System

Abstract

A system is provided.SOLUTION: A system comprising: means for automatically collecting information about an election using selective artificial intelligence; means for analyzing the collected information and generating a concise summary; means for categorizing the analyzed information by candidates and policies and displaying the categorized information through a user interface; and means for responding in real-time to user questions received through the user interface.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] This invention aims to address the low voting participation rate and low interest in politics among young people. Specifically, it aims to address the problem of young people not participating in elections due to a lack of information about which candidates and policies to choose and a lack of interest in politics. Furthermore, it addresses the lack of a system that provides complex election-related information in an easy-to-understand manner and attracts interest. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by the following means. Specifically, it provides a system including: means for automatically collecting information about elections using generative artificial intelligence; means for analyzing the collected information and generating concise summaries; means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface; and means for responding in real time to user questions received through the user interface. Furthermore, it also adds means for automatically comparing and analyzing the policies of each candidate and political party using generative artificial intelligence and extracting their differences and characteristics, and means for generating explanatory text about the evaluation points and impact of each policy using expert generative artificial intelligence, thereby enabling users to easily understand and select candidates and policies.

[0006] "Generative AI" refers to AI that automatically collects and analyzes information from the Internet and generates summaries and explanations in natural language.

[0007] "User interface" refers to the screens and operating means that allow users to interact with the system.

[0008] "Policy comparison and analysis" refers to the process of comparing the policies of multiple candidates or political parties in detail and automatically extracting their differences and characteristics.

[0009] "Expert-generated AI" refers to AI that has the ability to generate expert commentary on the evaluation points and impacts of policies.

[0010] "Information collection methods" refers to technologies and processes that automatically collect election-related information from the Internet.

[0011] "Information analysis methods" refers to the techniques and processes for analyzing collected information and extracting and summarizing important points.

[0012] "Classification and organization methods" refers to the technology and processes that classify and organize analyzed information by candidate and policy, and store and display it in an easy-to-use format.

[0013] "Real-time response means" refers to the technology and processes used to provide immediate responses to user questions. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention is a system that utilizes generative artificial intelligence to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals, and helps users easily understand candidates and policies and make selections. A specific embodiment of this system and the processing of related programs are described below.

[0036] Server-side implementation

[0037] Information gathering

[0038] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[0039] Data analysis and formatting

[0040] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[0041] Data classification and organization

[0042] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[0043] Policy comparison / analysis

[0044] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[0045] Application of expert-generating AI

[0046] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0047] Terminal side embodiment

[0048] Information provision interface

[0049] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0050] Question and Answer Function

[0051] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[0052] User-Side Embodiment

[0053] Information search and browsing

[0054] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[0055] Providing Feedback

[0056] Users can provide feedback on the usefulness of the information, which is sent via the terminal to the server and used to improve the system.

[0057] Specific examples

[0058] Server side

[0059] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0060] Terminal side

[0061] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0062] User side

[0063] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if users provide feedback such as "This information was helpful," it will be sent to the server and used to improve the system.

[0064] In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[0065] The processing flow will be explained below.

[0066] Server-side processing

[0067] Step 1:

[0068] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[0069] Step 2:

[0070] The server stores collected data (articles, social media posts, official announcements, etc.) in a database, removing duplicate data and converting it into the appropriate format.

[0071] Step 3:

[0072] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[0073] Step 4:

[0074] The server categorizes and organizes the analyzed data by candidate and policy, allowing information to be systematically managed within the database.

[0075] Step 5:

[0076] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[0077] Step 6:

[0078] The server uses expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, providing users with a deeper understanding.

[0079] Terminal side processing

[0080] Step 1:

[0081] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[0082] Step 2:

[0083] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[0084] Step 3:

[0085] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[0086] User-side processing

[0087] Step 1:

[0088] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[0089] Step 2:

[0090] Users can use the provided features to read and compare information about candidates and policies, which helps them understand the differences between each candidate and their policies.

[0091] Step 3:

[0092] The user inputs a specific question through the terminal interface. For example, a question such as "Please tell me the details of Candidate A's economic policies" is possible.

[0093] Step 4:

[0094] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and this feedback is transmitted to the server via the terminal.

[0095] The above are the specific processing steps of this system.

[0096] Example 1

[0097] 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."

[0098] In modern elections, the amount of policy information on candidates and political parties is enormous, making it difficult for voters to quickly and accurately grasp and compare this information. Furthermore, detailed understanding of individual policies and comparisons between them require specialized knowledge, making it difficult for many voters to choose. Therefore, there is a need for a system that can help voters easily understand candidates and policies and make appropriate choices.

[0099] 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.

[0100] In this invention, the server includes means for automatically collecting election information using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and storing it in a database, means for providing a user interface for providing information to users, means for responding in real time to user questions received through the user interface, and means for collecting user feedback received through the user interface and using it to improve the system. This enables voters to quickly and accurately obtain election information, compare candidates and policies, and make appropriate choices.

[0101] "Generative AI" is an AI that can generate natural language based on large amounts of data and understand and respond like a human.

[0102] "Means of automatically collecting information" refers to a system that automatically obtains election-related information from the Internet using web crawlers, scraping tools, etc.

[0103] The "means for analyzing information and generating a concise summary" is a system that uses natural language processing technology to analyze collected information, extract important information, and summarize it concisely.

[0104] "Means of classifying and organizing information by candidate and policy and storing it in a database" refers to a system that classifies analyzed information according to specific criteria, organizes it systematically, and stores it.

[0105] "Means for providing a user interface for providing information to users" refers to a system that provides a screen and operation method that allows users to easily access and view information.

[0106] "Means for responding in real time to user questions received through a user interface" refers to a system in which the generating AI immediately responds to questions asked by the user through the interface.

[0107] "Means for collecting user feedback received through the user interface and using it to improve the system" refers to the process of collecting opinions and evaluations from users through the interface and using them to improve the system.

[0108] "Means to automatically compare and analyze the policies of each candidate and political party and extract their differences and characteristics" refers to a system that uses generative AI to compare the policy data of candidates and political parties and clarify their differences and characteristics.

[0109] The "means of generating explanatory text about the evaluation points and impacts of each policy" is a system that uses expert generation AI to automatically generate easy-to-understand explanatory text about the evaluation and impacts of each policy.

[0110] MODE FOR CARRYING OUT THE INVENTION

[0111] The present invention is a system that utilizes generative artificial intelligence (AI) to automatically collect and analyze election information and provide it to users. This system is realized through collaboration between a server and a terminal, and helps users easily understand candidates and policies and make appropriate choices. Specific embodiments are described in detail below.

[0112] Server-side implementation

[0113] Information gathering

[0114] The server automatically collects election-related information from designated official websites, news articles, and candidate social media sites. This process uses web crawling tools such as Beautiful Soup and Scrapy, which allow for regular and automatic collection of various information from the Internet.

[0115] The collected data is stored in a MySQL or PostgreSQL database, and duplicate data is removed or filtered out using SQL queries.

[0116] Data analysis and formatting

[0117] The server uses generative AI (such as OpenAI's GPT-4) to analyze the collected data, extract important information, and concisely summarize it. For example, it generates a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." The script for this is often implemented in Python.

[0118] Data classification and organization

[0119] The analyzed data is then categorized and organized by candidate and policy. This process uses data analysis libraries such as "Pandas" and "scikit-learn." The categorized data is then systematically stored in a database.

[0120] Policy comparison / analysis

[0121] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, and extract their differences and characteristics. For this analysis, prompts (e.g., "Please tell me about the differences in the economic policies of Candidate A and Candidate B") are executed on the server.

[0122] Application of expert-generating AI

[0123] The server also uses expert-generating AI (such as HuggingFace's BERT model) to generate detailed commentary on the evaluation points and impacts of each policy, providing users with detailed information based on expert knowledge.

[0124] Terminal side embodiment

[0125] Information provision interface

[0126] The terminal provides a user-friendly interface, built using React and Vue.js, that allows users to select candidates and policies that interest them and view detailed information.

[0127] Question and Answer Function

[0128] The device receives questions from the user via text or voice input and sends them to the server, which uses the Google Speech-to-Text API for voice input. The server's AI then responds in real time and provides information to the user via the device.

[0129] User-Side Embodiment

[0130] Information search and browsing

[0131] Users can use their devices to search for and view detailed information about candidates and policies by entering keywords in the search field, which instantly displays relevant information.

[0132] Providing Feedback

[0133] Users can provide feedback on the usefulness of the information, which is sent to the server via their device and used to improve the system.

[0134] Specific examples

[0135] For example, a server crawls "articles about Candidate A" from a news site and uses generation AI to generate a summary such as "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0136] When a user searches for "Candidate A's economic policies" on their device, this summary information is displayed. Also, if a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends the question to the server, and the AI ​​generator responds with, "Candidate A proposes tax increases and strengthens infrastructure investment. Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0137] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if the user provides feedback such as "This information was helpful," it is sent to the server and used to improve the system. In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Server-side processing

[0140] Step 1: Gather information

[0141] Input: The server receives the specified official website, news article, and social media URLs of the candidate.

[0142] Specific operation: The server uses Python's "Beautiful Soup" and "Scrapy" to crawl the web, retrieve HTML data from the specified URL, and extract the necessary text information.

[0143] Data processing: The extracted text data is converted into clean data by removing unnecessary tags and symbols.

[0144] Output: The clean data is stored in a MySQL or PostgreSQL database.

[0145] Step 2: Data analysis and formatting

[0146] Input: Get the clean data stored in the database.

[0147] How it works: The server sends clean data to a generative AI (e.g., OpenAI's GPT-4), which analyzes the text data, extracts important information, and summarizes it succinctly.

[0148] Data processing: The extracted summary data is further formatted and converted into a form that is easy for users to understand.

[0149] Output: The formatted summary data is saved back to the database.

[0150] Step 3: Classify and organize data

[0151] Input: Get the formatted summary data.

[0152] How it works: The server uses data analysis libraries such as "Pandas" and "scikit-learn" to categorize the summary data by candidate and policy.

[0153] Data processing: Classify data into specific categories (e.g., economic policy, environmental policy) and organize them systematically.

[0154] Output: The classified data is tagged with a classification tag and stored in a database.

[0155] Step 4: Policy comparison and analysis

[0156] Input: Get the classified data.

[0157] Specific operation: The server sends a prompt (e.g., "Please tell me about the differences in economic policies between candidate A and candidate B") to the generation AI, which then performs a comparison and analysis.

[0158] Data processing: Generative AI extracts differences and characteristics between policies and formats the results in an easy-to-understand format.

[0159] Output: The comparison and analysis results are stored in a database and provided to the user.

[0160] Step 5: Applying expert-generating AI

[0161] Input: Obtain the comparison and analysis results.

[0162] Specific operation: The server uses an expert generation AI (e.g., Hugging Face's BERT model) to generate detailed explanatory text about the evaluation points and impacts of each policy.

[0163] Data processing: The explanatory text is further formatted to translate the expert perspective into readable language.

[0164] Output: The explanatory text is stored in a database and provided to the user.

[0165] Terminal side processing

[0166] Step 1: Informational interface

[0167] Input: Receives a request for information from the user.

[0168] What it does: The device uses React and Vue.js to provide a user interface, displaying a search field and dashboard on the screen to allow users to easily access information.

[0169] Data processing: Sends a user request to the server and retrieves the relevant data.

[0170] Output: Display the retrieved information to the user.

[0171] Step 2: Question and Answer Function

[0172] Input: Receives the user's question in text or voice format.

[0173] How it works: Voice input is converted to text using the Google Speech-to-Text API. Text questions are sent directly to the server, where the server's AI generates responses in real time based on the questions.

[0174] Data processing: Retrieving the response from the server, formatting it, and converting it into something user-friendly.

[0175] Output: Display the response results on the terminal interface.

[0176] User-side processing

[0177] Step 1: Search and browse information

[0178] Input: The user enters a keyword into the search field on the device.

[0179] Specific operation: The device sends this request to the server and retrieves the relevant data.

[0180] Data processing: Display the acquired data to the user in an easy-to-understand format.

[0181] Output: Search results are displayed on the device screen.

[0182] Step 2: Provide feedback

[0183] Input: The user provides feedback on the usefulness of the information.

[0184] Specific operation: The device collects opinions and ratings from users through a feedback form and sends this feedback to the server.

[0185] Data processing: The server aggregates the collected feedback and uses it to improve the system.

[0186] Output: User feedback is saved in a database.

[0187] (Application example 1)

[0188] 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."

[0189] Conventional election information systems have had the problem of being unable to properly collect and analyze large amounts of information and provide it to users in an easy-to-understand manner. In particular, there was no means of providing interactive information to customers in physical stores, making it difficult to provide real-time questions and answers about election information. This has made it difficult for users to obtain the information they need to make appropriate choices.

[0190] 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.

[0191] In this invention, the server includes means for automatically collecting election-related information using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, and means for providing the information using an interactive device, thereby enabling users to receive a large amount of election information in a concise and easy-to-understand format and ask questions on the spot in real time.

[0192] "Generative artificial intelligence" refers to a system in general that collects information from the Internet and other sources, and automatically analyzes, summarizes, classifies, and generates responses.

[0193] "Means of automatically collecting information" refers to the process of crawling to obtain election-related data from online news articles, official websites, social media, etc.

[0194] "Means of analyzing information and generating concise summaries" refers to the process of analyzing collected data, extracting key information, and presenting it in a concise, easy-to-understand format.

[0195] "Means of categorizing and organizing by candidate and policy" refers to the process of systematically separating and storing analyzed and summarized information in association with specific candidates and policies.

[0196] "Means for responding in real time to user questions received through a user interface" refers to the process of processing a user's text or voice question and providing an immediate response using generative AI.

[0197] "Interactive devices" refer to robots and devices that are installed in brick-and-mortar stores and other locations and provide information to users in an interactive format.

[0198] This invention is a system for interactively providing election information to users, and is realized through the cooperation of the following server and interactive device (robot).

[0199] Server-side implementation

[0200] Information gathering methods

[0201] The server uses generative artificial intelligence (generative AI models) to automatically crawl election-related data from online news articles, official websites, and candidate social media. The data collected through the crawling is stored in a database, and duplicate data is removed.

[0202] Data analysis and summary generation methods

[0203] The server then uses a generative AI model to analyze the collected data, extracting key information and generating concise summaries. This analysis process organizes a large amount of information into an easy-to-understand format.

[0204] Data classification and organization methods

[0205] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[0206] Application methods of expert-generating AI

[0207] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0208] Interactive Device Side Embodiment

[0209] Information provision interface means

[0210] Interactive devices (e.g., interactive robots) provide a user-friendly interface, allowing visitors to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0211] Question and Answer Function Means

[0212] The interactive device receives questions from the user via text or voice input and sends them to the server. The server's generating AI responds in real time and provides the response to the user via the interactive device. Specific examples of prompt sentences include "Tell me about candidate A's economic policies" and "Compare candidate B's education policies with candidate A's education policies."

[0213] User-Side Embodiment

[0214] Information search and browsing

[0215] Users can use the interactive devices to search for and view detailed information about candidates and policies, and there is also the ability to compare specific candidates and policies, providing users with the information they need to make the right choice.

[0216] Providing Feedback

[0217] Users can provide feedback on the usefulness of the information, which is sent via the interactive device to the server and used to improve the system.

[0218] For example, if a user asks the robot, "Tell me about Candidate A's economic policies," the AI ​​will respond, "Candidate A proposes tax increases and seeks to strengthen infrastructure investment." This response is provided to the user via the robot.

[0219] This will create a system where customers can get detailed election information on the spot and receive support in making their own choices.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] The server crawls election-related data from news articles, official websites, and social media sites on the Internet. This process collects a large amount of election-related information into a database. The input is data from the Internet, and the output is the collected raw data.

[0223] Step 2:

[0224] The server analyzes the collected raw data using a generative AI model, extracts important information, and generates a concise summary. Specifically, the generative AI model identifies important parts of the text data and outputs them as a summary. The input is the raw data collected in step 1, and the output is the summarized text data.

[0225] Step 3:

[0226] The server processes the generated summary data by classifying and organizing it by candidate and policy. This allows it to be systematically stored in a database. The input is the summary data obtained in step 2, and the output is the classified and organized data.

[0227] Step 4:

[0228] The server uses an expert generation AI to generate detailed explanatory text about the evaluation points and impacts of each policy. The input is the data classified in step 3, and the output is explanatory text. Specifically, the expert generation AI analyzes the content of the policy and generates explanatory text about its benefits and impacts.

[0229] Step 5:

[0230] The interactive device provides a user-friendly interface, allowing users to access the information they need. Users can select candidates and policies that interest them and view detailed information. The input is the user's selection, and the output is the display of the relevant information.

[0231] Step 6:

[0232] The user inputs a question to the interactive device by text or voice. Specifically, the user inputs a question such as "Tell me about the economic policies of candidate A" into the interactive device. The input is the user's question, and the output is request data to the server with which the interactive device communicates.

[0233] Step 7:

[0234] The server uses the generative AI model to generate a response to the user's question in real time. The input is the request data sent in step 6, and the output is the generated response text. Specifically, the generative AI model analyzes the question content and generates the relevant information as a response text.

[0235] Step 8:

[0236] The interactive device displays or speaks the response sentence sent from the server to the user. The input is the response sentence generated in step 7, and the output is the provision of information to the user. Specifically, the interactive device displays the response sentence on a display or reads it out loud.

[0237] 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.

[0238] The present invention is a system that utilizes generative artificial intelligence and an emotion engine to automatically collect, analyze, and provide users with information about elections. This system is realized through the cooperation of a server and a terminal, and helps users easily understand candidates and policies and make selections. In addition, by combining it with an emotion engine, the system analyzes the user's emotional state and provides appropriate information based on that analysis. A specific embodiment of this system and the processing of the related programs are described below.

[0239] Server-side implementation

[0240] Information gathering

[0241] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[0242] Data analysis and formatting

[0243] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[0244] Data classification and organization

[0245] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this, and the information is systematically managed in a database.

