System

Abstract

A system is provided.SOLUTION: The system includes an interface means for a user to input a figure to be simulated, a means for a server to analyze the input from the user and extract a related keyword, a means for the server to generate a filter setting on the basis of the extracted keyword, and a means for a terminal to acquire and display web contents on the basis of the received filter setting.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] Nowadays, it is common for internet advertisements and content to be personalized based on a user's interests and attributes. This creates the problem that users tend to receive similar information over and over, narrowing their perspective. Furthermore, limited opportunities to obtain information from different attributes and perspectives make it difficult to discover new things or spark interest. The present invention aims to solve these problems by providing a browser system that allows users to enjoy the internet from someone else's perspective. [Means for solving the problem]

[0005] The present invention provides a system that includes an interface for a user to input the character they wish to simulate; a server that analyzes the user's input and extracts relevant keywords; a server that generates filter settings based on the extracted keywords; and a terminal that acquires and displays web content based on the filter settings received. This configuration allows users to easily access information viewed by people with different attributes, enabling them to discover new perspectives and interests. Furthermore, because content controlled by the filter is displayed, users can expect to be freed from the filter bubble of everyday life.

[0006] "User" refers to a person who uses this system to input the image of the person they wish to simulate and receives and displays the content.

[0007] "Interface means" refers to the input device or software functions that allow the user to input the image of the person they wish to simulate.

[0008] "Server" refers to a device with computational resources for receiving input data from a user, performing analysis, and generating filter settings.

[0009] "Analysis" refers to the data processing procedure by which the server processes input data from the user and extracts relevant keywords.

[0010] "Keywords" refer to important words or phrases related to the person the user wants to simulate.

[0011] "Filter settings" refers to the rules and parameters that control the content displayed, generated based on keywords extracted by the server.

[0012] "Terminal" refers to a device (e.g., a PC, smartphone, or tablet) that a user operates and that displays filtered content.

[0013] "Web content" refers to information publicly available on the Internet (e.g., web pages, news articles, blog posts).

[0014] "Natural language analysis means" refers to technology in which the server analyzes text data entered by the user, understands the meaning, and extracts related keywords. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention provides a system that allows users to enjoy the Internet from different perspectives. This system is composed of the following main components:

[0037] System configuration

[0038] 1. Interface Method

[0039] This is an interface means for users to input the character they want to simulate. This interface includes a form installed on the browser, and users can input such things as "a 30-year-old IT engineer" or "a housewife raising children."

[0040] 2. Server

[0041] The server receives the person image data sent from the user.

[0042] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0043] 3. Filter Generation

[0044] The server generates filter configurations based on the extracted keywords, which contain rules for controlling content based on specific themes or interests, such as displaying only content related to "tech news" or "programming."

[0045] 4. Terminal

[0046] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0047] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[0048] Program processing

[0049] 1. User Input

[0050] The user inputs the image of the person they want to simulate using the interface. For example, they input "a 30-year-old IT engineer."

[0051] The user clicks the "Submit" button to send the input data to the server.

[0052] 2. Data Analysis

[0053] The server receives the input data and begins parsing it.

[0054] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0055] 3. Filter generation and transmission

[0056] Based on the extracted keywords, the server generates a filter configuration, which contains rules that control web content based on specific themes or interests.

[0057] The generated filter settings are sent to the device.

[0058] 4. Applying filters and retrieving content

[0059] The device applies the received filter settings and retrieves the controlled web content.

[0060] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[0061] Specific examples

[0062] 1. The user enters "30-year-old IT engineer."

[0063] 2. The server receives this input and analyzes it, extracting keywords such as "IT," "technology news," and "programming."

[0064] 3. The server generates filter settings based on these keywords, for example, creating a filter that includes "tech blogs," "latest IT news," "programming forums," etc.

[0065] 4. The device receives and applies the filter settings.

[0066] 5. The device retrieves the appropriate web content and displays it in the browser, allowing the user to enjoy the latest relevant information from the perspective of a 30-year-old IT engineer.

[0067] As described above, this system provides a new perspective by switching the user's perspective to other attributes, providing an internet experience that is free from the filter bubble of everyday life.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user launches a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button, sending the input data to the server.

[0071] Step 2:

[0072] The server receives the input data. The received profile data is analyzed using natural language processing (NLP) technology to extract related keywords. For example, if "IT engineer" is entered, keywords such as "technology news," "programming," and "latest gadgets" are extracted.

[0073] Step 3:

[0074] The server generates a filter configuration based on the extracted keywords. This filter configuration contains rules and parameters for controlling related web content, such as displaying content related to the categories "tech news" and "programming."

[0075] Step 4:

[0076] The server sends the generated filter settings to the terminal, and the terminal receives the filter settings sent from the server.

[0077] Step 5:

[0078] The terminal acquires web content based on the filter settings received, and selects appropriate information using a content acquisition means based on the filter.

[0079] Step 6:

[0080] The device displays the acquired web content in the browser. The displayed content is controlled by a filter, allowing the user to enjoy information from the perspective of other attributes.

[0081] Step 7:

[0082] Users can browse content provided from different perspectives on their browsers. For example, they can enjoy technical articles or the latest programming information. This allows users to experience the Internet from a new perspective.

[0083] The above is the specific flow of processing from inputting the image of the person the user wants to simulate and generating a filter based on that image to displaying content.

[0084] Example 1

[0085] 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."

[0086] In conventional Internet usage, it is difficult for users to obtain information based on specific perspectives or interests, and they often rely on biased information from the same source. Therefore, there is a need for methods to provide Internet experiences with new perspectives.

[0087] 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.

[0088] In this invention, the server includes means for receiving the image of a person the user wishes to simulate and extracting related keywords using natural language analysis means, means for generating filter settings based on the extracted keywords and transmitting them to the terminal, and means for the terminal to apply the received filter settings to retrieve and display web content, thereby enabling users to enjoy the Internet from different perspectives.

[0089] A "user" is an entity that uses the system to input a profile and obtain Internet content.

[0090] "Interface means" is a component that includes tools and forms for the user to input the image of the person they wish to simulate.

[0091] A "server" is a computer system that receives data entered by a user and performs analysis and filter generation.

[0092] "Natural language analysis means" refers to analysis techniques and software used to extract keywords related to the person profile entered by the user.

[0093] "Keywords" are important words or phrases extracted based on the persona entered by the user.

[0094] "Filter settings" are rules or settings generated based on extracted keywords to control web content based on specific themes or interests.

[0095] A "terminal" is a device that receives filter settings and retrieves and displays web content based on those settings.

[0096] "Web content" is information or data obtained over the Internet and displayed to a user by a terminal.

[0097] The present invention relates to a system that allows users to enjoy the Internet from different perspectives. This system displays related web content based on the image of a person the user wants to simulate. Specific embodiments of this system are described below.

[0098] System configuration

[0099] The system consists of the following main elements:

[0100] 1. Interface Method

[0101] It is a form that allows users to input the type of person they want to simulate. Specifically, it is a form that is set up on a web browser. This form includes fields where users can input specific person descriptions, such as "a 30-year-old IT engineer" or "a housewife raising children."

[0102] 2. Server

[0103] The server receives input data sent by the user. Specifically, a web framework such as Python's Flask can be used.

[0104] The server analyzes the received data using natural language processing libraries such as NLTK and spaCy to extract relevant keywords.

[0105] The server generates filter settings based on the extracted keywords and sends them to the client terminal.

[0106] 3. Terminal

[0107] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0108] The device applies the received filter settings and retrieves web content based on them. To retrieve content based on the filters, web scraping technologies (such as Beautiful Soup or Scrapy) can be used.

[0109] The terminal displays the acquired content on the browser and provides it to the user.

[0110] Example of operation

[0111] 1. The user enters "30-year-old IT engineer" into the form in a web browser and clicks the "Submit" button.

[0112] 2. The server receives the input data and performs natural language analysis to extract related keywords such as "tech news," "programming," and "latest gadgets."

[0113] 3. The server generates interest-related filter settings based on these keywords, such as "tech blogs," "latest IT news," or "programming forums."

[0114] 4. The device receives the generated filter settings from the server, applies them, and retrieves the appropriate web content.

[0115] 5. The content acquired by the device is displayed in a web browser, allowing the user to enjoy relevant information from the perspective of a "30-year-old IT engineer."

[0116] Prompt Sentence Examples

[0117] When a user enters "30-year-old IT engineer," the server receives and analyzes the input, extracts related keywords, and generates a filter that controls web content based on the keywords and sends it to the device. The device then applies the filter and displays appropriate content. For example, keywords such as "technology news," "programming," and "latest gadgets" are extracted, and web content with corresponding filter settings is displayed.

[0118] This invention allows users to enjoy a new internet experience by changing their perspective, thereby reducing bias in daily information acquisition and enabling information gathering from a new perspective.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] A user enters "30-year-old IT engineer" into a form on a web browser and clicks the "Submit" button.

[0122] Input: User enters a text description of the person (e.g., "30-year-old IT engineer")

[0123] Output: A request with input data sent to the server

[0124] What happens: When a user enters text into a form field and clicks a button, the data in the form is sent to the server as an HTTP request.

[0125] Step 2:

[0126] The server receives the input data sent by the user and begins natural language analysis.

[0127] Input: User-entered data included in the HTTP request (e.g., "30-year-old IT engineer")

[0128] Output: Text data for analysis

[0129] What happens: The server receives the request using the Python Flask framework and passes the text data to a natural language analysis library (e.g., NLTK or spaCy).

[0130] Step 3:

[0131] The server extracts related keywords using natural language analysis.

[0132] Input: Text data for analysis (e.g., "30-year-old IT engineer")

[0133] Output: Extracted keywords (e.g. "tech news", "programming", "latest gadgets")

[0134] What it does: The server uses natural language analysis libraries to extract key keywords from the text data, including tagging parts of speech and word segmentation, to identify keywords related to the topic.

[0135] Step 4:

[0136] The server generates a filter configuration based on the extracted keywords.

[0137] Input: Extracted keywords (e.g., "tech news," "programming," "latest gadgets")

[0138] Output: Generated filter configuration (e.g. filter rules in JSON format).

[0139] What it does: The server uses the extracted keywords to generate filter rules in JSON format to control web content related to specific topics or interests.

[0140] Step 5:

[0141] The server sends the generated filter settings to the device.

[0142] Input: Generated filter configuration (e.g. filter rules in JSON format)

[0143] Output: HTTP response containing the filter configuration

[0144] Specific operation: The server returns the generated JSON format filter settings to the device as an HTTP response.

[0145] Step 6:

[0146] Apply the filter settings received by the device.

[0147] Input: HTTP response containing filter settings (e.g., filter rules in JSON format)

[0148] Output: The result of applying the filter settings

[0149] Specific operation: The device analyzes the filter settings from the HTTP response and stores the filters required to retrieve web content in memory.

[0150] Step 7:

[0151] The device retrieves web content based on the filter settings.

[0152] Input: The result of applying filter settings (e.g. saved filter settings)

[0153] Output: Appropriate web content (e.g. web page based on filters)

[0154] Specific operation: The device will search the target website according to the filter settings using web scraping technology (e.g., Beautiful Soup, Scrapy) to obtain relevant content.

[0155] Step 8:

[0156] The content acquired by the terminal is displayed in the browser.

[0157] Input: Appropriate web content (e.g., a retrieved web page)

[0158] Output: The displayed web page

[0159] Specific behavior: The device renders web content in the browser and presents it visually to the user.

[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] Modern internet users face the challenge of having few opportunities to encounter information from diverse perspectives, due to the way they obtain information, which tends to be limited to their own interests. Furthermore, there are no appropriate means for users to enjoy information from the perspectives of different people, and users tend to fall into a fixed perspective. This can lead to problems such as filter bubbles and biased perceptions.

[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 an interface means for the user to input the character image they wish to simulate, a means for analyzing the user's input and extracting related keywords, a means for generating filter settings based on the extracted keywords, a means for acquiring and displaying web content based on the filter settings received by the terminal, and a means for operating a smartphone application including content acquisition means and display means based on the user's input data. This allows the user to easily acquire information from different perspectives and characters, avoiding filter bubbles and enabling wider and more diverse information acquisition.

[0165] The "interface means" is a means for the user to input the image of the person they wish to simulate.

[0166] A "server" is a device that receives input from a user, analyzes it, and extracts related keywords.

[0167] The "keyword extraction means" is a means for the server to analyze the data received from the user and extract related keywords.

[0168] The "filter setting generation means" is a means for generating filter settings based on keywords extracted by the server.

[0169] A "terminal" is a device that retrieves and displays web content based on filter settings received from a server.

[0170] The "web content acquisition means" is a means for searching for and acquiring appropriate web content based on the filter settings received by the terminal.

[0171] The "display means" is a means for displaying the acquired web content to the user.

[0172] A "smartphone application" is software that allows a user to set up a simulated experience and operate content acquisition means and display means.

[0173] The "natural language analysis means" is an analysis means that allows the server to extract words related to specific themes or interests from the image of the person the user wishes to simulate.

[0174] The following system configuration is conceivable as an embodiment for carrying out the present invention: This system allows users to enjoy content from different perspectives, and is realized by a smartphone application.

[0175] System Overview

[0176] 1. User Interface

[0177] The interface means of the application includes a form for the user to input the profile of the person he / she wants to simulate. For example, the user inputs the profile of a "30-year-old IT engineer."

[0178] 2. Server

[0179] The server analyzes the profile data received from the user and extracts related keywords. This analysis is performed using natural language analysis. As a result of the analysis, for example, in the case of "IT engineer," keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0180] The server generates filter configurations based on the extracted keywords, which create rules to control content based on specific themes or interests.

[0181] 3. Smartphone Applications

[0182] The application on the smartphone receives the filter settings sent from the server, and searches for and retrieves web content based on the filter settings.

[0183] The acquired content is provided to the user through the display means of the application.

[0184] Hardware and software used

[0185] Hardware: Smartphone

[0186] Software: Flask (web framework), HTML template engine

[0187] Data Flow and Processing

[0188] 1. User Input

[0189] The user uses the smartphone application interface to input the "character they would like to simulate."

[0190] When the user presses the "Submit" button, the input data is sent to the server.

[0191] 2. Analysis on the server

[0192] The server receives the input data and analyzes it using natural language analysis. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0193] 3. Generate filter settings

[0194] The server generates a filter configuration based on the extracted keywords, which contains rules that control information related to a particular subject or interest.

[0195] The generated filter settings are sent to the smartphone application.

[0196] 4. Retrieving and Displaying Content

[0197] The smartphone application searches and retrieves web content based on the received filter settings.

[0198] The acquired content is provided to the user through the display means of the application.

[0199] Specific examples

[0200] Implementation example

[0201] Suppose a user opens an application on their smartphone and types in "30-year-old IT engineer." The server receives this and uses natural language analysis to extract keywords such as "technology news," "programming," and "latest gadgets." It then generates filter settings and retrieves and displays web content containing appropriate technology articles and links to sites.

[0202] Example prompts for generative AI models

[0203] "Create an application that extracts relevant keywords based on the user's profile and displays relevant content based on those keywords. For example, if a user enters "30-year-old IT engineer," generate a system program that extracts keywords such as "tech news," "programming," and "latest gadgets" and displays content related to those keywords."

[0204] Using this prompt, the generative AI model can generate the appropriate program code.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1: The user launches the smartphone application and uses the interface to input the "image of the person they wish to simulate."

[0207] Input: The user inputs personal data such as "a 30-year-old IT engineer."

[0208] What happens: A user fills in the application's input form with the appropriate information and clicks the "Submit" button.

[0209] Step 2: The terminal sends the input data from the user to the server.

[0210] Input: Persona data entered by the user.

[0211] Operation: The terminal sends the input data to the server as an HTTP request.

[0212] Step 3: The server analyzes the received input data and extracts relevant keywords.

[0213] Input: Person profile data received by the server.

[0214] Data processing: The server analyzes the data using natural language analysis means and extracts relevant keywords.

[0215] Output: A list of extracted keywords (e.g. "tech news", "programming", "latest gadgets").

[0216] How it works: The server uses a data analysis library (e.g., nltk or spaCy) to parse the input data.

[0217] Step 4: The server generates filter settings based on the extracted keywords.

[0218] Input: Extracted keyword list.

[0219] Data processing: The server identifies content related to the extracted keywords and generates filter settings.

[0220] Output: The generated filter configuration (e.g. "Tech Blogs", "Latest IT News", "Programming Forums").

[0221] How it works: The server uses filtering logic to define the content types to retrieve and generates a filter configuration.

[0222] Step 5: The server sends the filter settings to the device.

[0223] Input: The generated filter settings.

[0224] Output: The filter settings sent to the terminal.

[0225] Operation: The server sends the generated filter settings to the device as an HTTP response.

[0226] Step 6: The device retrieves web content based on the filter settings received.

[0227] Input: The filter settings received by the device.

[0228] Data processing: The device searches for and retrieves relevant web content based on filter settings.

[0229] Output: The retrieved web content list.

[0230] What it does: The device retrieves relevant content using a web scraping library (e.g. BeautifulSoup) or API calls.

[0231] Step 7: The terminal displays the retrieved web content to the user.

[0232] Input: The retrieved web content list.

