this information to the server. The output is a URL request to the server.

[1241] Step 3:

[1242] The server retrieves the HTML content of the website based on the specified URL. Using the above request URL as input, it sends an HTTP request to retrieve the target HTML document. The output is the HTML content.

[1243] Step 4:

[1244] The server parses the retrieved HTML content and constructs a Document Object Model (DOM). The input is the retrieved HTML content, and a library such as BeautifulSoup is used to parse the HTML code and generate a DOM tree. The output is the constructed DOM tree. Specifically, the process converts HTML tags into a tree structure and identifies each element.

[1245] Step 5:

[1246] The server applies filtering to the constructed DOM tree based on user configuration information. The input is the user configuration information and the constructed DOM tree, and it applies user-specified filtering rules (e.g., removing violent content). The output is the filtered DOM tree.

[1247] Step 6:

[1248] The server applies the filtering rules and then recreates the web page content. The input is the filtered DOM tree, and the server recreates the HTML document based on the DOM content. The output is the recreated HTML content.

[1249] Step 7:

[1250] The server sends the regenerated HTML content to the user's terminal. The input is the regenerated HTML content, which is sent to the user's terminal as an HTTP response. The output is the HTML content converted into a format that can be displayed on the user's terminal.

[1251] Step 8:

[1252] The terminal displays the regenerated HTML content it receives. The input is the regenerated HTML content sent from the server, which is rendered in the terminal's browser and displayed to the user. This process allows the user to view a web page with the specified unwanted content filtered out. The output is the filtered web page displayed to the user.

[1253] The above are the processing steps of this system.

[1254] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1255] This invention is a browser system that combines an emotion engine that recognizes the user's emotions. In addition to the basic functions of receiving user settings, filtering, regenerating, and providing specific content, it also has the ability to analyze the user's emotional state in real time and dynamically change filtering rules. This system provides a comfortable Internet usage environment that is tailored to the user's psychological state.

[1256] User Settings

[1257] When users first launch the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter, such as ads related to sexual complexes or articles on politics, religion, and ideology. This configuration information is stored in a local database by the device and synchronized with the server.

[1258] Access to the web page

[1259] When a user attempts to access a specific web page using a browser, the terminal sends an access request to the server, along with the user setting information.

[1260] Content Acquisition and Analysis

[1261] The server retrieves the target web page based on the received access request and analyzes its HTML content. This analysis is performed using generative AI to identify each element on the page, such as advertisements, articles, and links.

[1262] Emotion recognition by emotion engine

[1263] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes emotions in real time from the user's facial expressions and voice. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice and recognizes their emotional state, such as positive or negative.

[1264] Content Filtering

[1265] The server identifies content elements to be filtered based on user settings and the emotion analysis results of the emotion engine. If the emotion engine recognizes the user's emotion as negative, specific content (e.g., articles or advertisements that may cause stress) will be filtered as well.

[1266] Creating and dynamically changing filtering rules

[1267] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS, and dynamically changes the filtering rules based on the analysis results of the emotion engine.

[1268] Regenerate and send content

[1269] The server applies the generated filtering rules to generate regenerated content and transmits it to the terminal.

[1270] User Browsing

[1271] The device then renders the received filtered content as a web page. The user then browses the web page, which displays content filtered based on real-time emotion recognition and user settings. For example, if the user's emotion is negative, articles or advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[1272] Specific examples

[1273] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[1274] This system allows users to have the optimal browsing environment according to their own emotions and preferences.

[1275] The processing flow will be explained below.

[1276] Step 1:

[1277] When a user first launches the browser, they are presented with an initial setup screen where they can select the categories of content they want to filter. This could include, for example, ads related to sexual complexes or articles related to politics, religion, or ideology. This setting allows filtering based on the user's preferences.

[1278] Step 2:

[1279] The device stores the user's selected settings in a local database, which is then synchronized with the server.

[1280] Step 3:

[1281] When a user accesses a specific web page using a browser, the access request is sent from the terminal to the server, which also includes user setting information.

[1282] Step 4:

[1283] The server retrieves the target web page based on the received access request, and the HTML content of this web page is analyzed.

[1284] Step 5:

[1285] The server uses a generation AI to analyze the retrieved HTML content, which identifies each element on the web page, such as advertisements, articles, and links.

[1286] Step 6:

[1287] The device is equipped with an emotion engine that recognizes the user's emotions. The device uses a camera and microphone to analyze the user's facial expressions and voice in real time, and recognizes positive and negative emotional states.