[0246] Policy comparison / analysis

[0247] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[0248] Application of expert-generating AI

[0249] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0250] Terminal side embodiment

[0251] Information provision interface

[0252] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0253] Question and Answer Function

[0254] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[0255] Applying the Emotion Engine

[0256] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. This allows it to identify the user's emotional state and provide information according to their emotions.

[0257] User-Side Embodiment

[0258] Information search and browsing

[0259] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[0260] Providing Feedback

[0261] Users can input feedback about the usefulness of the information into the terminal to help improve the system, and this feedback is sent to the server via the terminal.

[0262] Specific examples

[0263] Server side

[0264] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0265] Terminal side

[0266] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0267] Applying the Emotion Engine

[0268] When a user expresses doubts or concerns about a particular candidate's policies, the emotion engine analyzes that emotional state and sends it to the server. Based on this, the generation AI generates more appropriate information and comforting messages to provide to the user. For example, if a user says, "I'm worried about this policy," the AI ​​can provide additional details such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and he has received a certain level of praise from economic experts."

[0269] In this way, the present invention helps users easily obtain and understand election information and make their own choices while receiving appropriate emotional support.

[0270] The processing flow will be explained below.

[0271] Server-side processing

[0272] Step 1:

[0273] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[0274] Step 2:

[0275] The server collects data (articles, social media posts, official announcements, etc.) and stores it in a database, removing duplicate data and converting it into the appropriate format.

[0276] Step 3:

[0277] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[0278] Step 4:

[0279] The server categorizes and organizes the analyzed data by candidate and policy, using a classification algorithm to ensure that information is systematically managed within the database.

[0280] Step 5:

[0281] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[0282] Step 6:

[0283] The server uses an expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, using expert knowledge to provide users with a deeper understanding.

[0284] Step 7:

[0285] The server analyzes the user's emotional state sent from the emotion engine and generates information and messages that best suit the user's emotions.

[0286] Terminal side processing

[0287] Step 1:

[0288] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[0289] Step 2:

[0290] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[0291] Step 3:

[0292] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[0293] Step 4:

[0294] The device identifies the user's emotional state using an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. The identified emotional state is sent to the server.

[0295] User-side processing

[0296] Step 1:

[0297] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[0298] Step 2:

[0299] Utilize features that allow users to read and compare information about candidates and policies, helping them understand the differences between each candidate and their policies.

[0300] Step 3:

[0301] The user inputs a specific question through the terminal interface. For example, they can ask, "Please tell me the details of Candidate A's economic policies."

[0302] Step 4:

[0303] When a user is viewing a particular piece of information, the emotion engine analyzes the user's emotional state in real time, for example, if the user is feeling anxious, it will provide supportive information or comforting messages accordingly.

[0304] Step 5:

[0305] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and the feedback is transmitted to the server via the terminal.

[0306] The above are the specific processing steps of this system.

[0307] Example 2

[0308] 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."

[0309] Conventional election information systems collect and analyze information manually, making it difficult to organize and provide data on a large number of candidates and policies in a timely manner. Furthermore, they lack the ability to respond instantly to user questions and are unable to provide information that takes into account the user's emotional state. Therefore, a new system was needed to help users quickly and accurately understand election information and select appropriate candidates and policies.

[0310] 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.

[0311] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and displaying it on a display device, means for responding in real time to user questions received through the display device, and means for using an emotion engine that analyzes the user's facial expressions and tone of voice to identify their emotional state. This makes it possible to efficiently collect and analyze a huge amount of information about elections, generate and provide summaries on the spot, and also provide appropriate information according to the user's emotional state.

[0312] "Generative AI" refers to AI that has the ability to automatically generate, analyze, and respond to information using natural language processing.

[0313] An "emotion engine" refers to a technology that analyzes emotions from a user's facial expressions, voice tone, and text input, and identifies their emotional state.

[0314] A "crawler" is a program that automatically collects data from the Internet.

[0315] A "summary" refers to text that has been created by generative artificial intelligence, extracting important information and summarizing it concisely.

[0316] "Classification and organization" refers to the process of systematically grouping and managing collected and analyzed information based on specific criteria.

[0317] "Display device" refers to a device that includes a display or screen through which a user visually views information.

[0318] "Responsive in real time" refers to the ability to generate a response and provide an answer immediately to input from a user.

[0319] "Candidate" means a person running for public office in an election.

[0320] "Policy" refers to the specific plans and guidelines that candidates and political parties propose and aim to implement.

[0321] "Expert-generated AI" refers to AI that has the ability to generate detailed explanations and evaluations based on expert knowledge in a specific field.

[0322] "Analysis" refers to the process of examining collected data in detail to determine its meaning and relevance.

[0323] This invention is a system that uses a generative AI model and an emotion engine to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals. Specific embodiments of this system are described below from the perspectives of hardware and software.

[0324] Server-side configuration

[0325] Information gathering

[0326] The server has the ability to automatically collect election-related data from the Internet. Specifically, it uses a crawler (for example, a web scraping tool such as BeautifulSoup or Scrapy) to crawl election-related articles from official websites, news articles, and candidate social media accounts. Crawling is performed periodically, and if new information is detected, it is stored in a database (for example, MySQL or PostgreSQL). At the same time, a data cleansing process is performed to remove duplicate data.

[0327] Data analysis and formatting

[0328] The server analyzes the collected data and generates summaries. It uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the collected articles in natural language. It uses the input prompt "Please generate a summary of this article" and stores the results in a database as a concise summary.

[0329] Data classification and organization

[0330] The server is equipped with algorithms that classify and organize the analyzed data based on specific criteria, for example, using clustering algorithms (e.g., K-means clustering) or Naive Bayes classifiers to systematically group the data by candidate and policy. This information is efficiently managed in a database.

[0331] Policy comparison / analysis

[0332] The server utilizes a generative AI model to compare and analyze the policies of each candidate and political party. Specifically, it uses the prompt "Please explain the differences between the economic policies of candidate A and candidate B," and stores the generated comparison results in a database in a user-friendly format.

[0333] Application of expert-generating AI

[0334] The server has the ability to generate detailed commentaries using an expert generation AI (e.g., a GPT-4 model with specialized knowledge). It uses a prompt such as, "Please explain in detail your evaluation of Candidate A's economic policies" to describe the evaluation points and impacts of each policy, and stores the resulting commentary in a database.

[0335] Terminal configuration

[0336] Information provision interface

[0337] The terminal provides a user-friendly interface, allowing users to easily access the election information they need. Using a display device such as a tablet or smartphone, users can view detailed information about the candidates and policies that interest them.

[0338] Question and Answer Function

[0339] The device has the ability to receive user questions via text or voice and send them to a server. When a user asks, "What is Candidate A's education policy?", the device sends this information to the server, and the generative AI model generates a response in real time and sends it back to the device.

[0340] Applying the Emotion Engine

[0341] The device is equipped with an emotion engine that analyzes the user's facial expressions and vocal tone to identify their emotional state. For example, it uses the Microsoft Azure Emotion API or Google Cloud Vision API to provide appropriate information based on the user's emotional state. If the user shows an anxious expression, the device sends this information to a server, and a generative AI model provides additional information according to the emotion.

[0342] User-side example

[0343] Information search and browsing

[0344] Users can use their devices to search for and view detailed information about candidates and policies. For example, by entering "Candidate A's latest economic policies," the device will display summary information retrieved from the server.

[0345] Providing Feedback

[0346] Users can input feedback about the usefulness of the information provided and contribute to improving the system. This feedback is sent to the server via the terminal and is reflected in future data analysis and information provision.

[0347] Specific operation example

[0348] 1. Server side: News sites are crawled and articles titled "Candidate A announces new economic policies" are automatically collected, and the generative AI model generates a summary such as "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." This information is then categorized and organized and stored in a database.

[0349] 2. Device side: When a user searches for "Candidate A's economic policies," this summary information is displayed. Furthermore, if the user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this question to the server, and the generative AI model responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This response is sent back to the device and displayed to the user.

[0350] 3. Application of emotion engine: When a user says, "I'm worried about this policy," the device analyzes their voice tone and facial expression to identify the anxiety and sends this information to the server. The generative AI model generates additional information, such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and has received a certain level of praise from economic experts," and sends it back to the device. This information is then presented to the user.

[0351] As a result, the present invention supports users in selecting candidates and policies by allowing them to easily obtain election information, understand it easily, and receive appropriate emotional support.

[0352] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0353] Step 1: Gather information

[0354] The server automatically collects election-related data from the Internet.

[0355] Input: URL of news site or social media

[0356] Specific operation: The server uses a crawler (e.g., BeautifulSoup or Scrapy) to crawl information from the specified URL. As a result of the crawling, HTML data is obtained.

[0357] Data processing: Parse the acquired HTML data and extract important text information.

[0358] Output: The extracted text information is stored in a database, while the duplicate data is removed.

[0359] Step 2: Data analysis and formatting

[0360] The server analyzes the collected information and generates a concise summary.

[0361] Input: Raw data (text information) stored in the database

[0362] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) and inputs the prompt "Generate a summary of this article" for the text information.

[0363] Data processing: The generative AI model analyzes the text information, extracts key points, and generates a summary.

[0364] Output: The generated summary is saved in the database.

[0365] Step 3: Classify and organize data

[0366] The server classifies and organizes the analyzed data by candidate and policy.

[0367] Input: Abstracts stored in the database

[0368] How it works: The server uses a clustering algorithm or a Naive Bayes classifier to classify the summaries by candidate and policy. For example, it assigns tags such as "Candidate A" and "Economic Policy" to the data.

[0369] Data processing: Organizing tagged data and classifying it into appropriate categories within the database.

[0370] Output: Classified and organized data is saved in a database.

[0371] Step 4: Policy comparison and analysis

[0372] The server automatically compares and analyzes the policies of candidates and political parties.

[0373] Input: Categorized and organized data (summaries of different candidates and policies)

[0374] Specific operation: The server uses the generative AI model to input the prompt sentence, "Please explain the difference between the economic policies of candidate A and candidate B."

[0375] Data processing: The generative AI model analyzes the policies being compared, extracts their differences and characteristics, and generates detailed comparison results.

[0376] Output: The generated comparison results are stored in a database.

[0377] Step 5: Applying expert-generating AI

[0378] The server generates explanatory text about the evaluation points and impact of each policy.

[0379] Input: Classified and organized data (summaries of candidates and policies) and comparison results

[0380] Specific operation: The server uses an expert generation AI and inputs the prompt "Please provide a detailed evaluation of Candidate A's economic policies."

[0381] Data processing: Expert generation AI generates detailed explanatory text.

[0382] Output: Save the generated commentary in the database.

[0383] Step 6: Informational interface

[0384] The terminal provides a user-friendly interface to display information to the user.

[0385] Input: Search keywords from the user

[0386] Specific operation: When a user inputs "Candidate A's economic policy" into the terminal, the terminal retrieves the corresponding summary, comparison results, and explanatory text from the database.

[0387] Data processing: Formatting the acquired information for display.

[0388] Output: Displaying formatted information to the user.

[0389] Step 7: Question and Answer Function

[0390] The terminal receives the user's question, transmits it to the server, and displays the response.

[0391] Input: User question (text or voice)

[0392] Specific operation: When a user asks, "What is the difference between the economic policies of candidate A and candidate B?", the device sends this information to the server. The server uses the generative AI model to input the prompt "Please explain the difference between the economic policies of candidate A and candidate B," and sends the generated response back to the device.

[0393] Data processing: Formatting the generated response text.

[0394] Output: Displays the formatted response text to the user.

[0395] Step 8: Applying the Emotion Engine

[0396] The terminal analyzes the user's emotional state and provides information according to the emotion.

[0397] Input: User's facial expressions and voice tone data

[0398] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice tone, and then uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze emotions and identify their emotional state.

[0399] Data processing: The identified emotional state is sent to the server, and the generative AI model generates additional information adapted to the emotion.

[0400] Output: Provides the user with any additional information generated.

[0401] (Application example 2)

[0402] 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."

[0403] Conventional systems focused on collecting and analyzing election-related information, displaying it through a user interface, and providing real-time responses. However, they did not provide appropriate information or recommend products based on the user's emotional state. This made it difficult for users to obtain information or products that matched their emotions. Furthermore, incorporating emotion analysis would enable more personalized services and is expected to improve the user experience.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0405] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, means for responding in real time to user questions received through the user interface, means for analyzing the user's emotional state using an emotion analysis engine and providing appropriate information based on the analysis, and means for generating product recommendations according to the user's emotional state. This makes it possible to provide information and recommend products that match the user's emotional state.

[0406] "Generative AI" is an advanced AI technology that can learn from vast amounts of data and generate sentences in natural language and perform predictive analysis.

[0407] "Means of automatically collecting information" refers to technologies such as crawlers and scrapers that automatically obtain publicly available information on the Internet and store it in a database.

[0408] The "means of analyzing information and generating a concise summary" is a generative AI algorithm that extracts key points from collected information and summarizes them in short sentences.

[0409] "Means of classifying, organizing, and displaying through a user interface" refers to a technology that divides analyzed information into specific categories and displays them in an interface that is easy for users to use.

[0410] "Real-time response means" refers to a natural language processing system and generative AI that can instantly respond to user questions and requests.

[0411] An "emotion analysis engine" is a machine learning technology that analyzes a user's facial expressions, voice, text input, etc. to identify their emotional state.

[0412] "Means of analyzing the user's emotional state and providing appropriate information based on that" refers to a generative AI that identifies and provides the information the user needs at that time based on the analyzed emotional data.

[0413] The "means for generating product recommendations" is a recommendation engine that selects and suggests products that are likely to be beneficial to a user based on the user's emotions and past purchasing history.

[0414] This invention is a system that combines generative artificial intelligence and an emotion analysis engine to automatically collect, analyze, and provide election information to users. As an example of its application to an online shopping site, we will explain an application that recommends products based on the user's emotional state.

[0415] Server-side implementation

[0416] Information gathering

[0417] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, social media, etc. The collected data is stored in a database, and duplicate data is removed through analysis.

[0418] Data analysis and formatting

[0419] The server then uses a generative AI (e.g., GPT-4) to analyze the collected data, extract key information, and generate a concise summary in natural language. The analysis process utilizes machine learning algorithms to format the data in an easy-to-understand format.

[0420] Data classification and organization

[0421] The analyzed data is classified and organized by candidate, policy, and product category, and the server uses classification algorithms (e.g., K-means clustering) to systematically manage the information within the database.

[0422] Policy comparison / analysis

[0423] Generative AI is used to automatically compare and analyze the policies and product features of candidates and political parties, extracting their differences and distinctive features. The results of this analysis are presented in a format that is easy for users to understand.

[0424] Sentiment analysis and information provision

[0425] The user's facial expressions, voice tone, text input, etc. are analyzed using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to evaluate the user's emotional state. The emotion analysis results are sent to a generative AI, which generates information and product recommendations based on the user's emotions.

[0426] User Interface Embodiments

[0427] Information provision interface

[0428] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can search for information about candidates, policies, and products, and view the information they are interested in in detail.

[0429] Question and Answer Function

[0430] When a user inputs a question via text or voice through the device, it is sent to the server in real time, and the generative AI generates an appropriate answer to the question and displays it to the user through the device.

[0431] Emotion-based recommendations

[0432] Once the user's emotional state is analyzed, products and information tailored to that state are automatically recommended. For example, if you are feeling depressed, products with a relaxing effect will be recommended.

[0433] Specific examples

[0434] Election information provision scenario

[0435] The server automatically collects election-related articles from news sites using a crawler, and the AI ​​generator generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies." This information is stored in a database.

[0436] Recommendation function scenario for online shopping site

[0437] While a user is browsing an online shopping site through smart glasses, emotion analysis is performed. If the user is found to be depressed, products such as "relaxing aroma diffusers" are recommended in real time.

[0438] Example prompt sentences to use

[0439] "The user's emotional state is depressed. Please provide a natural-language summary of relaxation products that fit this emotion. Please include specific product names and features."

[0440] In this way, the present invention provides a system that allows users to easily obtain election information and receive product recommendations that match their emotional state.

[0441] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0442] Step 1:

[0443] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, and social media. Specifically, the crawler periodically visits each website, detecting and retrieving new articles and posts. This allows the server to collect the latest election information, product reviews, and more. The input data is text information retrieved from each website, and the output is stored in a database as collected raw data.

[0444] Step 2:

[0445] The server analyzes the collected raw data using a generative AI (e.g., GPT-4), extracts important information, and generates a concise summary. In this step, a machine learning algorithm is used to input text data and output key points such as summaries and headlines. Specifically, the generative AI analyzes the text data and generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies."

[0446] Step 3:

[0447] The server then classifies and organizes the generated summary data by candidate, policy, or product category. Using a classification algorithm (e.g., K-means clustering), it assigns each data point to the appropriate category. The input data is the summarized text, and the output is data organized by category. This step ensures that the information is managed systematically and can be easily searched by users.

[0448] Step 4:

[0449] The server uses generative AI to automatically compare and analyze the characteristics of the policies and products of each candidate and political party, extracting their differences and characteristics. Specifically, it compares candidates such as "Candidate A proposes tax increases and strengthens infrastructure investment" with "Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." In this process, the input data is summary information about each candidate, and the output is the compared and analyzed text.

[0450] Step 5:

[0451] When a user inputs a question via text or voice through their device, the question is sent to the server in real time. The server's generation AI generates an appropriate answer to the question and returns the answer to the device. The input data is the user's question, and the output data is the answer generated by the generation AI. Specifically, it returns detailed comparison results in response to a question such as, "Please tell me about the differences in economic policies between candidate A and candidate B."

[0452] Step 6:

[0453] The emotion analysis engine (e.g., Microsoft Azure Emotion API) analyzes the user's facial expressions, voice tone, text input, etc. to evaluate the user's emotional state. The input in this step is facial expression and voice data obtained from the user's camera and microphone, and the output is analyzed emotional information. Based on the analysis results, the generative AI provides information corresponding to the user's emotions.

[0454] Step 7:

[0455] Based on the user's emotional state, the results of the emotion analysis are sent to a generation AI, which then generates product and information recommendations tailored to the user's state. The input data is the emotion analysis results, and the output data is product recommendations optimal for the user. Specifically, if the emotion analysis reveals that the user is in a depressed state, the system will recommend an "aroma diffuser with a relaxing effect."