[0233] Output: The web content displayed to the user.

[0234] How it works: The device uses an HTML template engine to format and visually display web content.

[0235] The above processing steps allow users to easily obtain information from different perspectives and personalities, avoiding filter bubbles and enabling them to obtain a wider range of diverse information.

[0236] 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.

[0237] The present invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system consists of the following main components:

[0238] System configuration

[0239] 1. Interface Method

[0240] It is an interface means for users to input the character they want to simulate. They can enter "30-year-old IT engineer" or "housewife raising children" into a form on the browser. It also has an emotion engine that recognizes the emotions of users when they enter information.

[0241] 2. Emotion Engine

[0242] The emotion engine recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. This recognition result is used to adjust filter settings.

[0243] 3. Server

[0244] The server receives the person image and emotion data sent by the user.

[0245] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0246] 4. Filter Generation

[0247] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "joy," a configuration including "fun news" and "interesting blogs" will be generated.

[0248] 5. Terminal

[0249] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0250] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[0251] Program processing

[0252] 1. User Input and Emotion Recognition

[0253] The user uses the interface to input the image of the person they want to simulate. For example, they can input "30-year-old IT engineer." At the same time, the emotion engine recognizes the user's facial expressions and voice, and analyzes whether the user is expressing emotions such as "joy," "excitement," or "surprise."

[0254] 2. Data Analysis

[0255] The server receives the input data and emotion data and begins analysis.

[0256] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0257] Based on the analysis results of the emotion engine, keywords are weighted to match the user's emotions.

[0258] 3. Filter generation and transmission

[0259] Based on the extracted keywords and emotion recognition results, the server generates filter configurations, which contain rules for controlling web content based on specific themes or interests, such as displaying content related to the categories "tech news" or "programming."

[0260] The generated filter settings are sent to the device.

[0261] 4. Applying filters and retrieving content

[0262] The device applies the received filter settings and retrieves the controlled web content.

[0263] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[0264] Specific examples

[0265] 1. The user types in "30-year-old IT engineer" and the emotion engine recognizes this as "excited."

[0266] 2. The server receives and analyzes this input and sentiment data. For example, keywords such as "IT," "technology news," and "programming" are extracted, and filter settings related to "latest technology news" and "innovative gadget reviews" are generated based on the user's sentiment.

[0267] 3. The server sends the filter settings to the device.

[0268] 4. The device applies the filter settings to retrieve and display appropriate web content, such as "The latest innovative tech news" or "Gadget reviews for IT professionals."

[0269] 5. Users can enjoy relevant updates in an exciting state.

[0270] As a result, this system not only shifts the user's perspective to other attributes, but also provides an internet experience that takes into account the user's emotions, providing a new perspective and an internet experience that is free from the filter bubble of everyday life.

[0271] The processing flow will be explained below.

[0272] Step 1:

[0273] The user opens a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button. At the same time, the emotion engine analyzes the emotions (e.g., facial expressions and voice) that the user is expressing when they input their input.

[0274] Step 2:

[0275] The server receives the personality data and emotion data sent by the user, analyzes the received personality data using natural language processing (NLP) technology, and extracts related keywords such as "technology news," "programming," and "latest gadgets."

[0276] Step 3:

[0277] The server analyzes the emotional data received from the emotion engine. For example, it can obtain data that the user is "excited." Based on this emotional data, it adjusts the priority of the extracted keywords. For example, keywords such as "latest technology news" and "innovative gadget reviews" are highly ranked.

[0278] Step 4:

[0279] The server generates filter configurations based on the analysis, which contain rules for controlling content related to specific themes or interests based on the extracted keywords and sentiment data, such as displaying content related to the categories "tech news" or "programming."

[0280] Step 5:

[0281] The server sends the generated filter settings to the device, which receives them.

[0282] Step 6:

[0283] Based on the filter settings received, the device sends requests to retrieve controlled web content. For example, the device retrieves relevant updates from specific news sites or tech blogs.

[0284] Step 7:

[0285] The device retrieves web content and displays it in the browser. The content displayed is controlled by filters, providing information based on the user's profile and sentiment. For example, it can display "the latest innovative tech news" or "gadget reviews for IT professionals."

[0286] Step 8:

[0287] Users browse the content displayed on their browsers, which allows them to enjoy relevant and up-to-date information in an exciting state, giving them a new Internet experience based on different perspectives and emotions.

[0288] The above is the specific flow of processing from inputting the image of the person the user wants to simulate, to generating a filter that takes into account emotional data based on that image, to displaying the content.

[0289] Example 2

[0290] 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."

[0291] In the past, the Internet experience was largely one in which users selected content based on their own interests. However, this limited users' opportunities to gain new perspectives and experiences, limiting their access to new content. Furthermore, because information was provided without considering the user's emotions or psychological state, the Internet experience was one-sided and difficult to personalize.

[0292] 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.

[0293] In this invention, the server includes an interface means for allowing the user to input the image of the person they wish to simulate and simultaneously recognizing the user's emotions, a means for the server to analyze the input and emotional data from the user and extract related keywords, and a means for generating filter settings based on the keywords and emotional data extracted by the server. This allows the user to enjoy the Internet from a new perspective and makes it possible to provide personalized information that takes the user's emotions into consideration.

[0294] "User" refers to an entity that inputs information to use the system and receives the resulting content.

[0295] The "image of the person the user wishes to simulate" refers to data input by the user indicating the attributes of a virtual person related to the information and perspective the user wishes to experience.

[0296] "Interface means" refers to a form or user interface on a browser that allows a user to input information.

[0297] "Emotional data" refers to emotional information extracted from a user's facial expressions, voice, and text.

[0298] An "emotion engine" refers to a system that recognizes and analyzes emotions from a user's facial expressions, voice, text, etc.

[0299] "Server" refers to a computer system that receives user-submitted character and emotion data and generates analysis and filter settings.

[0300] "Natural language analysis means" refers to a technical means for analyzing text data entered by a user and extracting related keywords and themes.

[0301] "Keywords" refer to relevant information extracted from the information and emotion data entered by the user and that serves as the basis for filter settings.

[0302] "Filter settings" refers to the rules and parameters that control the relevant web content that is generated based on extracted keywords and sentiment data.

[0303] "Terminal" refers to a device that retrieves web content based on filter settings received from a server and displays it to a user.

[0304] "Web content" refers to information such as news, articles, blogs, and videos obtained from the Internet.

[0305] This invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system operates in cooperation with the user, server, and terminal. Specifically, it is configured as follows:

[0306] System configuration

[0307] 1. Interface Method

[0308] It is a means for users to input the character they wish to simulate. It is implemented as a form on the browser. Users can input such things as "30-year-old IT engineer" or "housewife raising children." It also incorporates an emotion engine that recognizes the emotions expressed when users input data. The emotion engine uses OpenFace (facial expression recognition) and Google Cloud Speech-to-Text API (voice recognition).

[0309] 2. Emotion Engine

[0310] It recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. The results of this recognition are used to adjust filter settings.

[0311] 3. Server

[0312] The server receives the persona data and emotion data sent by the user. The received data is analyzed using natural language analysis tools (e.g., spaCy or Google Cloud Natural Language API) to extract related keywords. For example, if "IT engineer" is entered, keywords such as "tech news," "programming," and "latest gadgets" are extracted. Based on the analysis results of the emotion engine, the extracted keywords are weighted to generate filter settings that match the user's emotions.

[0313] 4. Filter Generation

[0314] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "excitement," a configuration including "latest technology news" and "innovative gadget reviews" will be generated. The generated filter configuration is sent to the device.

[0315] 5. Terminal

[0316] The device receives the filter settings sent from the server. Based on the received filter settings, the device retrieves and displays appropriate web content. For example, it uses the Python requests library or JavaScript fetch API to retrieve information from related websites and news feeds. By viewing the content retrieved based on the filters, users can enjoy a different perspective on their internet experience.

[0317] Specific examples

[0318] 1. User Input

[0319] The user enters "30-year-old IT engineer," and the emotion engine recognizes "excitement" from the user's facial expression and voice. When the submit button on the form is clicked, the data is sent to the server.

[0320] 2. Data Analysis

[0321] The server analyzes the data received via HTTP requests and uses the Natural Language API and OpenFace to extract keywords such as "IT," "tech news," "programming," and "latest gadgets." Based on the emotional data, it generates a filter appropriate for the user's state of excitement.

[0322] 3. Filter Generation

[0323] The server generates filters based on the extracted keywords and emotion data, and the filters include content such as "technology news" and "latest gadget reviews." After the filters are generated, the server sends the filter settings to the device.

[0324] 4. Applying filters and retrieving content

[0325] The device applies the received filter settings and retrieves content from relevant websites and APIs. Specifically, it retrieves RSS feeds using Python requests and retrieves data from news APIs using JavaScript's fetch API. The retrieved content is then displayed in the user's browser, allowing users to enjoy the latest tech news and gadget reviews.

[0326] Prompt Sentence Examples

[0327] Here are some example prompts to input to a generative AI model:

[0328] Generate filter settings based on data that a user types in "30-year-old IT engineer" and is recognized as "excited" by the sentiment engine. Set rules to display appropriate web content, such as the latest tech news or gadget reviews for IT professionals.

[0329] In this way, the system allows users, servers, and terminals to cooperate to provide a customized Internet experience based on the user's emotions.

[0330] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0331] Step 1: User Input and Emotion Recognition

[0332] The user uses the interface to input the image of the person they want to simulate (for example, a "30-year-old IT engineer"), and the emotion engine simultaneously captures the user's facial expressions and voice in real time, recognizing emotions such as "joy," "excitement," and "surprise."

[0333] Input: User-entered character image text, facial expressions and voice that indicate the user's emotions

[0334] Output: Pairs of character image text and emotion data

[0335] Specific behavior: The formatted form data and captured emotion data are sent to the server in JSON format.

[0336] Step 2: Analyze the data

[0337] The server receives the character image data and emotion data sent by the user. It uses natural language analysis tools (such as spaCy or Google Cloud Natural Language API) to extract relevant keywords from the input text. It also weights the keywords using the analysis results of the emotion engine.

[0338] Input: Pairs of character image text and emotion data

[0339] Output: Extracted keywords and a weighted keyword list based on sentiment

[0340] How it works: A text analysis algorithm is run to extract relevant keywords such as "tech news," "programming," and "latest gadgets." Keywords are weighted according to excitement level based on emotion data.

[0341] Step 3: Generate the filter

[0342] The server generates filter settings based on the extracted keywords and emotion recognition results.

[0343] Input: Weighted keyword list

[0344] Output: Filter settings (related content rules and parameters)

[0345] Specific behavior: Based on the keywords and sentiment data, a specific category (e.g., "Latest Tech News" or "Innovative Gadget Reviews") is selected, and filter rules related to this category are generated. The generated filter settings are formatted as an HTTP response to be sent to the device.

[0346] Step 4: Submit filter settings

[0347] The server sends the generated filter settings to the terminal.

[0348] Input: Filter settings

[0349] Output: Filter settings sent to the terminal

[0350] Specific operation: The generated filter settings are sent as an HTTP response, and this data is received on the terminal side.

[0351] Step 5: Applying filters and retrieving content

[0352] The terminal retrieves relevant web content based on the filter settings received from the server and displays it to the user.

[0353] Input: Filter settings

[0354] Output: Retrieved web content

[0355] Specific operation: Uses Python's requests library or JavaScript's fetch API to retrieve content that matches the filter settings from RSS feeds and news APIs. Renders the retrieved data in the browser so that the user can view it.

[0356] In this way, each step works together to provide a customized internet experience based on the user's input and emotions.

[0357] (Application example 2)

[0358] 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."

[0359] Existing virtual store systems do not take user emotions into consideration when proposing products, making it difficult to provide personalized product suggestions that meet diverse user needs. Another problem is the lack of interfaces and systems that allow users to enjoy shopping experiences from different perspectives.

[0360] The identification process by the identification 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 an emotion engine that recognizes the user's emotions, means for analyzing input from the user and extracting related keywords, and means for generating filter settings based on the extracted keywords and emotion recognition results. This makes it possible to propose products and services optimized for the user based on the user's emotions and the character they wish to simulate.

[0361] "User" refers to a person who uses this system to have a simulated experience.

[0362] The "interface means" refers to a means for the user to input the image of the person he or she wishes to simulate, and also refers to an interface means for exchanging information between the user and the system.

[0363] "Server" refers to the main computer system that receives, analyzes, and processes input data and emotion data from users.

[0364] An "emotion engine" refers to a system for detecting a user's emotions using means such as facial recognition, voice recognition, and text analysis.

[0365] "Means for extracting keywords" refers to means for performing natural language analysis on the data input by the user and extracting related keywords.

[0366] The "means for generating filter settings" refers to a means for setting content display rules based on the extracted keywords and emotion recognition results.

[0367] "Terminal" refers to a device operated by a user for displaying web content using filter settings received from a server.

[0368] The "content selection means" refers to a means for selecting content containing the latest information based on the extracted keywords and emotion recognition results.

[0369] "Natural language analysis means" refers to means for analyzing user input data and extracting keywords related to specific themes or interests.

[0370] A system for implementing the present invention provides personalized products and services based on emotions when a user is shopping in a virtual store.

[0371] The system mainly consists of the following components:

[0372] 1. Interface Method

[0373] It is a means for users to input the image of the person they want to simulate, and is installed as a text input field on the smartphone application screen.

[0374] 2. Emotion Engine

[0375] This is an engine for recognizing user emotions. This engine uses machine learning models such as TensorFlow to analyze emotions through facial recognition, voice recognition, and text analysis.

[0376] 3. Server

[0377] This is the main computer system that receives and analyzes the input data from the user (the person they want to simulate) and the emotion data obtained by the emotion engine. The server uses natural language processing (NLP) techniques, for example, the NLTK library, to extract relevant keywords.

[0378] 4. Filter Generation Method

[0379] This is a means for generating product and service suggestion filters based on the server-extracted keywords and emotion recognition results. The generated filter settings include product categories and display priorities.

[0380] 5. Terminal

[0381] This is a device operated by the user, such as a smartphone or tablet. The device retrieves and displays appropriate product information based on the filter settings received from the server.

[0382] The specific operation is as follows.

[0383] 1. The user enters "Female in her 20s" on the application screen. At this time, the emotion engine recognizes that the user is feeling "curiosity" based on their facial expression.

[0384] 2. The server receives the input data and emotion data, extracts keywords such as "fashion," "trends," and "cosmetics" through natural language analysis, and generates filter settings based on the emotion.

[0385] 3. The generated filter settings are sent to the device, which then uses them to display the latest trending products, related fashion items, cosmetic products, and more to the user.

[0386] This approach allows users to find the most relevant product information based on their emotions and interests, improving the user experience in virtual stores and providing a more engaging shopping experience.

[0387] Prompt Sentence Examples

[0388] "We want to build a product recommendation system that allows users to input the character they want to simulate and recognize emotions. The system will then recommend products based on the user's emotions. The following prompts will allow us to get suggested product information:

[0389] For example, if you are a woman in your 20s and your emotion is curiosity, search for product information using the keywords "fashion," "trends," and "cosmetics."

[0390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0391] Step 1:

[0392] The user inputs the image of the person they want to simulate (e.g., "woman in her 20s") using the interface. At this time, the emotion engine analyzes the user's facial expressions and voice and recognizes the user's emotion (e.g., "curiosity").

[0393] Input: User's profile input data, user's face image or voice data

[0394] Output: User emotion recognition results, input person image data

[0395] Specific operation: Facial images are captured using a smartphone camera, and emotions are determined using a generative AI model such as TensorFlow.

[0396] Step 2:

[0397] The server receives input data from the user and emotion recognition results, and extracts related keywords using natural language analysis means.

[0398] Input: User's portrait input data and emotion recognition results received by the server

[0399] Output: Extracted keyword list

[0400] Specific operation: Natural language processing is performed using the NLTK library to extract keywords such as "fashion," "trends," and "cosmetics."

[0401] Step 3:

[0402] The server generates filter settings based on the extracted keywords and emotion recognition results, including product categories, display priorities, and latest information.

[0403] Input: Extracted keyword list, user emotion recognition results

[0404] Output: Filter setting data

[0405] What it does: Create filtering rules to set product categories and display priorities based on keywords and sentiment.

[0406] Step 4:

[0407] The server transmits the generated filter settings to the terminal, and the terminal receives them.

[0408] Input: Filter setting data

[0409] Output: Filter settings received by the device

[0410] Specific operation: Network communication is performed to send filter settings from the server to the smartphone.

[0411] Step 5:

[0412] The device retrieves relevant web content based on the received filter settings, and the retrieved content is optimized for the user according to the filter settings.

[0413] Input: Received filter settings

[0414] Output: Selected web content

[0415] What it does: Makes API calls to search and retrieve product information based on filter settings.

[0416] Step 6:

[0417] The terminal displays the acquired web content to the user, allowing the user to view personalized product information based on their emotions and interests.

[0418] Input: Selected web content

[0419] Output: Personalized product information displayed to the user

[0420] Specific operation: Update the UI to display product information on the smartphone screen.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] [Second embodiment]

[0425] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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."