[1288] Step 7:

[1289] The server identifies content elements to be filtered based on user settings and the analysis results of the emotion engine. For example, if the emotion engine recognizes the user's emotion as negative, articles and advertisements that may cause stress are additionally filtered.

[1290] Step 8:

[1291] The server lists the identified content elements and generates rules for filtering them, including hiding them using HTML and CSS.

[1292] Step 9:

[1293] The server applies these filtering rules to regenerate the content of the web page, and the regenerated content has unnecessary elements deleted or hidden.

[1294] Step 10:

[1295] The server transmits the regenerated filtered content to the terminal.

[1296] Step 11:

[1297] The device then renders the received filtered content as a web page, allowing the user to view the web page with the content filtered based on real-time emotion recognition and user settings.

[1298] Step 12:

[1299] For example, if a user visits a news site and the emotion engine recognizes the user's emotion as negative, political articles and articles that may cause stress will be filtered out from the news site, preventing these articles from appearing and allowing the user to enjoy a comfortable and stress-free browsing experience.

[1300] Example 2

[1301] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1302] Existing Internet browser systems provide the ability to filter content based on a user's specific preferences, but they are unable to dynamically change content filtering rules to take into account the user's real-time emotional state, making it difficult for users to obtain an optimal Internet usage environment that reflects their psychological state at any given time.

[1303] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1304] In this invention, the server includes means for receiving user setting information, means for filtering specific content based on the user setting information, means for using an emotion engine that analyzes the user's emotional state in real time, means for dynamically changing filtering rules based on the emotion analysis results, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal, thereby making it possible to provide an Internet usage environment that corresponds to the user's real-time emotional state.

[1305] "User setting information" is information about the categories of content to be filtered, which is set by the user when the user starts up the Internet browser for the first time.

[1306] "Means for filtering specific content" refers to a function that excludes content that should not be displayed based on user setting information.

[1307] The "emotion engine" is a system that analyzes the user's facial expressions and voice and recognizes the user's emotional state in real time.

[1308] "Means for dynamically changing filtering rules based on emotion analysis results" is a function that changes filtering rules each time according to the emotional state recognized by the emotion engine.

[1309] "Regenerated content" refers to the content of a web page that has been reconstructed after applying filtering rules.

[1310] A "terminal including a storage device" is a user's device that has a storage function for saving data such as user setting information.

[1311] A "server" is a central processing unit that receives a web page access request from a user, retrieves, analyzes, filters, and regenerates the content, and sends the results to a terminal.

[1312] A "storage device for saving user setting information" is a storage mechanism within the device for saving setting information specified by the user.

[1313] "Means for analyzing the content of a web page" refers to the ability to analyze the HTML and other code of a web page and identify each element within the page.

[1314] "Filtering rules" are a set of rules and conditions that determine whether content is displayed or hidden.

[1315] This invention is a system that recognizes a user's emotions and dynamically filters Internet content based on those emotions. This system aims to provide an environment in which users can comfortably use the Internet.

[1316] Specifically, the system includes a means for receiving user setting information, a means for filtering specific content, an emotion engine for analyzing the user's emotional state in real time, a means for dynamically changing filtering rules based on the emotion analysis results, a means for regenerating the filtered content, and a means for transmitting the regenerated content to the user's terminal.

[1317] Hardware and software used

[1318] To implement this system, the following hardware and software are required:

[1319] User device: A computer or smart device equipped with a camera, microphone, and a local database

[1320] Server: a central processing unit for high-performance analysis and data processing

[1321] Emotion Engine: Software that analyzes the user's facial expressions and voice

[1322] Generative AI: The model used to analyze content (e.g., GPT-4)

[1323] Communication protocol: Network communication technology such as HTTP / HTTPS

[1324] System processing overview

[1325] 1. User Settings: When a user launches the browser for the first time, an initial setup screen appears. The user selects the categories of content they do not want to see (e.g., sexual content, politics, religion, etc.). This setting information is stored in a local database on the device and synchronized with the server.

[1326] 2. Accessing a web page: When a user attempts to access a specific web page, an access request is sent from the terminal to the server, along with user setting information.

[1327] 3. Content retrieval and analysis: The server retrieves the HTML content of the web page based on the access request. It uses a generative AI model (e.g., GPT-4) to analyze the HTML content and identify each content element, such as an advertisement, article, or link.

