system

Abstract

We provide the system. [Solution] The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing said information in a database, A means for extracting candidate pledges and policy information from the information stored in the database using natural language processing technology, An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, A means for presenting the aforementioned evaluation results via a user interface, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In recent years, the voter turnout in elections has been decreasing, and many voters lack materials for judging who to vote for. One of the main reasons is that information on the policies, pledges, and past achievements of candidates is not sufficiently provided, making it difficult for voters to make decisions based on information. With conventional methods, voters themselves had to collect and analyze information individually, and there was also a problem in ensuring the reliability and objectivity of the information. 【Means for Solving the Problems】 【0005】 This invention provides a system in which an information processing device automatically acquires information about candidates from multiple information sources on an electronic network and extracts candidates' pledges and policy information from that information using natural language processing technology. Furthermore, this system includes an evaluation means for evaluating past performance and the feasibility of fulfilling pledges, and provides the evaluation results to voters through a user interface. This creates an environment in which voters can easily compare and analyze election candidates and supports informed decision-making. The system also includes a search means for receiving questions from users about policies and candidates and presenting corresponding information, and continuously tracks the progress of pledges and provides the latest information. This provides a means for voters to evaluate candidates' activities even after the election. 【0006】 An "information processing device" is a general term for electronic devices used to collect, process, store, and display information. 【0007】 An "electronic network" is a collection of communication lines and related infrastructure that enable the electronic transmission and reception of information, including the Internet. 【0008】 "Information sources" refer to media outlets, websites, and social media platforms from which information related to a candidate is disseminated. 【0009】 "Natural language processing technology" refers to the technology that enables computers to understand, generate, and process human language. 【0010】 A "campaign promise" refers to the policies and specific action plans that a candidate promises to implement if elected. 【0011】 "Policy information" refers to information about the solutions or policies that a candidate proposes for a particular issue. 【0012】 A "database" is an electronic information management system that systematically stores large amounts of information and data, making it easy to search and retrieve. 【0013】 "Evaluation methods" refer to methods or systems for analyzing a candidate's promises and achievements and scoring or judging the results based on certain criteria. 【0014】 "User interface" refers to the screens and operating methods that users use to interact with a system and input or retrieve information. 【0015】 A "search method" is a method or system for searching a database based on a specific request from a user and retrieving relevant information. 【0016】 "Progress status" refers to information that indicates the current stage of a pledge or project and how much has been achieved. [Brief explanation of the drawing] 【0017】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10]Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0018】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings. 【0019】 First, the language used in the following description will be explained. 【0020】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0021】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0022】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0023】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0024】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0025】 [First Embodiment] 【0026】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0027】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0028】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0029】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0030】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0031】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0032】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0033】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0034】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0035】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0036】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0037】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0038】 This invention is a system that uses an information processing device to analyze candidates' promises and achievements and provides useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0039】 Server Processing 【0040】 The server is the central hub for data collection, acquiring information about candidates from multiple sources on the electronic network. This includes candidates' official social media accounts and the websites of major news organizations. Crawler programs are run to automatically collect and store this information. Natural language processing is then used on the collected data to extract candidates' pledges and relevant policy information, which is then stored in a database as structured data. 【0041】 To analyze the information stored in the database, the server activates an evaluation algorithm. This algorithm quantifies each candidate's past performance and the likelihood of fulfilling their promises, and calculates an evaluation score. The evaluation score serves as an indicator to help users compare candidates more easily. 【0042】 Furthermore, the server regularly updates the database and tracks the progress of candidates' promises, ensuring that users are always provided with the latest information. 【0043】 Terminal processing 【0044】 The terminal provides information to the user through a user interface. When the user operates the terminal and selects a specific electoral district or candidate, the terminal sends a query to the server and retrieves the corresponding information. Based on the retrieved data, a list of candidates, details of their pledges, and information on their past performance are displayed. This information is visualized in tables and graphs to make it easy for the user to understand. 【0045】 User actions 【0046】 Users can use their devices to select candidates they are interested in and view detailed information. For example, if a user is interested in "building a medical center in front of the train station," they can search for information related to that policy and see the positions of both proponents and opponents displayed on their device. 【0047】 This system will enable users to make informed decisions and support their decision-making when participating in elections. 【0048】 The following describes the processing flow. 【0049】 Step 1: 【0050】 The server launches a crawler program to collect information related to the candidate from multiple sources on the electronic network. It retrieves the latest posts and articles from official social media accounts and news organizations' websites and saves them as text data. 【0051】 Step 2: 【0052】 The server runs a natural language processing algorithm on the stored text data. The algorithm analyzes and extracts candidate promises and policy information. The extracted information is stored in a database as structured data. 【0053】 Step 3: 【0054】 The server uses information from the database to evaluate each candidate's past performance and the likelihood of fulfilling their promises. An evaluation algorithm is executed, and a score is calculated for each candidate. This score is determined based on the quality and reliability of the information. 【0055】 Step 4: 【0056】 The server updates the database at regular intervals. When new information is collected, it updates the existing data and tracks the progress of the commitments. This ensures that users are provided with the most up-to-date information. 【0057】 Step 5: 【0058】 The terminal displays the user interface and prepares to receive the user. If the user selects details about a specific candidate or policy, the terminal sends a query to the server. 【0059】 Step 6: 【0060】 The server receives queries from the terminal, searches the database for the relevant data, and then sends the information back to the terminal. 【0061】 Step 7: 【0062】 The terminal displays candidate lists, detailed pledges, and comparable visual information on its screen based on data received from the server. Information is presented in tables and graphs on the user interface, making it easy for users to understand. 【0063】 Step 8: 【0064】 Users view information provided on their devices and research candidates and policies that interest them in detail. They find candidates that meet their criteria and make voting decisions based on that information. 【0065】 (Example 1) 【0066】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0067】 In recent years, it has become crucial for voters to make informed and informed decisions in elections. However, information about candidates is vast and fragmented, making its analysis and understanding extremely difficult. Furthermore, there are insufficient means to track the progress and feasibility of candidates' promises, and a comprehensive system to assist voters in making informed decisions does not exist. Addressing these challenges is essential. 【0068】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0069】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing the information in a data storage medium; means for extracting candidates' pledges and policy information from the information stored in the data storage medium using natural language processing technology; and means for generating evaluation scores for candidates and using the scores as evaluation indicators. This enables users to compare candidates based on quantitative evaluations. Furthermore, by including means for creating prompt sentences for a generative AI model and presenting them to the user, flexible responses to a variety of questions become possible. 【0070】 An "information processing device" is an electronic device used for collecting, analyzing, storing, and presenting data. 【0071】 "Data collection means" refers to technology that has the function of automatically acquiring target information from multiple information sources on an electronic network. 【0072】 A "data storage medium" is a physical or electronic storage device used to record and retain acquired information over a long period of time. 【0073】 "Natural language processing technology" refers to computational techniques that analyze text data written in human language to extract or understand specific information. 【0074】 "Evaluation means" refers to an algorithm or method for quantifying or scoring a specific object based on acquired information. 【0075】 A "display device" is a digital screen or related device used to visually present information to a user. 【0076】 An "evaluation score" is a value calculated using an evaluation method and is a numerical value used as a comparable indicator. 【0077】 A "generative AI model" is a computer program or system that uses artificial intelligence to generate output from specific input data. 【0078】 A "prompt statement" is a form of instruction or question input to a generative AI model to elicit a specific response. 【0079】 This invention relates to a system that uses an information processing device to collect and analyze diverse information about candidates and provide useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0080】 The server is the central device for data collection. The server runs a crawler program to automatically retrieve candidate information from multiple sources on the electronic network. This crawler program, built using, for example, Python, downloads data from candidates' official social media accounts and news organizations' websites. The retrieved text data is analyzed using natural language processing tools (e.g., NLTK or SpaCy) to extract keywords related to the candidates' pledges and policies. The analyzed data is stored in a structured format in a database. 