[0437] The present invention provides a system that allows users to enjoy the Internet from different perspectives. This system is composed of the following main components:

[0438] System configuration

[0439] 1. Interface Method

[0440] This is an interface means for users to input the character they want to simulate. This interface includes a form installed on the browser, and users can input such things as "a 30-year-old IT engineer" or "a housewife raising children."

[0441] 2. Server

[0442] The server receives the person image data sent from the user.

[0443] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0444] 3. Filter Generation

[0445] The server generates filter configurations based on the extracted keywords, which contain rules for controlling content based on specific themes or interests, such as displaying only content related to "tech news" or "programming."

[0446] 4. Terminal

[0447] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0448] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[0449] Program processing

[0450] 1. User Input

[0451] The user inputs the image of the person they want to simulate using the interface. For example, they input "a 30-year-old IT engineer."

[0452] The user clicks the "Submit" button to send the input data to the server.

[0453] 2. Data Analysis

[0454] The server receives the input data and begins parsing it.

[0455] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0456] 3. Filter generation and transmission

[0457] Based on the extracted keywords, the server generates a filter configuration, which contains rules that control web content based on specific themes or interests.

[0458] The generated filter settings are sent to the device.

[0459] 4. Applying filters and retrieving content

[0460] The device applies the received filter settings and retrieves the controlled web content.

[0461] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[0462] Specific examples

[0463] 1. The user enters "30-year-old IT engineer."

[0464] 2. The server receives this input and analyzes it, extracting keywords such as "IT," "technology news," and "programming."

[0465] 3. The server generates filter settings based on these keywords, for example, creating a filter that includes "tech blogs," "latest IT news," "programming forums," etc.

[0466] 4. The device receives and applies the filter settings.

[0467] 5. The device retrieves the appropriate web content and displays it in the browser, allowing the user to enjoy the latest relevant information from the perspective of a 30-year-old IT engineer.

[0468] As described above, this system provides a new perspective by switching the user's perspective to other attributes, providing an internet experience that is free from the filter bubble of everyday life.

[0469] The processing flow will be explained below.

[0470] Step 1:

[0471] The user launches a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button, sending the input data to the server.

[0472] Step 2:

[0473] The server receives the input data. The received profile data is analyzed using natural language processing (NLP) technology to extract related keywords. For example, if "IT engineer" is entered, keywords such as "technology news," "programming," and "latest gadgets" are extracted.

[0474] Step 3:

[0475] The server generates a filter configuration based on the extracted keywords. This filter configuration contains rules and parameters for controlling related web content, such as displaying content related to the categories "tech news" and "programming."

[0476] Step 4:

[0477] The server sends the generated filter settings to the terminal, and the terminal receives the filter settings sent from the server.

[0478] Step 5:

[0479] The terminal acquires web content based on the filter settings received, and selects appropriate information using a content acquisition means based on the filter.

[0480] Step 6:

[0481] The device displays the acquired web content in the browser. The displayed content is controlled by a filter, allowing the user to enjoy information from the perspective of other attributes.

[0482] Step 7:

[0483] Users can browse content provided from different perspectives on their browsers. For example, they can enjoy technical articles or the latest programming information. This allows users to experience the Internet from a new perspective.

[0484] The above is the specific flow of processing from inputting the image of the person the user wants to simulate and generating a filter based on that image to displaying content.

[0485] Example 1

[0486] 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."

[0487] In conventional Internet usage, it is difficult for users to obtain information based on specific perspectives or interests, and they often rely on biased information from the same source. Therefore, there is a need for methods to provide Internet experiences with new perspectives.

[0488] 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.

[0489] In this invention, the server includes means for receiving the image of a person the user wishes to simulate and extracting related keywords using natural language analysis means, means for generating filter settings based on the extracted keywords and transmitting them to the terminal, and means for the terminal to apply the received filter settings to retrieve and display web content, thereby enabling users to enjoy the Internet from different perspectives.

[0490] A "user" is an entity that uses the system to input a profile and obtain Internet content.

[0491] "Interface means" is a component that includes tools and forms for the user to input the image of the person they wish to simulate.

[0492] A "server" is a computer system that receives data entered by a user and performs analysis and filter generation.

[0493] "Natural language analysis means" refers to analysis techniques and software used to extract keywords related to the person profile entered by the user.

[0494] "Keywords" are important words or phrases extracted based on the persona entered by the user.

[0495] "Filter settings" are rules or settings generated based on extracted keywords to control web content based on specific themes or interests.

[0496] A "terminal" is a device that receives filter settings and retrieves and displays web content based on those settings.

[0497] "Web content" is information or data obtained over the Internet and displayed to a user by a terminal.

[0498] The present invention relates to a system that allows users to enjoy the Internet from different perspectives. This system displays related web content based on the image of a person the user wants to simulate. Specific embodiments of this system are described below.

[0499] System configuration

[0500] The system consists of the following main elements:

[0501] 1. Interface Method

[0502] It is a form that allows users to input the type of person they want to simulate. Specifically, it is a form that is set up on a web browser. This form includes fields where users can input specific person descriptions, such as "a 30-year-old IT engineer" or "a housewife raising children."

[0503] 2. Server

[0504] The server receives input data sent by the user. Specifically, a web framework such as Python's Flask can be used.

[0505] The server analyzes the received data using natural language processing libraries such as NLTK and spaCy to extract relevant keywords.

[0506] The server generates filter settings based on the extracted keywords and sends them to the client terminal.

[0507] 3. Terminal

[0508] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0509] The device applies the received filter settings and retrieves web content based on them. To retrieve content based on the filters, web scraping technologies (such as Beautiful Soup or Scrapy) can be used.

[0510] The terminal displays the acquired content on the browser and provides it to the user.

[0511] Example of operation

[0512] 1. The user enters "30-year-old IT engineer" into the form in a web browser and clicks the "Submit" button.

[0513] 2. The server receives the input data and performs natural language analysis to extract related keywords such as "tech news," "programming," and "latest gadgets."

[0514] 3. The server generates interest-related filter settings based on these keywords, such as "tech blogs," "latest IT news," or "programming forums."

[0515] 4. The device receives the generated filter settings from the server, applies them, and retrieves the appropriate web content.

[0516] 5. The content acquired by the device is displayed in a web browser, allowing the user to enjoy relevant information from the perspective of a "30-year-old IT engineer."

[0517] Prompt Sentence Examples

[0518] When a user enters "30-year-old IT engineer," the server receives and analyzes the input, extracts related keywords, and generates a filter that controls web content based on the keywords and sends it to the device. The device then applies the filter and displays appropriate content. For example, keywords such as "technology news," "programming," and "latest gadgets" are extracted, and web content with corresponding filter settings is displayed.

[0519] This invention allows users to enjoy a new internet experience by changing their perspective, thereby reducing bias in daily information acquisition and enabling information gathering from a new perspective.

[0520] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0521] Step 1:

[0522] A user enters "30-year-old IT engineer" into a form on a web browser and clicks the "Submit" button.

[0523] Input: User enters a text description of the person (e.g., "30-year-old IT engineer")

[0524] Output: A request with input data sent to the server

[0525] What happens: When a user enters text into a form field and clicks a button, the data in the form is sent to the server as an HTTP request.

[0526] Step 2:

[0527] The server receives the input data sent by the user and begins natural language analysis.

[0528] Input: User-entered data included in the HTTP request (e.g., "30-year-old IT engineer")

[0529] Output: Text data for analysis

[0530] What happens: The server receives the request using the Python Flask framework and passes the text data to a natural language analysis library (e.g., NLTK or spaCy).

[0531] Step 3:

[0532] The server extracts related keywords using natural language analysis.

[0533] Input: Text data for analysis (e.g., "30-year-old IT engineer")

[0534] Output: Extracted keywords (e.g. "tech news", "programming", "latest gadgets")

[0535] What it does: The server uses natural language analysis libraries to extract key keywords from the text data, including tagging parts of speech and word segmentation, to identify keywords related to the topic.

[0536] Step 4:

[0537] The server generates a filter configuration based on the extracted keywords.

[0538] Input: Extracted keywords (e.g., "tech news," "programming," "latest gadgets")

[0539] Output: Generated filter configuration (e.g. filter rules in JSON format).

[0540] What it does: The server uses the extracted keywords to generate filter rules in JSON format to control web content related to specific topics or interests.

[0541] Step 5:

[0542] The server sends the generated filter settings to the device.

[0543] Input: Generated filter configuration (e.g. filter rules in JSON format)

[0544] Output: HTTP response containing the filter configuration

[0545] Specific operation: The server returns the generated JSON format filter settings to the device as an HTTP response.

[0546] Step 6:

[0547] Apply the filter settings received by the device.

[0548] Input: HTTP response containing filter settings (e.g., filter rules in JSON format)

[0549] Output: The result of applying the filter settings

[0550] Specific operation: The device analyzes the filter settings from the HTTP response and stores the filters required to retrieve web content in memory.

[0551] Step 7:

[0552] The device retrieves web content based on the filter settings.

[0553] Input: The result of applying filter settings (e.g. saved filter settings)

[0554] Output: Appropriate web content (e.g. web page based on filters)

[0555] Specific operation: The device will search the target website according to the filter settings using web scraping technology (e.g., Beautiful Soup, Scrapy) to obtain relevant content.

[0556] Step 8:

[0557] The content acquired by the terminal is displayed in the browser.

[0558] Input: Appropriate web content (e.g., a retrieved web page)

[0559] Output: The displayed web page

[0560] Specific behavior: The device renders web content in the browser and presents it visually to the user.

[0561] (Application example 1)

[0562] 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."

[0563] Modern internet users face the challenge of having few opportunities to encounter information from diverse perspectives, due to the way they obtain information, which tends to be limited to their own interests. Furthermore, there are no appropriate means for users to enjoy information from the perspectives of different people, and users tend to fall into a fixed perspective. This can lead to problems such as filter bubbles and biased perceptions.

[0564] 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.

[0565] In this invention, the server includes an interface means for the user to input the character image they wish to simulate, a means for analyzing the user's input and extracting related keywords, a means for generating filter settings based on the extracted keywords, a means for acquiring and displaying web content based on the filter settings received by the terminal, and a means for operating a smartphone application including content acquisition means and display means based on the user's input data. This allows the user to easily acquire information from different perspectives and characters, avoiding filter bubbles and enabling wider and more diverse information acquisition.

[0566] The "interface means" is a means for the user to input the image of the person they wish to simulate.

[0567] A "server" is a device that receives input from a user, analyzes it, and extracts related keywords.

[0568] The "keyword extraction means" is a means for the server to analyze the data received from the user and extract related keywords.

[0569] The "filter setting generation means" is a means for generating filter settings based on keywords extracted by the server.

[0570] A "terminal" is a device that retrieves and displays web content based on filter settings received from a server.

[0571] The "web content acquisition means" is a means for searching for and acquiring appropriate web content based on the filter settings received by the terminal.

[0572] The "display means" is a means for displaying the acquired web content to the user.

[0573] A "smartphone application" is software that allows a user to set up a simulated experience and operate content acquisition means and display means.

[0574] The "natural language analysis means" is an analysis means that allows the server to extract words related to specific themes or interests from the image of the person the user wishes to simulate.

[0575] The following system configuration is conceivable as an embodiment for carrying out the present invention: This system allows users to enjoy content from different perspectives, and is realized by a smartphone application.

[0576] System Overview

[0577] 1. User Interface

[0578] The interface means of the application includes a form for the user to input the profile of the person he / she wants to simulate. For example, the user inputs the profile of a "30-year-old IT engineer."

[0579] 2. Server

[0580] The server analyzes the profile data received from the user and extracts related keywords. This analysis is performed using natural language analysis. As a result of the analysis, for example, in the case of "IT engineer," keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0581] The server generates filter configurations based on the extracted keywords, which create rules to control content based on specific themes or interests.

[0582] 3. Smartphone Applications

[0583] The application on the smartphone receives the filter settings sent from the server, and searches for and retrieves web content based on the filter settings.

[0584] The acquired content is provided to the user through the display means of the application.

[0585] Hardware and software used

[0586] Hardware: Smartphone

[0587] Software: Flask (web framework), HTML template engine

[0588] Data Flow and Processing

[0589] 1. User Input

[0590] The user uses the smartphone application interface to input the "character they would like to simulate."

[0591] When the user presses the "Submit" button, the input data is sent to the server.

[0592] 2. Analysis on the server

[0593] The server receives the input data and analyzes it using natural language analysis. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0594] 3. Generate filter settings

[0595] The server generates a filter configuration based on the extracted keywords, which contains rules that control information related to a particular subject or interest.

[0596] The generated filter settings are sent to the smartphone application.

[0597] 4. Retrieving and Displaying Content

[0598] The smartphone application searches and retrieves web content based on the received filter settings.

[0599] The acquired content is provided to the user through the display means of the application.

[0600] Specific examples

[0601] Implementation example

[0602] Suppose a user opens an application on their smartphone and types in "30-year-old IT engineer." The server receives this and uses natural language analysis to extract keywords such as "technology news," "programming," and "latest gadgets." It then generates filter settings and retrieves and displays web content containing appropriate technology articles and links to sites.

[0603] Example prompts for generative AI models

[0604] "Create an application that extracts relevant keywords based on the user's profile and displays relevant content based on those keywords. For example, if a user enters "30-year-old IT engineer," generate a system program that extracts keywords such as "tech news," "programming," and "latest gadgets" and displays content related to those keywords."

[0605] Using this prompt, the generative AI model can generate the appropriate program code.

[0606] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0607] Step 1: The user launches the smartphone application and uses the interface to input the "image of the person they wish to simulate."

[0608] Input: The user inputs personal data such as "a 30-year-old IT engineer."

[0609] What happens: A user fills in the application's input form with the appropriate information and clicks the "Submit" button.

[0610] Step 2: The terminal sends the input data from the user to the server.

[0611] Input: Persona data entered by the user.

[0612] Operation: The terminal sends the input data to the server as an HTTP request.

[0613] Step 3: The server analyzes the received input data and extracts relevant keywords.

[0614] Input: Person profile data received by the server.

[0615] Data processing: The server analyzes the data using natural language analysis means and extracts relevant keywords.

[0616] Output: A list of extracted keywords (e.g. "tech news", "programming", "latest gadgets").

[0617] How it works: The server uses a data analysis library (e.g., nltk or spaCy) to parse the input data.

[0618] Step 4: The server generates filter settings based on the extracted keywords.

[0619] Input: Extracted keyword list.

[0620] Data processing: The server identifies content related to the extracted keywords and generates filter settings.

[0621] Output: The generated filter configuration (e.g. "Tech Blogs", "Latest IT News", "Programming Forums").

[0622] How it works: The server uses filtering logic to define the content types to retrieve and generates a filter configuration.

[0623] Step 5: The server sends the filter settings to the device.

[0624] Input: The generated filter settings.

[0625] Output: The filter settings sent to the terminal.

[0626] Operation: The server sends the generated filter settings to the device as an HTTP response.

[0627] Step 6: The device retrieves web content based on the filter settings received.

[0628] Input: The filter settings received by the device.

[0629] Data processing: The device searches for and retrieves relevant web content based on filter settings.

[0630] Output: The retrieved web content list.

[0631] What it does: The device retrieves relevant content using a web scraping library (e.g. BeautifulSoup) or API calls.

[0632] Step 7: The terminal displays the retrieved web content to the user.

[0633] Input: The retrieved web content list.

[0634] Output: The web content displayed to the user.

[0635] How it works: The device uses an HTML template engine to format and visually display web content.

[0636] The above processing steps allow users to easily obtain information from different perspectives and personalities, avoiding filter bubbles and enabling them to obtain a wider range of diverse information.

[0637] 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.

[0638] The present invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system consists of the following main components:

[0639] System configuration

[0640] 1. Interface Method

[0641] It is an interface means for users to input the character they want to simulate. They can enter "30-year-old IT engineer" or "housewife raising children" into a form on the browser. It also has an emotion engine that recognizes the emotions of users when they enter information.

[0642] 2. Emotion Engine

[0643] The emotion engine recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. This recognition result is used to adjust filter settings.

[0644] 3. Server

[0645] The server receives the person image and emotion data sent by the user.

[0646] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0647] 4. Filter Generation

[0648] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "joy," a configuration including "fun news" and "interesting blogs" will be generated.

[0649] 5. Terminal

[0650] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0651] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[0652] Program processing

[0653] 1. User Input and Emotion Recognition

[0654] The user uses the interface to input the image of the person they want to simulate. For example, they can input "30-year-old IT engineer." At the same time, the emotion engine recognizes the user's facial expressions and voice, and analyzes whether the user is expressing emotions such as "joy," "excitement," or "surprise."

[0655] 2. Data Analysis

[0656] The server receives the input data and emotion data and begins analysis.

[0657] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0658] Based on the analysis results of the emotion engine, keywords are weighted to match the user's emotions.

[0659] 3. Filter generation and transmission

[0660] Based on the extracted keywords and emotion recognition results, the server generates filter configurations, which contain rules for controlling web content based on specific themes or interests, such as displaying content related to the categories "tech news" or "programming."

[0661] The generated filter settings are sent to the device.

[0662] 4. Applying filters and retrieving content

[0663] The device applies the received filter settings and retrieves the controlled web content.