[0456] In this way, a system is realized in which the server and terminal cooperate to recommend optimal information and products to the user.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] [Second embodiment]

[0461] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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).

[0467] 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.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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."

[0473] The present invention is a system that utilizes generative artificial intelligence to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals, and helps users easily understand candidates and policies and make selections. A specific embodiment of this system and the processing of related programs are described below.

[0474] Server-side implementation

[0475] Information gathering

[0476] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[0477] Data analysis and formatting

[0478] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[0479] Data classification and organization

[0480] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[0481] Policy comparison / analysis

[0482] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[0483] Application of expert-generating AI

[0484] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0485] Terminal side embodiment

[0486] Information provision interface

[0487] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0488] Question and Answer Function

[0489] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[0490] User-Side Embodiment

[0491] Information search and browsing

[0492] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[0493] Providing Feedback

[0494] Users can provide feedback on the usefulness of the information, which is sent via the terminal to the server and used to improve the system.

[0495] Specific examples

[0496] Server side

[0497] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0498] Terminal side

[0499] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0500] User side

[0501] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if users provide feedback such as "This information was helpful," it will be sent to the server and used to improve the system.

[0502] In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[0503] The processing flow will be explained below.

[0504] Server-side processing

[0505] Step 1:

[0506] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[0507] Step 2:

[0508] The server stores collected data (articles, social media posts, official announcements, etc.) in a database, removing duplicate data and converting it into the appropriate format.

[0509] Step 3:

[0510] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[0511] Step 4:

[0512] The server categorizes and organizes the analyzed data by candidate and policy, allowing information to be systematically managed within the database.

[0513] Step 5:

[0514] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[0515] Step 6:

[0516] The server uses expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, providing users with a deeper understanding.

[0517] Terminal side processing

[0518] Step 1:

[0519] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[0520] Step 2:

[0521] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[0522] Step 3:

[0523] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[0524] User-side processing

[0525] Step 1:

[0526] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[0527] Step 2:

[0528] Users can use the provided features to read and compare information about candidates and policies, which helps them understand the differences between each candidate and their policies.

[0529] Step 3:

[0530] The user inputs a specific question through the terminal interface. For example, a question such as "Please tell me the details of Candidate A's economic policies" is possible.

[0531] Step 4:

[0532] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and this feedback is transmitted to the server via the terminal.

[0533] The above are the specific processing steps of this system.

[0534] Example 1

[0535] 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."

[0536] In modern elections, the amount of policy information on candidates and political parties is enormous, making it difficult for voters to quickly and accurately grasp and compare this information. Furthermore, detailed understanding of individual policies and comparisons between them require specialized knowledge, making it difficult for many voters to choose. Therefore, there is a need for a system that can help voters easily understand candidates and policies and make appropriate choices.

[0537] 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.

[0538] In this invention, the server includes means for automatically collecting election information using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and storing it in a database, means for providing a user interface for providing information to users, means for responding in real time to user questions received through the user interface, and means for collecting user feedback received through the user interface and using it to improve the system. This enables voters to quickly and accurately obtain election information, compare candidates and policies, and make appropriate choices.

[0539] "Generative AI" is an AI that can generate natural language based on large amounts of data and understand and respond like a human.

[0540] "Means of automatically collecting information" refers to a system that automatically obtains election-related information from the Internet using web crawlers, scraping tools, etc.

[0541] The "means for analyzing information and generating a concise summary" is a system that uses natural language processing technology to analyze collected information, extract important information, and summarize it concisely.

[0542] "Means of classifying and organizing information by candidate and policy and storing it in a database" refers to a system that classifies analyzed information according to specific criteria, organizes it systematically, and stores it.

[0543] "Means for providing a user interface for providing information to users" refers to a system that provides a screen and operation method that allows users to easily access and view information.

[0544] "Means for responding in real time to user questions received through a user interface" refers to a system in which the generating AI immediately responds to questions asked by the user through the interface.

[0545] "Means for collecting user feedback received through the user interface and using it to improve the system" refers to the process of collecting opinions and evaluations from users through the interface and using them to improve the system.

[0546] "Means to automatically compare and analyze the policies of each candidate and political party and extract their differences and characteristics" refers to a system that uses generative AI to compare the policy data of candidates and political parties and clarify their differences and characteristics.

[0547] The "means of generating explanatory text about the evaluation points and impacts of each policy" is a system that uses expert generation AI to automatically generate easy-to-understand explanatory text about the evaluation and impacts of each policy.

[0548] MODE FOR CARRYING OUT THE INVENTION

[0549] The present invention is a system that utilizes generative artificial intelligence (AI) to automatically collect and analyze election information and provide it to users. This system is realized through collaboration between a server and a terminal, and helps users easily understand candidates and policies and make appropriate choices. Specific embodiments are described in detail below.

[0550] Server-side implementation

[0551] Information gathering

[0552] The server automatically collects election-related information from designated official websites, news articles, and candidate social media sites. This process uses web crawling tools such as Beautiful Soup and Scrapy, which allow for regular and automatic collection of various information from the Internet.

[0553] The collected data is stored in a MySQL or PostgreSQL database, and duplicate data is removed or filtered out using SQL queries.

[0554] Data analysis and formatting

[0555] The server uses generative AI (such as OpenAI's GPT-4) to analyze the collected data, extract important information, and concisely summarize it. For example, it generates a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." The script for this is often implemented in Python.

[0556] Data classification and organization

[0557] The analyzed data is then categorized and organized by candidate and policy. This process uses data analysis libraries such as "Pandas" and "scikit-learn." The categorized data is then systematically stored in a database.

[0558] Policy comparison / analysis

[0559] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, and extract their differences and characteristics. For this analysis, prompts (e.g., "Please tell me about the differences in the economic policies of Candidate A and Candidate B") are executed on the server.

[0560] Application of expert-generating AI

[0561] The server also uses expert-generating AI (such as HuggingFace's BERT model) to generate detailed commentary on the evaluation points and impacts of each policy, providing users with detailed information based on expert knowledge.

[0562] Terminal side embodiment

[0563] Information provision interface

[0564] The terminal provides a user-friendly interface, built using React and Vue.js, that allows users to select candidates and policies that interest them and view detailed information.

[0565] Question and Answer Function

[0566] The device receives questions from the user via text or voice input and sends them to the server, which uses the Google Speech-to-Text API for voice input. The server's AI then responds in real time and provides information to the user via the device.

[0567] User-Side Embodiment

[0568] Information search and browsing

[0569] Users can use their devices to search for and view detailed information about candidates and policies by entering keywords in the search field, which instantly displays relevant information.

[0570] Providing Feedback

[0571] Users can provide feedback on the usefulness of the information, which is sent to the server via their device and used to improve the system.

[0572] Specific examples

[0573] For example, a server crawls "articles about Candidate A" from a news site and uses generation AI to generate a summary such as "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0574] When a user searches for "Candidate A's economic policies" on their device, this summary information is displayed. Also, if a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends the question to the server, and the AI ​​generator responds with, "Candidate A proposes tax increases and strengthens infrastructure investment. Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0575] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if the user provides feedback such as "This information was helpful," it is sent to the server and used to improve the system. In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[0576] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0577] Server-side processing

[0578] Step 1: Gather information

[0579] Input: The server receives the specified official website, news article, and social media URLs of the candidate.

[0580] Specific operation: The server uses Python's "Beautiful Soup" and "Scrapy" to crawl the web, retrieve HTML data from the specified URL, and extract the necessary text information.

[0581] Data processing: The extracted text data is converted into clean data by removing unnecessary tags and symbols.

[0582] Output: The clean data is stored in a MySQL or PostgreSQL database.

[0583] Step 2: Data analysis and formatting

[0584] Input: Get the clean data stored in the database.

[0585] How it works: The server sends clean data to a generative AI (e.g., OpenAI's GPT-4), which analyzes the text data, extracts important information, and summarizes it succinctly.

[0586] Data processing: The extracted summary data is further formatted and converted into a form that is easy for users to understand.

[0587] Output: The formatted summary data is saved back to the database.

[0588] Step 3: Classify and organize data

[0589] Input: Get the formatted summary data.

[0590] How it works: The server uses data analysis libraries such as "Pandas" and "scikit-learn" to categorize the summary data by candidate and policy.

[0591] Data processing: Classify data into specific categories (e.g., economic policy, environmental policy) and organize them systematically.

[0592] Output: The classified data is tagged with a classification tag and stored in a database.

[0593] Step 4: Policy comparison and analysis

[0594] Input: Get the classified data.

[0595] Specific operation: The server sends a prompt (e.g., "Please tell me about the differences in economic policies between candidate A and candidate B") to the generation AI, which then performs a comparison and analysis.

[0596] Data processing: Generative AI extracts differences and characteristics between policies and formats the results in an easy-to-understand format.

[0597] Output: The comparison and analysis results are stored in a database and provided to the user.

[0598] Step 5: Applying expert-generating AI

[0599] Input: Obtain the comparison and analysis results.

[0600] Specific operation: The server uses an expert generation AI (e.g., Hugging Face's BERT model) to generate detailed explanatory text about the evaluation points and impacts of each policy.

[0601] Data processing: The explanatory text is further formatted to translate the expert perspective into readable language.

[0602] Output: The explanatory text is stored in a database and provided to the user.

[0603] Terminal side processing

[0604] Step 1: Informational interface

[0605] Input: Receives a request for information from the user.

[0606] What it does: The device uses React and Vue.js to provide a user interface, displaying a search field and dashboard on the screen to allow users to easily access information.

[0607] Data processing: Sends a user request to the server and retrieves the relevant data.

[0608] Output: Display the retrieved information to the user.

[0609] Step 2: Question and Answer Function

[0610] Input: Receives the user's question in text or voice format.

[0611] How it works: Voice input is converted to text using the Google Speech-to-Text API. Text questions are sent directly to the server, where the server's AI generates responses in real time based on the questions.

[0612] Data processing: Retrieving the response from the server, formatting it, and converting it into something user-friendly.

[0613] Output: Display the response results on the terminal interface.

[0614] User-side processing

[0615] Step 1: Search and browse information

[0616] Input: The user enters a keyword into the search field on the device.

[0617] Specific operation: The device sends this request to the server and retrieves the relevant data.

[0618] Data processing: Display the acquired data to the user in an easy-to-understand format.

[0619] Output: Search results are displayed on the device screen.

[0620] Step 2: Provide feedback

[0621] Input: The user provides feedback on the usefulness of the information.

[0622] Specific operation: The device collects opinions and ratings from users through a feedback form and sends this feedback to the server.

[0623] Data processing: The server aggregates the collected feedback and uses it to improve the system.

[0624] Output: User feedback is saved in a database.

[0625] (Application example 1)

[0626] 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."

[0627] Conventional election information systems have had the problem of being unable to properly collect and analyze large amounts of information and provide it to users in an easy-to-understand manner. In particular, there was no means of providing interactive information to customers in physical stores, making it difficult to provide real-time questions and answers about election information. This has made it difficult for users to obtain the information they need to make appropriate choices.

[0628] 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.

[0629] In this invention, the server includes means for automatically collecting election-related information using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, and means for providing the information using an interactive device, thereby enabling users to receive a large amount of election information in a concise and easy-to-understand format and ask questions on the spot in real time.

[0630] "Generative artificial intelligence" refers to a system in general that collects information from the Internet and other sources, and automatically analyzes, summarizes, classifies, and generates responses.

[0631] "Means of automatically collecting information" refers to the process of crawling to obtain election-related data from online news articles, official websites, social media, etc.

[0632] "Means of analyzing information and generating concise summaries" refers to the process of analyzing collected data, extracting key information, and presenting it in a concise, easy-to-understand format.

[0633] "Means of categorizing and organizing by candidate and policy" refers to the process of systematically separating and storing analyzed and summarized information in association with specific candidates and policies.

[0634] "Means for responding in real time to user questions received through a user interface" refers to the process of processing a user's text or voice question and providing an immediate response using generative AI.

[0635] "Interactive devices" refer to robots and devices that are installed in brick-and-mortar stores and other locations and provide information to users in an interactive format.

[0636] This invention is a system for interactively providing election information to users, and is realized through the cooperation of the following server and interactive device (robot).

[0637] Server-side implementation

[0638] Information gathering methods

[0639] The server uses generative artificial intelligence (generative AI models) to automatically crawl election-related data from online news articles, official websites, and candidate social media. The data collected through the crawling is stored in a database, and duplicate data is removed.

[0640] Data analysis and summary generation methods

[0641] The server then uses a generative AI model to analyze the collected data, extracting key information and generating concise summaries. This analysis process organizes a large amount of information into an easy-to-understand format.

[0642] Data classification and organization methods

[0643] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[0644] Application methods of expert-generating AI

[0645] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0646] Interactive Device Side Embodiment

[0647] Information provision interface means

[0648] Interactive devices (e.g., interactive robots) provide a user-friendly interface, allowing visitors to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0649] Question and Answer Function Means

[0650] The interactive device receives questions from the user via text or voice input and sends them to the server. The server's generating AI responds in real time and provides the response to the user via the interactive device. Specific examples of prompt sentences include "Tell me about candidate A's economic policies" and "Compare candidate B's education policies with candidate A's education policies."

[0651] User-Side Embodiment

[0652] Information search and browsing

[0653] Users can use the interactive devices to search for and view detailed information about candidates and policies, and there is also the ability to compare specific candidates and policies, providing users with the information they need to make the right choice.

[0654] Providing Feedback

[0655] Users can provide feedback on the usefulness of the information, which is sent via the interactive device to the server and used to improve the system.

[0656] For example, if a user asks the robot, "Tell me about Candidate A's economic policies," the AI ​​will respond, "Candidate A proposes tax increases and seeks to strengthen infrastructure investment." This response is provided to the user via the robot.

[0657] This will create a system where customers can get detailed election information on the spot and receive support in making their own choices.

[0658] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0659] Step 1:

[0660] The server crawls election-related data from news articles, official websites, and social media sites on the Internet. This process collects a large amount of election-related information into a database. The input is data from the Internet, and the output is the collected raw data.

[0661] Step 2:

[0662] The server analyzes the collected raw data using a generative AI model, extracts important information, and generates a concise summary. Specifically, the generative AI model identifies important parts of the text data and outputs them as a summary. The input is the raw data collected in step 1, and the output is the summarized text data.

[0663] Step 3:

[0664] The server processes the generated summary data by classifying and organizing it by candidate and policy. This allows it to be systematically stored in a database. The input is the summary data obtained in step 2, and the output is the classified and organized data.

[0665] Step 4:

[0666] The server uses an expert generation AI to generate detailed explanatory text about the evaluation points and impacts of each policy. The input is the data classified in step 3, and the output is explanatory text. Specifically, the expert generation AI analyzes the content of the policy and generates explanatory text about its benefits and impacts.

[0667] Step 5:

[0668] The interactive device provides a user-friendly interface, allowing users to access the information they need. Users can select candidates and policies that interest them and view detailed information. The input is the user's selection, and the output is the display of the relevant information.

[0669] Step 6:

[0670] The user inputs a question to the interactive device by text or voice. Specifically, the user inputs a question such as "Tell me about the economic policies of candidate A" into the interactive device. The input is the user's question, and the output is request data to the server with which the interactive device communicates.

[0671] Step 7:

[0672] The server uses the generative AI model to generate a response to the user's question in real time. The input is the request data sent in step 6, and the output is the generated response text. Specifically, the generative AI model analyzes the question content and generates the relevant information as a response text.

[0673] Step 8:

[0674] The interactive device displays or speaks the response sentence sent from the server to the user. The input is the response sentence generated in step 7, and the output is the provision of information to the user. Specifically, the interactive device displays the response sentence on a display or reads it out loud.

[0675] 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.

[0676] The present invention is a system that utilizes generative artificial intelligence and an emotion engine to automatically collect, analyze, and provide users with information about elections. This system is realized through the cooperation of a server and a terminal, and helps users easily understand candidates and policies and make selections. In addition, by combining it with an emotion engine, the system analyzes the user's emotional state and provides appropriate information based on that analysis. A specific embodiment of this system and the processing of the related programs are described below.

[0677] Server-side implementation

[0678] Information gathering

[0679] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[0680] Data analysis and formatting

[0681] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[0682] Data classification and organization

[0683] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this, and the information is systematically managed in a database.

[0684] Policy comparison / analysis

[0685] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[0686] Application of expert-generating AI

[0687] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0688] Terminal side embodiment

[0689] Information provision interface

[0690] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0691] Question and Answer Function

[0692] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[0693] Applying the Emotion Engine

[0694] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. This allows it to identify the user's emotional state and provide information according to their emotions.

[0695] User-Side Embodiment

[0696] Information search and browsing

[0697] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[0698] Providing Feedback

[0699] Users can input feedback about the usefulness of the information into the terminal to help improve the system, and this feedback is sent to the server via the terminal.

[0700] Specific examples

[0701] Server side

[0702] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0703] Terminal side

[0704] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0705] Applying the Emotion Engine

[0706] When a user expresses doubts or concerns about a particular candidate's policies, the emotion engine analyzes that emotional state and sends it to the server. Based on this, the generation AI generates more appropriate information and comforting messages to provide to the user. For example, if a user says, "I'm worried about this policy," the AI ​​can provide additional details such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and he has received a certain level of praise from economic experts."

[0707] In this way, the present invention helps users easily obtain and understand election information and make their own choices while receiving appropriate emotional support.

[0708] The processing flow will be explained below.

[0709] Server-side processing

[0710] Step 1:

[0711] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[0712] Step 2:

[0713] The server collects data (articles, social media posts, official announcements, etc.) and stores it in a database, removing duplicate data and converting it into the appropriate format.

[0714] Step 3:

[0715] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[0716] Step 4:

[0717] The server categorizes and organizes the analyzed data by candidate and policy, using a classification algorithm to ensure that information is systematically managed within the database.

[0718] Step 5:

[0719] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[0720] Step 6:

[0721] The server uses an expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, using expert knowledge to provide users with a deeper understanding.