【0081】 The terminal plays the role of providing information to the user through an interface. When a user requests information about a specific electoral district or candidate, the terminal sends a query to the server, retrieves the relevant information, and displays it. The displayed information is then formatted into a visualized form, such as a table or graph, to facilitate comparison and understanding. 【0082】 Users can select candidates they are interested in via their device and view detailed information. For example, if a user expresses interest in "building a medical center in front of the train station," they can search for information related to that policy and check the positions of candidates who support and oppose it. It is also possible to use generative AI models to create prompts for specific questions, and the AI ​​can organize and present information about the candidates. 【0083】 For example, if a user wants to know "the candidates' opinions on the greening project," they can efficiently obtain the desired information by inputting a prompt into the AI ​​model that says, "Compare the promises and achievements of the candidates promoting the greening project." In this way, the present invention functions as an advanced information provision system that supports decision-making in elections. 【0084】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0085】 Step 1: 【0086】 The server uses data collection tools to obtain information about candidates from multiple sources on the electronic network. It receives a list of URLs for candidates' official social media accounts and news organizations as input, and executes a crawler program (e.g., Python's Scrapy) based on this. Specifically, the server sends an HTTP request to each URL and downloads HTML content from the web pages. The output is a collection of raw text data. 【0087】 Step 2: 【0088】 The server performs natural language processing on the acquired text data. It receives the text data obtained in step 1 as input. The server tokenizes the text using Python's NLTK or SpaCy and extracts important keywords and phrases. Specific operations include morphological analysis and keyword matching. The output is structured data containing candidate pledges and policy information. 【0089】 Step 3: 【0090】 The server applies an evaluation algorithm based on the extracted information. It receives the structured data generated in step 2 as input. The evaluation algorithm calculates an evaluation score for each candidate based on the feasibility of fulfilling their promises and their past performance. Specifically, it performs numerical scoring and applies statistical models. The output is a list of candidates assigned evaluation scores. 【0091】 Step 4: 【0092】 The terminal sends queries to the server based on user requests to retrieve candidate information. The input consists of the electoral district and candidate criteria specified by the user. The terminal processes the retrieved information and generates tables and graphs for visual presentation to the user. Specific operations include sending and receiving SQL queries to and from the database and formatting the information. The output is detailed information that the user can view on the terminal. 【0093】 Step 5: 【0094】 Users use their devices to view detailed information about candidates and policies they are interested in and ask questions to a generative AI model. For example, a user might input the prompt, "Please tell me the latest pledges of candidates who focus on environmental policy and their evaluation scores," and the model would then present the corresponding information. The input consists of the user's questions and filter conditions, while the output is candidate information and proposals organized by the generative AI model. 【0095】 (Application Example 1) 【0096】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0097】 In modern elections, a challenge exists in that voters find it difficult to fully understand candidates' promises and track records, and to make appropriate comparisons and evaluations. They are often overwhelmed by the sheer volume of information and the complexity of the policies, resulting in an inability to make informed decisions. Furthermore, voters want to efficiently obtain information directly relevant to their interests, but existing methods are insufficient to do so. 【0098】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0099】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic communication network and storing it in an information aggregator; means for extracting pledges and policy information from the stored information using natural language processing technology; and means for analyzing the similarities between candidates and highlighting and visualizing the most relevant information in order to provide information based on the user's interests. This enables voters to efficiently compare information on each candidate and make informed decisions. 【0100】 An "information processing device" is an electronic device used to collect data, perform analysis based on that data, and provide information to users. 【0101】 An "electronic communication network" is a communication infrastructure that enables the exchange of information via the internet and other means. 【0102】 "Information sources" refer to various media outlets, such as websites, official accounts, and news organizations, that provide information about the candidates. 【0103】 "Information aggregation" refers to a database that centrally stores acquired data to prepare it for later analysis and retrieval. 【0104】 "Natural language processing technology" is a technique for extracting useful information from text data and converting it into a format that humans can understand. 【0105】 A "campaign promise" is a set of policy promises that an election candidate makes to voters during their campaign. 【0106】 "Policy information" refers to data on specific policies related to campaign promises, as well as past performance. 【0107】 An "evaluation tool" is a system for quantifying the feasibility of a candidate's promises and achievements and conducting comparative analysis. 【0108】 A "user interface" refers to screens and output methods that allow users to visually understand the collected data and evaluation results. 【0109】 "Similarity analysis" is a method for identifying similarities in policies and promises among different candidates and visualizing their relative positions. 【0110】 This invention is centered around an information processing device and is realized with three main components: a server, a terminal, and a user. 【0111】 First, the server collects information about candidates from multiple sources via an electronic communication network. A crawler program is used to automatically retrieve data, which is then stored in an information repository. The stored information is effectively managed using Python libraries such as BeautifulSoup and requests. Next, natural language processing techniques are used to extract candidate pledges and policy information from the stored data. Specifically, TfidfVectorizer is used to vectorize text data, and then information summarization and semantic analysis are performed. 【0112】 The terminal is responsible for displaying information via a user interface based on the provided data. Based on the extracted information, it evaluates the candidates' past performance and the feasibility of fulfilling their promises. This evaluation process uses technologies such as cosine_similarity to analyze the similarities of policies among candidates and highlights more relevant information. This visualized information is presented in graphs and tables, making it easy for users to understand. 【0113】 Users interact with their devices to obtain information based on their interests. For example, when seeking information on candidates with pledges related to "environmental policy," they use prompts to request specific information from the server. A concrete example of such a prompt might be: "Please collect information on candidates with pledges focused on environmental policy and generate an evaluation score." 【0114】 This allows users to efficiently compare the promises and track records of multiple candidates and make informed decisions. The entire system aims to support voters in elections by processing data quickly and accurately. 【0115】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0116】 Step 1: 【0117】 The server collects information about candidates from multiple sources via an electronic communication network. The input is a list of website URLs. The server accesses the web pages using the requests library and parses the HTML structure using BeautifulSoup. The parsed data is stored in an information repository. The output is a structured list of candidate information. 【0118】 Step 2: 【0119】 The server applies natural language processing techniques to the stored information. Specifically, it uses the text data acquired as input and vectorizes it using TfidfVectorizer. This process extracts pledges and policy information. As output, data is generated in which the topics of the text have been vectorized. 【0120】 Step 3: 【0121】 The server evaluates candidates' pledges and past performance based on vectorized data. It uses `cosine_similarity` to calculate textual similarity. The input data consists of vectorized policy information for each candidate. The output generates a matrix of similarity scores, enabling comparative analysis of candidates. 【0122】 Step 4: 【0123】 The terminal displays the evaluation results received from the server on the user interface. Similarity scores and evaluation scores obtained from the server are provided as input. The terminal visualizes the results in graph and table format and provides them to the user. The visualized data is displayed on the screen as output, converted into a format easily understandable to the user. 【0124】 Step 5: 【0125】 Users search for information about campaign promises and policies that interest them through their terminal. Prompts related to specific policies are used as input. Based on the user's interests, the terminal sends queries to the server. The output displayed on the terminal includes relevant candidate information and evaluation scores. 【0126】 Step 6: 【0127】 Users compare candidates' policies and make decisions based on the information presented. They utilize visualized information and reliable data as input. The output is a decision based on the user's selection, which is then used as a basis for their election participation decisions. 【0128】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0129】 This invention combines a system that provides information based on candidates' promises and policies with an emotion engine that analyzes user emotions. The system comprises an information processing device, a user interface, and an emotion engine. 【0130】 Server Processing 【0131】 The server efficiently collects information related to candidates from the electronic network and uses natural language processing to extract candidates' pledges and policies into a database. Furthermore, it evaluates candidates' past performance and the feasibility of fulfilling their pledges, and generates data to present the evaluation results in the user interface. 【0132】 Emotional Engine Processing 【0133】 The emotion engine analyzes user input through the user interface and recognizes their emotional state. For example, it determines the user's level of interest and stress when researching information about election candidates. This data is received by the server and used to adjust how information is presented in the user interface. 【0134】 Terminal processing 【0135】 The terminal provides a user interface, displaying detailed information about candidates and offering information tailored to the user's emotions. After data from the emotion engine is analyzed by the server, the terminal prioritizes and displays the information most relevant to that user. For example, if a user expresses interest in a particular policy, it highlights and displays information about relevant candidates. 【0136】 The device also uses an emotion engine to recognize the user's emotions in response to a question. For example, if the user indicates anxiety, the device will present information to alleviate that anxiety or data on the candidate's trustworthiness. 【0137】 User actions 【0138】 Users can research specific candidates and policies through the device's user interface. By recognizing the user's emotions through an emotion engine, the system can provide personalized information tailored to the user, increasing their interest in the election campaign and helping them make more informed decisions. This allows users to participate more actively in the election. 【0139】 The following describes the processing flow. 