[0664] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[0665] Specific examples

[0666] 1. The user types in "30-year-old IT engineer" and the emotion engine recognizes this as "excited."

[0667] 2. The server receives and analyzes this input and sentiment data. For example, keywords such as "IT," "technology news," and "programming" are extracted, and filter settings related to "latest technology news" and "innovative gadget reviews" are generated based on the user's sentiment.

[0668] 3. The server sends the filter settings to the device.

[0669] 4. The device applies the filter settings to retrieve and display appropriate web content, such as "The latest innovative tech news" or "Gadget reviews for IT professionals."

[0670] 5. Users can enjoy relevant updates in an exciting state.

[0671] As a result, this system not only shifts the user's perspective to other attributes, but also provides an internet experience that takes into account the user's emotions, providing a new perspective and an internet experience that is free from the filter bubble of everyday life.

[0672] The processing flow will be explained below.

[0673] Step 1:

[0674] The user opens a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button. At the same time, the emotion engine analyzes the emotions (e.g., facial expressions and voice) that the user is expressing when they input their input.

[0675] Step 2:

[0676] The server receives the personality data and emotion data sent by the user, analyzes the received personality data using natural language processing (NLP) technology, and extracts related keywords such as "technology news," "programming," and "latest gadgets."

[0677] Step 3:

[0678] The server analyzes the emotional data received from the emotion engine. For example, it can obtain data that the user is "excited." Based on this emotional data, it adjusts the priority of the extracted keywords. For example, keywords such as "latest technology news" and "innovative gadget reviews" are highly ranked.

[0679] Step 4:

[0680] The server generates filter configurations based on the analysis, which contain rules for controlling content related to specific themes or interests based on the extracted keywords and sentiment data, such as displaying content related to the categories "tech news" or "programming."

[0681] Step 5:

[0682] The server sends the generated filter settings to the device, which receives them.

[0683] Step 6:

[0684] Based on the filter settings received, the device sends requests to retrieve controlled web content. For example, the device retrieves relevant updates from specific news sites or tech blogs.

[0685] Step 7:

[0686] The device retrieves web content and displays it in the browser. The content displayed is controlled by filters, providing information based on the user's profile and sentiment. For example, it can display "the latest innovative tech news" or "gadget reviews for IT professionals."

[0687] Step 8:

[0688] Users browse the content displayed on their browsers, which allows them to enjoy relevant and up-to-date information in an exciting state, giving them a new Internet experience based on different perspectives and emotions.

[0689] The above is the specific flow of processing from inputting the image of the person the user wants to simulate, to generating a filter that takes into account emotional data based on that image, to displaying the content.

[0690] Example 2

[0691] 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."

[0692] In the past, the Internet experience was largely one in which users selected content based on their own interests. However, this limited users' opportunities to gain new perspectives and experiences, limiting their access to new content. Furthermore, because information was provided without considering the user's emotions or psychological state, the Internet experience was one-sided and difficult to personalize.

[0693] 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.

[0694] In this invention, the server includes an interface means for allowing the user to input the image of the person they wish to simulate and simultaneously recognizing the user's emotions, a means for the server to analyze the input and emotional data from the user and extract related keywords, and a means for generating filter settings based on the keywords and emotional data extracted by the server. This allows the user to enjoy the Internet from a new perspective and makes it possible to provide personalized information that takes the user's emotions into consideration.

[0695] "User" refers to an entity that inputs information to use the system and receives the resulting content.

[0696] The "image of the person the user wishes to simulate" refers to data input by the user indicating the attributes of a virtual person related to the information and perspective the user wishes to experience.

[0697] "Interface means" refers to a form or user interface on a browser that allows a user to input information.

[0698] "Emotional data" refers to emotional information extracted from a user's facial expressions, voice, and text.

[0699] An "emotion engine" refers to a system that recognizes and analyzes emotions from a user's facial expressions, voice, text, etc.

[0700] "Server" refers to a computer system that receives user-submitted character and emotion data and generates analysis and filter settings.

[0701] "Natural language analysis means" refers to a technical means for analyzing text data entered by a user and extracting related keywords and themes.

[0702] "Keywords" refer to relevant information extracted from the information and emotion data entered by the user and that serves as the basis for filter settings.

[0703] "Filter settings" refers to the rules and parameters that control the relevant web content that is generated based on extracted keywords and sentiment data.

[0704] "Terminal" refers to a device that retrieves web content based on filter settings received from a server and displays it to a user.

[0705] "Web content" refers to information such as news, articles, blogs, and videos obtained from the Internet.

[0706] This invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system operates in cooperation with the user, server, and terminal. Specifically, it is configured as follows:

[0707] System configuration

[0708] 1. Interface Method

[0709] It is a means for users to input the character they wish to simulate. It is implemented as a form on the browser. Users can input such things as "30-year-old IT engineer" or "housewife raising children." It also incorporates an emotion engine that recognizes the emotions expressed when users input data. The emotion engine uses OpenFace (facial expression recognition) and Google Cloud Speech-to-Text API (voice recognition).

[0710] 2. Emotion Engine

[0711] It recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. The results of this recognition are used to adjust filter settings.

[0712] 3. Server

[0713] The server receives the persona data and emotion data sent by the user. The received data is analyzed using natural language analysis tools (e.g., spaCy or Google Cloud Natural Language API) to extract related keywords. For example, if "IT engineer" is entered, keywords such as "tech news," "programming," and "latest gadgets" are extracted. Based on the analysis results of the emotion engine, the extracted keywords are weighted to generate filter settings that match the user's emotions.

[0714] 4. Filter Generation

[0715] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "excitement," a configuration including "latest technology news" and "innovative gadget reviews" will be generated. The generated filter configuration is sent to the device.

[0716] 5. Terminal

[0717] The device receives the filter settings sent from the server. Based on the received filter settings, the device retrieves and displays appropriate web content. For example, it uses the Python requests library or JavaScript fetch API to retrieve information from related websites and news feeds. By viewing the content retrieved based on the filters, users can enjoy a different perspective on their internet experience.

[0718] Specific examples

[0719] 1. User Input

[0720] The user enters "30-year-old IT engineer," and the emotion engine recognizes "excitement" from the user's facial expression and voice. When the submit button on the form is clicked, the data is sent to the server.

[0721] 2. Data Analysis

[0722] The server analyzes the data received via HTTP requests and uses the Natural Language API and OpenFace to extract keywords such as "IT," "tech news," "programming," and "latest gadgets." Based on the emotional data, it generates a filter appropriate for the user's state of excitement.

[0723] 3. Filter Generation

[0724] The server generates filters based on the extracted keywords and emotion data, and the filters include content such as "technology news" and "latest gadget reviews." After the filters are generated, the server sends the filter settings to the device.

[0725] 4. Applying filters and retrieving content

[0726] The device applies the received filter settings and retrieves content from relevant websites and APIs. Specifically, it retrieves RSS feeds using Python requests and retrieves data from news APIs using JavaScript's fetch API. The retrieved content is then displayed in the user's browser, allowing users to enjoy the latest tech news and gadget reviews.

[0727] Prompt Sentence Examples

[0728] Here are some example prompts to input to a generative AI model:

[0729] Generate filter settings based on data that a user types in "30-year-old IT engineer" and is recognized as "excited" by the sentiment engine. Set rules to display appropriate web content, such as the latest tech news or gadget reviews for IT professionals.

[0730] In this way, the system allows users, servers, and terminals to cooperate to provide a customized Internet experience based on the user's emotions.

[0731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0732] Step 1: User Input and Emotion Recognition

[0733] The user uses the interface to input the image of the person they want to simulate (for example, a "30-year-old IT engineer"), and the emotion engine simultaneously captures the user's facial expressions and voice in real time, recognizing emotions such as "joy," "excitement," and "surprise."

[0734] Input: User-entered character image text, facial expressions and voice that indicate the user's emotions

[0735] Output: Pairs of character image text and emotion data

[0736] Specific behavior: The formatted form data and captured emotion data are sent to the server in JSON format.

[0737] Step 2: Analyze the data

[0738] The server receives the character image data and emotion data sent by the user. It uses natural language analysis tools (such as spaCy or Google Cloud Natural Language API) to extract relevant keywords from the input text. It also weights the keywords using the analysis results of the emotion engine.

[0739] Input: Pairs of character image text and emotion data

[0740] Output: Extracted keywords and a weighted keyword list based on sentiment

[0741] How it works: A text analysis algorithm is run to extract relevant keywords such as "tech news," "programming," and "latest gadgets." Keywords are weighted according to excitement level based on emotion data.

[0742] Step 3: Generate the filter

[0743] The server generates filter settings based on the extracted keywords and emotion recognition results.

[0744] Input: Weighted keyword list

[0745] Output: Filter settings (related content rules and parameters)

[0746] Specific behavior: Based on the keywords and sentiment data, a specific category (e.g., "Latest Tech News" or "Innovative Gadget Reviews") is selected, and filter rules related to this category are generated. The generated filter settings are formatted as an HTTP response to be sent to the device.

[0747] Step 4: Submit filter settings

[0748] The server sends the generated filter settings to the terminal.

[0749] Input: Filter settings

[0750] Output: Filter settings sent to the terminal

[0751] Specific operation: The generated filter settings are sent as an HTTP response, and this data is received on the terminal side.

[0752] Step 5: Applying filters and retrieving content

[0753] The terminal retrieves relevant web content based on the filter settings received from the server and displays it to the user.

[0754] Input: Filter settings

[0755] Output: Retrieved web content

[0756] Specific operation: Uses Python's requests library or JavaScript's fetch API to retrieve content that matches the filter settings from RSS feeds and news APIs. Renders the retrieved data in the browser so that the user can view it.

[0757] In this way, each step works together to provide a customized internet experience based on the user's input and emotions.

[0758] (Application example 2)

[0759] 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."

[0760] Existing virtual store systems do not take user emotions into consideration when proposing products, making it difficult to provide personalized product suggestions that meet diverse user needs. Another problem is the lack of interfaces and systems that allow users to enjoy shopping experiences from different perspectives.

[0761] The identification process by the identification 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 an emotion engine that recognizes the user's emotions, means for analyzing input from the user and extracting related keywords, and means for generating filter settings based on the extracted keywords and emotion recognition results. This makes it possible to propose products and services optimized for the user based on the user's emotions and the character they wish to simulate.

[0762] "User" refers to a person who uses this system to have a simulated experience.

[0763] The "interface means" refers to a means for the user to input the image of the person he or she wishes to simulate, and also refers to an interface means for exchanging information between the user and the system.

[0764] "Server" refers to the main computer system that receives, analyzes, and processes input data and emotion data from users.

[0765] An "emotion engine" refers to a system for detecting a user's emotions using means such as facial recognition, voice recognition, and text analysis.

[0766] "Means for extracting keywords" refers to means for performing natural language analysis on the data input by the user and extracting related keywords.

[0767] The "means for generating filter settings" refers to a means for setting content display rules based on the extracted keywords and emotion recognition results.

[0768] "Terminal" refers to a device operated by a user for displaying web content using filter settings received from a server.

[0769] The "content selection means" refers to a means for selecting content containing the latest information based on the extracted keywords and emotion recognition results.

[0770] "Natural language analysis means" refers to means for analyzing user input data and extracting keywords related to specific themes or interests.

[0771] A system for implementing the present invention provides personalized products and services based on emotions when a user is shopping in a virtual store.

[0772] The system mainly consists of the following components:

[0773] 1. Interface Method

[0774] It is a means for users to input the image of the person they want to simulate, and is installed as a text input field on the smartphone application screen.

[0775] 2. Emotion Engine

[0776] This is an engine for recognizing user emotions. This engine uses machine learning models such as TensorFlow to analyze emotions through facial recognition, voice recognition, and text analysis.

[0777] 3. Server

[0778] This is the main computer system that receives and analyzes the input data from the user (the person they want to simulate) and the emotion data obtained by the emotion engine. The server uses natural language processing (NLP) techniques, for example, the NLTK library, to extract relevant keywords.

[0779] 4. Filter Generation Method

[0780] This is a means for generating product and service suggestion filters based on the server-extracted keywords and emotion recognition results. The generated filter settings include product categories and display priorities.

[0781] 5. Terminal

[0782] This is a device operated by the user, such as a smartphone or tablet. The device retrieves and displays appropriate product information based on the filter settings received from the server.

[0783] The specific operation is as follows.

[0784] 1. The user enters "Female in her 20s" on the application screen. At this time, the emotion engine recognizes that the user is feeling "curiosity" based on their facial expression.

[0785] 2. The server receives the input data and emotion data, extracts keywords such as "fashion," "trends," and "cosmetics" through natural language analysis, and generates filter settings based on the emotion.

[0786] 3. The generated filter settings are sent to the device, which then uses them to display the latest trending products, related fashion items, cosmetic products, and more to the user.

[0787] This approach allows users to find the most relevant product information based on their emotions and interests, improving the user experience in virtual stores and providing a more engaging shopping experience.

[0788] Prompt Sentence Examples

[0789] "We want to build a product recommendation system that allows users to input the character they want to simulate and recognize emotions. The system will then recommend products based on the user's emotions. The following prompts will allow us to get suggested product information:

[0790] For example, if you are a woman in your 20s and your emotion is curiosity, search for product information using the keywords "fashion," "trends," and "cosmetics."

[0791] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0792] Step 1:

[0793] The user inputs the image of the person they want to simulate (e.g., "woman in her 20s") using the interface. At this time, the emotion engine analyzes the user's facial expressions and voice and recognizes the user's emotion (e.g., "curiosity").

[0794] Input: User's profile input data, user's face image or voice data

[0795] Output: User emotion recognition results, input person image data

[0796] Specific operation: Facial images are captured using a smartphone camera, and emotions are determined using a generative AI model such as TensorFlow.

[0797] Step 2:

[0798] The server receives input data from the user and emotion recognition results, and extracts related keywords using natural language analysis means.

[0799] Input: User's portrait input data and emotion recognition results received by the server

[0800] Output: Extracted keyword list

[0801] Specific operation: Natural language processing is performed using the NLTK library to extract keywords such as "fashion," "trends," and "cosmetics."

[0802] Step 3:

[0803] The server generates filter settings based on the extracted keywords and emotion recognition results, including product categories, display priorities, and latest information.

[0804] Input: Extracted keyword list, user emotion recognition results

[0805] Output: Filter setting data

[0806] What it does: Create filtering rules to set product categories and display priorities based on keywords and sentiment.

[0807] Step 4:

[0808] The server transmits the generated filter settings to the terminal, and the terminal receives them.

[0809] Input: Filter setting data

[0810] Output: Filter settings received by the device

[0811] Specific operation: Network communication is performed to send filter settings from the server to the smartphone.

[0812] Step 5:

[0813] The device retrieves relevant web content based on the received filter settings, and the retrieved content is optimized for the user according to the filter settings.

[0814] Input: Received filter settings

[0815] Output: Selected web content

[0816] What it does: Makes API calls to search and retrieve product information based on filter settings.

[0817] Step 6:

[0818] The terminal displays the acquired web content to the user, allowing the user to view personalized product information based on their emotions and interests.

[0819] Input: Selected web content

[0820] Output: Personalized product information displayed to the user

[0821] Specific operation: Update the UI to display product information on the smartphone screen.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] [Third embodiment]

[0826] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0827] 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.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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).

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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."

[0838] The present invention provides a system that allows users to enjoy the Internet from different perspectives. This system is composed of the following main components:

[0839] System configuration

[0840] 1. Interface Method

[0841] This is an interface means for users to input the character they want to simulate. This interface includes a form installed on the browser, and users can input such things as "a 30-year-old IT engineer" or "a housewife raising children."

[0842] 2. Server

[0843] The server receives the person image data sent from the user.

[0844] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0845] 3. Filter Generation

[0846] The server generates filter configurations based on the extracted keywords, which contain rules for controlling content based on specific themes or interests, such as displaying only content related to "tech news" or "programming."

[0847] 4. Terminal

[0848] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0849] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[0850] Program processing

[0851] 1. User Input

[0852] The user inputs the image of the person they want to simulate using the interface. For example, they input "a 30-year-old IT engineer."

[0853] The user clicks the "Submit" button to send the input data to the server.

[0854] 2. Data Analysis

[0855] The server receives the input data and begins parsing it.

[0856] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[0857] 3. Filter generation and transmission

[0858] Based on the extracted keywords, the server generates a filter configuration, which contains rules that control web content based on specific themes or interests.

[0859] The generated filter settings are sent to the device.

[0860] 4. Applying filters and retrieving content

[0861] The device applies the received filter settings and retrieves the controlled web content.

[0862] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[0863] Specific examples

[0864] 1. The user enters "30-year-old IT engineer."

[0865] 2. The server receives this input and analyzes it, extracting keywords such as "IT," "technology news," and "programming."

[0866] 3. The server generates filter settings based on these keywords, for example, creating a filter that includes "tech blogs," "latest IT news," "programming forums," etc.

[0867] 4. The device receives and applies the filter settings.

[0868] 5. The device retrieves the appropriate web content and displays it in the browser, allowing the user to enjoy the latest relevant information from the perspective of a 30-year-old IT engineer.

[0869] As described above, this system provides a new perspective by switching the user's perspective to other attributes, providing an internet experience that is free from the filter bubble of everyday life.