[0722] Step 7:

[0723] The server analyzes the user's emotional state sent from the emotion engine and generates information and messages that best suit the user's emotions.

[0724] Terminal side processing

[0725] Step 1:

[0726] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[0727] Step 2:

[0728] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[0729] Step 3:

[0730] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[0731] Step 4:

[0732] The device identifies the user's emotional state using an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. The identified emotional state is sent to the server.

[0733] User-side processing

[0734] Step 1:

[0735] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[0736] Step 2:

[0737] Utilize features that allow users to read and compare information about candidates and policies, helping them understand the differences between each candidate and their policies.

[0738] Step 3:

[0739] The user inputs a specific question through the terminal interface. For example, they can ask, "Please tell me the details of Candidate A's economic policies."

[0740] Step 4:

[0741] When a user is viewing a particular piece of information, the emotion engine analyzes the user's emotional state in real time, for example, if the user is feeling anxious, it will provide supportive information or comforting messages accordingly.

[0742] Step 5:

[0743] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and the feedback is transmitted to the server via the terminal.

[0744] The above are the specific processing steps of this system.

[0745] Example 2

[0746] 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."

[0747] Conventional election information systems collect and analyze information manually, making it difficult to organize and provide data on a large number of candidates and policies in a timely manner. Furthermore, they lack the ability to respond instantly to user questions and are unable to provide information that takes into account the user's emotional state. Therefore, a new system was needed to help users quickly and accurately understand election information and select appropriate candidates and policies.

[0748] 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.

[0749] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and displaying it on a display device, means for responding in real time to user questions received through the display device, and means for using an emotion engine that analyzes the user's facial expressions and tone of voice to identify their emotional state. This makes it possible to efficiently collect and analyze a huge amount of information about elections, generate and provide summaries on the spot, and also provide appropriate information according to the user's emotional state.

[0750] "Generative AI" refers to AI that has the ability to automatically generate, analyze, and respond to information using natural language processing.

[0751] An "emotion engine" refers to a technology that analyzes emotions from a user's facial expressions, voice tone, and text input, and identifies their emotional state.

[0752] A "crawler" is a program that automatically collects data from the Internet.

[0753] A "summary" refers to text that has been created by generative artificial intelligence, extracting important information and summarizing it concisely.

[0754] "Classification and organization" refers to the process of systematically grouping and managing collected and analyzed information based on specific criteria.

[0755] "Display device" refers to a device that includes a display or screen through which a user visually views information.

[0756] "Responsive in real time" refers to the ability to generate a response and provide an answer immediately to input from a user.

[0757] "Candidate" means a person running for public office in an election.

[0758] "Policy" refers to the specific plans and guidelines that candidates and political parties propose and aim to implement.

[0759] "Expert-generated AI" refers to AI that has the ability to generate detailed explanations and evaluations based on expert knowledge in a specific field.

[0760] "Analysis" refers to the process of examining collected data in detail to determine its meaning and relevance.

[0761] This invention is a system that uses a generative AI model and an emotion engine to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals. Specific embodiments of this system are described below from the perspectives of hardware and software.

[0762] Server-side configuration

[0763] Information gathering

[0764] The server has the ability to automatically collect election-related data from the Internet. Specifically, it uses a crawler (for example, a web scraping tool such as BeautifulSoup or Scrapy) to crawl election-related articles from official websites, news articles, and candidate social media accounts. Crawling is performed periodically, and if new information is detected, it is stored in a database (for example, MySQL or PostgreSQL). At the same time, a data cleansing process is performed to remove duplicate data.

[0765] Data analysis and formatting

[0766] The server analyzes the collected data and generates summaries. It uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the collected articles in natural language. It uses the input prompt "Please generate a summary of this article" and stores the results in a database as a concise summary.

[0767] Data classification and organization

[0768] The server is equipped with algorithms that classify and organize the analyzed data based on specific criteria, for example, using clustering algorithms (e.g., K-means clustering) or Naive Bayes classifiers to systematically group the data by candidate and policy. This information is efficiently managed in a database.

[0769] Policy comparison / analysis

[0770] The server utilizes a generative AI model to compare and analyze the policies of each candidate and political party. Specifically, it uses the prompt "Please explain the differences between the economic policies of candidate A and candidate B," and stores the generated comparison results in a database in a user-friendly format.

[0771] Application of expert-generating AI

[0772] The server has the ability to generate detailed commentaries using an expert generation AI (e.g., a GPT-4 model with specialized knowledge). It uses a prompt such as, "Please explain in detail your evaluation of Candidate A's economic policies" to describe the evaluation points and impacts of each policy, and stores the resulting commentary in a database.

[0773] Terminal configuration

[0774] Information provision interface

[0775] The terminal provides a user-friendly interface, allowing users to easily access the election information they need. Using a display device such as a tablet or smartphone, users can view detailed information about the candidates and policies that interest them.

[0776] Question and Answer Function

[0777] The device has the ability to receive user questions via text or voice and send them to a server. When a user asks, "What is Candidate A's education policy?", the device sends this information to the server, and the generative AI model generates a response in real time and sends it back to the device.

[0778] Applying the Emotion Engine

[0779] The device is equipped with an emotion engine that analyzes the user's facial expressions and vocal tone to identify their emotional state. For example, it uses the Microsoft Azure Emotion API or Google Cloud Vision API to provide appropriate information based on the user's emotional state. If the user shows an anxious expression, the device sends this information to a server, and a generative AI model provides additional information according to the emotion.

[0780] User-side example

[0781] Information search and browsing

[0782] Users can use their devices to search for and view detailed information about candidates and policies. For example, by entering "Candidate A's latest economic policies," the device will display summary information retrieved from the server.

[0783] Providing Feedback

[0784] Users can input feedback about the usefulness of the information provided and contribute to improving the system. This feedback is sent to the server via the terminal and is reflected in future data analysis and information provision.

[0785] Specific operation example

[0786] 1. Server side: News sites are crawled and articles titled "Candidate A announces new economic policies" are automatically collected, and the generative AI model generates a summary such as "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." This information is then categorized and organized and stored in a database.

[0787] 2. Device side: When a user searches for "Candidate A's economic policies," this summary information is displayed. Furthermore, if the user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this question to the server, and the generative AI model responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This response is sent back to the device and displayed to the user.

[0788] 3. Application of emotion engine: When a user says, "I'm worried about this policy," the device analyzes their voice tone and facial expression to identify the anxiety and sends this information to the server. The generative AI model generates additional information, such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and has received a certain level of praise from economic experts," and sends it back to the device. This information is then presented to the user.

[0789] As a result, the present invention supports users in selecting candidates and policies by allowing them to easily obtain election information, understand it easily, and receive appropriate emotional support.

[0790] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0791] Step 1: Gather information

[0792] The server automatically collects election-related data from the Internet.

[0793] Input: URL of news site or social media

[0794] Specific operation: The server uses a crawler (e.g., BeautifulSoup or Scrapy) to crawl information from the specified URL. As a result of the crawling, HTML data is obtained.

[0795] Data processing: Parse the acquired HTML data and extract important text information.

[0796] Output: The extracted text information is stored in a database, while the duplicate data is removed.

[0797] Step 2: Data analysis and formatting

[0798] The server analyzes the collected information and generates a concise summary.

[0799] Input: Raw data (text information) stored in the database

[0800] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) and inputs the prompt "Generate a summary of this article" for the text information.

[0801] Data processing: The generative AI model analyzes the text information, extracts key points, and generates a summary.

[0802] Output: The generated summary is saved in the database.

[0803] Step 3: Classify and organize data

[0804] The server classifies and organizes the analyzed data by candidate and policy.

[0805] Input: Abstracts stored in the database

[0806] How it works: The server uses a clustering algorithm or a Naive Bayes classifier to classify the summaries by candidate and policy. For example, it assigns tags such as "Candidate A" and "Economic Policy" to the data.

[0807] Data processing: Organizing tagged data and classifying it into appropriate categories within the database.

[0808] Output: Classified and organized data is saved in a database.

[0809] Step 4: Policy comparison and analysis

[0810] The server automatically compares and analyzes the policies of candidates and political parties.

[0811] Input: Categorized and organized data (summaries of different candidates and policies)

[0812] Specific operation: The server uses the generative AI model to input the prompt sentence, "Please explain the difference between the economic policies of candidate A and candidate B."

[0813] Data processing: The generative AI model analyzes the policies being compared, extracts their differences and characteristics, and generates detailed comparison results.

[0814] Output: The generated comparison results are stored in a database.

[0815] Step 5: Applying expert-generating AI

[0816] The server generates explanatory text about the evaluation points and impact of each policy.

[0817] Input: Classified and organized data (summaries of candidates and policies) and comparison results

[0818] Specific operation: The server uses an expert generation AI and inputs the prompt "Please provide a detailed evaluation of Candidate A's economic policies."

[0819] Data processing: Expert generation AI generates detailed explanatory text.

[0820] Output: Save the generated commentary in the database.

[0821] Step 6: Informational interface

[0822] The terminal provides a user-friendly interface to display information to the user.

[0823] Input: Search keywords from the user

[0824] Specific operation: When a user inputs "Candidate A's economic policy" into the terminal, the terminal retrieves the corresponding summary, comparison results, and explanatory text from the database.

[0825] Data processing: Formatting the acquired information for display.

[0826] Output: Displaying formatted information to the user.

[0827] Step 7: Question and Answer Function

[0828] The terminal receives the user's question, transmits it to the server, and displays the response.

[0829] Input: User question (text or voice)

[0830] Specific operation: When a user asks, "What is the difference between the economic policies of candidate A and candidate B?", the device sends this information to the server. The server uses the generative AI model to input the prompt "Please explain the difference between the economic policies of candidate A and candidate B," and sends the generated response back to the device.

[0831] Data processing: Formatting the generated response text.

[0832] Output: Displays the formatted response text to the user.

[0833] Step 8: Applying the Emotion Engine

[0834] The terminal analyzes the user's emotional state and provides information according to the emotion.

[0835] Input: User's facial expressions and voice tone data

[0836] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice tone, and then uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze emotions and identify their emotional state.

[0837] Data processing: The identified emotional state is sent to the server, and the generative AI model generates additional information adapted to the emotion.

[0838] Output: Provides the user with any additional information generated.

[0839] (Application example 2)

[0840] 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."

[0841] Conventional systems focused on collecting and analyzing election-related information, displaying it through a user interface, and providing real-time responses. However, they did not provide appropriate information or recommend products based on the user's emotional state. This made it difficult for users to obtain information or products that matched their emotions. Furthermore, incorporating emotion analysis would enable more personalized services and is expected to improve the user experience.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0843] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, means for responding in real time to user questions received through the user interface, means for analyzing the user's emotional state using an emotion analysis engine and providing appropriate information based on the analysis, and means for generating product recommendations according to the user's emotional state. This makes it possible to provide information and recommend products that match the user's emotional state.

[0844] "Generative AI" is an advanced AI technology that can learn from vast amounts of data and generate sentences in natural language and perform predictive analysis.

[0845] "Means of automatically collecting information" refers to technologies such as crawlers and scrapers that automatically obtain publicly available information on the Internet and store it in a database.

[0846] The "means of analyzing information and generating a concise summary" is a generative AI algorithm that extracts key points from collected information and summarizes them in short sentences.

[0847] "Means of classifying, organizing, and displaying through a user interface" refers to a technology that divides analyzed information into specific categories and displays them in an interface that is easy for users to use.

[0848] "Real-time response means" refers to a natural language processing system and generative AI that can instantly respond to user questions and requests.

[0849] An "emotion analysis engine" is a machine learning technology that analyzes a user's facial expressions, voice, text input, etc. to identify their emotional state.

[0850] "Means of analyzing the user's emotional state and providing appropriate information based on that" refers to a generative AI that identifies and provides the information the user needs at that time based on the analyzed emotional data.

[0851] The "means for generating product recommendations" is a recommendation engine that selects and suggests products that are likely to be beneficial to a user based on the user's emotions and past purchasing history.

[0852] This invention is a system that combines generative artificial intelligence and an emotion analysis engine to automatically collect, analyze, and provide election information to users. As an example of its application to an online shopping site, we will explain an application that recommends products based on the user's emotional state.

[0853] Server-side implementation

[0854] Information gathering

[0855] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, social media, etc. The collected data is stored in a database, and duplicate data is removed through analysis.

[0856] Data analysis and formatting

[0857] The server then uses a generative AI (e.g., GPT-4) to analyze the collected data, extract key information, and generate a concise summary in natural language. The analysis process utilizes machine learning algorithms to format the data in an easy-to-understand format.

[0858] Data classification and organization

[0859] The analyzed data is classified and organized by candidate, policy, and product category, and the server uses classification algorithms (e.g., K-means clustering) to systematically manage the information within the database.

[0860] Policy comparison / analysis

[0861] Generative AI is used to automatically compare and analyze the policies and product features of candidates and political parties, extracting their differences and distinctive features. The results of this analysis are presented in a format that is easy for users to understand.

[0862] Sentiment analysis and information provision

[0863] The user's facial expressions, voice tone, text input, etc. are analyzed using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to evaluate the user's emotional state. The emotion analysis results are sent to a generative AI, which generates information and product recommendations based on the user's emotions.

[0864] User Interface Embodiments

[0865] Information provision interface

[0866] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can search for information about candidates, policies, and products, and view the information they are interested in in detail.

[0867] Question and Answer Function

[0868] When a user inputs a question via text or voice through the device, it is sent to the server in real time, and the generative AI generates an appropriate answer to the question and displays it to the user through the device.

[0869] Emotion-based recommendations

[0870] Once the user's emotional state is analyzed, products and information tailored to that state are automatically recommended. For example, if you are feeling depressed, products with a relaxing effect will be recommended.

[0871] Specific examples

[0872] Election information provision scenario

[0873] The server automatically collects election-related articles from news sites using a crawler, and the AI ​​generator generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies." This information is stored in a database.

[0874] Recommendation function scenario for online shopping site

[0875] While a user is browsing an online shopping site through smart glasses, emotion analysis is performed. If the user is found to be depressed, products such as "relaxing aroma diffusers" are recommended in real time.

[0876] Example prompt sentences to use

[0877] "The user's emotional state is depressed. Please provide a natural-language summary of relaxation products that fit this emotion. Please include specific product names and features."

[0878] In this way, the present invention provides a system that allows users to easily obtain election information and receive product recommendations that match their emotional state.

[0879] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0880] Step 1:

[0881] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, and social media. Specifically, the crawler periodically visits each website, detecting and retrieving new articles and posts. This allows the server to collect the latest election information, product reviews, and more. The input data is text information retrieved from each website, and the output is stored in a database as collected raw data.

[0882] Step 2:

[0883] The server analyzes the collected raw data using a generative AI (e.g., GPT-4), extracts important information, and generates a concise summary. In this step, a machine learning algorithm is used to input text data and output key points such as summaries and headlines. Specifically, the generative AI analyzes the text data and generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies."

[0884] Step 3:

[0885] The server then classifies and organizes the generated summary data by candidate, policy, or product category. Using a classification algorithm (e.g., K-means clustering), it assigns each data point to the appropriate category. The input data is the summarized text, and the output is data organized by category. This step ensures that the information is managed systematically and can be easily searched by users.

[0886] Step 4:

[0887] The server uses generative AI to automatically compare and analyze the characteristics of the policies and products of each candidate and political party, extracting their differences and characteristics. Specifically, it compares candidates such as "Candidate A proposes tax increases and strengthens infrastructure investment" with "Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." In this process, the input data is summary information about each candidate, and the output is the compared and analyzed text.

[0888] Step 5:

[0889] When a user inputs a question via text or voice through their device, the question is sent to the server in real time. The server's generation AI generates an appropriate answer to the question and returns the answer to the device. The input data is the user's question, and the output data is the answer generated by the generation AI. Specifically, it returns detailed comparison results in response to a question such as, "Please tell me about the differences in economic policies between candidate A and candidate B."

[0890] Step 6:

[0891] The emotion analysis engine (e.g., Microsoft Azure Emotion API) analyzes the user's facial expressions, voice tone, text input, etc. to evaluate the user's emotional state. The input in this step is facial expression and voice data obtained from the user's camera and microphone, and the output is analyzed emotional information. Based on the analysis results, the generative AI provides information corresponding to the user's emotions.

[0892] Step 7:

[0893] Based on the user's emotional state, the results of the emotion analysis are sent to a generation AI, which then generates product and information recommendations tailored to the user's state. The input data is the emotion analysis results, and the output data is product recommendations optimal for the user. Specifically, if the emotion analysis reveals that the user is in a depressed state, the system will recommend an "aroma diffuser with a relaxing effect."

[0894] In this way, a system is realized in which the server and terminal cooperate to recommend optimal information and products to the user.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] [Third embodiment]

[0899] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0900] 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.

[0901] 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).

[0902] 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.

[0903] 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.

[0904] 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).

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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."

[0911] The present invention is a system that utilizes generative artificial intelligence to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals, and helps users easily understand candidates and policies and make selections. A specific embodiment of this system and the processing of related programs are described below.

[0912] Server-side implementation

[0913] Information gathering

[0914] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[0915] Data analysis and formatting

[0916] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[0917] Data classification and organization

[0918] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[0919] Policy comparison / analysis

[0920] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[0921] Application of expert-generating AI

[0922] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[0923] Terminal side embodiment

[0924] Information provision interface

[0925] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[0926] Question and Answer Function

[0927] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[0928] User-Side Embodiment

[0929] Information search and browsing

[0930] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[0931] Providing Feedback

[0932] Users can provide feedback on the usefulness of the information, which is sent via the terminal to the server and used to improve the system.

[0933] Specific examples

[0934] Server side

[0935] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[0936] Terminal side

[0937] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[0938] User side

[0939] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if users provide feedback such as "This information was helpful," it will be sent to the server and used to improve the system.

[0940] In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[0941] The processing flow will be explained below.

[0942] Server-side processing

[0943] Step 1:

[0944] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[0945] Step 2:

[0946] The server stores collected data (articles, social media posts, official announcements, etc.) in a database, removing duplicate data and converting it into the appropriate format.