【0140】 Step 1: 【0141】 The server uses a crawler program to collect data about candidates from multiple sources on the electronic network. This includes the candidates' official social media accounts and the websites of major news organizations. The collected information is stored on the server in text format. 【0142】 Step 2: 【0143】 The server uses natural language processing algorithms to analyze the stored text data. The algorithms extract pledges and policy information from the text and store this information in a database as structured data. 【0144】 Step 3: 【0145】 The server runs an evaluation algorithm that assesses candidates' past performance and the feasibility of fulfilling their promises based on a database. The evaluation results are calculated as a score that facilitates comparison between candidates. 【0146】 Step 4: 【0147】 The emotion engine built into the server receives input from the user and analyzes the user's emotional state. In this process, it evaluates the user's level of interest and stress based on the words used and the information selected. 【0148】 Step 5: 【0149】 The terminal receives evaluation results and sentiment engine analysis data from the server via the user interface. The user interface is adjusted according to the user's emotions and prioritizes the presentation of relevant candidate information. 【0150】 Step 6: 【0151】 Users interact with the device to express interest in candidates and policies and view detailed information. For example, if a user expresses interest in a particular policy, the device will highlight the positions and evaluations of candidates related to that policy. 【0152】 Step 7: 【0153】 When a user makes a query on their device, the sentiment engine recognizes the user's emotion in response to that question. The server then presents information about candidates and policies that address the question, taking the user's emotional state into consideration. 【0154】 Step 8: 【0155】 The device optimizes the information displayed on the screen based on updated information and user sentiment analysis results. This allows users to receive more accurate and personalized information to help them make informed decisions. 【0156】 (Example 2) 【0157】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0158】 In modern election campaigns, it is crucial for voters to make informed decisions based on candidates' promises and achievements. However, efficiently obtaining useful information from a vast amount of data is difficult. Furthermore, providing information tailored to each voter's emotional state and maintaining their interest is also challenging. Therefore, there is a need for a system that personalizes information based on the emotions and interests of individual users, providing higher-quality information. 【0159】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0160】 In this invention, the server includes means for acquiring information from information sources on a communication network, which serve as an information aggregation unit; means for extracting information using natural language processing technology; and means for recognizing the user's emotional state, which are equipped with an emotion analysis unit. This enables the user to receive information that is tailored to their emotions and interests quickly and accurately. 【0161】 An "information aggregation unit" is a function that collects data from various information sources on a communication network and stores it in a memory device within the system. 【0162】 A "communication network" is a network system that enables digital communication, including the internet, and is used for acquiring and transmitting data. 【0163】 A "storage device" is a storage medium or device that holds data within a system and makes it accessible as needed. 【0164】 "Natural language analysis technology" refers to techniques for analyzing meaning from text data and extracting useful information, and includes natural language processing. 【0165】 An "emotional analysis unit" is a function within a system that analyzes user input data to recognize emotional states and psychological tendencies. 【0166】 A "presentation device" is a device or interface that displays information to a user visually or audibly. 【0167】 An "evaluation unit" is a function within a system that evaluates a candidate's past actions and the feasibility of fulfilling their promises, and generates results. 【0168】 A "search unit" is a function that searches for information within a storage device in response to a specific question from the user and retrieves the relevant information. 【0169】 This invention demonstrates a combination of hardware and software that enables the construction of a system that efficiently collects and analyzes candidate pledges and policy information and provides information in accordance with the user's emotions. 【0170】 The server first collects data from internet sources via a communication network. This involves using web crawlers and data acquisition technologies via APIs. The collected data is stored in storage. For natural language processing, open-source natural language processing tools such as NLTK and SpaCy are used to structure the data and extract necessary information. This process yields information on campaign promises and policies, as well as information on candidates' past performance. 【0171】 The server also has an emotion analysis unit that analyzes text data entered by the user through the terminal in real time. This process uses emotion analysis APIs and machine learning models to identify the user's emotional state. For example, it determines the level of interest and stress based on the speed and content of the user's typing. 【0172】 The terminal receives analysis results transmitted from the server and provides them to the user through a display device. In this process, information is visualized using HTML and CSS, and presented in a user-friendly interface. Furthermore, based on data obtained from sentiment analysis, highly relevant information is prioritized and displayed. 【0173】 Furthermore, the system uses a generative AI model to enable users to resolve their questions through prompts. A typical prompt might be something like, "Tell me how your views on tax reform differ from those of the other candidates." Based on this prompt, the AI ​​model scrutinizes the information most useful to the user and generates a response. 【0174】 In this way, the system enables the provision of information that is tailored to the user's interests and emotions, and supports their decision-making. 【0175】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0176】 Step 1: 【0177】 The server collects information about candidates from multiple sources on the internet via a communication network. Using specified keywords and URL lists as input, it extracts relevant data through web crawling techniques. As output, it stores text data containing candidate information in a temporary storage area. 【0178】 Step 2: 【0179】 The server processes the collected information using natural language processing (NLP) techniques. The input is text data, and natural language processing tools are used to tokenize sentences, tag parts of speech, and perform semantic analysis. The output is structured data, such as candidates' pledges, policies, and past achievements. This process includes converting the data into a format that can be stored in a database. 【0180】 Step 3: 【0181】 The terminal accepts queries through the user interface. It receives a request for information on a specified policy or candidate from the user as input, and then queries the server based on that information. The output is a visual presentation of relevant details to the user. Specifically, it uses HTML / CSS to format and display the information clearly. 【0182】 Step 4: 【0183】 The emotion analysis unit continuously monitors user input through the interface. It analyzes user text input and interaction patterns as input, quantifying the emotional state. The output is data regarding the user's level of interest and emotional state, which is used to determine the optimal method of information presentation. 【0184】 Step 5: 【0185】 The server personalizes information presentation based on sentiment analysis results. The input is data from sentiment analysis, and an algorithm is applied to prioritize information that the user is most likely to be interested in. The output is a selection and highlighting of the most relevant information for the user, thereby supporting the user in obtaining the most optimal information from the system. 【0186】 Step 6: 【0187】 The generative AI model generates responses in response to user prompts. It receives prompts as input and uses natural language generation techniques to generate relevant answers. The output is a text response to the user's question, which is presented in real time through the interface. 【0188】 (Application Example 2) 【0189】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0190】 In modern elections, voters must sift through a vast amount of information about candidates' promises and policies, and spend considerable time and effort judging whether that information aligns with their interests. Furthermore, because emotions related to the information are not taken into account, there is a high likelihood of anxiety and mismatches of interests. 【0191】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0192】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network and storing it in a database, means for extracting candidates' pledges and policy information from the stored information using natural language processing technology, and means for presenting information tailored to the user's interests and emotions using sentiment analysis results. This makes it possible for users to quickly and easily obtain election information that matches their interests and emotions. 【0193】 An "information processing device" is a device that collects and processes data from multiple information sources via an electronic network. 【0194】 A "data collection method" is a means that has the function of acquiring information through an electronic network and storing it in a database. 【0195】 "Natural language processing technology" is a technology that analyzes human language and extracts information from it. 【0196】 An "evaluation tool" is a means that has the function of evaluating a candidate's past performance and the feasibility of fulfilling their promises based on extracted information. 【0197】 "User interface" refers to the screens or consoles that users use to interact with a system. 【0198】 "Emotional analysis tools" are functions that analyze a user's emotional state based on their input and behavior. 【0199】 An "information presentation means" is a means that has the function of presenting collected information to the user in an appropriate format. 【0200】 A "database" is a structure for organizing and storing information so that it can be accessed efficiently. 【0201】 A "search function" is a feature that allows users to quickly retrieve the information they need from a database. 【0202】 This invention is a system for providing election information and is built around an information processing device. The system includes multiple components, each with its own role in processing information. 【0203】 The server collects data on candidates from numerous sources via an electronic network and stores it in a database. The server also uses natural language processing technologies (e.g., spaCy and NLTK) to analyze the information in the database and extract candidate promises and policy information. Based on the extracted data, it evaluates the candidate's past performance and the feasibility of fulfilling their promises. Furthermore, it uses a sentiment analysis engine (e.g., IBM Watson® Tone Analyzer) to analyze the user's emotional state from their input and behavior. This allows the server to adjust the information presented according to the user's interests and emotions, displaying particularly high-demand information in the user interface. 【0204】 The device displays relevant information to the user through its user interface. Detailed information on policies of interest to the user is presented in a highlighted format. Furthermore, the results of sentiment analysis are used to provide additional information beneficial to the user. In this process, the aim is to improve the user experience by prioritizing the presentation of areas of particular user interest. 【0205】 For example, if a user uses a smartphone app and expresses interest in "environmental policy," the system will prioritize displaying relevant policy information, presenting past success stories and reliable data. Additionally, based on the user's concerns and interests, the system will provide information that alleviates their emotions or piques their specific interest. 