[0870] The processing flow will be explained below.

[0871] Step 1:

[0872] The user launches a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button, sending the input data to the server.

[0873] Step 2:

[0874] The server receives the input data. The received profile data is analyzed using natural language processing (NLP) technology to extract related keywords. For example, if "IT engineer" is entered, keywords such as "technology news," "programming," and "latest gadgets" are extracted.

[0875] Step 3:

[0876] The server generates a filter configuration based on the extracted keywords. This filter configuration contains rules and parameters for controlling related web content, such as displaying content related to the categories "tech news" and "programming."

[0877] Step 4:

[0878] The server sends the generated filter settings to the terminal, and the terminal receives the filter settings sent from the server.

[0879] Step 5:

[0880] The terminal acquires web content based on the filter settings received, and selects appropriate information using a content acquisition means based on the filter.

[0881] Step 6:

[0882] The device displays the acquired web content in the browser. The displayed content is controlled by a filter, allowing the user to enjoy information from the perspective of other attributes.

[0883] Step 7:

[0884] Users can browse content provided from different perspectives on their browsers. For example, they can enjoy technical articles or the latest programming information. This allows users to experience the Internet from a new perspective.

[0885] The above is the specific flow of processing from inputting the image of the person the user wants to simulate and generating a filter based on that image to displaying content.

[0886] Example 1

[0887] 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."

[0888] In conventional Internet usage, it is difficult for users to obtain information based on specific perspectives or interests, and they often rely on biased information from the same source. Therefore, there is a need for methods to provide Internet experiences with new perspectives.

[0889] 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.

[0890] In this invention, the server includes means for receiving the image of a person the user wishes to simulate and extracting related keywords using natural language analysis means, means for generating filter settings based on the extracted keywords and transmitting them to the terminal, and means for the terminal to apply the received filter settings to retrieve and display web content, thereby enabling users to enjoy the Internet from different perspectives.

[0891] A "user" is an entity that uses the system to input a profile and obtain Internet content.

[0892] "Interface means" is a component that includes tools and forms for the user to input the image of the person they wish to simulate.

[0893] A "server" is a computer system that receives data entered by a user and performs analysis and filter generation.

[0894] "Natural language analysis means" refers to analysis techniques and software used to extract keywords related to the person profile entered by the user.

[0895] "Keywords" are important words or phrases extracted based on the persona entered by the user.

[0896] "Filter settings" are rules or settings generated based on extracted keywords to control web content based on specific themes or interests.

[0897] A "terminal" is a device that receives filter settings and retrieves and displays web content based on those settings.

[0898] "Web content" is information or data obtained over the Internet and displayed to a user by a terminal.

[0899] The present invention relates to a system that allows users to enjoy the Internet from different perspectives. This system displays related web content based on the image of a person the user wants to simulate. Specific embodiments of this system are described below.

[0900] System configuration

[0901] The system consists of the following main elements:

[0902] 1. Interface Method

[0903] It is a form that allows users to input the type of person they want to simulate. Specifically, it is a form that is set up on a web browser. This form includes fields where users can input specific person descriptions, such as "a 30-year-old IT engineer" or "a housewife raising children."

[0904] 2. Server

[0905] The server receives input data sent by the user. Specifically, a web framework such as Python's Flask can be used.

[0906] The server analyzes the received data using natural language processing libraries such as NLTK and spaCy to extract relevant keywords.

[0907] The server generates filter settings based on the extracted keywords and sends them to the client terminal.

[0908] 3. Terminal

[0909] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[0910] The device applies the received filter settings and retrieves web content based on them. To retrieve content based on the filters, web scraping technologies (such as Beautiful Soup or Scrapy) can be used.

[0911] The terminal displays the acquired content on the browser and provides it to the user.

[0912] Example of operation

[0913] 1. The user enters "30-year-old IT engineer" into the form in a web browser and clicks the "Submit" button.

[0914] 2. The server receives the input data and performs natural language analysis to extract related keywords such as "tech news," "programming," and "latest gadgets."

[0915] 3. The server generates interest-related filter settings based on these keywords, such as "tech blogs," "latest IT news," or "programming forums."

[0916] 4. The device receives the generated filter settings from the server, applies them, and retrieves the appropriate web content.

[0917] 5. The content acquired by the device is displayed in a web browser, allowing the user to enjoy relevant information from the perspective of a "30-year-old IT engineer."

[0918] Prompt Sentence Examples

[0919] When a user enters "30-year-old IT engineer," the server receives and analyzes the input, extracts related keywords, and generates a filter that controls web content based on the keywords and sends it to the device. The device then applies the filter and displays appropriate content. For example, keywords such as "technology news," "programming," and "latest gadgets" are extracted, and web content with corresponding filter settings is displayed.

[0920] This invention allows users to enjoy a new internet experience by changing their perspective, thereby reducing bias in daily information acquisition and enabling information gathering from a new perspective.

[0921] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0922] Step 1:

[0923] A user enters "30-year-old IT engineer" into a form on a web browser and clicks the "Submit" button.

[0924] Input: User enters a text description of the person (e.g., "30-year-old IT engineer")

[0925] Output: A request with input data sent to the server

[0926] What happens: When a user enters text into a form field and clicks a button, the data in the form is sent to the server as an HTTP request.

[0927] Step 2:

[0928] The server receives the input data sent by the user and begins natural language analysis.

[0929] Input: User-entered data included in the HTTP request (e.g., "30-year-old IT engineer")

[0930] Output: Text data for analysis

[0931] What happens: The server receives the request using the Python Flask framework and passes the text data to a natural language analysis library (e.g., NLTK or spaCy).

[0932] Step 3:

[0933] The server extracts related keywords using natural language analysis.

[0934] Input: Text data for analysis (e.g., "30-year-old IT engineer")

[0935] Output: Extracted keywords (e.g. "tech news", "programming", "latest gadgets")

[0936] What it does: The server uses natural language analysis libraries to extract key keywords from the text data, including tagging parts of speech and word segmentation, to identify keywords related to the topic.

[0937] Step 4:

[0938] The server generates a filter configuration based on the extracted keywords.

[0939] Input: Extracted keywords (e.g., "tech news," "programming," "latest gadgets")

[0940] Output: Generated filter configuration (e.g. filter rules in JSON format).

[0941] What it does: The server uses the extracted keywords to generate filter rules in JSON format to control web content related to specific topics or interests.

[0942] Step 5:

[0943] The server sends the generated filter settings to the device.

[0944] Input: Generated filter configuration (e.g. filter rules in JSON format)

[0945] Output: HTTP response containing the filter configuration

[0946] Specific operation: The server returns the generated JSON format filter settings to the device as an HTTP response.

[0947] Step 6:

[0948] Apply the filter settings received by the device.

[0949] Input: HTTP response containing filter settings (e.g., filter rules in JSON format)

[0950] Output: The result of applying the filter settings

[0951] Specific operation: The device analyzes the filter settings from the HTTP response and stores the filters required to retrieve web content in memory.

[0952] Step 7:

[0953] The device retrieves web content based on the filter settings.

[0954] Input: The result of applying filter settings (e.g. saved filter settings)

[0955] Output: Appropriate web content (e.g. web page based on filters)

[0956] Specific operation: The device will search the target website according to the filter settings using web scraping technology (e.g., Beautiful Soup, Scrapy) to obtain relevant content.

[0957] Step 8:

[0958] The content acquired by the terminal is displayed in the browser.

[0959] Input: Appropriate web content (e.g., a retrieved web page)

[0960] Output: The displayed web page

[0961] Specific behavior: The device renders web content in the browser and presents it visually to the user.

[0962] (Application example 1)

[0963] 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."

[0964] Modern internet users face the challenge of having few opportunities to encounter information from diverse perspectives, due to the way they obtain information, which tends to be limited to their own interests. Furthermore, there are no appropriate means for users to enjoy information from the perspectives of different people, and users tend to fall into a fixed perspective. This can lead to problems such as filter bubbles and biased perceptions.

[0965] 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.

[0966] In this invention, the server includes an interface means for the user to input the character image they wish to simulate, a means for analyzing the user's input and extracting related keywords, a means for generating filter settings based on the extracted keywords, a means for acquiring and displaying web content based on the filter settings received by the terminal, and a means for operating a smartphone application including content acquisition means and display means based on the user's input data. This allows the user to easily acquire information from different perspectives and characters, avoiding filter bubbles and enabling wider and more diverse information acquisition.

[0967] The "interface means" is a means for the user to input the image of the person they wish to simulate.

[0968] A "server" is a device that receives input from a user, analyzes it, and extracts related keywords.

[0969] The "keyword extraction means" is a means for the server to analyze the data received from the user and extract related keywords.

[0970] The "filter setting generation means" is a means for generating filter settings based on keywords extracted by the server.

[0971] A "terminal" is a device that retrieves and displays web content based on filter settings received from a server.

[0972] The "web content acquisition means" is a means for searching for and acquiring appropriate web content based on the filter settings received by the terminal.

[0973] The "display means" is a means for displaying the acquired web content to the user.

[0974] A "smartphone application" is software that allows a user to set up a simulated experience and operate content acquisition means and display means.

[0975] The "natural language analysis means" is an analysis means that allows the server to extract words related to specific themes or interests from the image of the person the user wishes to simulate.

[0976] The following system configuration is conceivable as an embodiment for carrying out the present invention: This system allows users to enjoy content from different perspectives, and is realized by a smartphone application.

[0977] System Overview

[0978] 1. User Interface

[0979] The interface means of the application includes a form for the user to input the profile of the person he / she wants to simulate. For example, the user inputs the profile of a "30-year-old IT engineer."

[0980] 2. Server

[0981] The server analyzes the profile data received from the user and extracts related keywords. This analysis is performed using natural language analysis. As a result of the analysis, for example, in the case of "IT engineer," keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0982] The server generates filter configurations based on the extracted keywords, which create rules to control content based on specific themes or interests.

[0983] 3. Smartphone Applications

[0984] The application on the smartphone receives the filter settings sent from the server, and searches for and retrieves web content based on the filter settings.

[0985] The acquired content is provided to the user through the display means of the application.

[0986] Hardware and software used

[0987] Hardware: Smartphone

[0988] Software: Flask (web framework), HTML template engine

[0989] Data Flow and Processing

[0990] 1. User Input

[0991] The user uses the smartphone application interface to input the "character they would like to simulate."

[0992] When the user presses the "Submit" button, the input data is sent to the server.

[0993] 2. Analysis on the server

[0994] The server receives the input data and analyzes it using natural language analysis. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[0995] 3. Generate filter settings

[0996] The server generates a filter configuration based on the extracted keywords, which contains rules that control information related to a particular subject or interest.

[0997] The generated filter settings are sent to the smartphone application.

[0998] 4. Retrieving and Displaying Content

[0999] The smartphone application searches and retrieves web content based on the received filter settings.

[1000] The acquired content is provided to the user through the display means of the application.

[1001] Specific examples

[1002] Implementation example

[1003] Suppose a user opens an application on their smartphone and types in "30-year-old IT engineer." The server receives this and uses natural language analysis to extract keywords such as "technology news," "programming," and "latest gadgets." It then generates filter settings and retrieves and displays web content containing appropriate technology articles and links to sites.

[1004] Example prompts for generative AI models

[1005] "Create an application that extracts relevant keywords based on the user's profile and displays relevant content based on those keywords. For example, if a user enters "30-year-old IT engineer," generate a system program that extracts keywords such as "tech news," "programming," and "latest gadgets" and displays content related to those keywords."

[1006] Using this prompt, the generative AI model can generate the appropriate program code.

[1007] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1008] Step 1: The user launches the smartphone application and uses the interface to input the "image of the person they wish to simulate."

[1009] Input: The user inputs personal data such as "a 30-year-old IT engineer."

[1010] What happens: A user fills in the application's input form with the appropriate information and clicks the "Submit" button.

[1011] Step 2: The terminal sends the input data from the user to the server.

[1012] Input: Persona data entered by the user.

[1013] Operation: The terminal sends the input data to the server as an HTTP request.

[1014] Step 3: The server analyzes the received input data and extracts relevant keywords.

[1015] Input: Person profile data received by the server.

[1016] Data processing: The server analyzes the data using natural language analysis means and extracts relevant keywords.

[1017] Output: A list of extracted keywords (e.g. "tech news", "programming", "latest gadgets").

[1018] How it works: The server uses a data analysis library (e.g., nltk or spaCy) to parse the input data.

[1019] Step 4: The server generates filter settings based on the extracted keywords.

[1020] Input: Extracted keyword list.

[1021] Data processing: The server identifies content related to the extracted keywords and generates filter settings.

[1022] Output: The generated filter configuration (e.g. "Tech Blogs", "Latest IT News", "Programming Forums").

[1023] How it works: The server uses filtering logic to define the content types to retrieve and generates a filter configuration.

[1024] Step 5: The server sends the filter settings to the device.

[1025] Input: The generated filter settings.

[1026] Output: The filter settings sent to the terminal.

[1027] Operation: The server sends the generated filter settings to the device as an HTTP response.

[1028] Step 6: The device retrieves web content based on the filter settings received.

[1029] Input: The filter settings received by the device.

[1030] Data processing: The device searches for and retrieves relevant web content based on filter settings.

[1031] Output: The retrieved web content list.

[1032] What it does: The device retrieves relevant content using a web scraping library (e.g. BeautifulSoup) or API calls.

[1033] Step 7: The terminal displays the retrieved web content to the user.

[1034] Input: The retrieved web content list.

[1035] Output: The web content displayed to the user.

[1036] How it works: The device uses an HTML template engine to format and visually display web content.

[1037] The above processing steps allow users to easily obtain information from different perspectives and personalities, avoiding filter bubbles and enabling them to obtain a wider range of diverse information.

[1038] 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.

[1039] The present invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system consists of the following main components:

[1040] System configuration

[1041] 1. Interface Method

[1042] It is an interface means for users to input the character they want to simulate. They can enter "30-year-old IT engineer" or "housewife raising children" into a form on the browser. It also has an emotion engine that recognizes the emotions of users when they enter information.

[1043] 2. Emotion Engine

[1044] The emotion engine recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. This recognition result is used to adjust filter settings.

[1045] 3. Server

[1046] The server receives the person image and emotion data sent by the user.

[1047] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1048] 4. Filter Generation

[1049] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "joy," a configuration including "fun news" and "interesting blogs" will be generated.

[1050] 5. Terminal

[1051] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[1052] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[1053] Program processing

[1054] 1. User Input and Emotion Recognition

[1055] The user uses the interface to input the image of the person they want to simulate. For example, they can input "30-year-old IT engineer." At the same time, the emotion engine recognizes the user's facial expressions and voice, and analyzes whether the user is expressing emotions such as "joy," "excitement," or "surprise."

[1056] 2. Data Analysis

[1057] The server receives the input data and emotion data and begins analysis.

[1058] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1059] Based on the analysis results of the emotion engine, keywords are weighted to match the user's emotions.

[1060] 3. Filter generation and transmission

[1061] Based on the extracted keywords and emotion recognition results, the server generates filter configurations, which contain rules for controlling web content based on specific themes or interests, such as displaying content related to the categories "tech news" or "programming."

[1062] The generated filter settings are sent to the device.

[1063] 4. Applying filters and retrieving content

[1064] The device applies the received filter settings and retrieves the controlled web content.

[1065] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[1066] Specific examples

[1067] 1. The user types in "30-year-old IT engineer" and the emotion engine recognizes this as "excited."

[1068] 2. The server receives and analyzes this input and sentiment data. For example, keywords such as "IT," "technology news," and "programming" are extracted, and filter settings related to "latest technology news" and "innovative gadget reviews" are generated based on the user's sentiment.

[1069] 3. The server sends the filter settings to the device.

[1070] 4. The device applies the filter settings to retrieve and display appropriate web content, such as "The latest innovative tech news" or "Gadget reviews for IT professionals."

[1071] 5. Users can enjoy relevant updates in an exciting state.

[1072] As a result, this system not only shifts the user's perspective to other attributes, but also provides an internet experience that takes into account the user's emotions, providing a new perspective and an internet experience that is free from the filter bubble of everyday life.

[1073] The processing flow will be explained below.

[1074] Step 1:

[1075] The user opens a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button. At the same time, the emotion engine analyzes the emotions (e.g., facial expressions and voice) that the user is expressing when they input their input.

[1076] Step 2:

[1077] The server receives the personality data and emotion data sent by the user, analyzes the received personality data using natural language processing (NLP) technology, and extracts related keywords such as "technology news," "programming," and "latest gadgets."

[1078] Step 3:

[1079] The server analyzes the emotional data received from the emotion engine. For example, it can obtain data that the user is "excited." Based on this emotional data, it adjusts the priority of the extracted keywords. For example, keywords such as "latest technology news" and "innovative gadget reviews" are highly ranked.

[1080] Step 4:

[1081] The server generates filter configurations based on the analysis, which contain rules for controlling content related to specific themes or interests based on the extracted keywords and sentiment data, such as displaying content related to the categories "tech news" or "programming."

[1082] Step 5:

[1083] The server sends the generated filter settings to the device, which receives them.