[1328] 4. Emotion recognition using an emotion engine: The emotion engine installed on the device uses the camera and microphone to analyze the user's facial expressions and voice in real time and recognize positive and negative emotional states.

[1329] 5. Content filtering: The server identifies content elements to filter based on user preferences and the analysis results of the emotion engine. If a negative emotional state is detected, certain content (e.g., articles or advertisements that may cause stress) will be additionally filtered.

[1330] 6. Generation and dynamic modification of filtering rules: The server generates filtering rules for the identified content elements. The filtering rules may be dynamically modified based on the analysis results of the emotion engine.

[1331] 7. Regenerate and send content: The server applies the filtering rules and sends the regenerated content to the terminal.

[1332] 8. User browsing: The device renders the filtered content as a web page, and the user browses the web page, with content based on real-time emotion recognition and user preferences.

[1333] Specific examples

[1334] For example, suppose a user accesses a news site and has set their browser to hide political articles, and the emotion engine detects negative emotions at that time. In this case, the server retrieves the news site's HTML and analyzes it using generative AI. Political articles are identified, and filtering rules are generated for those target elements. Furthermore, based on the negative emotion analysis results, news articles that may cause additional stress are also filtered. The content is regenerated with the generated filtering rules applied and sent to the user's device. As a result, the user can comfortably browse the news site with political articles and news that may cause stress hidden.

[1335] Prompt Sentence Examples

[1336] Here are some example prompts to input to a generative AI model:

[1337] Please provide a step-by-step description of the process a browser system uses to enforce filtering when user sentiment is negative, starting from saving the user's preferences to finally displaying filtered content to the user.

[1338] This prompt allows the generative AI model to explain each processing step in detail.

[1339] In this way, the present invention can provide an optimal Internet usage environment based on the user's feelings and preferences.

[1340] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1341] Step 1: Enter and save your user settings

[1342] When a user first launches the browser, they are presented with an initial setup screen. They select the categories of content they do not want to view (e.g., sexual content, politics, religion, etc.). This information is stored in a local database on the device and serves as input. The settings are then synchronized with the server and serve as output. For example, if a user chooses to hide the "Politics" category, that setting is stored on the device and sent to the server.

[1343] Step 2: Access the web page

[1344] When a user attempts to access a specific web page, the request is sent from the terminal to the server. The user setting information stored in the terminal's database is also sent here, and this becomes input. The server receives the access request and outputs the URL of the web page and the user setting information.

[1345] Step 3: Acquire and parse content

[1346] Based on the received access request, the server retrieves the HTML content of the specified web page from the Internet. The retrieved HTML content is used as input and analyzed using a generative AI model (e.g., GPT-4). This analysis identifies each element, such as advertisements, articles, and links, and outputs the analysis results. For example, all advertisements and articles on a news site are identified.

[1347] Step 4: Emotion Recognition with the Emotion Engine

[1348] The device is equipped with an emotion engine that recognizes the user's emotions. It uses a camera and microphone to analyze the user's facial expressions and voice in real time and recognizes positive and negative emotional states. The user's facial expressions and voice are input, and the emotion analysis results are output. For example, if the user's facial expression is smiling, it is judged as positive, and if they are frowning, it is judged as negative.

[1349] Step 5: Filtering content

[1350] The server identifies content elements to be filtered based on user settings and the emotion engine's analysis results. User settings and emotion analysis results are input, and a list of content to be filtered is output. For example, if a user hides the "Politics" category and the emotion is negative, certain news articles will be filtered.

[1351] Step 6: Creating and dynamically changing filtering rules

[1352] The server generates filtering rules for the identified content elements. These rules include hiding settings using HTML and CSS. The list of content to be filtered is input, and the filtering rules are output. In addition, the filtering rules may be dynamically changed based on the analysis results of the emotion engine. For example, if the emotion changes to a positive one, the filtered content will be redisplayed.

[1353] Step 7: Regenerate and submit content

[1354] The server applies the generated filtering rules to create regenerated content. The filtering rules and the original HTML content are input, and regenerated HTML content is output. This is then sent to the terminal. For example, content with CSS rules applied to hide specific HTML tags is generated and sent to the terminal.

[1355] Step 8: User Browsing

[1356] The device renders the received filtered content as a web page. The transmitted regenerated content is input and the rendered web page is output. The user then browses the web page, which displays content filtered based on emotion recognition and user settings. For example, if the user is in a negative emotional state, news articles and advertisements that may cause stress are hidden, allowing the user to enjoy a comfortable and stress-free browsing experience.