【0206】 An example of a prompt might be, "Please describe in detail the candidate's track record, which could be helpful in providing information if the user is feeling anxious." This prompt prompts the system to select and present appropriate information through the user interface. 【0207】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0208】 Step 1: 【0209】 The server collects information about candidates from various sources via an electronic network. The input is data from each source, and the output is data stored in a processable format. A data collection module on the server performs this task, and the resulting data is stored in a database. 【0210】 Step 2: 【0211】 The server uses natural language processing techniques to extract candidate pledges and policy information from the database. The input is raw data from the database, and the output is organized information about pledges and policies. Natural language processing libraries (e.g., spaCy, NLTK) are applied to classify and organize the information. 【0212】 Step 3: 【0213】 The server evaluates the candidate's past performance and the feasibility of fulfilling their promises based on the extracted information. The input is the information obtained in step 2, and the output is the evaluation result. The evaluation algorithm analyzes the feasibility of fulfilling promises using past performance data and generates an evaluation score. 【0214】 Step 4: 【0215】 The sentiment analysis engine analyzes user input via the user interface to recognize the emotional state. The input is real-time data from the user, and the output is analyzed sentiment data. The sentiment analysis engine (e.g., IBM Watson Tone Analyzer) performs this task and outputs the results. 【0216】 Step 5: 【0217】 The device adjusts information based on the user's interests and emotions, using sentiment analysis results. Input consists of output data from the sentiment analysis engine and evaluation results from the server. The device's algorithm analyzes the data and adjusts the information presented based on priority. 【0218】 Step 6: 【0219】 Users review the organized information through the user interface. The input is organized information presented from the device, and the output is useful information to aid in the user's decision-making. The user interface presents highlighted information and relevant data, which the user uses to select candidates. 【0220】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0221】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0222】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0223】 [Second Embodiment] 【0224】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0225】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0226】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0227】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0228】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0229】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0230】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0231】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0232】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0233】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0234】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0235】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0236】 This invention is a system that uses an information processing device to analyze candidates' promises and achievements and provides useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0237】 Server Processing 【0238】 The server is the central hub for data collection, acquiring information about candidates from multiple sources on the electronic network. This includes candidates' official social media accounts and the websites of major news organizations. Crawler programs are run to automatically collect and store this information. Natural language processing is then used on the collected data to extract candidates' pledges and relevant policy information, which is then stored in a database as structured data. 【0239】 To analyze the information stored in the database, the server activates an evaluation algorithm. This algorithm quantifies each candidate's past performance and the likelihood of fulfilling their promises, and calculates an evaluation score. The evaluation score serves as an indicator to help users compare candidates more easily. 【0240】 Furthermore, the server regularly updates the database and tracks the progress of candidates' promises, ensuring that users are always provided with the latest information. 【0241】 Terminal processing 【0242】 The terminal provides information to the user through a user interface. When the user operates the terminal and selects a specific electoral district or candidate, the terminal sends a query to the server and retrieves the corresponding information. Based on the retrieved data, a list of candidates, details of their pledges, and information on their past performance are displayed. This information is visualized in tables and graphs to make it easy for the user to understand. 【0243】 User actions 【0244】 Users can use their devices to select candidates they are interested in and view detailed information. For example, if a user is interested in "building a medical center in front of the train station," they can search for information related to that policy and see the positions of both proponents and opponents displayed on their device. 【0245】 This system will enable users to make informed decisions and support their decision-making when participating in elections. 【0246】 The following describes the processing flow. 【0247】 Step 1: 【0248】 The server launches a crawler program to collect information related to the candidate from multiple sources on the electronic network. It retrieves the latest posts and articles from official social media accounts and news organizations' websites and saves them as text data. 【0249】 Step 2: 【0250】 The server runs a natural language processing algorithm on the stored text data. The algorithm analyzes and extracts candidate promises and policy information. The extracted information is stored in a database as structured data. 【0251】 Step 3: 【0252】 The server uses information from the database to evaluate each candidate's past performance and the likelihood of fulfilling their promises. An evaluation algorithm is executed, and a score is calculated for each candidate. This score is determined based on the quality and reliability of the information. 【0253】 Step 4: 【0254】 The server updates the database at regular intervals. When new information is collected, it updates the existing data and tracks the progress of the commitments. This ensures that users are provided with the most up-to-date information. 【0255】 Step 5: 【0256】 The terminal displays the user interface and prepares to receive the user. If the user selects details about a specific candidate or policy, the terminal sends a query to the server. 【0257】 Step 6: 【0258】 The server receives queries from the terminal, searches the database for the relevant data, and then sends the information back to the terminal. 【0259】 Step 7: 【0260】 The terminal displays candidate lists, detailed pledges, and comparable visual information on its screen based on data received from the server. Information is presented in tables and graphs on the user interface, making it easy for users to understand. 【0261】 Step 8: 【0262】 Users view information provided on their devices and research candidates and policies that interest them in detail. They find candidates that meet their criteria and make voting decisions based on that information. 【0263】 (Example 1) 【0264】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0265】 In recent years, it has become crucial for voters to make informed and informed decisions in elections. However, information about candidates is vast and fragmented, making its analysis and understanding extremely difficult. Furthermore, there are insufficient means to track the progress and feasibility of candidates' promises, and a comprehensive system to assist voters in making informed decisions does not exist. Addressing these challenges is essential. 【0266】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0267】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing the information in a data storage medium; means for extracting candidates' pledges and policy information from the information stored in the data storage medium using natural language processing technology; and means for generating evaluation scores for candidates and using the scores as evaluation indicators. This enables users to compare candidates based on quantitative evaluations. Furthermore, by including means for creating prompt sentences for a generative AI model and presenting them to the user, flexible responses to a variety of questions become possible. 【0268】 An "information processing device" is an electronic device used for collecting, analyzing, storing, and presenting data. 【0269】 "Data collection means" refers to technology that has the function of automatically acquiring target information from multiple information sources on an electronic network. 【0270】 A "data storage medium" is a physical or electronic storage device used to record and retain acquired information over a long period of time. 【0271】 "Natural language processing technology" refers to computational techniques that analyze text data written in human language to extract or understand specific information. 【0272】 "Evaluation means" refers to an algorithm or method for quantifying or scoring a specific object based on acquired information. 【0273】 A "display device" is a digital screen or related device used to visually present information to a user. 【0274】 An "evaluation score" is a value calculated using an evaluation method and is a numerical value used as a comparable indicator. 【0275】 A "generative AI model" is a computer program or system that uses artificial intelligence to generate output from specific input data. 【0276】 A "prompt statement" is a form of instruction or question input to a generative AI model to elicit a specific response. 【0277】 This invention relates to a system that uses an information processing device to collect and analyze diverse information about candidates and provide useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0278】 The server is the central device for data collection. The server runs a crawler program to automatically retrieve candidate information from multiple sources on the electronic network. This crawler program, built using, for example, Python, downloads data from candidates' official social media accounts and news organizations' websites. The retrieved text data is analyzed using natural language processing tools (e.g., NLTK or SpaCy) to extract keywords related to the candidates' pledges and policies. The analyzed data is stored in a structured format in a database. 【0279】 The terminal plays the role of providing information to the user through an interface. When a user requests information about a specific electoral district or candidate, the terminal sends a query to the server, retrieves the relevant information, and displays it. The displayed information is then formatted into a visualized form, such as a table or graph, to facilitate comparison and understanding. 【0280】 The user can select candidates of interest via the terminal and view detailed information. For example, if the user shows interest in the "Construction of a medical center near the station", the user can search for information related to that policy and check the positions of candidate proponents and opponents. It is also possible to utilize a generative AI model to create a prompt sentence for a specific question, and have the AI organize and present the information of the candidates. 【0281】 As a specific example, when the user wants to know the "opinions of candidates regarding the greening project", by inputting the prompt sentence "Please compare the pledges and achievements of candidates who promote the greening project" into the generative AI model, the user can efficiently obtain the information they seek. In this way, the present invention functions as an advanced information provision system that supports decision-making in elections. 【0282】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0283】 Step 1: 【0284】 The server uses data collection means to obtain information about candidates from multiple information sources on the electronic network. As input, it receives the official SNS accounts of the candidates and a list of URLs of news agencies, and based on this, executes a crawler program (e.g., Scrapy in Python). As a specific operation, the server sends an HTTP request to each URL and downloads HTML content from the web page. The output is a collection of raw text data. 