[1084] Step 6:

[1085] Based on the filter settings received, the device sends requests to retrieve controlled web content. For example, the device retrieves relevant updates from specific news sites or tech blogs.

[1086] Step 7:

[1087] The device retrieves web content and displays it in the browser. The content displayed is controlled by filters, providing information based on the user's profile and sentiment. For example, it can display "the latest innovative tech news" or "gadget reviews for IT professionals."

[1088] Step 8:

[1089] Users browse the content displayed on their browsers, which allows them to enjoy relevant and up-to-date information in an exciting state, giving them a new Internet experience based on different perspectives and emotions.

[1090] The above is the specific flow of processing from inputting the image of the person the user wants to simulate, to generating a filter that takes into account emotional data based on that image, to displaying the content.

[1091] Example 2

[1092] 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."

[1093] In the past, the Internet experience was largely one in which users selected content based on their own interests. However, this limited users' opportunities to gain new perspectives and experiences, limiting their access to new content. Furthermore, because information was provided without considering the user's emotions or psychological state, the Internet experience was one-sided and difficult to personalize.

[1094] 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.

[1095] In this invention, the server includes an interface means for allowing the user to input the image of the person they wish to simulate and simultaneously recognizing the user's emotions, a means for the server to analyze the input and emotional data from the user and extract related keywords, and a means for generating filter settings based on the keywords and emotional data extracted by the server. This allows the user to enjoy the Internet from a new perspective and makes it possible to provide personalized information that takes the user's emotions into consideration.

[1096] "User" refers to an entity that inputs information to use the system and receives the resulting content.

[1097] The "image of the person the user wishes to simulate" refers to data input by the user indicating the attributes of a virtual person related to the information and perspective the user wishes to experience.

[1098] "Interface means" refers to a form or user interface on a browser that allows a user to input information.

[1099] "Emotional data" refers to emotional information extracted from a user's facial expressions, voice, and text.

[1100] An "emotion engine" refers to a system that recognizes and analyzes emotions from a user's facial expressions, voice, text, etc.

[1101] "Server" refers to a computer system that receives user-submitted character and emotion data and generates analysis and filter settings.

[1102] "Natural language analysis means" refers to a technical means for analyzing text data entered by a user and extracting related keywords and themes.

[1103] "Keywords" refer to relevant information extracted from the information and emotion data entered by the user and that serves as the basis for filter settings.

[1104] "Filter settings" refers to the rules and parameters that control the relevant web content that is generated based on extracted keywords and sentiment data.

[1105] "Terminal" refers to a device that retrieves web content based on filter settings received from a server and displays it to a user.

[1106] "Web content" refers to information such as news, articles, blogs, and videos obtained from the Internet.

[1107] This invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system operates in cooperation with the user, server, and terminal. Specifically, it is configured as follows:

[1108] System configuration

[1109] 1. Interface Method

[1110] It is a means for users to input the character they wish to simulate. It is implemented as a form on the browser. Users can input such things as "30-year-old IT engineer" or "housewife raising children." It also incorporates an emotion engine that recognizes the emotions expressed when users input data. The emotion engine uses OpenFace (facial expression recognition) and Google Cloud Speech-to-Text API (voice recognition).

[1111] 2. Emotion Engine

[1112] It recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. The results of this recognition are used to adjust filter settings.

[1113] 3. Server

[1114] The server receives the persona data and emotion data sent by the user. The received data is analyzed using natural language analysis tools (e.g., spaCy or Google Cloud Natural Language API) to extract related keywords. For example, if "IT engineer" is entered, keywords such as "tech news," "programming," and "latest gadgets" are extracted. Based on the analysis results of the emotion engine, the extracted keywords are weighted to generate filter settings that match the user's emotions.

[1115] 4. Filter Generation

[1116] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "excitement," a configuration including "latest technology news" and "innovative gadget reviews" will be generated. The generated filter configuration is sent to the device.

[1117] 5. Terminal

[1118] The device receives the filter settings sent from the server. Based on the received filter settings, the device retrieves and displays appropriate web content. For example, it uses the Python requests library or JavaScript fetch API to retrieve information from related websites and news feeds. By viewing the content retrieved based on the filters, users can enjoy a different perspective on their internet experience.

[1119] Specific examples

[1120] 1. User Input

[1121] The user enters "30-year-old IT engineer," and the emotion engine recognizes "excitement" from the user's facial expression and voice. When the submit button on the form is clicked, the data is sent to the server.

[1122] 2. Data Analysis

[1123] The server analyzes the data received via HTTP requests and uses the Natural Language API and OpenFace to extract keywords such as "IT," "tech news," "programming," and "latest gadgets." Based on the emotional data, it generates a filter appropriate for the user's state of excitement.

[1124] 3. Filter Generation

[1125] The server generates filters based on the extracted keywords and emotion data, and the filters include content such as "technology news" and "latest gadget reviews." After the filters are generated, the server sends the filter settings to the device.

[1126] 4. Applying filters and retrieving content

[1127] The device applies the received filter settings and retrieves content from relevant websites and APIs. Specifically, it retrieves RSS feeds using Python requests and retrieves data from news APIs using JavaScript's fetch API. The retrieved content is then displayed in the user's browser, allowing users to enjoy the latest tech news and gadget reviews.

[1128] Prompt Sentence Examples

[1129] Here are some example prompts to input to a generative AI model:

[1130] Generate filter settings based on data that a user types in "30-year-old IT engineer" and is recognized as "excited" by the sentiment engine. Set rules to display appropriate web content, such as the latest tech news or gadget reviews for IT professionals.

[1131] In this way, the system allows users, servers, and terminals to cooperate to provide a customized Internet experience based on the user's emotions.

[1132] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1133] Step 1: User Input and Emotion Recognition

[1134] The user uses the interface to input the image of the person they want to simulate (for example, a "30-year-old IT engineer"), and the emotion engine simultaneously captures the user's facial expressions and voice in real time, recognizing emotions such as "joy," "excitement," and "surprise."

[1135] Input: User-entered character image text, facial expressions and voice that indicate the user's emotions

[1136] Output: Pairs of character image text and emotion data

[1137] Specific behavior: The formatted form data and captured emotion data are sent to the server in JSON format.

[1138] Step 2: Analyze the data

[1139] The server receives the character image data and emotion data sent by the user. It uses natural language analysis tools (such as spaCy or Google Cloud Natural Language API) to extract relevant keywords from the input text. It also weights the keywords using the analysis results of the emotion engine.

[1140] Input: Pairs of character image text and emotion data

[1141] Output: Extracted keywords and a weighted keyword list based on sentiment

[1142] How it works: A text analysis algorithm is run to extract relevant keywords such as "tech news," "programming," and "latest gadgets." Keywords are weighted according to excitement level based on emotion data.

[1143] Step 3: Generate the filter

[1144] The server generates filter settings based on the extracted keywords and emotion recognition results.

[1145] Input: Weighted keyword list

[1146] Output: Filter settings (related content rules and parameters)

[1147] Specific behavior: Based on the keywords and sentiment data, a specific category (e.g., "Latest Tech News" or "Innovative Gadget Reviews") is selected, and filter rules related to this category are generated. The generated filter settings are formatted as an HTTP response to be sent to the device.

[1148] Step 4: Submit filter settings

[1149] The server sends the generated filter settings to the terminal.

[1150] Input: Filter settings

[1151] Output: Filter settings sent to the terminal

[1152] Specific operation: The generated filter settings are sent as an HTTP response, and this data is received on the terminal side.

[1153] Step 5: Applying filters and retrieving content

[1154] The terminal retrieves relevant web content based on the filter settings received from the server and displays it to the user.

[1155] Input: Filter settings

[1156] Output: Retrieved web content

[1157] Specific operation: Uses Python's requests library or JavaScript's fetch API to retrieve content that matches the filter settings from RSS feeds and news APIs. Renders the retrieved data in the browser so that the user can view it.

[1158] In this way, each step works together to provide a customized internet experience based on the user's input and emotions.

[1159] (Application example 2)

[1160] 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."

[1161] Existing virtual store systems do not take user emotions into consideration when proposing products, making it difficult to provide personalized product suggestions that meet diverse user needs. Another problem is the lack of interfaces and systems that allow users to enjoy shopping experiences from different perspectives.

[1162] The identification process by the identification 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 an emotion engine that recognizes the user's emotions, means for analyzing input from the user and extracting related keywords, and means for generating filter settings based on the extracted keywords and emotion recognition results. This makes it possible to propose products and services optimized for the user based on the user's emotions and the character they wish to simulate.

[1163] "User" refers to a person who uses this system to have a simulated experience.

[1164] The "interface means" refers to a means for the user to input the image of the person he or she wishes to simulate, and also refers to an interface means for exchanging information between the user and the system.

[1165] "Server" refers to the main computer system that receives, analyzes, and processes input data and emotion data from users.

[1166] An "emotion engine" refers to a system for detecting a user's emotions using means such as facial recognition, voice recognition, and text analysis.

[1167] "Means for extracting keywords" refers to means for performing natural language analysis on the data input by the user and extracting related keywords.

[1168] The "means for generating filter settings" refers to a means for setting content display rules based on the extracted keywords and emotion recognition results.

[1169] "Terminal" refers to a device operated by a user for displaying web content using filter settings received from a server.

[1170] The "content selection means" refers to a means for selecting content containing the latest information based on the extracted keywords and emotion recognition results.

[1171] "Natural language analysis means" refers to means for analyzing user input data and extracting keywords related to specific themes or interests.

[1172] A system for implementing the present invention provides personalized products and services based on emotions when a user is shopping in a virtual store.

[1173] The system mainly consists of the following components:

[1174] 1. Interface Method

[1175] It is a means for users to input the image of the person they want to simulate, and is installed as a text input field on the smartphone application screen.

[1176] 2. Emotion Engine

[1177] This is an engine for recognizing user emotions. This engine uses machine learning models such as TensorFlow to analyze emotions through facial recognition, voice recognition, and text analysis.

[1178] 3. Server

[1179] This is the main computer system that receives and analyzes the input data from the user (the person they want to simulate) and the emotion data obtained by the emotion engine. The server uses natural language processing (NLP) techniques, for example, the NLTK library, to extract relevant keywords.

[1180] 4. Filter Generation Method

[1181] This is a means for generating product and service suggestion filters based on the server-extracted keywords and emotion recognition results. The generated filter settings include product categories and display priorities.

[1182] 5. Terminal

[1183] This is a device operated by the user, such as a smartphone or tablet. The device retrieves and displays appropriate product information based on the filter settings received from the server.

[1184] The specific operation is as follows.

[1185] 1. The user enters "Female in her 20s" on the application screen. At this time, the emotion engine recognizes that the user is feeling "curiosity" based on their facial expression.

[1186] 2. The server receives the input data and emotion data, extracts keywords such as "fashion," "trends," and "cosmetics" through natural language analysis, and generates filter settings based on the emotion.

[1187] 3. The generated filter settings are sent to the device, which then uses them to display the latest trending products, related fashion items, cosmetic products, and more to the user.

[1188] This approach allows users to find the most relevant product information based on their emotions and interests, improving the user experience in virtual stores and providing a more engaging shopping experience.

[1189] Prompt Sentence Examples

[1190] "We want to build a product recommendation system that allows users to input the character they want to simulate and recognize emotions. The system will then recommend products based on the user's emotions. The following prompts will allow us to get suggested product information:

[1191] For example, if you are a woman in your 20s and your emotion is curiosity, search for product information using the keywords "fashion," "trends," and "cosmetics."

[1192] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1193] Step 1:

[1194] The user inputs the image of the person they want to simulate (e.g., "woman in her 20s") using the interface. At this time, the emotion engine analyzes the user's facial expressions and voice and recognizes the user's emotion (e.g., "curiosity").

[1195] Input: User's profile input data, user's face image or voice data

[1196] Output: User emotion recognition results, input person image data

[1197] Specific operation: Facial images are captured using a smartphone camera, and emotions are determined using a generative AI model such as TensorFlow.

[1198] Step 2:

[1199] The server receives input data from the user and emotion recognition results, and extracts related keywords using natural language analysis means.

[1200] Input: User's portrait input data and emotion recognition results received by the server

[1201] Output: Extracted keyword list

[1202] Specific operation: Natural language processing is performed using the NLTK library to extract keywords such as "fashion," "trends," and "cosmetics."

[1203] Step 3:

[1204] The server generates filter settings based on the extracted keywords and emotion recognition results, including product categories, display priorities, and latest information.

[1205] Input: Extracted keyword list, user emotion recognition results

[1206] Output: Filter setting data

[1207] What it does: Create filtering rules to set product categories and display priorities based on keywords and sentiment.

[1208] Step 4:

[1209] The server transmits the generated filter settings to the terminal, and the terminal receives them.

[1210] Input: Filter setting data

[1211] Output: Filter settings received by the device

[1212] Specific operation: Network communication is performed to send filter settings from the server to the smartphone.

[1213] Step 5:

[1214] The device retrieves relevant web content based on the received filter settings, and the retrieved content is optimized for the user according to the filter settings.

[1215] Input: Received filter settings

[1216] Output: Selected web content

[1217] What it does: Makes API calls to search and retrieve product information based on filter settings.

[1218] Step 6:

[1219] The terminal displays the acquired web content to the user, allowing the user to view personalized product information based on their emotions and interests.

[1220] Input: Selected web content

[1221] Output: Personalized product information displayed to the user

[1222] Specific operation: Update the UI to display product information on the smartphone screen.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] [Fourth embodiment]

[1227] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1228] 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.

[1229] 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).

[1230] 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.

[1231] 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.

[1232] 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).

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] 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.

[1239] 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."

[1240] The present invention provides a system that allows users to enjoy the Internet from different perspectives. This system is composed of the following main components:

[1241] System configuration

[1242] 1. Interface Method

[1243] This is an interface means for users to input the character they want to simulate. This interface includes a form installed on the browser, and users can input such things as "a 30-year-old IT engineer" or "a housewife raising children."

[1244] 2. Server

[1245] The server receives the person image data sent from the user.

[1246] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1247] 3. Filter Generation

[1248] The server generates filter configurations based on the extracted keywords, which contain rules for controlling content based on specific themes or interests, such as displaying only content related to "tech news" or "programming."

[1249] 4. Terminal

[1250] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[1251] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[1252] Program processing

[1253] 1. User Input

[1254] The user inputs the image of the person they want to simulate using the interface. For example, they input "a 30-year-old IT engineer."

[1255] The user clicks the "Submit" button to send the input data to the server.

[1256] 2. Data Analysis

[1257] The server receives the input data and begins parsing it.

[1258] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1259] 3. Filter generation and transmission

[1260] Based on the extracted keywords, the server generates a filter configuration, which contains rules that control web content based on specific themes or interests.

[1261] The generated filter settings are sent to the device.

[1262] 4. Applying filters and retrieving content

[1263] The device applies the received filter settings and retrieves the controlled web content.

[1264] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[1265] Specific examples

[1266] 1. The user enters "30-year-old IT engineer."

[1267] 2. The server receives this input and analyzes it, extracting keywords such as "IT," "technology news," and "programming."

[1268] 3. The server generates filter settings based on these keywords, for example, creating a filter that includes "tech blogs," "latest IT news," "programming forums," etc.

[1269] 4. The device receives and applies the filter settings.

[1270] 5. The device retrieves the appropriate web content and displays it in the browser, allowing the user to enjoy the latest relevant information from the perspective of a 30-year-old IT engineer.

[1271] As described above, this system provides a new perspective by switching the user's perspective to other attributes, providing an internet experience that is free from the filter bubble of everyday life.

[1272] The processing flow will be explained below.

[1273] Step 1:

[1274] The user launches a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button, sending the input data to the server.

[1275] Step 2:

[1276] The server receives the input data. The received profile data is analyzed using natural language processing (NLP) technology to extract related keywords. For example, if "IT engineer" is entered, keywords such as "technology news," "programming," and "latest gadgets" are extracted.

[1277] Step 3:

[1278] The server generates a filter configuration based on the extracted keywords. This filter configuration contains rules and parameters for controlling related web content, such as displaying content related to the categories "tech news" and "programming."

[1279] Step 4:

[1280] The server sends the generated filter settings to the terminal, and the terminal receives the filter settings sent from the server.

[1281] Step 5:

[1282] The terminal acquires web content based on the filter settings received, and selects appropriate information using a content acquisition means based on the filter.

[1283] Step 6:

[1284] The device displays the acquired web content in the browser. The displayed content is controlled by a filter, allowing the user to enjoy information from the perspective of other attributes.

[1285] Step 7:

[1286] Users can browse content provided from different perspectives on their browsers. For example, they can enjoy technical articles or the latest programming information. This allows users to experience the Internet from a new perspective.

[1287] The above is the specific flow of processing from inputting the image of the person the user wants to simulate and generating a filter based on that image to displaying content.

[1288] Example 1

[1289] 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."

[1290] In conventional Internet usage, it is difficult for users to obtain information based on specific perspectives or interests, and they often rely on biased information from the same source. Therefore, there is a need for methods to provide Internet experiences with new perspectives.

[1291] 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.