[1357] (Application example 2)

[1358] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1359] In modern content distribution services, many users browse content from various categories, which can often cause psychological stress. In particular, when a user is experiencing negative emotions, content that exacerbates those emotions can make the user's experience even more unpleasant. In such situations, users need to receive content that is appropriately filtered according to their emotions.

[1360] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user setting information, means for filtering specific content, emotion recognition means for recognizing the user's emotion in real time, means for dynamically changing the filtering rules based on the emotion analysis result by the emotion recognition means, means for regenerating the filtered content, and means for transmitting the regenerated content to the user's terminal. This enables the user to receive filtered content that is suited to their emotional state in real time.

[1361] "User setting information" is information about the category of content that the user selects on the initial setting screen of a browser or application to display or hide.

[1362] The "content filtering means" is a means having a function of selecting specific content and determining whether to display or hide it based on user setting information.

[1363] The "emotion recognition means" is a means having the function of analyzing the user's emotions in real time from their facial expressions and tone of voice, and recognizing their emotional state.

[1364] The "means for dynamically changing filtering rules" refers to a means having a function for changing in real time the rules for adding or removing content to be filtered based on the emotion analysis results obtained by the emotion recognition means.

[1365] The "content regeneration means" is a means having the function of applying the filtering rules defined above and reconstructing the content to be provided to the user.

[1366] The "content transmitting means" is a means having a function of transmitting the regenerated content to the user's terminal.

[1367] A "local database" is a database that is installed on a user terminal and that saves and temporarily stores user setting information.

[1368] A "server" is a central management system that receives access requests from user terminals, analyzes and filters the content, and provides the regenerated content to the user.

[1369] This invention relates to a system that recognizes a user's emotions in real time and filters content according to the user's psychological state. This system mainly comprises the following elements: a means for receiving user setting information, a means for filtering specific content, an emotion recognition means for recognizing the user's emotions, a means for dynamically changing filtering rules, a means for providing the regenerated content to the user, and a means for transmitting the regenerated content to the user's terminal.

[1370] System configuration and operation

[1371] 1. Receiving user settings information:

[1372] When a user first uses the system, they enter content filtering configuration information, which specifies the categories of content they do not want to see. This configuration information is stored in a local database on the device and synchronized with the server.

[1373] 2. Real-time emotion recognition:

[1374] The device utilizes a built-in camera and microphone to capture the user's facial expressions and voice, and then analyzes emotions in real time using emotion recognition, which is powered by a pre-trained generative AI model.

[1375] 3. Integrating emotion data and user preference information:

[1376] The server dynamically changes the filtering rules based on the received user setting information and real-time emotional states detected by the emotion recognition means. The filtering rules include HTML and CSS settings for hiding specific content.

[1377] 4. Content Acquisition and Analysis:

[1378] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is identified by specific categories. Based on these analysis results, the server generates filtering rules to provide content appropriate to the user.

[1379] 5. Reproducing and Submitting Content:

[1380] The server regenerates the filtered content based on the generated filtering rules and transmits the content to the user's terminal, which then renders the received content and displays it to the user.

[1381] Hardware and software configuration

[1382] The main hardware and software used in this system are as follows:

[1383] Camera and microphone: Captures the user's facial expressions and voice.

[1384] Emotion recognition: Using generative AI models trained using machine learning frameworks such as TensorFlow.

[1385] Server: Acquires content, analyzes it, generates filtering rules, and regenerates content.

[1386] Local Database: A database for storing user configuration information and synchronizing it with the server.

[1387] Specific examples

[1388] For example, if a user is using a video streaming service and has set horror movies to be hidden, and the emotion recognition means analyzes the user's emotion as "sad," the server will filter out not only horror movie content but also movies that may evoke sad emotions. As a result, the user can watch safe and comfortable content that is adapted to their emotional state.

[1389] Prompt Sentence Examples

[1390] "Generate a model that analyzes emotions from a user's facial expressions and voice in real time."

[1391] "Generate an algorithm that dynamically changes filtering rules based on the user's emotional state."

[1392] "Build a system that filters content that may cause stress based on emotion recognition results."

[1393] Such a system allows users to enjoy content that is optimal for their emotional state, providing a stress-free experience.