【0285】 Step 2: 【0286】 The server performs natural language processing on the acquired text data. As input, it receives the text data obtained in Step 1. The server tokenizes the text using NLTK or SpaCy in Python and extracts important keywords and phrases. Specific operations include morphological analysis and keyword matching. The output is structured data containing the candidates' conventions and policy information. 【0287】 Step 3: 【0288】 The server applies an evaluation algorithm based on the extracted information. As input, it receives the structured data generated in Step 2. The evaluation algorithm calculates an evaluation score based on the feasibility of each candidate's convention and past performance. Specific operations include numerical scoring and application of statistical models. The output is a list of candidates with evaluation scores assigned. 【0289】 Step 4: 【0290】 The terminal sends a query to the server based on the user's request and obtains candidate information. The input is the constituency and candidate conditions specified by the user. The terminal processes the acquired information and generates tables and graphs for visually presenting to the user. Specific operations include sending and receiving SQL queries to and from the database and formatting the information. The output is detailed information that the user can view on the terminal. 【0291】 Step 5: 【0292】 The user uses the terminal to view detailed information about candidates and policies of interest and asks questions to the generative AI model. As a specific example, the user inputs a prompt such as "Please tell me the latest convention of the candidates focusing on environmental policies and their evaluation scores", and the model presents the corresponding information. The input is the user's question or filter conditions, and the output is candidate information and proposals organized by the generative AI model. 【0293】 (Application Example 1) 【0294】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0295】 In modern elections, a challenge exists in that voters find it difficult to fully understand candidates' promises and track records, and to make appropriate comparisons and evaluations. They are often overwhelmed by the sheer volume of information and the complexity of the policies, resulting in an inability to make informed decisions. Furthermore, voters want to efficiently obtain information directly relevant to their interests, but existing methods are insufficient to do so. 【0296】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0297】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic communication network and storing it in an information aggregator; means for extracting pledges and policy information from the stored information using natural language processing technology; and means for analyzing the similarities between candidates and highlighting and visualizing the most relevant information in order to provide information based on the user's interests. This enables voters to efficiently compare information on each candidate and make informed decisions. 【0298】 An "information processing device" is an electronic device used to collect data, perform analysis based on that data, and provide information to users. 【0299】 An "electronic communication network" is a communication infrastructure that enables the exchange of information via the internet and other means. 【0300】 "Information sources" refer to various media outlets, such as websites, official accounts, and news organizations, that provide information about the candidates. 【0301】 "Information aggregation" refers to a database that centrally stores acquired data to prepare it for later analysis and retrieval. 【0302】 "Natural language processing technology" is a technology for extracting useful information from text data and converting it into a form that can be understood by humans. 【0303】 "Convention" refers to the promise of policies that election candidates present to voters during an election campaign. 【0304】 "Policy information" refers to data on the details of specific policies related to the convention and past performance. 【0305】 "Evaluation means" is a mechanism for quantifying the feasibility of a candidate's convention and achievements and performing comparative analysis. 【0306】 "User interface" refers to a screen or output means for enabling users to visually understand the collected data and evaluation results. 【0307】 "Similarity analysis" is a method for finding similarities in policies and conventions among different candidates and visualizing their relative positions. 【0308】 This invention is mainly composed of an information processing device and is realized by three main components: a server, a terminal, and a user. 【0309】 First, the server collects information about candidates from multiple information sources through an electronic communication network. At this time, a crawler program is used to automatically acquire data and store the information in an information integration. The stored information is effectively managed by using libraries in Python such as BeautifulSoup and requests. Then, natural language processing technology is used to extract the convention and policy information of the candidates from the stored information. Specifically, TfidfVectorizer is utilized to vectorize the text data, and information summarization and semantic analysis are performed. 【0310】 The terminal is responsible for displaying information via a user interface based on the provided data. Based on the extracted information, it evaluates the candidates' past performance and the feasibility of fulfilling their promises. This evaluation process uses technologies such as cosine_similarity to analyze the similarities of policies among candidates and highlights more relevant information. This visualized information is presented in graphs and tables, making it easy for users to understand. 【0311】 Users interact with their devices to obtain information based on their interests. For example, when seeking information on candidates with pledges related to "environmental policy," they use prompts to request specific information from the server. A concrete example of such a prompt might be: "Please collect information on candidates with pledges focused on environmental policy and generate an evaluation score." 【0312】 This allows users to efficiently compare the promises and track records of multiple candidates and make informed decisions. The entire system aims to support voters in elections by processing data quickly and accurately. 【0313】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0314】 Step 1: 【0315】 The server collects information about candidates from multiple sources via an electronic communication network. The input is a list of website URLs. The server accesses the web pages using the requests library and parses the HTML structure using BeautifulSoup. The parsed data is stored in an information repository. The output is a structured list of candidate information. 【0316】 Step 2: 【0317】 The server applies natural language processing techniques to the stored information. Specifically, it uses the text data acquired as input and vectorizes it using TfidfVectorizer. This process extracts pledges and policy information. As output, data is generated in which the topics of the text have been vectorized. 【0318】 Step 3: 【0319】 The server evaluates candidates' pledges and past performance based on vectorized data. It uses `cosine_similarity` to calculate textual similarity. The input data consists of vectorized policy information for each candidate. The output generates a matrix of similarity scores, enabling comparative analysis of candidates. 【0320】 Step 4: 【0321】 The terminal displays the evaluation results received from the server on the user interface. Similarity scores and evaluation scores obtained from the server are provided as input. The terminal visualizes the results in graph and table format and provides them to the user. The visualized data is displayed on the screen as output, converted into a format easily understandable to the user. 【0322】 Step 5: 【0323】 Users search for information about campaign promises and policies that interest them through their terminal. Prompts related to specific policies are used as input. Based on the user's interests, the terminal sends queries to the server. The output displayed on the terminal includes relevant candidate information and evaluation scores. 【0324】 Step 6: 【0325】 Users compare candidates' policies and make decisions based on the information presented. They utilize visualized information and reliable data as input. The output is a decision based on the user's selection, which is then used as a basis for their election participation decisions. 【0326】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0327】 This invention combines a system that provides information based on candidates' promises and policies with an emotion engine that analyzes user emotions. The system comprises an information processing device, a user interface, and an emotion engine. 【0328】 Server Processing 【0329】 The server efficiently collects information related to candidates from the electronic network and uses natural language processing to extract candidates' pledges and policies into a database. Furthermore, it evaluates candidates' past performance and the feasibility of fulfilling their pledges, and generates data to present the evaluation results in the user interface. 【0330】 Emotional Engine Processing 【0331】 The emotion engine analyzes user input through the user interface and recognizes their emotional state. For example, it determines the user's level of interest and stress when researching information about election candidates. This data is received by the server and used to adjust how information is presented in the user interface. 【0332】 Terminal processing 【0333】 The terminal provides a user interface, displaying detailed information about candidates and offering information tailored to the user's emotions. After data from the emotion engine is analyzed by the server, the terminal prioritizes and displays the information most relevant to that user. For example, if a user expresses interest in a particular policy, it highlights and displays information about relevant candidates. 【0334】 The device also uses an emotion engine to recognize the user's emotions in response to a question. For example, if the user indicates anxiety, the device will present information to alleviate that anxiety or data on the candidate's trustworthiness. 【0335】 User actions 【0336】 Users can research specific candidates and policies through the device's user interface. By recognizing the user's emotions through an emotion engine, the system can provide personalized information tailored to the user, increasing their interest in the election campaign and helping them make more informed decisions. This allows users to participate more actively in the election. 【0337】 The following describes the processing flow. 【0338】 Step 1: 【0339】 The server uses a crawler program to collect data about candidates from multiple sources on the electronic network. This includes the candidates' official social media accounts and the websites of major news organizations. The collected information is stored on the server in text format. 【0340】 Step 2: 【0341】 The server uses natural language processing algorithms to analyze the stored text data. The algorithms extract pledges and policy information from the text and store this information in a database as structured data. 【0342】 Step 3: 【0343】 The server runs an evaluation algorithm that assesses candidates' past performance and the feasibility of fulfilling their promises based on a database. The evaluation results are calculated as a score that facilitates comparison between candidates. 【0344】 Step 4: 【0345】 The emotion engine built into the server receives input from the user and analyzes the user's emotional state. In this process, it evaluates the user's level of interest and stress based on the words used and the information selected. 【0346】 Step 5: 【0347】 The terminal receives evaluation results and sentiment engine analysis data from the server via the user interface. The user interface is adjusted according to the user's emotions and prioritizes the presentation of relevant candidate information. 【0348】 Step 6: 【0349】 Users interact with the device to express interest in candidates and policies and view detailed information. For example, if a user expresses interest in a particular policy, the device will highlight the positions and evaluations of candidates related to that policy. 