[1292] In this invention, the server includes means for receiving the image of a person the user wishes to simulate and extracting related keywords using natural language analysis means, means for generating filter settings based on the extracted keywords and transmitting them to the terminal, and means for the terminal to apply the received filter settings to retrieve and display web content, thereby enabling users to enjoy the Internet from different perspectives.

[1293] A "user" is an entity that uses the system to input a profile and obtain Internet content.

[1294] "Interface means" is a component that includes tools and forms for the user to input the image of the person they wish to simulate.

[1295] A "server" is a computer system that receives data entered by a user and performs analysis and filter generation.

[1296] "Natural language analysis means" refers to analysis techniques and software used to extract keywords related to the person profile entered by the user.

[1297] "Keywords" are important words or phrases extracted based on the persona entered by the user.

[1298] "Filter settings" are rules or settings generated based on extracted keywords to control web content based on specific themes or interests.

[1299] A "terminal" is a device that receives filter settings and retrieves and displays web content based on those settings.

[1300] "Web content" is information or data obtained over the Internet and displayed to a user by a terminal.

[1301] The present invention relates to a system that allows users to enjoy the Internet from different perspectives. This system displays related web content based on the image of a person the user wants to simulate. Specific embodiments of this system are described below.

[1302] System configuration

[1303] The system consists of the following main elements:

[1304] 1. Interface Method

[1305] It is a form that allows users to input the type of person they want to simulate. Specifically, it is a form that is set up on a web browser. This form includes fields where users can input specific person descriptions, such as "a 30-year-old IT engineer" or "a housewife raising children."

[1306] 2. Server

[1307] The server receives input data sent by the user. Specifically, a web framework such as Python's Flask can be used.

[1308] The server analyzes the received data using natural language processing libraries such as NLTK and spaCy to extract relevant keywords.

[1309] The server generates filter settings based on the extracted keywords and sends them to the client terminal.

[1310] 3. Terminal

[1311] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[1312] The device applies the received filter settings and retrieves web content based on them. To retrieve content based on the filters, web scraping technologies (such as Beautiful Soup or Scrapy) can be used.

[1313] The terminal displays the acquired content on the browser and provides it to the user.

[1314] Example of operation

[1315] 1. The user enters "30-year-old IT engineer" into the form in a web browser and clicks the "Submit" button.

[1316] 2. The server receives the input data and performs natural language analysis to extract related keywords such as "tech news," "programming," and "latest gadgets."

[1317] 3. The server generates interest-related filter settings based on these keywords, such as "tech blogs," "latest IT news," or "programming forums."

[1318] 4. The device receives the generated filter settings from the server, applies them, and retrieves the appropriate web content.

[1319] 5. The content acquired by the device is displayed in a web browser, allowing the user to enjoy relevant information from the perspective of a "30-year-old IT engineer."

[1320] Prompt Sentence Examples

[1321] When a user enters "30-year-old IT engineer," the server receives and analyzes the input, extracts related keywords, and generates a filter that controls web content based on the keywords and sends it to the device. The device then applies the filter and displays appropriate content. For example, keywords such as "technology news," "programming," and "latest gadgets" are extracted, and web content with corresponding filter settings is displayed.

[1322] This invention allows users to enjoy a new internet experience by changing their perspective, thereby reducing bias in daily information acquisition and enabling information gathering from a new perspective.

[1323] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1324] Step 1:

[1325] A user enters "30-year-old IT engineer" into a form on a web browser and clicks the "Submit" button.

[1326] Input: User enters a text description of the person (e.g., "30-year-old IT engineer")

[1327] Output: A request with input data sent to the server

[1328] What happens: When a user enters text into a form field and clicks a button, the data in the form is sent to the server as an HTTP request.

[1329] Step 2:

[1330] The server receives the input data sent by the user and begins natural language analysis.

[1331] Input: User-entered data included in the HTTP request (e.g., "30-year-old IT engineer")

[1332] Output: Text data for analysis

[1333] What happens: The server receives the request using the Python Flask framework and passes the text data to a natural language analysis library (e.g., NLTK or spaCy).

[1334] Step 3:

[1335] The server extracts related keywords using natural language analysis.

[1336] Input: Text data for analysis (e.g., "30-year-old IT engineer")

[1337] Output: Extracted keywords (e.g. "tech news", "programming", "latest gadgets")

[1338] What it does: The server uses natural language analysis libraries to extract key keywords from the text data, including tagging parts of speech and word segmentation, to identify keywords related to the topic.

[1339] Step 4:

[1340] The server generates a filter configuration based on the extracted keywords.

[1341] Input: Extracted keywords (e.g., "tech news," "programming," "latest gadgets")

[1342] Output: Generated filter configuration (e.g. filter rules in JSON format).

[1343] What it does: The server uses the extracted keywords to generate filter rules in JSON format to control web content related to specific topics or interests.

[1344] Step 5:

[1345] The server sends the generated filter settings to the device.

[1346] Input: Generated filter configuration (e.g. filter rules in JSON format)

[1347] Output: HTTP response containing the filter configuration

[1348] Specific operation: The server returns the generated JSON format filter settings to the device as an HTTP response.

[1349] Step 6:

[1350] Apply the filter settings received by the device.

[1351] Input: HTTP response containing filter settings (e.g., filter rules in JSON format)

[1352] Output: The result of applying the filter settings

[1353] Specific operation: The device analyzes the filter settings from the HTTP response and stores the filters required to retrieve web content in memory.

[1354] Step 7:

[1355] The device retrieves web content based on the filter settings.

[1356] Input: The result of applying filter settings (e.g. saved filter settings)

[1357] Output: Appropriate web content (e.g. web page based on filters)

[1358] Specific operation: The device will search the target website according to the filter settings using web scraping technology (e.g., Beautiful Soup, Scrapy) to obtain relevant content.

[1359] Step 8:

[1360] The content acquired by the terminal is displayed in the browser.

[1361] Input: Appropriate web content (e.g., a retrieved web page)

[1362] Output: The displayed web page

[1363] Specific behavior: The device renders web content in the browser and presents it visually to the user.

[1364] (Application example 1)

[1365] 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."

[1366] Modern internet users face the challenge of having few opportunities to encounter information from diverse perspectives, due to the way they obtain information, which tends to be limited to their own interests. Furthermore, there are no appropriate means for users to enjoy information from the perspectives of different people, and users tend to fall into a fixed perspective. This can lead to problems such as filter bubbles and biased perceptions.

[1367] 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.

[1368] In this invention, the server includes an interface means for the user to input the character image they wish to simulate, a means for analyzing the user's input and extracting related keywords, a means for generating filter settings based on the extracted keywords, a means for acquiring and displaying web content based on the filter settings received by the terminal, and a means for operating a smartphone application including content acquisition means and display means based on the user's input data. This allows the user to easily acquire information from different perspectives and characters, avoiding filter bubbles and enabling wider and more diverse information acquisition.

[1369] The "interface means" is a means for the user to input the image of the person they wish to simulate.

[1370] A "server" is a device that receives input from a user, analyzes it, and extracts related keywords.

[1371] The "keyword extraction means" is a means for the server to analyze the data received from the user and extract related keywords.

[1372] The "filter setting generation means" is a means for generating filter settings based on keywords extracted by the server.

[1373] A "terminal" is a device that retrieves and displays web content based on filter settings received from a server.

[1374] The "web content acquisition means" is a means for searching for and acquiring appropriate web content based on the filter settings received by the terminal.

[1375] The "display means" is a means for displaying the acquired web content to the user.

[1376] A "smartphone application" is software that allows a user to set up a simulated experience and operate content acquisition means and display means.

[1377] The "natural language analysis means" is an analysis means that allows the server to extract words related to specific themes or interests from the image of the person the user wishes to simulate.

[1378] The following system configuration is conceivable as an embodiment for carrying out the present invention: This system allows users to enjoy content from different perspectives, and is realized by a smartphone application.

[1379] System Overview

[1380] 1. User Interface

[1381] The interface means of the application includes a form for the user to input the profile of the person he / she wants to simulate. For example, the user inputs the profile of a "30-year-old IT engineer."

[1382] 2. Server

[1383] The server analyzes the profile data received from the user and extracts related keywords. This analysis is performed using natural language analysis. As a result of the analysis, for example, in the case of "IT engineer," keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[1384] The server generates filter configurations based on the extracted keywords, which create rules to control content based on specific themes or interests.

[1385] 3. Smartphone Applications

[1386] The application on the smartphone receives the filter settings sent from the server, and searches for and retrieves web content based on the filter settings.

[1387] The acquired content is provided to the user through the display means of the application.

[1388] Hardware and software used

[1389] Hardware: Smartphone

[1390] Software: Flask (web framework), HTML template engine

[1391] Data Flow and Processing

[1392] 1. User Input

[1393] The user uses the smartphone application interface to input the "character they would like to simulate."

[1394] When the user presses the "Submit" button, the input data is sent to the server.

[1395] 2. Analysis on the server

[1396] The server receives the input data and analyzes it using natural language analysis. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" are extracted.

[1397] 3. Generate filter settings

[1398] The server generates a filter configuration based on the extracted keywords, which contains rules that control information related to a particular subject or interest.

[1399] The generated filter settings are sent to the smartphone application.

[1400] 4. Retrieving and Displaying Content

[1401] The smartphone application searches and retrieves web content based on the received filter settings.

[1402] The acquired content is provided to the user through the display means of the application.

[1403] Specific examples

[1404] Implementation example

[1405] Suppose a user opens an application on their smartphone and types in "30-year-old IT engineer." The server receives this and uses natural language analysis to extract keywords such as "technology news," "programming," and "latest gadgets." It then generates filter settings and retrieves and displays web content containing appropriate technology articles and links to sites.

[1406] Example prompts for generative AI models

[1407] "Create an application that extracts relevant keywords based on the user's profile and displays relevant content based on those keywords. For example, if a user enters "30-year-old IT engineer," generate a system program that extracts keywords such as "tech news," "programming," and "latest gadgets" and displays content related to those keywords."

[1408] Using this prompt, the generative AI model can generate the appropriate program code.

[1409] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1410] Step 1: The user launches the smartphone application and uses the interface to input the "image of the person they wish to simulate."

[1411] Input: The user inputs personal data such as "a 30-year-old IT engineer."

[1412] What happens: A user fills in the application's input form with the appropriate information and clicks the "Submit" button.

[1413] Step 2: The terminal sends the input data from the user to the server.

[1414] Input: Persona data entered by the user.

[1415] Operation: The terminal sends the input data to the server as an HTTP request.

[1416] Step 3: The server analyzes the received input data and extracts relevant keywords.

[1417] Input: Person profile data received by the server.

[1418] Data processing: The server analyzes the data using natural language analysis means and extracts relevant keywords.

[1419] Output: A list of extracted keywords (e.g. "tech news", "programming", "latest gadgets").

[1420] How it works: The server uses a data analysis library (e.g., nltk or spaCy) to parse the input data.

[1421] Step 4: The server generates filter settings based on the extracted keywords.

[1422] Input: Extracted keyword list.

[1423] Data processing: The server identifies content related to the extracted keywords and generates filter settings.

[1424] Output: The generated filter configuration (e.g. "Tech Blogs", "Latest IT News", "Programming Forums").

[1425] How it works: The server uses filtering logic to define the content types to retrieve and generates a filter configuration.

[1426] Step 5: The server sends the filter settings to the device.

[1427] Input: The generated filter settings.

[1428] Output: The filter settings sent to the terminal.

[1429] Operation: The server sends the generated filter settings to the device as an HTTP response.

[1430] Step 6: The device retrieves web content based on the filter settings received.

[1431] Input: The filter settings received by the device.

[1432] Data processing: The device searches for and retrieves relevant web content based on filter settings.

[1433] Output: The retrieved web content list.

[1434] What it does: The device retrieves relevant content using a web scraping library (e.g. BeautifulSoup) or API calls.

[1435] Step 7: The terminal displays the retrieved web content to the user.

[1436] Input: The retrieved web content list.

[1437] Output: The web content displayed to the user.

[1438] How it works: The device uses an HTML template engine to format and visually display web content.

[1439] The above processing steps allow users to easily obtain information from different perspectives and personalities, avoiding filter bubbles and enabling them to obtain a wider range of diverse information.

[1440] 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.

[1441] The present invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system consists of the following main components:

[1442] System configuration

[1443] 1. Interface Method

[1444] It is an interface means for users to input the character they want to simulate. They can enter "30-year-old IT engineer" or "housewife raising children" into a form on the browser. It also has an emotion engine that recognizes the emotions of users when they enter information.

[1445] 2. Emotion Engine

[1446] The emotion engine recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. This recognition result is used to adjust filter settings.

[1447] 3. Server

[1448] The server receives the person image and emotion data sent by the user.

[1449] The server analyzes the received data using natural language analysis tools and extracts related keywords. For example, if "IT engineer" is entered, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1450] 4. Filter Generation

[1451] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "joy," a configuration including "fun news" and "interesting blogs" will be generated.

[1452] 5. Terminal

[1453] The terminal is a device operated by the user, and receives the filter settings sent from the server.

[1454] The terminal retrieves and displays web content based on the filter settings, and provides appropriate information to the user through content retrieval based on the filter.

[1455] Program processing

[1456] 1. User Input and Emotion Recognition

[1457] The user uses the interface to input the image of the person they want to simulate. For example, they can input "30-year-old IT engineer." At the same time, the emotion engine recognizes the user's facial expressions and voice, and analyzes whether the user is expressing emotions such as "joy," "excitement," or "surprise."

[1458] 2. Data Analysis

[1459] The server receives the input data and emotion data and begins analysis.

[1460] The server uses natural language analysis to extract related keywords from the input person profile. For example, if "IT engineer" is input, keywords such as "technical news," "programming," and "latest gadgets" will be extracted.

[1461] Based on the analysis results of the emotion engine, keywords are weighted to match the user's emotions.

[1462] 3. Filter generation and transmission

[1463] Based on the extracted keywords and emotion recognition results, the server generates filter configurations, which contain rules for controlling web content based on specific themes or interests, such as displaying content related to the categories "tech news" or "programming."

[1464] The generated filter settings are sent to the device.

[1465] 4. Applying filters and retrieving content

[1466] The device applies the received filter settings and retrieves the controlled web content.

[1467] The terminal displays the acquired content in the browser, allowing the user to enjoy an Internet experience from a different perspective.

[1468] Specific examples

[1469] 1. The user types in "30-year-old IT engineer" and the emotion engine recognizes this as "excited."

[1470] 2. The server receives and analyzes this input and sentiment data. For example, keywords such as "IT," "technology news," and "programming" are extracted, and filter settings related to "latest technology news" and "innovative gadget reviews" are generated based on the user's sentiment.

[1471] 3. The server sends the filter settings to the device.

[1472] 4. The device applies the filter settings to retrieve and display appropriate web content, such as "The latest innovative tech news" or "Gadget reviews for IT professionals."

[1473] 5. Users can enjoy relevant updates in an exciting state.

[1474] As a result, this system not only shifts the user's perspective to other attributes, but also provides an internet experience that takes into account the user's emotions, providing a new perspective and an internet experience that is free from the filter bubble of everyday life.

[1475] The processing flow will be explained below.

[1476] Step 1:

[1477] The user opens a browser and fills in a form to input the type of person they want to simulate, describing a specific person, such as a "30-year-old IT engineer." The user then clicks the "Submit" button. At the same time, the emotion engine analyzes the emotions (e.g., facial expressions and voice) that the user is expressing when they input their input.

[1478] Step 2:

[1479] The server receives the personality data and emotion data sent by the user, analyzes the received personality data using natural language processing (NLP) technology, and extracts related keywords such as "technology news," "programming," and "latest gadgets."

[1480] Step 3:

[1481] The server analyzes the emotional data received from the emotion engine. For example, it can obtain data that the user is "excited." Based on this emotional data, it adjusts the priority of the extracted keywords. For example, keywords such as "latest technology news" and "innovative gadget reviews" are highly ranked.

[1482] Step 4:

[1483] The server generates filter configurations based on the analysis, which contain rules for controlling content related to specific themes or interests based on the extracted keywords and sentiment data, such as displaying content related to the categories "tech news" or "programming."

[1484] Step 5:

[1485] The server sends the generated filter settings to the device, which receives them.

[1486] Step 6:

[1487] Based on the filter settings received, the device sends requests to retrieve controlled web content. For example, the device retrieves relevant updates from specific news sites or tech blogs.

[1488] Step 7:

[1489] The device retrieves web content and displays it in the browser. The content displayed is controlled by filters, providing information based on the user's profile and sentiment. For example, it can display "the latest innovative tech news" or "gadget reviews for IT professionals."

[1490] Step 8:

[1491] Users browse the content displayed on their browsers, which allows them to enjoy relevant and up-to-date information in an exciting state, giving them a new Internet experience based on different perspectives and emotions.

[1492] The above is the specific flow of processing from inputting the image of the person the user wants to simulate, to generating a filter that takes into account emotional data based on that image, to displaying the content.

[1493] Example 2

[1494] 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."

[1495] In the past, the Internet experience was largely one in which users selected content based on their own interests. However, this limited users' opportunities to gain new perspectives and experiences, limiting their access to new content. Furthermore, because information was provided without considering the user's emotions or psychological state, the Internet experience was one-sided and difficult to personalize.

[1496] 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.