[1394] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1395] Step 1:

[1396] When a user first uses the system, they enter their user configuration information, select the content categories they do not want to see (e.g., violence, horror, politics), and the information is stored in a local database on the device and synchronized with the server.

[1397] Input: Content category selection by user.

[1398] Output: Saved user settings information.

[1399] Step 2:

[1400] The device uses a built-in camera and microphone to capture the user's facial expressions and voice in real time.

[1401] Input: User's facial expression data, voice data.

[1402] Output: Captured facial and speech data.

[1403] Step 3:

[1404] The device analyzes the captured data using emotion recognition means – for example, a generative AI model using TensorFlow – to recognize the user's emotions in real time.

[1405] Input: Captured facial expression data, audio data.

[1406] Data processing: Sentiment analysis is performed using generative AI models.

[1407] Output: Perceived emotional state (e.g., positive, negative).

[1408] Step 4:

[1409] The device sends the analyzed emotional state to the server, and the server dynamically generates and modifies filtering rules based on the received user settings and emotion recognition results, including HTML and CSS settings to hide specific content (e.g., articles or videos that may cause stress).

[1410] Input: User preference information, perceived emotional state.

[1411] Data processing: Applying algorithms to generate filtering rules.

[1412] Output: The generated filtering rules.

[1413] Step 5:

[1414] The server retrieves the content of the web page based on the user's access request and analyzes it using generative AI. The analyzed content is then identified by specific categories.

[1415] Input: Web page URL, filtering rules.

[1416] Data processing: Analyze web content using a generative AI model and identify it by category.

[1417] Output: Parsed content information.

[1418] Step 6:

[1419] The server then regenerates the parsed content based on the generated filtering rules to create a filtered web page, which involves using HTML and CSS to hide certain elements.

[1420] Input: Parsed content information, filtering rules.

[1421] Data manipulation: Regenerate content by applying HTML and CSS.

[1422] Output: The regenerated filtered web page.

[1423] Step 7:

[1424] The server sends the regenerated web page to the user's device, which renders the received content and displays it to the user.

[1425] Input: The regenerated web page.

[1426] Output: The filtered content that is displayed to the user.

[1427] In this way, filtering adapted to the user's emotional state is performed through a series of steps, providing a stress-free content viewing environment.

[1428] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1429] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1430] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1431] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1432] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1433] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1434] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1435] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1436] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1437] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1438] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1439] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1440] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1441] 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.

[1442] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1443] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1444] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1445] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1446] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1447] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1448] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1449] The following is further disclosed regarding the above embodiment.

[1450] (Claim 1)

[1451] means for receiving user setting information;

[1452] means for filtering specific content based on said user setting information;

[1453] means for regenerating the filtered content for presentation to a user;

[1454] means for transmitting the regenerated content to a user terminal;

[1455] A system including:

[1456] (Claim 2)

[1457] means for receiving user-desired content preferences;

[1458] means for analyzing the content of a web page based on the settings;

[1459] means for generating filtering rules based on the analysis results;

[1460] means for regenerating the content of a web page by applying the filtering rules;

[1461] means for transmitting the regenerated content to a user terminal;

[1462] 10. The system of claim 1, comprising:

[1463] (Claim 3)

[1464] a terminal including a local database for storing user configuration information;

[1465] means for synchronizing information in said local database with a server;

[1466] means for applying filtering rules received from the server;

[1467] 10. The system of claim 1, comprising:

[1468] "Example 1"

[1469] (Claim 1)

[1470] means for receiving user setting information;

[1471] means for filtering specific content based on said user setting information;

[1472] means for regenerating the filtered content for presentation to a user;

[1473] means for transmitting the regenerated content to a user terminal;

[1474] A means of analyzing the HTML content of a web page using a generative AI model;

[1475] means for generating filtering rules based on the analysis;

[1476] A system including:

[1477] (Claim 2)

[1478] means for receiving user-desired content preferences;

[1479] means for analyzing the content of a web page based on the settings;

[1480] means for generating filtering rules based on the analysis results;

[1481] means for regenerating the content of a web page by applying the filtering rules;

[1482] means for transmitting the regenerated content to a user terminal;

[1483] 10. The system of claim 1, comprising:

[1484] (Claim 3)

[1485] a terminal including a local database for storing user configuration information;

[1486] means for synchronizing information in said local database with a server;

[1487] means for applying filtering rules received from the server;

[1488] 10. The system of claim 1, comprising:

[1489] "Application Example 1"

[1490] (Claim 1)

[1491] means for receiving user setting information;

[1492] means for filtering specific content based on said user setting information;

[1493] means for regenerating the filtered content for presentation to a user;

[1494] means for transmitting the regenerated content to a user terminal;

[1495] A means for receiving a website URL designated by a user and retrieving HTML content;

[1496] a means for parsing the retrieved HTML content and constructing a document object model;

[1497] means for applying filtering to the constructed document object model based on user setting information;

[1498] means for transmitting the filtered content to a user's terminal for display;

[1499] A system including:

[1500] (Claim 2)

[1501] means for receiving user-desired content preferences;

[1502] means for analyzing the content of a web page based on the settings;

[1503] means for generating filtering rules based on the analysis results;

[1504] means for regenerating the content of a web page by applying the filtering rules;

[1505] means for transmitting the regenerated content to a user terminal;

[1506] means for receiving a URL of a website accessed by a user and retrieving an HTML document;

[1507] means for parsing the HTML document;

[1508] means for applying filtering rules based on the parsed document object model;

[1509] 10. The system of claim 1, comprising:

[1510] (Claim 3)

[1511] a terminal including a local database for storing user configuration information;

[1512] means for synchronizing information in said local database with a server;

[1513] means for applying filtering rules received from the server;

[1514] means for storing parsed document object models of websites accessed by a user and applying filtering;

[1515] means for storing the content regenerated based on the filtering rules in a local database and displaying the content;

[1516] 10. The system of claim 1, comprising:

[1517] "Example 2: Combining Emotion Engines"

[1518] (Claim 1)

[1519] means for receiving user setting information;

[1520] means for filtering specific content based on said user setting information;

[1521] means for using an emotion engine to analyze the user's emotional state in real time;

[1522] means for dynamically changing filtering rules based on the emotion analysis results;

[1523] means for regenerating the filtered content;

[1524] means for transmitting the regenerated content to a user terminal;

[1525] A system including:

[1526] (Claim 2)

[1527] means for receiving user-desired content preferences;

[1528] means for analyzing the content of a web page based on the settings;

[1529] means for generating filtering rules based on the analysis results;

[1530] means for regenerating the content of a web page by applying the filtering rules;

[1531] means for transmitting the regenerated content to a user terminal;

[1532] 10. The system of claim 1, comprising:

[1533] (Claim 3)

[1534] a terminal including a storage device for storing user setting information;

[1535] means for synchronizing information in the storage device with a server;

[1536] means for applying filtering rules received from the server;

[1537] 10. The system of claim 1, comprising:

[1538] "Application example 2 when combining emotion engines"

[1539] (Claim 1)

[1540] means for receiving user setting information;

[1541] means for filtering specific content based on said user setting information;

[1542] emotion recognition means for recognizing the user's emotions in real time;

[1543] means for dynamically changing filtering rules based on emotion analysis results by the emotion recognition means;

[1544] means for regenerating the filtered content for presentation to a user;

[1545] means for transmitting the regenerated content to a user terminal;

[1546] A system including:

[1547] (Claim 2)

[1548] means for receiving user-desired content preferences;

[1549] means for analyzing the content of a web page based on the settings;

[1550] means for generating filtering rules based on the result of the user's emotion analysis;

[1551] means for regenerating the content of a web page by applying the filtering rules;

[1552] means for transmitting the regenerated content to a user terminal;

[1553] 10. The system of claim 1, comprising:

[1554] (Claim 3)

[1555] a terminal including a local database for storing user configuration information;

[1556] means for synchronizing information in said local database with a server;

[1557] a terminal including the emotion recognition means;

[1558] means for applying filtering rules received from the server;

[1559] 10. The system of claim 1, comprising: [Explanation of symbols]

[1560] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving user setting information; means for filtering specific content based on said user setting information; means for regenerating the filtered content for presentation to a user; means for transmitting the regenerated content to a user terminal; A system including:

2. means for receiving user-desired content preferences; means for analyzing the content of a web page based on the settings; means for generating filtering rules based on the analysis results; means for regenerating the content of a web page by applying the filtering rules; means for transmitting the regenerated content to a user terminal; The system of claim 1 , comprising:

3. a terminal including a local database for storing user configuration information; means for synchronizing information in said local database with a server; means for applying filtering rules received from the server; The system of claim 1 , comprising:

Images