【0350】 Step 7: 【0351】 When a user makes a query on their device, the sentiment engine recognizes the user's emotion in response to that question. The server then presents information about candidates and policies that address the question, taking the user's emotional state into consideration. 【0352】 Step 8: 【0353】 The device optimizes the information displayed on the screen based on updated information and user sentiment analysis results. This allows users to receive more accurate and personalized information to help them make informed decisions. 【0354】 (Example 2) 【0355】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0356】 In modern election campaigns, it is crucial for voters to make informed decisions based on candidates' promises and achievements. However, efficiently obtaining useful information from a vast amount of data is difficult. Furthermore, providing information tailored to each voter's emotional state and maintaining their interest is also challenging. Therefore, there is a need for a system that personalizes information based on the emotions and interests of individual users, providing higher-quality information. 【0357】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0358】 In this invention, the server includes means for acquiring information from information sources on a communication network, which serve as an information aggregation unit; means for extracting information using natural language processing technology; and means for recognizing the user's emotional state, which are equipped with an emotion analysis unit. This enables the user to receive information that is tailored to their emotions and interests quickly and accurately. 【0359】 An "information aggregation unit" is a function that collects data from various information sources on a communication network and stores it in a memory device within the system. 【0360】 A "communication network" is a network system that enables digital communication, including the internet, and is used for acquiring and transmitting data. 【0361】 A "storage device" is a storage medium or device that holds data within a system and makes it accessible as needed. 【0362】 "Natural language analysis technology" refers to techniques for analyzing meaning from text data and extracting useful information, and includes natural language processing. 【0363】 An "emotional analysis unit" is a function within a system that analyzes user input data to recognize emotional states and psychological tendencies. 【0364】 A "presentation device" is a device or interface that displays information to a user visually or audibly. 【0365】 An "evaluation unit" is a function within a system that evaluates a candidate's past actions and the feasibility of fulfilling their promises, and generates results. 【0366】 A "search unit" is a function that searches for information within a storage device in response to a specific question from the user and retrieves the relevant information. 【0367】 This invention demonstrates a combination of hardware and software that enables the construction of a system that efficiently collects and analyzes candidate pledges and policy information and provides information in accordance with the user's emotions. 【0368】 The server first collects data from internet sources via a communication network. This involves using web crawlers and data acquisition technologies via APIs. The collected data is stored in storage. For natural language processing, open-source natural language processing tools such as NLTK and SpaCy are used to structure the data and extract necessary information. This process yields information on campaign promises and policies, as well as information on candidates' past performance. 【0369】 The server also has an emotion analysis unit that analyzes text data entered by the user through the terminal in real time. This process uses emotion analysis APIs and machine learning models to identify the user's emotional state. For example, it determines the level of interest and stress based on the speed and content of the user's typing. 【0370】 The terminal receives analysis results transmitted from the server and provides them to the user through a display device. In this process, information is visualized using HTML and CSS, and presented in a user-friendly interface. Furthermore, based on data obtained from sentiment analysis, highly relevant information is prioritized and displayed. 【0371】 Furthermore, the system uses a generative AI model to enable users to resolve their questions through prompts. A typical prompt might be something like, "Tell me how your views on tax reform differ from those of the other candidates." Based on this prompt, the AI ​​model scrutinizes the information most useful to the user and generates a response. 【0372】 In this way, the system enables the provision of information that is tailored to the user's interests and emotions, and supports their decision-making. 【0373】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0374】 Step 1: 【0375】 The server collects information about candidates from multiple sources on the internet via a communication network. Using specified keywords and URL lists as input, it extracts relevant data through web crawling techniques. As output, it stores text data containing candidate information in a temporary storage area. 【0376】 Step 2: 【0377】 The server processes the collected information using natural language processing (NLP) techniques. The input is text data, and natural language processing tools are used to tokenize sentences, tag parts of speech, and perform semantic analysis. The output is structured data, such as candidates' pledges, policies, and past achievements. This process includes converting the data into a format that can be stored in a database. 【0378】 Step 3: 【0379】 The terminal accepts queries through the user interface. It receives a request for information on a specified policy or candidate from the user as input, and then queries the server based on that information. The output is a visual presentation of relevant details to the user. Specifically, it uses HTML / CSS to format and display the information clearly. 【0380】 Step 4: 【0381】 The emotion analysis unit continuously monitors user input through the interface. It analyzes user text input and interaction patterns as input, quantifying the emotional state. The output is data regarding the user's level of interest and emotional state, which is used to determine the optimal method of information presentation. 【0382】 Step 5: 【0383】 The server personalizes information presentation based on sentiment analysis results. The input is data from sentiment analysis, and an algorithm is applied to prioritize information that the user is most likely to be interested in. The output is a selection and highlighting of the most relevant information for the user, thereby supporting the user in obtaining the most optimal information from the system. 【0384】 Step 6: 【0385】 The generative AI model generates responses in response to user prompts. It receives prompts as input and uses natural language generation techniques to generate relevant answers. The output is a text response to the user's question, which is presented in real time through the interface. 【0386】 (Application Example 2) 【0387】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0388】 In modern elections, voters must sift through a vast amount of information about candidates' promises and policies, and spend considerable time and effort judging whether that information aligns with their interests. Furthermore, because emotions related to the information are not taken into account, there is a high likelihood of anxiety and mismatches of interests. 【0389】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0390】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network and storing it in a database, means for extracting candidates' pledges and policy information from the stored information using natural language processing technology, and means for presenting information tailored to the user's interests and emotions using sentiment analysis results. This makes it possible for users to quickly and easily obtain election information that matches their interests and emotions. 【0391】 An "information processing device" is a device that collects and processes data from multiple information sources via an electronic network. 【0392】 A "data collection method" is a means that has the function of acquiring information through an electronic network and storing it in a database. 【0393】 "Natural language processing technology" is a technology that analyzes human language and extracts information from it. 【0394】 An "evaluation tool" is a means that has the function of evaluating a candidate's past performance and the feasibility of fulfilling their promises based on extracted information. 【0395】 "User interface" refers to the screens or consoles that users use to interact with a system. 【0396】 "Emotional analysis tools" are functions that analyze a user's emotional state based on their input and behavior. 【0397】 An "information presentation means" is a means that has the function of presenting collected information to the user in an appropriate format. 【0398】 A "database" is a structure for organizing and storing information so that it can be accessed efficiently. 【0399】 A "search function" is a feature that allows users to quickly retrieve the information they need from a database. 【0400】 This invention is a system for providing election information and is built around an information processing device. The system includes multiple components, each with its own role in processing information. 【0401】 The server collects data about candidates from numerous sources via an electronic network and stores it in a database. The server also uses natural language processing technologies (e.g., spaCy and NLTK) to analyze the information in the database and extract candidate promises and policy information. Based on the extracted data, it evaluates the candidate's past performance and the feasibility of fulfilling their promises. Furthermore, it uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state from their input and behavior. This allows the server to adjust the information presented according to the user's interests and emotions, displaying particularly high-demand information in the user interface. 【0402】 The device displays relevant information to the user through its user interface. Detailed information on policies of interest to the user is presented in a highlighted format. Furthermore, the results of sentiment analysis are used to provide additional information beneficial to the user. In this process, the aim is to improve the user experience by prioritizing the presentation of areas of particular user interest. 【0403】 For example, if a user uses a smartphone app and expresses interest in "environmental policy," the system will prioritize displaying relevant policy information, presenting past success stories and reliable data. Additionally, based on the user's concerns and interests, the system will provide information that alleviates their emotions or piques their specific interest. 【0404】 An example of a prompt might be, "Please describe in detail the candidate's track record, which could be helpful in providing information if the user is feeling anxious." This prompt prompts the system to select and present appropriate information through the user interface. 【0405】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0406】 Step 1: 【0407】 The server collects information about candidates from various sources via an electronic network. The input is data from each source, and the output is data stored in a processable format. A data collection module on the server performs this task, and the resulting data is stored in a database. 【0408】 Step 2: 【0409】 The server uses natural language processing techniques to extract candidate pledges and policy information from the database. The input is raw data from the database, and the output is organized information about pledges and policies. Natural language processing libraries (e.g., spaCy, NLTK) are applied to classify and organize the information. 【0410】 Step 3: 【0411】 The server evaluates the candidate's past performance and the feasibility of fulfilling their promises based on the extracted information. The input is the information obtained in step 2, and the output is the evaluation result. The evaluation algorithm analyzes the feasibility of fulfilling promises using past performance data and generates an evaluation score. 