[0947] Step 3:

[0948] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[0949] Step 4:

[0950] The server categorizes and organizes the analyzed data by candidate and policy, allowing information to be systematically managed within the database.

[0951] Step 5:

[0952] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[0953] Step 6:

[0954] The server uses expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, providing users with a deeper understanding.

[0955] Terminal side processing

[0956] Step 1:

[0957] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[0958] Step 2:

[0959] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[0960] Step 3:

[0961] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[0962] User-side processing

[0963] Step 1:

[0964] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[0965] Step 2:

[0966] Users can use the provided features to read and compare information about candidates and policies, which helps them understand the differences between each candidate and their policies.

[0967] Step 3:

[0968] The user inputs a specific question through the terminal interface. For example, a question such as "Please tell me the details of Candidate A's economic policies" is possible.

[0969] Step 4:

[0970] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and this feedback is transmitted to the server via the terminal.

[0971] The above are the specific processing steps of this system.

[0972] Example 1

[0973] 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."

[0974] In modern elections, the amount of policy information on candidates and political parties is enormous, making it difficult for voters to quickly and accurately grasp and compare this information. Furthermore, detailed understanding of individual policies and comparisons between them require specialized knowledge, making it difficult for many voters to choose. Therefore, there is a need for a system that can help voters easily understand candidates and policies and make appropriate choices.

[0975] 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.

[0976] In this invention, the server includes means for automatically collecting election information using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and storing it in a database, means for providing a user interface for providing information to users, means for responding in real time to user questions received through the user interface, and means for collecting user feedback received through the user interface and using it to improve the system. This enables voters to quickly and accurately obtain election information, compare candidates and policies, and make appropriate choices.

[0977] "Generative AI" is an AI that can generate natural language based on large amounts of data and understand and respond like a human.

[0978] "Means of automatically collecting information" refers to a system that automatically obtains election-related information from the Internet using web crawlers, scraping tools, etc.

[0979] The "means for analyzing information and generating a concise summary" is a system that uses natural language processing technology to analyze collected information, extract important information, and summarize it concisely.

[0980] "Means of classifying and organizing information by candidate and policy and storing it in a database" refers to a system that classifies analyzed information according to specific criteria, organizes it systematically, and stores it.

[0981] "Means for providing a user interface for providing information to users" refers to a system that provides a screen and operation method that allows users to easily access and view information.

[0982] "Means for responding in real time to user questions received through a user interface" refers to a system in which the generating AI immediately responds to questions asked by the user through the interface.

[0983] "Means for collecting user feedback received through the user interface and using it to improve the system" refers to the process of collecting opinions and evaluations from users through the interface and using them to improve the system.

[0984] "Means to automatically compare and analyze the policies of each candidate and political party and extract their differences and characteristics" refers to a system that uses generative AI to compare the policy data of candidates and political parties and clarify their differences and characteristics.

[0985] The "means of generating explanatory text about the evaluation points and impacts of each policy" is a system that uses expert generation AI to automatically generate easy-to-understand explanatory text about the evaluation and impacts of each policy.

[0986] MODE FOR CARRYING OUT THE INVENTION

[0987] The present invention is a system that utilizes generative artificial intelligence (AI) to automatically collect and analyze election information and provide it to users. This system is realized through collaboration between a server and a terminal, and helps users easily understand candidates and policies and make appropriate choices. Specific embodiments are described in detail below.

[0988] Server-side implementation

[0989] Information gathering

[0990] The server automatically collects election-related information from designated official websites, news articles, and candidate social media sites. This process uses web crawling tools such as Beautiful Soup and Scrapy, which allow for regular and automatic collection of various information from the Internet.

[0991] The collected data is stored in a MySQL or PostgreSQL database, and duplicate data is removed or filtered out using SQL queries.

[0992] Data analysis and formatting

[0993] The server uses generative AI (such as OpenAI's GPT-4) to analyze the collected data, extract important information, and concisely summarize it. For example, it generates a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." The script for this is often implemented in Python.

[0994] Data classification and organization

[0995] The analyzed data is then categorized and organized by candidate and policy. This process uses data analysis libraries such as "Pandas" and "scikit-learn." The categorized data is then systematically stored in a database.

[0996] Policy comparison / analysis

[0997] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, and extract their differences and characteristics. For this analysis, prompts (e.g., "Please tell me about the differences in the economic policies of Candidate A and Candidate B") are executed on the server.

[0998] Application of expert-generating AI

[0999] The server also uses expert-generating AI (such as HuggingFace's BERT model) to generate detailed commentary on the evaluation points and impacts of each policy, providing users with detailed information based on expert knowledge.

[1000] Terminal side embodiment

[1001] Information provision interface

[1002] The terminal provides a user-friendly interface, built using React and Vue.js, that allows users to select candidates and policies that interest them and view detailed information.

[1003] Question and Answer Function

[1004] The device receives questions from the user via text or voice input and sends them to the server, which uses the Google Speech-to-Text API for voice input. The server's AI then responds in real time and provides information to the user via the device.

[1005] User-Side Embodiment

[1006] Information search and browsing

[1007] Users can use their devices to search for and view detailed information about candidates and policies by entering keywords in the search field, which instantly displays relevant information.

[1008] Providing Feedback

[1009] Users can provide feedback on the usefulness of the information, which is sent to the server via their device and used to improve the system.

[1010] Specific examples

[1011] For example, a server crawls "articles about Candidate A" from a news site and uses generation AI to generate a summary such as "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[1012] When a user searches for "Candidate A's economic policies" on their device, this summary information is displayed. Also, if a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends the question to the server, and the AI ​​generator responds with, "Candidate A proposes tax increases and strengthens infrastructure investment. Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[1013] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if the user provides feedback such as "This information was helpful," it is sent to the server and used to improve the system. In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[1014] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1015] Server-side processing

[1016] Step 1: Gather information

[1017] Input: The server receives the specified official website, news article, and social media URLs of the candidate.

[1018] Specific operation: The server uses Python's "Beautiful Soup" and "Scrapy" to crawl the web, retrieve HTML data from the specified URL, and extract the necessary text information.

[1019] Data processing: The extracted text data is converted into clean data by removing unnecessary tags and symbols.

[1020] Output: The clean data is stored in a MySQL or PostgreSQL database.

[1021] Step 2: Data analysis and formatting

[1022] Input: Get the clean data stored in the database.

[1023] How it works: The server sends clean data to a generative AI (e.g., OpenAI's GPT-4), which analyzes the text data, extracts important information, and summarizes it succinctly.

[1024] Data processing: The extracted summary data is further formatted and converted into a form that is easy for users to understand.

[1025] Output: The formatted summary data is saved back to the database.

[1026] Step 3: Classify and organize data

[1027] Input: Get the formatted summary data.

[1028] How it works: The server uses data analysis libraries such as "Pandas" and "scikit-learn" to categorize the summary data by candidate and policy.

[1029] Data processing: Classify data into specific categories (e.g., economic policy, environmental policy) and organize them systematically.

[1030] Output: The classified data is tagged with a classification tag and stored in a database.

[1031] Step 4: Policy comparison and analysis

[1032] Input: Get the classified data.

[1033] Specific operation: The server sends a prompt (e.g., "Please tell me about the differences in economic policies between candidate A and candidate B") to the generation AI, which then performs a comparison and analysis.

[1034] Data processing: Generative AI extracts differences and characteristics between policies and formats the results in an easy-to-understand format.

[1035] Output: The comparison and analysis results are stored in a database and provided to the user.

[1036] Step 5: Applying expert-generating AI

[1037] Input: Obtain the comparison and analysis results.

[1038] Specific operation: The server uses an expert generation AI (e.g., Hugging Face's BERT model) to generate detailed explanatory text about the evaluation points and impacts of each policy.

[1039] Data processing: The explanatory text is further formatted to translate the expert perspective into readable language.

[1040] Output: The explanatory text is stored in a database and provided to the user.

[1041] Terminal side processing

[1042] Step 1: Informational interface

[1043] Input: Receives a request for information from the user.

[1044] What it does: The device uses React and Vue.js to provide a user interface, displaying a search field and dashboard on the screen to allow users to easily access information.

[1045] Data processing: Sends a user request to the server and retrieves the relevant data.

[1046] Output: Display the retrieved information to the user.

[1047] Step 2: Question and Answer Function

[1048] Input: Receives the user's question in text or voice format.

[1049] How it works: Voice input is converted to text using the Google Speech-to-Text API. Text questions are sent directly to the server, where the server's AI generates responses in real time based on the questions.

[1050] Data processing: Retrieving the response from the server, formatting it, and converting it into something user-friendly.

[1051] Output: Display the response results on the terminal interface.

[1052] User-side processing

[1053] Step 1: Search and browse information

[1054] Input: The user enters a keyword into the search field on the device.

[1055] Specific operation: The device sends this request to the server and retrieves the relevant data.

[1056] Data processing: Display the acquired data to the user in an easy-to-understand format.

[1057] Output: Search results are displayed on the device screen.

[1058] Step 2: Provide feedback

[1059] Input: The user provides feedback on the usefulness of the information.

[1060] Specific operation: The device collects opinions and ratings from users through a feedback form and sends this feedback to the server.

[1061] Data processing: The server aggregates the collected feedback and uses it to improve the system.

[1062] Output: User feedback is saved in a database.

[1063] (Application example 1)

[1064] 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."

[1065] Conventional election information systems have had the problem of being unable to properly collect and analyze large amounts of information and provide it to users in an easy-to-understand manner. In particular, there was no means of providing interactive information to customers in physical stores, making it difficult to provide real-time questions and answers about election information. This has made it difficult for users to obtain the information they need to make appropriate choices.

[1066] 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.

[1067] In this invention, the server includes means for automatically collecting election-related information using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, and means for providing the information using an interactive device, thereby enabling users to receive a large amount of election information in a concise and easy-to-understand format and ask questions on the spot in real time.

[1068] "Generative artificial intelligence" refers to a system in general that collects information from the Internet and other sources, and automatically analyzes, summarizes, classifies, and generates responses.

[1069] "Means of automatically collecting information" refers to the process of crawling to obtain election-related data from online news articles, official websites, social media, etc.

[1070] "Means of analyzing information and generating concise summaries" refers to the process of analyzing collected data, extracting key information, and presenting it in a concise, easy-to-understand format.

[1071] "Means of categorizing and organizing by candidate and policy" refers to the process of systematically separating and storing analyzed and summarized information in association with specific candidates and policies.

[1072] "Means for responding in real time to user questions received through a user interface" refers to the process of processing a user's text or voice question and providing an immediate response using generative AI.

[1073] "Interactive devices" refer to robots and devices that are installed in brick-and-mortar stores and other locations and provide information to users in an interactive format.

[1074] This invention is a system for interactively providing election information to users, and is realized through the cooperation of the following server and interactive device (robot).

[1075] Server-side implementation

[1076] Information gathering methods

[1077] The server uses generative artificial intelligence (generative AI models) to automatically crawl election-related data from online news articles, official websites, and candidate social media. The data collected through the crawling is stored in a database, and duplicate data is removed.

[1078] Data analysis and summary generation methods

[1079] The server then uses a generative AI model to analyze the collected data, extracting key information and generating concise summaries. This analysis process organizes a large amount of information into an easy-to-understand format.

[1080] Data classification and organization methods

[1081] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[1082] Application methods of expert-generating AI

[1083] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[1084] Interactive Device Side Embodiment

[1085] Information provision interface means

[1086] Interactive devices (e.g., interactive robots) provide a user-friendly interface, allowing visitors to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[1087] Question and Answer Function Means

[1088] The interactive device receives questions from the user via text or voice input and sends them to the server. The server's generating AI responds in real time and provides the response to the user via the interactive device. Specific examples of prompt sentences include "Tell me about candidate A's economic policies" and "Compare candidate B's education policies with candidate A's education policies."

[1089] User-Side Embodiment

[1090] Information search and browsing

[1091] Users can use the interactive devices to search for and view detailed information about candidates and policies, and there is also the ability to compare specific candidates and policies, providing users with the information they need to make the right choice.

[1092] Providing Feedback

[1093] Users can provide feedback on the usefulness of the information, which is sent via the interactive device to the server and used to improve the system.

[1094] For example, if a user asks the robot, "Tell me about Candidate A's economic policies," the AI ​​will respond, "Candidate A proposes tax increases and seeks to strengthen infrastructure investment." This response is provided to the user via the robot.

[1095] This will create a system where customers can get detailed election information on the spot and receive support in making their own choices.

[1096] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1097] Step 1:

[1098] The server crawls election-related data from news articles, official websites, and social media sites on the Internet. This process collects a large amount of election-related information into a database. The input is data from the Internet, and the output is the collected raw data.

[1099] Step 2:

[1100] The server analyzes the collected raw data using a generative AI model, extracts important information, and generates a concise summary. Specifically, the generative AI model identifies important parts of the text data and outputs them as a summary. The input is the raw data collected in step 1, and the output is the summarized text data.

[1101] Step 3:

[1102] The server processes the generated summary data by classifying and organizing it by candidate and policy. This allows it to be systematically stored in a database. The input is the summary data obtained in step 2, and the output is the classified and organized data.

[1103] Step 4:

[1104] The server uses an expert generation AI to generate detailed explanatory text about the evaluation points and impacts of each policy. The input is the data classified in step 3, and the output is explanatory text. Specifically, the expert generation AI analyzes the content of the policy and generates explanatory text about its benefits and impacts.

[1105] Step 5:

[1106] The interactive device provides a user-friendly interface, allowing users to access the information they need. Users can select candidates and policies that interest them and view detailed information. The input is the user's selection, and the output is the display of the relevant information.

[1107] Step 6:

[1108] The user inputs a question to the interactive device by text or voice. Specifically, the user inputs a question such as "Tell me about the economic policies of candidate A" into the interactive device. The input is the user's question, and the output is request data to the server with which the interactive device communicates.

[1109] Step 7:

[1110] The server uses the generative AI model to generate a response to the user's question in real time. The input is the request data sent in step 6, and the output is the generated response text. Specifically, the generative AI model analyzes the question content and generates the relevant information as a response text.

[1111] Step 8:

[1112] The interactive device displays or speaks the response sentence sent from the server to the user. The input is the response sentence generated in step 7, and the output is the provision of information to the user. Specifically, the interactive device displays the response sentence on a display or reads it out loud.

[1113] 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.

[1114] The present invention is a system that utilizes generative artificial intelligence and an emotion engine to automatically collect, analyze, and provide users with information about elections. This system is realized through the cooperation of a server and a terminal, and helps users easily understand candidates and policies and make selections. In addition, by combining it with an emotion engine, the system analyzes the user's emotional state and provides appropriate information based on that analysis. A specific embodiment of this system and the processing of the related programs are described below.

[1115] Server-side implementation

[1116] Information gathering

[1117] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[1118] Data analysis and formatting

[1119] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[1120] Data classification and organization

[1121] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this, and the information is systematically managed in a database.

[1122] Policy comparison / analysis

[1123] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[1124] Application of expert-generating AI

[1125] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[1126] Terminal side embodiment

[1127] Information provision interface

[1128] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[1129] Question and Answer Function

[1130] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[1131] Applying the Emotion Engine

[1132] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. This allows it to identify the user's emotional state and provide information according to their emotions.

[1133] User-Side Embodiment

[1134] Information search and browsing

[1135] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[1136] Providing Feedback

[1137] Users can input feedback about the usefulness of the information into the terminal to help improve the system, and this feedback is sent to the server via the terminal.

[1138] Specific examples

[1139] Server side

[1140] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[1141] Terminal side

[1142] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[1143] Applying the Emotion Engine

[1144] When a user expresses doubts or concerns about a particular candidate's policies, the emotion engine analyzes that emotional state and sends it to the server. Based on this, the generation AI generates more appropriate information and comforting messages to provide to the user. For example, if a user says, "I'm worried about this policy," the AI ​​can provide additional details such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and he has received a certain level of praise from economic experts."

[1145] In this way, the present invention helps users easily obtain and understand election information and make their own choices while receiving appropriate emotional support.

[1146] The processing flow will be explained below.

[1147] Server-side processing

[1148] Step 1:

[1149] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[1150] Step 2:

[1151] The server collects data (articles, social media posts, official announcements, etc.) and stores it in a database, removing duplicate data and converting it into the appropriate format.

[1152] Step 3:

[1153] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[1154] Step 4:

[1155] The server categorizes and organizes the analyzed data by candidate and policy, using a classification algorithm to ensure that information is systematically managed within the database.

[1156] Step 5:

[1157] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[1158] Step 6:

[1159] The server uses an expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, using expert knowledge to provide users with a deeper understanding.

[1160] Step 7:

[1161] The server analyzes the user's emotional state sent from the emotion engine and generates information and messages that best suit the user's emotions.

[1162] Terminal side processing

[1163] Step 1:

[1164] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[1165] Step 2:

[1166] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[1167] Step 3:

[1168] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[1169] Step 4:

[1170] The device identifies the user's emotional state using an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. The identified emotional state is sent to the server.

[1171] User-side processing

[1172] Step 1:

[1173] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[1174] Step 2:

[1175] Utilize features that allow users to read and compare information about candidates and policies, helping them understand the differences between each candidate and their policies.

[1176] Step 3:

[1177] The user inputs a specific question through the terminal interface. For example, they can ask, "Please tell me the details of Candidate A's economic policies."

[1178] Step 4:

[1179] When a user is viewing a particular piece of information, the emotion engine analyzes the user's emotional state in real time, for example, if the user is feeling anxious, it will provide supportive information or comforting messages accordingly.

[1180] Step 5:

[1181] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and the feedback is transmitted to the server via the terminal.

[1182] The above are the specific processing steps of this system.

[1183] Example 2

[1184] 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."

[1185] Conventional election information systems collect and analyze information manually, making it difficult to organize and provide data on a large number of candidates and policies in a timely manner. Furthermore, they lack the ability to respond instantly to user questions and are unable to provide information that takes into account the user's emotional state. Therefore, a new system was needed to help users quickly and accurately understand election information and select appropriate candidates and policies.

[1186] 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.