[1497] In this invention, the server includes an interface means for allowing the user to input the image of the person they wish to simulate and simultaneously recognizing the user's emotions, a means for the server to analyze the input and emotional data from the user and extract related keywords, and a means for generating filter settings based on the keywords and emotional data extracted by the server. This allows the user to enjoy the Internet from a new perspective and makes it possible to provide personalized information that takes the user's emotions into consideration.

[1498] "User" refers to an entity that inputs information to use the system and receives the resulting content.

[1499] The "image of the person the user wishes to simulate" refers to data input by the user indicating the attributes of a virtual person related to the information and perspective the user wishes to experience.

[1500] "Interface means" refers to a form or user interface on a browser that allows a user to input information.

[1501] "Emotional data" refers to emotional information extracted from a user's facial expressions, voice, and text.

[1502] An "emotion engine" refers to a system that recognizes and analyzes emotions from a user's facial expressions, voice, text, etc.

[1503] "Server" refers to a computer system that receives user-submitted character and emotion data and generates analysis and filter settings.

[1504] "Natural language analysis means" refers to a technical means for analyzing text data entered by a user and extracting related keywords and themes.

[1505] "Keywords" refer to relevant information extracted from the information and emotion data entered by the user and that serves as the basis for filter settings.

[1506] "Filter settings" refers to the rules and parameters that control the relevant web content that is generated based on extracted keywords and sentiment data.

[1507] "Terminal" refers to a device that retrieves web content based on filter settings received from a server and displays it to a user.

[1508] "Web content" refers to information such as news, articles, blogs, and videos obtained from the Internet.

[1509] This invention combines a system that allows users to enjoy the Internet from different perspectives with an emotion engine that recognizes the user's emotions. This system operates in cooperation with the user, server, and terminal. Specifically, it is configured as follows:

[1510] System configuration

[1511] 1. Interface Method

[1512] It is a means for users to input the character they wish to simulate. It is implemented as a form on the browser. Users can input such things as "30-year-old IT engineer" or "housewife raising children." It also incorporates an emotion engine that recognizes the emotions expressed when users input data. The emotion engine uses OpenFace (facial expression recognition) and Google Cloud Speech-to-Text API (voice recognition).

[1513] 2. Emotion Engine

[1514] It recognizes the user's emotions from their facial expressions, voice, text, etc. as they type. The results of this recognition are used to adjust filter settings.

[1515] 3. Server

[1516] The server receives the persona data and emotion data sent by the user. The received data is analyzed using natural language analysis tools (e.g., spaCy or Google Cloud Natural Language API) to extract related keywords. For example, if "IT engineer" is entered, keywords such as "tech news," "programming," and "latest gadgets" are extracted. Based on the analysis results of the emotion engine, the extracted keywords are weighted to generate filter settings that match the user's emotions.

[1517] 4. Filter Generation

[1518] The server generates a filter configuration based on the extracted keywords and emotion recognition results. This filter configuration includes rules and parameters for controlling related web content. For example, if a user inputs "excitement," a configuration including "latest technology news" and "innovative gadget reviews" will be generated. The generated filter configuration is sent to the device.

[1519] 5. Terminal

[1520] The device receives the filter settings sent from the server. Based on the received filter settings, the device retrieves and displays appropriate web content. For example, it uses the Python requests library or JavaScript fetch API to retrieve information from related websites and news feeds. By viewing the content retrieved based on the filters, users can enjoy a different perspective on their internet experience.

[1521] Specific examples

[1522] 1. User Input

[1523] The user enters "30-year-old IT engineer," and the emotion engine recognizes "excitement" from the user's facial expression and voice. When the submit button on the form is clicked, the data is sent to the server.

[1524] 2. Data Analysis

[1525] The server analyzes the data received via HTTP requests and uses the Natural Language API and OpenFace to extract keywords such as "IT," "tech news," "programming," and "latest gadgets." Based on the emotional data, it generates a filter appropriate for the user's state of excitement.

[1526] 3. Filter Generation

[1527] The server generates filters based on the extracted keywords and emotion data, and the filters include content such as "technology news" and "latest gadget reviews." After the filters are generated, the server sends the filter settings to the device.

[1528] 4. Applying filters and retrieving content

[1529] The device applies the received filter settings and retrieves content from relevant websites and APIs. Specifically, it retrieves RSS feeds using Python requests and retrieves data from news APIs using JavaScript's fetch API. The retrieved content is then displayed in the user's browser, allowing users to enjoy the latest tech news and gadget reviews.

[1530] Prompt Sentence Examples

[1531] Here are some example prompts to input to a generative AI model:

[1532] Generate filter settings based on data that a user types in "30-year-old IT engineer" and is recognized as "excited" by the sentiment engine. Set rules to display appropriate web content, such as the latest tech news or gadget reviews for IT professionals.

[1533] In this way, the system allows users, servers, and terminals to cooperate to provide a customized Internet experience based on the user's emotions.

[1534] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1535] Step 1: User Input and Emotion Recognition

[1536] The user uses the interface to input the image of the person they want to simulate (for example, a "30-year-old IT engineer"), and the emotion engine simultaneously captures the user's facial expressions and voice in real time, recognizing emotions such as "joy," "excitement," and "surprise."

[1537] Input: User-entered character image text, facial expressions and voice that indicate the user's emotions

[1538] Output: Pairs of character image text and emotion data

[1539] Specific behavior: The formatted form data and captured emotion data are sent to the server in JSON format.

[1540] Step 2: Analyze the data

[1541] The server receives the character image data and emotion data sent by the user. It uses natural language analysis tools (such as spaCy or Google Cloud Natural Language API) to extract relevant keywords from the input text. It also weights the keywords using the analysis results of the emotion engine.

[1542] Input: Pairs of character image text and emotion data

[1543] Output: Extracted keywords and a weighted keyword list based on sentiment

[1544] How it works: A text analysis algorithm is run to extract relevant keywords such as "tech news," "programming," and "latest gadgets." Keywords are weighted according to excitement level based on emotion data.

[1545] Step 3: Generate the filter

[1546] The server generates filter settings based on the extracted keywords and emotion recognition results.

[1547] Input: Weighted keyword list

[1548] Output: Filter settings (related content rules and parameters)

[1549] Specific behavior: Based on the keywords and sentiment data, a specific category (e.g., "Latest Tech News" or "Innovative Gadget Reviews") is selected, and filter rules related to this category are generated. The generated filter settings are formatted as an HTTP response to be sent to the device.

[1550] Step 4: Submit filter settings

[1551] The server sends the generated filter settings to the terminal.

[1552] Input: Filter settings

[1553] Output: Filter settings sent to the terminal

[1554] Specific operation: The generated filter settings are sent as an HTTP response, and this data is received on the terminal side.

[1555] Step 5: Applying filters and retrieving content

[1556] The terminal retrieves relevant web content based on the filter settings received from the server and displays it to the user.

[1557] Input: Filter settings

[1558] Output: Retrieved web content

[1559] Specific operation: Uses Python's requests library or JavaScript's fetch API to retrieve content that matches the filter settings from RSS feeds and news APIs. Renders the retrieved data in the browser so that the user can view it.

[1560] In this way, each step works together to provide a customized internet experience based on the user's input and emotions.

[1561] (Application example 2)

[1562] 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."

[1563] Existing virtual store systems do not take user emotions into consideration when proposing products, making it difficult to provide personalized product suggestions that meet diverse user needs. Another problem is the lack of interfaces and systems that allow users to enjoy shopping experiences from different perspectives.

[1564] The identification process by the identification 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 an emotion engine that recognizes the user's emotions, means for analyzing input from the user and extracting related keywords, and means for generating filter settings based on the extracted keywords and emotion recognition results. This makes it possible to propose products and services optimized for the user based on the user's emotions and the character they wish to simulate.

[1565] "User" refers to a person who uses this system to have a simulated experience.

[1566] The "interface means" refers to a means for the user to input the image of the person he or she wishes to simulate, and also refers to an interface means for exchanging information between the user and the system.

[1567] "Server" refers to the main computer system that receives, analyzes, and processes input data and emotion data from users.

[1568] An "emotion engine" refers to a system for detecting a user's emotions using means such as facial recognition, voice recognition, and text analysis.

[1569] "Means for extracting keywords" refers to means for performing natural language analysis on the data input by the user and extracting related keywords.

[1570] The "means for generating filter settings" refers to a means for setting content display rules based on the extracted keywords and emotion recognition results.

[1571] "Terminal" refers to a device operated by a user for displaying web content using filter settings received from a server.

[1572] The "content selection means" refers to a means for selecting content containing the latest information based on the extracted keywords and emotion recognition results.

[1573] "Natural language analysis means" refers to means for analyzing user input data and extracting keywords related to specific themes or interests.

[1574] A system for implementing the present invention provides personalized products and services based on emotions when a user is shopping in a virtual store.

[1575] The system mainly consists of the following components:

[1576] 1. Interface Method

[1577] It is a means for users to input the image of the person they want to simulate, and is installed as a text input field on the smartphone application screen.

[1578] 2. Emotion Engine

[1579] This is an engine for recognizing user emotions. This engine uses machine learning models such as TensorFlow to analyze emotions through facial recognition, voice recognition, and text analysis.

[1580] 3. Server

[1581] This is the main computer system that receives and analyzes the input data from the user (the person they want to simulate) and the emotion data obtained by the emotion engine. The server uses natural language processing (NLP) techniques, for example, the NLTK library, to extract relevant keywords.

[1582] 4. Filter Generation Method

[1583] This is a means for generating product and service suggestion filters based on the server-extracted keywords and emotion recognition results. The generated filter settings include product categories and display priorities.

[1584] 5. Terminal

[1585] This is a device operated by the user, such as a smartphone or tablet. The device retrieves and displays appropriate product information based on the filter settings received from the server.

[1586] The specific operation is as follows.

[1587] 1. The user enters "Female in her 20s" on the application screen. At this time, the emotion engine recognizes that the user is feeling "curiosity" based on their facial expression.

[1588] 2. The server receives the input data and emotion data, extracts keywords such as "fashion," "trends," and "cosmetics" through natural language analysis, and generates filter settings based on the emotion.

[1589] 3. The generated filter settings are sent to the device, which then uses them to display the latest trending products, related fashion items, cosmetic products, and more to the user.

[1590] This approach allows users to find the most relevant product information based on their emotions and interests, improving the user experience in virtual stores and providing a more engaging shopping experience.

[1591] Prompt Sentence Examples

[1592] "We want to build a product recommendation system that allows users to input the character they want to simulate and recognize emotions. The system will then recommend products based on the user's emotions. The following prompts will allow us to get suggested product information:

[1593] For example, if you are a woman in your 20s and your emotion is curiosity, search for product information using the keywords "fashion," "trends," and "cosmetics."

[1594] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1595] Step 1:

[1596] The user inputs the image of the person they want to simulate (e.g., "woman in her 20s") using the interface. At this time, the emotion engine analyzes the user's facial expressions and voice and recognizes the user's emotion (e.g., "curiosity").

[1597] Input: User's profile input data, user's face image or voice data

[1598] Output: User emotion recognition results, input person image data

[1599] Specific operation: Facial images are captured using a smartphone camera, and emotions are determined using a generative AI model such as TensorFlow.

[1600] Step 2:

[1601] The server receives input data from the user and emotion recognition results, and extracts related keywords using natural language analysis means.

[1602] Input: User's portrait input data and emotion recognition results received by the server

[1603] Output: Extracted keyword list

[1604] Specific operation: Natural language processing is performed using the NLTK library to extract keywords such as "fashion," "trends," and "cosmetics."

[1605] Step 3:

[1606] The server generates filter settings based on the extracted keywords and emotion recognition results, including product categories, display priorities, and latest information.

[1607] Input: Extracted keyword list, user emotion recognition results

[1608] Output: Filter setting data

[1609] What it does: Create filtering rules to set product categories and display priorities based on keywords and sentiment.

[1610] Step 4:

[1611] The server transmits the generated filter settings to the terminal, and the terminal receives them.

[1612] Input: Filter setting data

[1613] Output: Filter settings received by the device

[1614] Specific operation: Network communication is performed to send filter settings from the server to the smartphone.

[1615] Step 5:

[1616] The device retrieves relevant web content based on the received filter settings, and the retrieved content is optimized for the user according to the filter settings.

[1617] Input: Received filter settings

[1618] Output: Selected web content

[1619] What it does: Makes API calls to search and retrieve product information based on filter settings.

[1620] Step 6:

[1621] The terminal displays the acquired web content to the user, allowing the user to view personalized product information based on their emotions and interests.

[1622] Input: Selected web content

[1623] Output: Personalized product information displayed to the user

[1624] Specific operation: Update the UI to display product information on the smartphone screen.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1630] 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.

[1631] 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).

[1632] 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.

[1633] 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."

[1634] 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.

[1635] 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).

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] The following is further disclosed regarding the above embodiment.

[1647] (Claim 1)

[1648] an interface means for allowing a user to input a character image that the user wishes to simulate;

[1649] A means for the server to analyze the input from the user and extract related keywords;

[1650] a means for generating filter settings based on the extracted keywords by the server;

[1651] a means for retrieving and displaying web content based on the filter settings received by the terminal;

[1652] A system including:

[1653] (Claim 2)

[1654] 2. The system according to claim 1, further comprising means for selecting content containing the latest information based on the keywords extracted by the server.

[1655] (Claim 3)

[1656] 2. The system according to claim 1, further comprising a natural language analysis means for the server to extract words related to a particular theme or interest based on the image of a person the user wishes to simulate.

[1657] "Example 1"

[1658] (Claim 1)

[1659] an interface means for allowing a user to input a character image that the user wishes to simulate;

[1660] a server receiving an input from a user and extracting related keywords using natural language analysis means;

[1661] a means for the server to generate a filter configuration based on the extracted keywords;

[1662] means for applying the received filter settings to retrieve and display web content by the device;

[1663] A system including:

[1664] (Claim 2)

[1665] 2. The system of claim 1, further comprising means for the server to transmit generated filter settings based on the extracted keywords to the terminal as rules according to a specific theme or interest.

[1666] (Claim 3)

[1667] The system according to claim 1, further comprising a natural language analysis means for the server to automatically extract words related to specific themes or interests based on the image of the person the user wishes to simulate, and to set filters based on the extracted words.

[1668] "Application Example 1"

[1669] (Claim 1)

[1670] an interface means for allowing a user to input a character image that the user wishes to simulate;

[1671] A means for the server to analyze the input from the user and extract related keywords;

[1672] a means for generating filter settings based on the extracted keywords by the server;

[1673] a means for retrieving and displaying web content based on the filter settings received by the terminal;

[1674] A means for operating a smartphone application including a content acquisition means and a display means based on user input data;

[1675] A system including:

[1676] (Claim 2)

[1677] 2. The system according to claim 1, further comprising means for selecting content containing the latest information based on the keywords extracted by the server.

[1678] (Claim 3)

[1679] 2. The system according to claim 1, further comprising a natural language analysis means for the server to extract words related to a particular theme or interest based on the image of a person the user wishes to simulate.

[1680] "Example 2: Combining Emotion Engines"

[1681] (Claim 1)

[1682] an interface means for inputting a character image that the user wishes to simulate and for recognizing the user's emotions at the same time;

[1683] A means for the server to analyze input and emotion data from a user and extract related keywords;

[1684] means for generating filter settings based on the extracted keywords and emotion data by the server;

[1685] a means for retrieving and displaying web content based on the filter settings received by the terminal;

[1686] A system including:

[1687] (Claim 2)

[1688] 10. The system of claim 1, further comprising means for selecting content containing the most recent information based on the keywords and emotion data extracted by the server.

[1689] (Claim 3)

[1690] 2. The system according to claim 1, wherein the server includes natural language analysis means for extracting words related to a specific theme or interest based on the image of the person and emotion data input by the user that the user wishes to simulate.

[1691] "Application example 2 when combining emotion engines"

[1692] (Claim 1)

[1693] an interface means for allowing a user to input a character image that the user wishes to simulate;

[1694] The server has an emotion engine that recognizes the user's emotion, a means for analyzing the input from the user and extracting related keywords,

[1695] a means for generating filter settings based on the extracted keywords and emotion recognition results by the server;

[1696] a means for retrieving and displaying web content based on the filter settings received by the terminal;

[1697] A system including:

[1698] (Claim 2)

[1699] 10. The system according to claim 1, further comprising means for selecting content including the latest information based on the keywords and emotion recognition results extracted by the server.

[1700] (Claim 3)

[1701] 2. The system according to claim 1, wherein the server includes natural language analysis means for extracting words related to a specific theme or interest based on the image of the person and emotion data input by the user that the user wishes to simulate. [Explanation of symbols]

[1702] 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. an interface means for allowing a user to input a character image that the user wishes to simulate; A means for the server to analyze the input from the user and extract related keywords; a means for generating filter settings based on the extracted keywords by the server; a means for retrieving and displaying web content based on the filter settings received by the terminal; A system including:

2. 2. The system according to claim 1, further comprising means for selecting content containing the latest information based on the keywords extracted by the server.

3. 2. The system according to claim 1, further comprising a natural language analysis means for extracting words related to a particular theme or interest from the server based on the image of a person the user wishes to simulate.

Images