【0412】 Step 4: 【0413】 The sentiment analysis engine analyzes user input via the user interface to recognize the emotional state. The input is real-time data from the user, and the output is analyzed sentiment data. The sentiment analysis engine (e.g., IBM Watson Tone Analyzer) performs this task and outputs the results. 【0414】 Step 5: 【0415】 The device adjusts information based on the user's interests and emotions, using sentiment analysis results. Input consists of output data from the sentiment analysis engine and evaluation results from the server. The device's algorithm analyzes the data and adjusts the information presented based on priority. 【0416】 Step 6: 【0417】 Users review the organized information through the user interface. The input is organized information presented from the device, and the output is useful information to aid in the user's decision-making. The user interface presents highlighted information and relevant data, which the user uses to select candidates. 【0418】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0419】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0420】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0421】 [Third Embodiment] 【0422】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0423】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0424】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0425】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0426】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0427】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0428】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0429】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0430】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0431】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0432】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0433】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0434】 This invention is a system that uses an information processing device to analyze candidates' promises and achievements and provides useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0435】 Server Processing 【0436】 The server is the central hub for data collection, acquiring information about candidates from multiple sources on the electronic network. This includes candidates' official social media accounts and the websites of major news organizations. Crawler programs are run to automatically collect and store this information. Natural language processing is then used on the collected data to extract candidates' pledges and relevant policy information, which is then stored in a database as structured data. 【0437】 To analyze the information stored in the database, the server activates an evaluation algorithm. This algorithm quantifies each candidate's past performance and the likelihood of fulfilling their promises, and calculates an evaluation score. The evaluation score serves as an indicator to help users compare candidates more easily. 【0438】 Furthermore, the server regularly updates the database and tracks the progress of candidates' promises, ensuring that users are always provided with the latest information. 【0439】 Terminal processing 【0440】 The terminal provides information to the user through a user interface. When the user operates the terminal and selects a specific electoral district or candidate, the terminal sends a query to the server and retrieves the corresponding information. Based on the retrieved data, a list of candidates, details of their pledges, and information on their past performance are displayed. This information is visualized in tables and graphs to make it easy for the user to understand. 【0441】 User actions 【0442】 Users can use their devices to select candidates they are interested in and view detailed information. For example, if a user is interested in "building a medical center in front of the train station," they can search for information related to that policy and see the positions of both proponents and opponents displayed on their device. 【0443】 This system will enable users to make informed decisions and support their decision-making when participating in elections. 【0444】 The following describes the processing flow. 【0445】 Step 1: 【0446】 The server launches a crawler program to collect information related to the candidate from multiple sources on the electronic network. It retrieves the latest posts and articles from official social media accounts and news organizations' websites and saves them as text data. 【0447】 Step 2: 【0448】 The server runs a natural language processing algorithm on the stored text data. The algorithm analyzes and extracts candidate promises and policy information. The extracted information is stored in a database as structured data. 【0449】 Step 3: 【0450】 The server uses information from the database to evaluate each candidate's past performance and the likelihood of fulfilling their promises. An evaluation algorithm is executed, and a score is calculated for each candidate. This score is determined based on the quality and reliability of the information. 【0451】 Step 4: 【0452】 The server updates the database at regular intervals. When new information is collected, it updates the existing data and tracks the progress of the commitments. This ensures that users are provided with the most up-to-date information. 【0453】 Step 5: 【0454】 The terminal displays the user interface and prepares to receive the user. If the user selects details about a specific candidate or policy, the terminal sends a query to the server. 【0455】 Step 6: 【0456】 The server receives queries from the terminal, searches the database for the relevant data, and then sends the information back to the terminal. 【0457】 Step 7: 【0458】 The terminal displays candidate lists, detailed pledges, and comparable visual information on its screen based on data received from the server. Information is presented in tables and graphs on the user interface, making it easy for users to understand. 【0459】 Step 8: 【0460】 Users view information provided on their devices and research candidates and policies that interest them in detail. They find candidates that meet their criteria and make voting decisions based on that information. 【0461】 (Example 1) 【0462】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0463】 In recent years, it has become crucial for voters to make informed and informed decisions in elections. However, information about candidates is vast and fragmented, making its analysis and understanding extremely difficult. Furthermore, there are insufficient means to track the progress and feasibility of candidates' promises, and a comprehensive system to assist voters in making informed decisions does not exist. Addressing these challenges is essential. 【0464】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0465】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing the information in a data storage medium; means for extracting candidates' pledges and policy information from the information stored in the data storage medium using natural language processing technology; and means for generating evaluation scores for candidates and using the scores as evaluation indicators. This enables users to compare candidates based on quantitative evaluations. Furthermore, by including means for creating prompt sentences for a generative AI model and presenting them to the user, flexible responses to a variety of questions become possible. 【0466】 An "information processing device" is an electronic device used for collecting, analyzing, storing, and presenting data. 【0467】 "Data collection means" refers to technology that has the function of automatically acquiring target information from multiple information sources on an electronic network. 【0468】 A "data storage medium" is a physical or electronic storage device used to record and retain acquired information over a long period of time. 【0469】 "Natural language processing technology" refers to computational techniques that analyze text data written in human language to extract or understand specific information. 【0470】 "Evaluation means" refers to an algorithm or method for quantifying or scoring a specific object based on acquired information. 【0471】 A "display device" is a digital screen or related device used to visually present information to a user. 【0472】 An "evaluation score" is a value calculated using an evaluation method and is a numerical value used as a comparable indicator. 【0473】 A "generative AI model" is a computer program or system that uses artificial intelligence to generate output from specific input data. 【0474】 A "prompt statement" is a form of instruction or question input to a generative AI model to elicit a specific response. 【0475】 This invention relates to a system that uses an information processing device to collect and analyze diverse information about candidates and provide useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0476】 The server is the central device for data collection. The server runs a crawler program to automatically retrieve candidate information from multiple sources on the electronic network. This crawler program, built using, for example, Python, downloads data from candidates' official social media accounts and news organizations' websites. The retrieved text data is analyzed using natural language processing tools (e.g., NLTK or SpaCy) to extract keywords related to the candidates' pledges and policies. The analyzed data is stored in a structured format in a database. 【0477】 The terminal plays the role of providing information to the user through an interface. When a user requests information about a specific electoral district or candidate, the terminal sends a query to the server, retrieves the relevant information, and displays it. The displayed information is then formatted into a visualized form, such as a table or graph, to facilitate comparison and understanding. 【0478】 Users can select candidates they are interested in via their device and view detailed information. For example, if a user expresses interest in "building a medical center in front of the train station," they can search for information related to that policy and check the positions of candidates who support and oppose it. It is also possible to use generative AI models to create prompts for specific questions, and the AI ​​can organize and present information about the candidates. 【0479】 For example, if a user wants to know "the candidates' opinions on the greening project," they can efficiently obtain the desired information by inputting a prompt into the AI ​​model that says, "Compare the promises and achievements of the candidates promoting the greening project." In this way, the present invention functions as an advanced information provision system that supports decision-making in elections. 【0480】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0481】 Step 1: 【0482】 The server uses data collection tools to obtain information about candidates from multiple sources on the electronic network. It receives a list of URLs for candidates' official social media accounts and news organizations as input, and executes a crawler program (e.g., Python's Scrapy) based on this. Specifically, the server sends an HTTP request to each URL and downloads HTML content from the web pages. The output is a collection of raw text data. 【0483】 Step 2: 【0484】 The server performs natural language processing on the acquired text data. It receives the text data obtained in step 1 as input. The server tokenizes the text using Python's NLTK or SpaCy and extracts important keywords and phrases. Specific operations include morphological analysis and keyword matching. The output is structured data containing candidate pledges and policy information. 【0485】 Step 3: 【0486】 The server applies an evaluation algorithm based on the extracted information. It receives the structured data generated in step 2 as input. The evaluation algorithm calculates an evaluation score for each candidate based on the feasibility of fulfilling their promises and their past performance. Specifically, it performs numerical scoring and applies statistical models. The output is a list of candidates assigned evaluation scores. 【0487】 Step 4: 【0488】 The terminal sends queries to the server based on user requests to retrieve candidate information. The input consists of the electoral district and candidate criteria specified by the user. The terminal processes the retrieved information and generates tables and graphs for visual presentation to the user. Specific operations include sending and receiving SQL queries to and from the database and formatting the information. The output is detailed information that the user can view on the terminal. 