[1187] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and displaying it on a display device, means for responding in real time to user questions received through the display device, and means for using an emotion engine that analyzes the user's facial expressions and tone of voice to identify their emotional state. This makes it possible to efficiently collect and analyze a huge amount of information about elections, generate and provide summaries on the spot, and also provide appropriate information according to the user's emotional state.

[1188] "Generative AI" refers to AI that has the ability to automatically generate, analyze, and respond to information using natural language processing.

[1189] An "emotion engine" refers to a technology that analyzes emotions from a user's facial expressions, voice tone, and text input, and identifies their emotional state.

[1190] A "crawler" is a program that automatically collects data from the Internet.

[1191] A "summary" refers to text that has been created by generative artificial intelligence, extracting important information and summarizing it concisely.

[1192] "Classification and organization" refers to the process of systematically grouping and managing collected and analyzed information based on specific criteria.

[1193] "Display device" refers to a device that includes a display or screen through which a user visually views information.

[1194] "Responsive in real time" refers to the ability to generate a response and provide an answer immediately to input from a user.

[1195] "Candidate" means a person running for public office in an election.

[1196] "Policy" refers to the specific plans and guidelines that candidates and political parties propose and aim to implement.

[1197] "Expert-generated AI" refers to AI that has the ability to generate detailed explanations and evaluations based on expert knowledge in a specific field.

[1198] "Analysis" refers to the process of examining collected data in detail to determine its meaning and relevance.

[1199] This invention is a system that uses a generative AI model and an emotion engine to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals. Specific embodiments of this system are described below from the perspectives of hardware and software.

[1200] Server-side configuration

[1201] Information gathering

[1202] The server has the ability to automatically collect election-related data from the Internet. Specifically, it uses a crawler (for example, a web scraping tool such as BeautifulSoup or Scrapy) to crawl election-related articles from official websites, news articles, and candidate social media accounts. Crawling is performed periodically, and if new information is detected, it is stored in a database (for example, MySQL or PostgreSQL). At the same time, a data cleansing process is performed to remove duplicate data.

[1203] Data analysis and formatting

[1204] The server analyzes the collected data and generates summaries. It uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the collected articles in natural language. It uses the input prompt "Please generate a summary of this article" and stores the results in a database as a concise summary.

[1205] Data classification and organization

[1206] The server is equipped with algorithms that classify and organize the analyzed data based on specific criteria, for example, using clustering algorithms (e.g., K-means clustering) or Naive Bayes classifiers to systematically group the data by candidate and policy. This information is efficiently managed in a database.

[1207] Policy comparison / analysis

[1208] The server utilizes a generative AI model to compare and analyze the policies of each candidate and political party. Specifically, it uses the prompt "Please explain the differences between the economic policies of candidate A and candidate B," and stores the generated comparison results in a database in a user-friendly format.

[1209] Application of expert-generating AI

[1210] The server has the ability to generate detailed commentaries using an expert generation AI (e.g., a GPT-4 model with specialized knowledge). It uses a prompt such as, "Please explain in detail your evaluation of Candidate A's economic policies" to describe the evaluation points and impacts of each policy, and stores the resulting commentary in a database.

[1211] Terminal configuration

[1212] Information provision interface

[1213] The terminal provides a user-friendly interface, allowing users to easily access the election information they need. Using a display device such as a tablet or smartphone, users can view detailed information about the candidates and policies that interest them.

[1214] Question and Answer Function

[1215] The device has the ability to receive user questions via text or voice and send them to a server. When a user asks, "What is Candidate A's education policy?", the device sends this information to the server, and the generative AI model generates a response in real time and sends it back to the device.

[1216] Applying the Emotion Engine

[1217] The device is equipped with an emotion engine that analyzes the user's facial expressions and vocal tone to identify their emotional state. For example, it uses the Microsoft Azure Emotion API or Google Cloud Vision API to provide appropriate information based on the user's emotional state. If the user shows an anxious expression, the device sends this information to a server, and a generative AI model provides additional information according to the emotion.

[1218] User-side example

[1219] Information search and browsing

[1220] Users can use their devices to search for and view detailed information about candidates and policies. For example, by entering "Candidate A's latest economic policies," the device will display summary information retrieved from the server.

[1221] Providing Feedback

[1222] Users can input feedback about the usefulness of the information provided and contribute to improving the system. This feedback is sent to the server via the terminal and is reflected in future data analysis and information provision.

[1223] Specific operation example

[1224] 1. Server side: News sites are crawled and articles titled "Candidate A announces new economic policies" are automatically collected, and the generative AI model generates a summary such as "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." This information is then categorized and organized and stored in a database.

[1225] 2. Device side: When a user searches for "Candidate A's economic policies," this summary information is displayed. Furthermore, if the user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this question to the server, and the generative AI model responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This response is sent back to the device and displayed to the user.

[1226] 3. Application of emotion engine: When a user says, "I'm worried about this policy," the device analyzes their voice tone and facial expression to identify the anxiety and sends this information to the server. The generative AI model generates additional information, such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and has received a certain level of praise from economic experts," and sends it back to the device. This information is then presented to the user.

[1227] As a result, the present invention supports users in selecting candidates and policies by allowing them to easily obtain election information, understand it easily, and receive appropriate emotional support.

[1228] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1229] Step 1: Gather information

[1230] The server automatically collects election-related data from the Internet.

[1231] Input: URL of news site or social media

[1232] Specific operation: The server uses a crawler (e.g., BeautifulSoup or Scrapy) to crawl information from the specified URL. As a result of the crawling, HTML data is obtained.

[1233] Data processing: Parse the acquired HTML data and extract important text information.

[1234] Output: The extracted text information is stored in a database, while the duplicate data is removed.

[1235] Step 2: Data analysis and formatting

[1236] The server analyzes the collected information and generates a concise summary.

[1237] Input: Raw data (text information) stored in the database

[1238] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) and inputs the prompt "Generate a summary of this article" for the text information.

[1239] Data processing: The generative AI model analyzes the text information, extracts key points, and generates a summary.

[1240] Output: The generated summary is saved in the database.

[1241] Step 3: Classify and organize data

[1242] The server classifies and organizes the analyzed data by candidate and policy.

[1243] Input: Abstracts stored in the database

[1244] How it works: The server uses a clustering algorithm or a Naive Bayes classifier to classify the summaries by candidate and policy. For example, it assigns tags such as "Candidate A" and "Economic Policy" to the data.

[1245] Data processing: Organizing tagged data and classifying it into appropriate categories within the database.

[1246] Output: Classified and organized data is saved in a database.

[1247] Step 4: Policy comparison and analysis

[1248] The server automatically compares and analyzes the policies of candidates and political parties.

[1249] Input: Categorized and organized data (summaries of different candidates and policies)

[1250] Specific operation: The server uses the generative AI model to input the prompt sentence, "Please explain the difference between the economic policies of candidate A and candidate B."

[1251] Data processing: The generative AI model analyzes the policies being compared, extracts their differences and characteristics, and generates detailed comparison results.

[1252] Output: The generated comparison results are stored in a database.

[1253] Step 5: Applying expert-generating AI

[1254] The server generates explanatory text about the evaluation points and impact of each policy.

[1255] Input: Classified and organized data (summaries of candidates and policies) and comparison results

[1256] Specific operation: The server uses an expert generation AI and inputs the prompt "Please provide a detailed evaluation of Candidate A's economic policies."

[1257] Data processing: Expert generation AI generates detailed explanatory text.

[1258] Output: Save the generated commentary in the database.

[1259] Step 6: Informational interface

[1260] The terminal provides a user-friendly interface to display information to the user.

[1261] Input: Search keywords from the user

[1262] Specific operation: When a user inputs "Candidate A's economic policy" into the terminal, the terminal retrieves the corresponding summary, comparison results, and explanatory text from the database.

[1263] Data processing: Formatting the acquired information for display.

[1264] Output: Displaying formatted information to the user.

[1265] Step 7: Question and Answer Function

[1266] The terminal receives the user's question, transmits it to the server, and displays the response.

[1267] Input: User question (text or voice)

[1268] Specific operation: When a user asks, "What is the difference between the economic policies of candidate A and candidate B?", the device sends this information to the server. The server uses the generative AI model to input the prompt "Please explain the difference between the economic policies of candidate A and candidate B," and sends the generated response back to the device.

[1269] Data processing: Formatting the generated response text.

[1270] Output: Displays the formatted response text to the user.

[1271] Step 8: Applying the Emotion Engine

[1272] The terminal analyzes the user's emotional state and provides information according to the emotion.

[1273] Input: User's facial expressions and voice tone data

[1274] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice tone, and then uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze emotions and identify their emotional state.

[1275] Data processing: The identified emotional state is sent to the server, and the generative AI model generates additional information adapted to the emotion.

[1276] Output: Provides the user with any additional information generated.

[1277] (Application example 2)

[1278] 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."

[1279] Conventional systems focused on collecting and analyzing election-related information, displaying it through a user interface, and providing real-time responses. However, they did not provide appropriate information or recommend products based on the user's emotional state. This made it difficult for users to obtain information or products that matched their emotions. Furthermore, incorporating emotion analysis would enable more personalized services and is expected to improve the user experience.

[1280] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1281] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, means for responding in real time to user questions received through the user interface, means for analyzing the user's emotional state using an emotion analysis engine and providing appropriate information based on the analysis, and means for generating product recommendations according to the user's emotional state. This makes it possible to provide information and recommend products that match the user's emotional state.

[1282] "Generative AI" is an advanced AI technology that can learn from vast amounts of data and generate sentences in natural language and perform predictive analysis.

[1283] "Means of automatically collecting information" refers to technologies such as crawlers and scrapers that automatically obtain publicly available information on the Internet and store it in a database.

[1284] The "means of analyzing information and generating a concise summary" is a generative AI algorithm that extracts key points from collected information and summarizes them in short sentences.

[1285] "Means of classifying, organizing, and displaying through a user interface" refers to a technology that divides analyzed information into specific categories and displays them in an interface that is easy for users to use.

[1286] "Real-time response means" refers to a natural language processing system and generative AI that can instantly respond to user questions and requests.

[1287] An "emotion analysis engine" is a machine learning technology that analyzes a user's facial expressions, voice, text input, etc. to identify their emotional state.

[1288] "Means of analyzing the user's emotional state and providing appropriate information based on that" refers to a generative AI that identifies and provides the information the user needs at that time based on the analyzed emotional data.

[1289] The "means for generating product recommendations" is a recommendation engine that selects and suggests products that are likely to be beneficial to a user based on the user's emotions and past purchasing history.

[1290] This invention is a system that combines generative artificial intelligence and an emotion analysis engine to automatically collect, analyze, and provide election information to users. As an example of its application to an online shopping site, we will explain an application that recommends products based on the user's emotional state.

[1291] Server-side implementation

[1292] Information gathering

[1293] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, social media, etc. The collected data is stored in a database, and duplicate data is removed through analysis.

[1294] Data analysis and formatting

[1295] The server then uses a generative AI (e.g., GPT-4) to analyze the collected data, extract key information, and generate a concise summary in natural language. The analysis process utilizes machine learning algorithms to format the data in an easy-to-understand format.

[1296] Data classification and organization

[1297] The analyzed data is classified and organized by candidate, policy, and product category, and the server uses classification algorithms (e.g., K-means clustering) to systematically manage the information within the database.

[1298] Policy comparison / analysis

[1299] Generative AI is used to automatically compare and analyze the policies and product features of candidates and political parties, extracting their differences and distinctive features. The results of this analysis are presented in a format that is easy for users to understand.

[1300] Sentiment analysis and information provision

[1301] The user's facial expressions, voice tone, text input, etc. are analyzed using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to evaluate the user's emotional state. The emotion analysis results are sent to a generative AI, which generates information and product recommendations based on the user's emotions.

[1302] User Interface Embodiments

[1303] Information provision interface

[1304] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can search for information about candidates, policies, and products, and view the information they are interested in in detail.

[1305] Question and Answer Function

[1306] When a user inputs a question via text or voice through the device, it is sent to the server in real time, and the generative AI generates an appropriate answer to the question and displays it to the user through the device.

[1307] Emotion-based recommendations

[1308] Once the user's emotional state is analyzed, products and information tailored to that state are automatically recommended. For example, if you are feeling depressed, products with a relaxing effect will be recommended.

[1309] Specific examples

[1310] Election information provision scenario

[1311] The server automatically collects election-related articles from news sites using a crawler, and the AI ​​generator generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies." This information is stored in a database.

[1312] Recommendation function scenario for online shopping site

[1313] While a user is browsing an online shopping site through smart glasses, emotion analysis is performed. If the user is found to be depressed, products such as "relaxing aroma diffusers" are recommended in real time.

[1314] Example prompt sentences to use

[1315] "The user's emotional state is depressed. Please provide a natural-language summary of relaxation products that fit this emotion. Please include specific product names and features."

[1316] In this way, the present invention provides a system that allows users to easily obtain election information and receive product recommendations that match their emotional state.

[1317] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1318] Step 1:

[1319] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, and social media. Specifically, the crawler periodically visits each website, detecting and retrieving new articles and posts. This allows the server to collect the latest election information, product reviews, and more. The input data is text information retrieved from each website, and the output is stored in a database as collected raw data.

[1320] Step 2:

[1321] The server analyzes the collected raw data using a generative AI (e.g., GPT-4), extracts important information, and generates a concise summary. In this step, a machine learning algorithm is used to input text data and output key points such as summaries and headlines. Specifically, the generative AI analyzes the text data and generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies."

[1322] Step 3:

[1323] The server then classifies and organizes the generated summary data by candidate, policy, or product category. Using a classification algorithm (e.g., K-means clustering), it assigns each data point to the appropriate category. The input data is the summarized text, and the output is data organized by category. This step ensures that the information is managed systematically and can be easily searched by users.

[1324] Step 4:

[1325] The server uses generative AI to automatically compare and analyze the characteristics of the policies and products of each candidate and political party, extracting their differences and characteristics. Specifically, it compares candidates such as "Candidate A proposes tax increases and strengthens infrastructure investment" with "Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." In this process, the input data is summary information about each candidate, and the output is the compared and analyzed text.

[1326] Step 5:

[1327] When a user inputs a question via text or voice through their device, the question is sent to the server in real time. The server's generation AI generates an appropriate answer to the question and returns the answer to the device. The input data is the user's question, and the output data is the answer generated by the generation AI. Specifically, it returns detailed comparison results in response to a question such as, "Please tell me about the differences in economic policies between candidate A and candidate B."

[1328] Step 6:

[1329] The emotion analysis engine (e.g., Microsoft Azure Emotion API) analyzes the user's facial expressions, voice tone, text input, etc. to evaluate the user's emotional state. The input in this step is facial expression and voice data obtained from the user's camera and microphone, and the output is analyzed emotional information. Based on the analysis results, the generative AI provides information corresponding to the user's emotions.

[1330] Step 7:

[1331] Based on the user's emotional state, the results of the emotion analysis are sent to a generation AI, which then generates product and information recommendations tailored to the user's state. The input data is the emotion analysis results, and the output data is product recommendations optimal for the user. Specifically, if the emotion analysis reveals that the user is in a depressed state, the system will recommend an "aroma diffuser with a relaxing effect."

[1332] In this way, a system is realized in which the server and terminal cooperate to recommend optimal information and products to the user.

[1333] 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.

[1334] 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.

[1335] 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.

[1336] [Fourth embodiment]

[1337] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1338] 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.

[1339] 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).

[1340] 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.

[1341] 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.

[1342] 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).

[1343] 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.

[1344] 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.

[1345] 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.

[1346] 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.

[1347] 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.

[1348] 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.

[1349] 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."

[1350] The present invention is a system that utilizes generative artificial intelligence to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals, and helps users easily understand candidates and policies and make selections. A specific embodiment of this system and the processing of related programs are described below.

[1351] Server-side implementation

[1352] Information gathering

[1353] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[1354] Data analysis and formatting

[1355] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[1356] Data classification and organization

[1357] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[1358] Policy comparison / analysis

[1359] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[1360] Application of expert-generating AI

[1361] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[1362] Terminal side embodiment

[1363] Information provision interface

[1364] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[1365] Question and Answer Function

[1366] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[1367] User-Side Embodiment

[1368] Information search and browsing

[1369] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[1370] Providing Feedback

[1371] Users can provide feedback on the usefulness of the information, which is sent via the terminal to the server and used to improve the system.

[1372] Specific examples

[1373] Server side

[1374] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[1375] Terminal side

[1376] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[1377] User side

[1378] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if users provide feedback such as "This information was helpful," it will be sent to the server and used to improve the system.

[1379] In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[1380] The processing flow will be explained below.

[1381] Server-side processing

[1382] Step 1:

[1383] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[1384] Step 2:

[1385] The server stores collected data (articles, social media posts, official announcements, etc.) in a database, removing duplicate data and converting it into the appropriate format.

[1386] Step 3:

[1387] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[1388] Step 4:

[1389] The server categorizes and organizes the analyzed data by candidate and policy, allowing information to be systematically managed within the database.

[1390] Step 5:

[1391] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[1392] Step 6:

[1393] The server uses expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, providing users with a deeper understanding.

[1394] Terminal side processing

[1395] Step 1:

[1396] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[1397] Step 2:

[1398] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[1399] Step 3:

[1400] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[1401] User-side processing

[1402] Step 1:

[1403] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[1404] Step 2:

[1405] Users can use the provided features to read and compare information about candidates and policies, which helps them understand the differences between each candidate and their policies.

[1406] Step 3:

[1407] The user inputs a specific question through the terminal interface. For example, a question such as "Please tell me the details of Candidate A's economic policies" is possible.

[1408] Step 4:

[1409] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and this feedback is transmitted to the server via the terminal.

[1410] The above are the specific processing steps of this system.

[1411] Example 1

[1412] 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."

[1413] In modern elections, the amount of policy information on candidates and political parties is enormous, making it difficult for voters to quickly and accurately grasp and compare this information. Furthermore, detailed understanding of individual policies and comparisons between them require specialized knowledge, making it difficult for many voters to choose. Therefore, there is a need for a system that can help voters easily understand candidates and policies and make appropriate choices.

[1414] 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.

[1415] In this invention, the server includes means for automatically collecting election information using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and storing it in a database, means for providing a user interface for providing information to users, means for responding in real time to user questions received through the user interface, and means for collecting user feedback received through the user interface and using it to improve the system. This enables voters to quickly and accurately obtain election information, compare candidates and policies, and make appropriate choices.

[1416] "Generative AI" is an AI that can generate natural language based on large amounts of data and understand and respond like a human.

[1417] "Means of automatically collecting information" refers to a system that automatically obtains election-related information from the Internet using web crawlers, scraping tools, etc.

[1418] The "means for analyzing information and generating a concise summary" is a system that uses natural language processing technology to analyze collected information, extract important information, and summarize it concisely.

[1419] "Means of classifying and organizing information by candidate and policy and storing it in a database" refers to a system that classifies analyzed information according to specific criteria, organizes it systematically, and stores it.

[1420] "Means for providing a user interface for providing information to users" refers to a system that provides a screen and operation method that allows users to easily access and view information.

[1421] "Means for responding in real time to user questions received through a user interface" refers to a system in which the generating AI immediately responds to questions asked by the user through the interface.

[1422] "Means for collecting user feedback received through the user interface and using it to improve the system" refers to the process of collecting opinions and evaluations from users through the interface and using them to improve the system.

[1423] "Means to automatically compare and analyze the policies of each candidate and political party and extract their differences and characteristics" refers to a system that uses generative AI to compare the policy data of candidates and political parties and clarify their differences and characteristics.

[1424] The "means of generating explanatory text about the evaluation points and impacts of each policy" is a system that uses expert generation AI to automatically generate easy-to-understand explanatory text about the evaluation and impacts of each policy.

[1425] MODE FOR CARRYING OUT THE INVENTION

[1426] The present invention is a system that utilizes generative artificial intelligence (AI) to automatically collect and analyze election information and provide it to users. This system is realized through collaboration between a server and a terminal, and helps users easily understand candidates and policies and make appropriate choices. Specific embodiments are described in detail below.

[1427] Server-side implementation

[1428] Information gathering

[1429] The server automatically collects election-related information from designated official websites, news articles, and candidate social media sites. This process uses web crawling tools such as Beautiful Soup and Scrapy, which allow for regular and automatic collection of various information from the Internet.

[1430] The collected data is stored in a MySQL or PostgreSQL database, and duplicate data is removed or filtered out using SQL queries.

[1431] Data analysis and formatting

[1432] The server uses generative AI (such as OpenAI's GPT-4) to analyze the collected data, extract important information, and concisely summarize it. For example, it generates a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." The script for this is often implemented in Python.

[1433] Data classification and organization

[1434] The analyzed data is then categorized and organized by candidate and policy. This process uses data analysis libraries such as "Pandas" and "scikit-learn." The categorized data is then systematically stored in a database.

[1435] Policy comparison / analysis

[1436] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, and extract their differences and characteristics. For this analysis, prompts (e.g., "Please tell me about the differences in the economic policies of Candidate A and Candidate B") are executed on the server.

[1437] Application of expert-generating AI

[1438] The server also uses expert-generating AI (such as HuggingFace's BERT model) to generate detailed commentary on the evaluation points and impacts of each policy, providing users with detailed information based on expert knowledge.

[1439] Terminal side embodiment

[1440] Information provision interface

[1441] The terminal provides a user-friendly interface, built using React and Vue.js, that allows users to select candidates and policies that interest them and view detailed information.

[1442] Question and Answer Function

[1443] The device receives questions from the user via text or voice input and sends them to the server, which uses the Google Speech-to-Text API for voice input. The server's AI then responds in real time and provides information to the user via the device.

[1444] User-Side Embodiment

[1445] Information search and browsing

[1446] Users can use their devices to search for and view detailed information about candidates and policies by entering keywords in the search field, which instantly displays relevant information.

[1447] Providing Feedback

[1448] Users can provide feedback on the usefulness of the information, which is sent to the server via their device and used to improve the system.

[1449] Specific examples

[1450] For example, a server crawls "articles about Candidate A" from a news site and uses generation AI to generate a summary such as "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[1451] When a user searches for "Candidate A's economic policies" on their device, this summary information is displayed. Also, if a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends the question to the server, and the AI ​​generator responds with, "Candidate A proposes tax increases and strengthens infrastructure investment. Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[1452] Based on this information, users can decide which of Candidate A's or Candidate B's policies is closest to their own. Furthermore, if the user provides feedback such as "This information was helpful," it is sent to the server and used to improve the system. In this way, the present invention helps users easily obtain and understand election information and make their own choices.

[1453] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1454] Server-side processing

[1455] Step 1: Gather information

[1456] Input: The server receives the specified official website, news article, and social media URLs of the candidate.

[1457] Specific operation: The server uses Python's "Beautiful Soup" and "Scrapy" to crawl the web, retrieve HTML data from the specified URL, and extract the necessary text information.

[1458] Data processing: The extracted text data is converted into clean data by removing unnecessary tags and symbols.

[1459] Output: The clean data is stored in a MySQL or PostgreSQL database.

[1460] Step 2: Data analysis and formatting

[1461] Input: Get the clean data stored in the database.

[1462] How it works: The server sends clean data to a generative AI (e.g., OpenAI's GPT-4), which analyzes the text data, extracts important information, and summarizes it succinctly.

[1463] Data processing: The extracted summary data is further formatted and converted into a form that is easy for users to understand.

[1464] Output: The formatted summary data is saved back to the database.

[1465] Step 3: Classify and organize data

[1466] Input: Get the formatted summary data.

[1467] How it works: The server uses data analysis libraries such as "Pandas" and "scikit-learn" to categorize the summary data by candidate and policy.

[1468] Data processing: Classify data into specific categories (e.g., economic policy, environmental policy) and organize them systematically.

[1469] Output: The classified data is tagged with a classification tag and stored in a database.

[1470] Step 4: Policy comparison and analysis

[1471] Input: Get the classified data.

[1472] Specific operation: The server sends a prompt (e.g., "Please tell me about the differences in economic policies between candidate A and candidate B") to the generation AI, which then performs a comparison and analysis.

[1473] Data processing: Generative AI extracts differences and characteristics between policies and formats the results in an easy-to-understand format.

[1474] Output: The comparison and analysis results are stored in a database and provided to the user.

[1475] Step 5: Applying expert-generating AI

[1476] Input: Obtain the comparison and analysis results.

[1477] Specific operation: The server uses an expert generation AI (e.g., Hugging Face's BERT model) to generate detailed explanatory text about the evaluation points and impacts of each policy.

[1478] Data processing: The explanatory text is further formatted to translate the expert perspective into readable language.

[1479] Output: The explanatory text is stored in a database and provided to the user.

[1480] Terminal side processing

[1481] Step 1: Informational interface

[1482] Input: Receives a request for information from the user.

[1483] What it does: The device uses React and Vue.js to provide a user interface, displaying a search field and dashboard on the screen to allow users to easily access information.

[1484] Data processing: Sends a user request to the server and retrieves the relevant data.

[1485] Output: Display the retrieved information to the user.

[1486] Step 2: Question and Answer Function

[1487] Input: Receives the user's question in text or voice format.

[1488] How it works: Voice input is converted to text using the Google Speech-to-Text API. Text questions are sent directly to the server, where the server's AI generates responses in real time based on the questions.

[1489] Data processing: Retrieving the response from the server, formatting it, and converting it into something user-friendly.

[1490] Output: Display the response results on the terminal interface.

[1491] User-side processing

[1492] Step 1: Search and browse information

[1493] Input: The user enters a keyword into the search field on the device.

[1494] Specific operation: The device sends this request to the server and retrieves the relevant data.

[1495] Data processing: Display the acquired data to the user in an easy-to-understand format.

[1496] Output: Search results are displayed on the device screen.

[1497] Step 2: Provide feedback

[1498] Input: The user provides feedback on the usefulness of the information.

[1499] Specific operation: The device collects opinions and ratings from users through a feedback form and sends this feedback to the server.

[1500] Data processing: The server aggregates the collected feedback and uses it to improve the system.

[1501] Output: User feedback is saved in a database.

[1502] (Application example 1)

[1503] 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."

[1504] Conventional election information systems have had the problem of being unable to properly collect and analyze large amounts of information and provide it to users in an easy-to-understand manner. In particular, there was no means of providing interactive information to customers in physical stores, making it difficult to provide real-time questions and answers about election information. This has made it difficult for users to obtain the information they need to make appropriate choices.

[1505] 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.

[1506] In this invention, the server includes means for automatically collecting election-related information using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, and means for providing the information using an interactive device, thereby enabling users to receive a large amount of election information in a concise and easy-to-understand format and ask questions on the spot in real time.

[1507] "Generative artificial intelligence" refers to a system in general that collects information from the Internet and other sources, and automatically analyzes, summarizes, classifies, and generates responses.

[1508] "Means of automatically collecting information" refers to the process of crawling to obtain election-related data from online news articles, official websites, social media, etc.

[1509] "Means of analyzing information and generating concise summaries" refers to the process of analyzing collected data, extracting key information, and presenting it in a concise, easy-to-understand format.

[1510] "Means of categorizing and organizing by candidate and policy" refers to the process of systematically separating and storing analyzed and summarized information in association with specific candidates and policies.

[1511] "Means for responding in real time to user questions received through a user interface" refers to the process of processing a user's text or voice question and providing an immediate response using generative AI.

[1512] "Interactive devices" refer to robots and devices that are installed in brick-and-mortar stores and other locations and provide information to users in an interactive format.

[1513] This invention is a system for interactively providing election information to users, and is realized through the cooperation of the following server and interactive device (robot).

[1514] Server-side implementation

[1515] Information gathering methods

[1516] The server uses generative artificial intelligence (generative AI models) to automatically crawl election-related data from online news articles, official websites, and candidate social media. The data collected through the crawling is stored in a database, and duplicate data is removed.

[1517] Data analysis and summary generation methods

[1518] The server then uses a generative AI model to analyze the collected data, extracting key information and generating concise summaries. This analysis process organizes a large amount of information into an easy-to-understand format.

[1519] Data classification and organization methods

[1520] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this and stores the data systematically in a database.

[1521] Application methods of expert-generating AI

[1522] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[1523] Interactive Device Side Embodiment

[1524] Information provision interface means

[1525] Interactive devices (e.g., interactive robots) provide a user-friendly interface, allowing visitors to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[1526] Question and Answer Function Means

[1527] The interactive device receives questions from the user via text or voice input and sends them to the server. The server's generating AI responds in real time and provides the response to the user via the interactive device. Specific examples of prompt sentences include "Tell me about candidate A's economic policies" and "Compare candidate B's education policies with candidate A's education policies."

[1528] User-Side Embodiment

[1529] Information search and browsing

[1530] Users can use the interactive devices to search for and view detailed information about candidates and policies, and there is also the ability to compare specific candidates and policies, providing users with the information they need to make the right choice.

[1531] Providing Feedback

[1532] Users can provide feedback on the usefulness of the information, which is sent via the interactive device to the server and used to improve the system.

[1533] For example, if a user asks the robot, "Tell me about Candidate A's economic policies," the AI ​​will respond, "Candidate A proposes tax increases and seeks to strengthen infrastructure investment." This response is provided to the user via the robot.

[1534] This will create a system where customers can get detailed election information on the spot and receive support in making their own choices.

[1535] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1536] Step 1:

[1537] The server crawls election-related data from news articles, official websites, and social media sites on the Internet. This process collects a large amount of election-related information into a database. The input is data from the Internet, and the output is the collected raw data.

[1538] Step 2:

[1539] The server analyzes the collected raw data using a generative AI model, extracts important information, and generates a concise summary. Specifically, the generative AI model identifies important parts of the text data and outputs them as a summary. The input is the raw data collected in step 1, and the output is the summarized text data.

[1540] Step 3:

[1541] The server processes the generated summary data by classifying and organizing it by candidate and policy. This allows it to be systematically stored in a database. The input is the summary data obtained in step 2, and the output is the classified and organized data.

[1542] Step 4:

[1543] The server uses an expert generation AI to generate detailed explanatory text about the evaluation points and impacts of each policy. The input is the data classified in step 3, and the output is explanatory text. Specifically, the expert generation AI analyzes the content of the policy and generates explanatory text about its benefits and impacts.

[1544] Step 5:

[1545] The interactive device provides a user-friendly interface, allowing users to access the information they need. Users can select candidates and policies that interest them and view detailed information. The input is the user's selection, and the output is the display of the relevant information.

[1546] Step 6:

[1547] The user inputs a question to the interactive device by text or voice. Specifically, the user inputs a question such as "Tell me about the economic policies of candidate A" into the interactive device. The input is the user's question, and the output is request data to the server with which the interactive device communicates.

[1548] Step 7:

[1549] The server uses the generative AI model to generate a response to the user's question in real time. The input is the request data sent in step 6, and the output is the generated response text. Specifically, the generative AI model analyzes the question content and generates the relevant information as a response text.

[1550] Step 8:

[1551] The interactive device displays or speaks the response sentence sent from the server to the user. The input is the response sentence generated in step 7, and the output is the provision of information to the user. Specifically, the interactive device displays the response sentence on a display or reads it out loud.

[1552] 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.

[1553] The present invention is a system that utilizes generative artificial intelligence and an emotion engine to automatically collect, analyze, and provide users with information about elections. This system is realized through the cooperation of a server and a terminal, and helps users easily understand candidates and policies and make selections. In addition, by combining it with an emotion engine, the system analyzes the user's emotional state and provides appropriate information based on that analysis. A specific embodiment of this system and the processing of the related programs are described below.

[1554] Server-side implementation

[1555] Information gathering

[1556] The server automatically crawls and collects election-related articles from official websites, news articles, and candidate social media accounts on the Internet. The collected data is stored in a database, and duplicate data is removed.

[1557] Data analysis and formatting

[1558] The server then uses generative AI to analyze the collected data, extract key information, and generate concise summaries in natural language. This analysis process organizes a large amount of information into an easy-to-understand format.

[1559] Data classification and organization

[1560] The analyzed data is then categorized and organized by candidate and policy. The server uses algorithms to do this, and the information is systematically managed in a database.

[1561] Policy comparison / analysis

[1562] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties, extracting their differences and characteristics, and presenting the results of this analysis in a format that is easy for users to understand.

[1563] Application of expert-generating AI

[1564] Furthermore, the server uses an expert generation AI to generate detailed commentary on the evaluation points and impacts of each policy, thereby providing users with a deeper understanding using expert knowledge.

[1565] Terminal side embodiment

[1566] Information provision interface

[1567] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can select candidates and policies that interest them and view detailed information.

[1568] Question and Answer Function

[1569] The device receives questions from the user via text or voice input and sends them to the server, where the server's AI generates a response in real time and provides it to the user via the device.

[1570] Applying the Emotion Engine

[1571] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. This allows it to identify the user's emotional state and provide information according to their emotions.

[1572] User-Side Embodiment

[1573] Information search and browsing

[1574] Users can use the device to search for and view detailed information about candidates and policies, and it also has the ability to compare specific candidates and policies, giving users the information they need to make the right choice.

[1575] Providing Feedback

[1576] Users can input feedback about the usefulness of the information into the terminal to help improve the system, and this feedback is sent to the server via the terminal.

[1577] Specific examples

[1578] Server side

[1579] The server automatically crawls articles about Candidate A from news sites, and the AI ​​analyzes the content to generate a summary such as, "Candidate A proposes tax increases as an economic policy, but aims to create jobs by strengthening infrastructure investment." This information is stored in a database and categorized by candidate and policy.

[1580] Terminal side

[1581] When a user searches for "Candidate A's economic policies" using a device, this summary information is displayed. When a user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this to the server, and the generation AI responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This information is returned to the device and displayed to the user.

[1582] Applying the Emotion Engine

[1583] When a user expresses doubts or concerns about a particular candidate's policies, the emotion engine analyzes that emotional state and sends it to the server. Based on this, the generation AI generates more appropriate information and comforting messages to provide to the user. For example, if a user says, "I'm worried about this policy," the AI ​​can provide additional details such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and he has received a certain level of praise from economic experts."

[1584] In this way, the present invention helps users easily obtain and understand election information and make their own choices while receiving appropriate emotional support.

[1585] The processing flow will be explained below.

[1586] Server-side processing

[1587] Step 1:

[1588] The server will begin crawling election-related websites (news sites, official candidate pages, political party social media, etc.) according to a pre-set schedule, preparing to automatically collect the latest election information.

[1589] Step 2:

[1590] The server collects data (articles, social media posts, official announcements, etc.) and stores it in a database, removing duplicate data and converting it into the appropriate format.

[1591] Step 3:

[1592] The server analyzes the collected data using generative AI, which extracts key information from each piece of data and summarizes it in natural language.

[1593] Step 4:

[1594] The server categorizes and organizes the analyzed data by candidate and policy, using a classification algorithm to ensure that information is systematically managed within the database.

[1595] Step 5:

[1596] The server uses generative AI to automatically compare and analyze the policies of candidates and political parties. The generative AI extracts differences and characteristics of policies and summarizes them in an easy-to-understand format.

[1597] Step 6:

[1598] The server uses an expert generation AI to generate detailed explanations of the evaluation points and impacts of each policy, using expert knowledge to provide users with a deeper understanding.

[1599] Step 7:

[1600] The server analyzes the user's emotional state sent from the emotion engine and generates information and messages that best suit the user's emotions.

[1601] Terminal side processing

[1602] Step 1:

[1603] The terminal provides a user-friendly interface, allowing users to easily access the information they need. The terminal is equipped with a search function for election information.

[1604] Step 2:

[1605] The device receives the user's questions or concerns via text or voice input, generates an appropriate query based on the input question, and sends it to the server.

[1606] Step 3:

[1607] The device receives a response from the server and displays it to the user in real time, and the answer may be provided in text, audio, or sign language format.

[1608] Step 4:

[1609] The device identifies the user's emotional state using an emotion engine that analyzes the user's facial expressions, voice tone, text input, etc. The identified emotional state is sent to the server.

[1610] User-side processing

[1611] Step 1:

[1612] A user uses a device to search for election information (candidates, policies, etc.) Search results are displayed and the user can access detailed information.

[1613] Step 2:

[1614] Utilize features that allow users to read and compare information about candidates and policies, helping them understand the differences between each candidate and their policies.

[1615] Step 3:

[1616] The user inputs a specific question through the terminal interface. For example, they can ask, "Please tell me the details of Candidate A's economic policies."

[1617] Step 4:

[1618] When a user is viewing a particular piece of information, the emotion engine analyzes the user's emotional state in real time, for example, if the user is feeling anxious, it will provide supportive information or comforting messages accordingly.

[1619] Step 5:

[1620] The user inputs feedback on the usefulness of the provided information into the terminal to support improvements to the system, and the feedback is transmitted to the server via the terminal.

[1621] The above are the specific processing steps of this system.

[1622] Example 2

[1623] 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."

[1624] Conventional election information systems collect and analyze information manually, making it difficult to organize and provide data on a large number of candidates and policies in a timely manner. Furthermore, they lack the ability to respond instantly to user questions and are unable to provide information that takes into account the user's emotional state. Therefore, a new system was needed to help users quickly and accurately understand election information and select appropriate candidates and policies.

[1625] 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.

[1626] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating concise summaries, means for classifying and organizing the analyzed information by candidate and policy and displaying it on a display device, means for responding in real time to user questions received through the display device, and means for using an emotion engine that analyzes the user's facial expressions and tone of voice to identify their emotional state. This makes it possible to efficiently collect and analyze a huge amount of information about elections, generate and provide summaries on the spot, and also provide appropriate information according to the user's emotional state.

[1627] "Generative AI" refers to AI that has the ability to automatically generate, analyze, and respond to information using natural language processing.

[1628] An "emotion engine" refers to a technology that analyzes emotions from a user's facial expressions, voice tone, and text input, and identifies their emotional state.

[1629] A "crawler" is a program that automatically collects data from the Internet.

[1630] A "summary" refers to text that has been created by generative artificial intelligence, extracting important information and summarizing it concisely.

[1631] "Classification and organization" refers to the process of systematically grouping and managing collected and analyzed information based on specific criteria.

[1632] "Display device" refers to a device that includes a display or screen through which a user visually views information.

[1633] "Responsive in real time" refers to the ability to generate a response and provide an answer immediately to input from a user.

[1634] "Candidate" means a person running for public office in an election.

[1635] "Policy" refers to the specific plans and guidelines that candidates and political parties propose and aim to implement.

[1636] "Expert-generated AI" refers to AI that has the ability to generate detailed explanations and evaluations based on expert knowledge in a specific field.

[1637] "Analysis" refers to the process of examining collected data in detail to determine its meaning and relevance.

[1638] This invention is a system that uses a generative AI model and an emotion engine to automatically collect, analyze, and provide information about elections to users. This system is realized through the cooperation of a server and terminals. Specific embodiments of this system are described below from the perspectives of hardware and software.

[1639] Server-side configuration

[1640] Information gathering

[1641] The server has the ability to automatically collect election-related data from the Internet. Specifically, it uses a crawler (for example, a web scraping tool such as BeautifulSoup or Scrapy) to crawl election-related articles from official websites, news articles, and candidate social media accounts. Crawling is performed periodically, and if new information is detected, it is stored in a database (for example, MySQL or PostgreSQL). At the same time, a data cleansing process is performed to remove duplicate data.

[1642] Data analysis and formatting

[1643] The server analyzes the collected data and generates summaries. It uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the collected articles in natural language. It uses the input prompt "Please generate a summary of this article" and stores the results in a database as a concise summary.

[1644] Data classification and organization

[1645] The server is equipped with algorithms that classify and organize the analyzed data based on specific criteria, for example, using clustering algorithms (e.g., K-means clustering) or Naive Bayes classifiers to systematically group the data by candidate and policy. This information is efficiently managed in a database.

[1646] Policy comparison / analysis

[1647] The server utilizes a generative AI model to compare and analyze the policies of each candidate and political party. Specifically, it uses the prompt "Please explain the differences between the economic policies of candidate A and candidate B," and stores the generated comparison results in a database in a user-friendly format.

[1648] Application of expert-generating AI

[1649] The server has the ability to generate detailed commentaries using an expert generation AI (e.g., a GPT-4 model with specialized knowledge). It uses a prompt such as, "Please explain in detail your evaluation of Candidate A's economic policies" to describe the evaluation points and impacts of each policy, and stores the resulting commentary in a database.

[1650] Terminal configuration

[1651] Information provision interface

[1652] The terminal provides a user-friendly interface, allowing users to easily access the election information they need. Using a display device such as a tablet or smartphone, users can view detailed information about the candidates and policies that interest them.

[1653] Question and Answer Function

[1654] The device has the ability to receive user questions via text or voice and send them to a server. When a user asks, "What is Candidate A's education policy?", the device sends this information to the server, and the generative AI model generates a response in real time and sends it back to the device.

[1655] Applying the Emotion Engine

[1656] The device is equipped with an emotion engine that analyzes the user's facial expressions and vocal tone to identify their emotional state. For example, it uses the Microsoft Azure Emotion API or Google Cloud Vision API to provide appropriate information based on the user's emotional state. If the user shows an anxious expression, the device sends this information to a server, and a generative AI model provides additional information according to the emotion.

[1657] User-side example

[1658] Information search and browsing

[1659] Users can use their devices to search for and view detailed information about candidates and policies. For example, by entering "Candidate A's latest economic policies," the device will display summary information retrieved from the server.

[1660] Providing Feedback

[1661] Users can input feedback about the usefulness of the information provided and contribute to improving the system. This feedback is sent to the server via the terminal and is reflected in future data analysis and information provision.

[1662] Specific operation example

[1663] 1. Server side: News sites are crawled and articles titled "Candidate A announces new economic policies" are automatically collected, and the generative AI model generates a summary such as "Candidate A proposes tax increases as an economic policy, but aims to increase infrastructure investment and create jobs." This information is then categorized and organized and stored in a database.

[1664] 2. Device side: When a user searches for "Candidate A's economic policies," this summary information is displayed. Furthermore, if the user asks, "Please tell me the differences between the economic policies of Candidate A and Candidate B," the device sends this question to the server, and the generative AI model responds, "Candidate A proposes tax increases and strengthens infrastructure investment. On the other hand, Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." This response is sent back to the device and displayed to the user.

[1665] 3. Application of emotion engine: When a user says, "I'm worried about this policy," the device analyzes their voice tone and facial expression to identify the anxiety and sends this information to the server. The generative AI model generates additional information, such as, "Candidate A has explained the specific risk management measures he will implement through this policy, and has received a certain level of praise from economic experts," and sends it back to the device. This information is then presented to the user.

[1666] As a result, the present invention supports users in selecting candidates and policies by allowing them to easily obtain election information, understand it easily, and receive appropriate emotional support.

[1667] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1668] Step 1: Gather information

[1669] The server automatically collects election-related data from the Internet.

[1670] Input: URL of news site or social media

[1671] Specific operation: The server uses a crawler (e.g., BeautifulSoup or Scrapy) to crawl information from the specified URL. As a result of the crawling, HTML data is obtained.

[1672] Data processing: Parse the acquired HTML data and extract important text information.

[1673] Output: The extracted text information is stored in a database, while the duplicate data is removed.

[1674] Step 2: Data analysis and formatting

[1675] The server analyzes the collected information and generates a concise summary.

[1676] Input: Raw data (text information) stored in the database

[1677] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) and inputs the prompt "Generate a summary of this article" for the text information.

[1678] Data processing: The generative AI model analyzes the text information, extracts key points, and generates a summary.

[1679] Output: The generated summary is saved in the database.

[1680] Step 3: Classify and organize data

[1681] The server classifies and organizes the analyzed data by candidate and policy.

[1682] Input: Abstracts stored in the database

[1683] How it works: The server uses a clustering algorithm or a Naive Bayes classifier to classify the summaries by candidate and policy. For example, it assigns tags such as "Candidate A" and "Economic Policy" to the data.

[1684] Data processing: Organizing tagged data and classifying it into appropriate categories within the database.

[1685] Output: Classified and organized data is saved in a database.

[1686] Step 4: Policy comparison and analysis

[1687] The server automatically compares and analyzes the policies of candidates and political parties.

[1688] Input: Categorized and organized data (summaries of different candidates and policies)

[1689] Specific operation: The server uses the generative AI model to input the prompt sentence, "Please explain the difference between the economic policies of candidate A and candidate B."

[1690] Data processing: The generative AI model analyzes the policies being compared, extracts their differences and characteristics, and generates detailed comparison results.

[1691] Output: The generated comparison results are stored in a database.

[1692] Step 5: Applying expert-generating AI

[1693] The server generates explanatory text about the evaluation points and impact of each policy.

[1694] Input: Classified and organized data (summaries of candidates and policies) and comparison results

[1695] Specific operation: The server uses an expert generation AI and inputs the prompt "Please provide a detailed evaluation of Candidate A's economic policies."

[1696] Data processing: Expert generation AI generates detailed explanatory text.

[1697] Output: Save the generated commentary in the database.

[1698] Step 6: Informational interface

[1699] The terminal provides a user-friendly interface to display information to the user.

[1700] Input: Search keywords from the user

[1701] Specific operation: When a user inputs "Candidate A's economic policy" into the terminal, the terminal retrieves the corresponding summary, comparison results, and explanatory text from the database.

[1702] Data processing: Formatting the acquired information for display.

[1703] Output: Displaying formatted information to the user.

[1704] Step 7: Question and Answer Function

[1705] The terminal receives the user's question, transmits it to the server, and displays the response.

[1706] Input: User question (text or voice)

[1707] Specific operation: When a user asks, "What is the difference between the economic policies of candidate A and candidate B?", the device sends this information to the server. The server uses the generative AI model to input the prompt "Please explain the difference between the economic policies of candidate A and candidate B," and sends the generated response back to the device.

[1708] Data processing: Formatting the generated response text.

[1709] Output: Displays the formatted response text to the user.

[1710] Step 8: Applying the Emotion Engine

[1711] The terminal analyzes the user's emotional state and provides information according to the emotion.

[1712] Input: User's facial expressions and voice tone data

[1713] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice tone, and then uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze emotions and identify their emotional state.

[1714] Data processing: The identified emotional state is sent to the server, and the generative AI model generates additional information adapted to the emotion.

[1715] Output: Provides the user with any additional information generated.

[1716] (Application example 2)

[1717] 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."

[1718] Conventional systems focused on collecting and analyzing election-related information, displaying it through a user interface, and providing real-time responses. However, they did not provide appropriate information or recommend products based on the user's emotional state. This made it difficult for users to obtain information or products that matched their emotions. Furthermore, incorporating emotion analysis would enable more personalized services and is expected to improve the user experience.

[1719] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1720] In this invention, the server includes means for automatically collecting information about elections using generative artificial intelligence, means for analyzing the collected information and generating a concise summary, means for classifying and organizing the analyzed information by candidate and policy and displaying it through a user interface, means for responding in real time to user questions received through the user interface, means for analyzing the user's emotional state using an emotion analysis engine and providing appropriate information based on the analysis, and means for generating product recommendations according to the user's emotional state. This makes it possible to provide information and recommend products that match the user's emotional state.

[1721] "Generative AI" is an advanced AI technology that can learn from vast amounts of data and generate sentences in natural language and perform predictive analysis.

[1722] "Means of automatically collecting information" refers to technologies such as crawlers and scrapers that automatically obtain publicly available information on the Internet and store it in a database.

[1723] The "means of analyzing information and generating a concise summary" is a generative AI algorithm that extracts key points from collected information and summarizes them in short sentences.

[1724] "Means of classifying, organizing, and displaying through a user interface" refers to a technology that divides analyzed information into specific categories and displays them in an interface that is easy for users to use.

[1725] "Real-time response means" refers to a natural language processing system and generative AI that can instantly respond to user questions and requests.

[1726] An "emotion analysis engine" is a machine learning technology that analyzes a user's facial expressions, voice, text input, etc. to identify their emotional state.

[1727] "Means of analyzing the user's emotional state and providing appropriate information based on that" refers to a generative AI that identifies and provides the information the user needs at that time based on the analyzed emotional data.

[1728] The "means for generating product recommendations" is a recommendation engine that selects and suggests products that are likely to be beneficial to a user based on the user's emotions and past purchasing history.

[1729] This invention is a system that combines generative artificial intelligence and an emotion analysis engine to automatically collect, analyze, and provide election information to users. As an example of its application to an online shopping site, we will explain an application that recommends products based on the user's emotional state.

[1730] Server-side implementation

[1731] Information gathering

[1732] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, social media, etc. The collected data is stored in a database, and duplicate data is removed through analysis.

[1733] Data analysis and formatting

[1734] The server then uses a generative AI (e.g., GPT-4) to analyze the collected data, extract key information, and generate a concise summary in natural language. The analysis process utilizes machine learning algorithms to format the data in an easy-to-understand format.

[1735] Data classification and organization

[1736] The analyzed data is classified and organized by candidate, policy, and product category, and the server uses classification algorithms (e.g., K-means clustering) to systematically manage the information within the database.

[1737] Policy comparison / analysis

[1738] Generative AI is used to automatically compare and analyze the policies and product features of candidates and political parties, extracting their differences and distinctive features. The results of this analysis are presented in a format that is easy for users to understand.

[1739] Sentiment analysis and information provision

[1740] The user's facial expressions, voice tone, text input, etc. are analyzed using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to evaluate the user's emotional state. The emotion analysis results are sent to a generative AI, which generates information and product recommendations based on the user's emotions.

[1741] User Interface Embodiments

[1742] Information provision interface

[1743] The terminal provides a user-friendly interface, allowing users to easily access the information they need. Users can search for information about candidates, policies, and products, and view the information they are interested in in detail.

[1744] Question and Answer Function

[1745] When a user inputs a question via text or voice through the device, it is sent to the server in real time, and the generative AI generates an appropriate answer to the question and displays it to the user through the device.

[1746] Emotion-based recommendations

[1747] Once the user's emotional state is analyzed, products and information tailored to that state are automatically recommended. For example, if you are feeling depressed, products with a relaxing effect will be recommended.

[1748] Specific examples

[1749] Election information provision scenario

[1750] The server automatically collects election-related articles from news sites using a crawler, and the AI ​​generator generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies." This information is stored in a database.

[1751] Recommendation function scenario for online shopping site

[1752] While a user is browsing an online shopping site through smart glasses, emotion analysis is performed. If the user is found to be depressed, products such as "relaxing aroma diffusers" are recommended in real time.

[1753] Example prompt sentences to use

[1754] "The user's emotional state is depressed. Please provide a natural-language summary of relaxation products that fit this emotion. Please include specific product names and features."

[1755] In this way, the present invention provides a system that allows users to easily obtain election information and receive product recommendations that match their emotional state.

[1756] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1757] Step 1:

[1758] The server uses a crawler to automatically collect election-related and product information from online news sites, official websites, and social media. Specifically, the crawler periodically visits each website, detecting and retrieving new articles and posts. This allows the server to collect the latest election information, product reviews, and more. The input data is text information retrieved from each website, and the output is stored in a database as collected raw data.

[1759] Step 2:

[1760] The server analyzes the collected raw data using a generative AI (e.g., GPT-4), extracts important information, and generates a concise summary. In this step, a machine learning algorithm is used to input text data and output key points such as summaries and headlines. Specifically, the generative AI analyzes the text data and generates a summary such as, "Candidate A proposes tax increases and strengthens infrastructure investment as economic policies."

[1761] Step 3:

[1762] The server then classifies and organizes the generated summary data by candidate, policy, or product category. Using a classification algorithm (e.g., K-means clustering), it assigns each data point to the appropriate category. The input data is the summarized text, and the output is data organized by category. This step ensures that the information is managed systematically and can be easily searched by users.

[1763] Step 4:

[1764] The server uses generative AI to automatically compare and analyze the characteristics of the policies and products of each candidate and political party, extracting their differences and characteristics. Specifically, it compares candidates such as "Candidate A proposes tax increases and strengthens infrastructure investment" with "Candidate B advocates tax cuts and plans to expand support for small and medium-sized businesses." In this process, the input data is summary information about each candidate, and the output is the compared and analyzed text.

[1765] Step 5:

[1766] When a user inputs a question via text or voice through their device, the question is sent to the server in real time. The server's generation AI generates an appropriate answer to the question and returns the answer to the device. The input data is the user's question, and the output data is the answer generated by the generation AI. Specifically, it returns detailed comparison results in response to a question such as, "Please tell me about the differences in economic policies between candidate A and candidate B."

[1767] Step 6:

[1768] The emotion analysis engine (e.g., Microsoft Azure Emotion API) analyzes the user's facial expressions, voice tone, text input, etc. to evaluate the user's emotional state. The input in this step is facial expression and voice data obtained from the user's camera and microphone, and the output is analyzed emotional information. Based on the analysis results, the generative AI provides information corresponding to the user's emotions.

[1769] Step 7:

[1770] Based on the user's emotional state, the results of the emotion analysis are sent to a generation AI, which then generates product and information recommendations tailored to the user's state. The input data is the emotion analysis results, and the output data is product recommendations optimal for the user. Specifically, if the emotion analysis reveals that the user is in a depressed state, the system will recommend an "aroma diffuser with a relaxing effect."

[1771] In this way, a system is realized in which the server and terminal cooperate to recommend optimal information and products to the user.

[1772] 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.

[1773] 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.

[1774] 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.

[1775] 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.

[1776] 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.

[1777] 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.

[1778] 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).

[1779] 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.

[1780] 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."

[1781] 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.

[1782] 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 ...

Claims

1. A means for automatically collecting information about elections using generative artificial intelligence; means for analyzing the collected information and generating a concise summary; A means for classifying and organizing the analyzed information by candidate and policy, and displaying it through a user interface; means for responding in real time to user queries received through said user interface; A system including:

2. The system of claim 1 further comprising means for automatically comparing and analyzing the policies of each candidate and political party using generative artificial intelligence and extracting the differences and characteristics thereof.

3. The system of claim 1 , further comprising means for generating explanatory statements about the evaluation points and impacts of each policy using expert-generated artificial intelligence.

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