【0489】 Step 5: 【0490】 Users use their devices to view detailed information about candidates and policies they are interested in and ask questions to a generative AI model. For example, a user might input the prompt, "Please tell me the latest pledges of candidates who focus on environmental policy and their evaluation scores," and the model would then present the corresponding information. The input consists of the user's questions and filter conditions, while the output is candidate information and proposals organized by the generative AI model. 【0491】 (Application Example 1) 【0492】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0493】 In modern elections, a challenge exists in that voters find it difficult to fully understand candidates' promises and track records, and to make appropriate comparisons and evaluations. They are often overwhelmed by the sheer volume of information and the complexity of the policies, resulting in an inability to make informed decisions. Furthermore, voters want to efficiently obtain information directly relevant to their interests, but existing methods are insufficient to do so. 【0494】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0495】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic communication network and storing it in an information aggregator; means for extracting pledges and policy information from the stored information using natural language processing technology; and means for analyzing the similarities between candidates and highlighting and visualizing the most relevant information in order to provide information based on the user's interests. This enables voters to efficiently compare information on each candidate and make informed decisions. 【0496】 An "information processing device" is an electronic device used to collect data, perform analysis based on that data, and provide information to users. 【0497】 An "electronic communication network" is a communication infrastructure that enables the exchange of information via the internet and other means. 【0498】 "Information sources" refer to various media outlets, such as websites, official accounts, and news organizations, that provide information about the candidates. 【0499】 "Information aggregation" refers to a database that centrally stores acquired data to prepare it for later analysis and retrieval. 【0500】 "Natural language processing technology" is a technique for extracting useful information from text data and converting it into a format that humans can understand. 【0501】 A "campaign promise" is a set of policy promises that an election candidate makes to voters during their campaign. 【0502】 "Policy information" refers to data on specific policies related to campaign promises, as well as past performance. 【0503】 An "evaluation tool" is a system for quantifying the feasibility of a candidate's promises and achievements and conducting comparative analysis. 【0504】 A "user interface" refers to screens and output methods that allow users to visually understand the collected data and evaluation results. 【0505】 "Similarity analysis" is a method for identifying similarities in policies and promises among different candidates and visualizing their relative positions. 【0506】 This invention is centered around an information processing device and is realized with three main components: a server, a terminal, and a user. 【0507】 First, the server collects information about candidates from multiple sources via an electronic communication network. A crawler program is used to automatically retrieve data, which is then stored in an information repository. The stored information is effectively managed using Python libraries such as BeautifulSoup and requests. Next, natural language processing techniques are used to extract candidate pledges and policy information from the stored data. Specifically, TfidfVectorizer is used to vectorize text data, and then information summarization and semantic analysis are performed. 【0508】 The terminal is responsible for displaying information via a user interface based on the provided data. Based on the extracted information, it evaluates the candidates' past performance and the feasibility of fulfilling their promises. This evaluation process uses technologies such as cosine_similarity to analyze the similarities of policies among candidates and highlights more relevant information. This visualized information is presented in graphs and tables, making it easy for users to understand. 【0509】 Users interact with their devices to obtain information based on their interests. For example, when seeking information on candidates with pledges related to "environmental policy," they use prompts to request specific information from the server. A concrete example of such a prompt might be: "Please collect information on candidates with pledges focused on environmental policy and generate an evaluation score." 【0510】 This allows users to efficiently compare the promises and track records of multiple candidates and make informed decisions. The entire system aims to support voters in elections by processing data quickly and accurately. 【0511】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0512】 Step 1: 【0513】 The server collects information about candidates from multiple sources via an electronic communication network. The input is a list of website URLs. The server accesses the web pages using the requests library and parses the HTML structure using BeautifulSoup. The parsed data is stored in an information repository. The output is a structured list of candidate information. 【0514】 Step 2: 【0515】 The server applies natural language processing techniques to the stored information. Specifically, it uses the text data acquired as input and vectorizes it using TfidfVectorizer. This process extracts pledges and policy information. As output, data is generated in which the topics of the text have been vectorized. 【0516】 Step 3: 【0517】 The server evaluates candidates' pledges and past performance based on vectorized data. It uses `cosine_similarity` to calculate textual similarity. The input data consists of vectorized policy information for each candidate. The output generates a matrix of similarity scores, enabling comparative analysis of candidates. 【0518】 Step 4: 【0519】 The terminal displays the evaluation results received from the server on the user interface. Similarity scores and evaluation scores obtained from the server are provided as input. The terminal visualizes the results in graph and table format and provides them to the user. The visualized data is displayed on the screen as output, converted into a format easily understandable to the user. 【0520】 Step 5: 【0521】 Users search for information about campaign promises and policies that interest them through their terminal. Prompts related to specific policies are used as input. Based on the user's interests, the terminal sends queries to the server. The output displayed on the terminal includes relevant candidate information and evaluation scores. 【0522】 Step 6: 【0523】 Users compare candidates' policies and make decisions based on the information presented. They utilize visualized information and reliable data as input. The output is a decision based on the user's selection, which is then used as a basis for their election participation decisions. 【0524】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0525】 This invention combines a system that provides information based on candidates' promises and policies with an emotion engine that analyzes user emotions. The system comprises an information processing device, a user interface, and an emotion engine. 【0526】 Server Processing 【0527】 The server efficiently collects information related to candidates from the electronic network and uses natural language processing to extract candidates' pledges and policies into a database. Furthermore, it evaluates candidates' past performance and the feasibility of fulfilling their pledges, and generates data to present the evaluation results in the user interface. 【0528】 Emotional Engine Processing 【0529】 The emotion engine analyzes user input through the user interface and recognizes their emotional state. For example, it determines the user's level of interest and stress when researching information about election candidates. This data is received by the server and used to adjust how information is presented in the user interface. 【0530】 Terminal processing 【0531】 The terminal provides a user interface, displaying detailed information about candidates and offering information tailored to the user's emotions. After data from the emotion engine is analyzed by the server, the terminal prioritizes and displays the information most relevant to that user. For example, if a user expresses interest in a particular policy, it highlights and displays information about relevant candidates. 【0532】 The device also uses an emotion engine to recognize the user's emotions in response to a question. For example, if the user indicates anxiety, the device will present information to alleviate that anxiety or data on the candidate's trustworthiness. 【0533】 User actions 【0534】 Users can research specific candidates and policies through the device's user interface. By recognizing the user's emotions through an emotion engine, the system can provide personalized information tailored to the user, increasing their interest in the election campaign and helping them make more informed decisions. This allows users to participate more actively in the election. 【0535】 The following describes the processing flow. 【0536】 Step 1: 【0537】 The server uses a crawler program to collect data about candidates from multiple sources on the electronic network. This includes the candidates' official social media accounts and the websites of major news organizations. The collected information is stored on the server in text format. 【0538】 Step 2: 【0539】 The server uses natural language processing algorithms to analyze the stored text data. The algorithms extract pledges and policy information from the text and store this information in a database as structured data. 【0540】 Step 3: 【0541】 The server runs an evaluation algorithm that assesses candidates' past performance and the feasibility of fulfilling their promises based on a database. The evaluation results are calculated as a score that facilitates comparison between candidates. 【0542】 Step 4: 【0543】 The emotion engine built into the server receives input from the user and analyzes the user's emotional state. In this process, it evaluates the user's level of interest and stress based on the words used and the information selected. 【0544】 Step 5: 【0545】 The terminal receives evaluation results and sentiment engine analysis data from the server via the user interface. The user interface is adjusted according to the user's emotions and prioritizes the presentation of relevant candidate information. 【0546】 Step 6: 【0547】 Users interact with the device to express interest in candidates and policies and view detailed information. For example, if a user expresses interest in a particular policy, the device will highlight the positions and evaluations of candidates related to that policy. 【0548】 Step 7: 【0549】 When a user makes a query on their device, the sentiment engine recognizes the user's emotion in response to that question. The server then presents information about candidates and policies that address the question, taking the user's emotional state into consideration. 【0550】 Step 8: 【0551】 The device optimizes the information displayed on the screen based on updated information and user sentiment analysis results. This allows users to receive more accurate and personalized information to help them make informed decisions. 【0552】 (Example 2) 【0553】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0554】 In modern election campaigns, it is crucial for voters to make informed decisions based on candidates' promises and achievements. However, efficiently obtaining useful information from a vast amount of data is difficult. Furthermore, providing information tailored to each voter's emotional state and maintaining their interest is also challenging. Therefore, there is a need for a system that personalizes information based on the emotions and interests of individual users, providing higher-quality information. 【0555】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0556】 In this invention, the server includes means for acquiring information from information sources on a communication network, which serve as an information aggregation unit; means for extracting information using natural language processing technology; and means for recognizing the user's emotional state, which are equipped with an emotion analysis unit. This enables the user to receive information that is tailored to their emotions and interests quickly and accurately. 【0557】 An "information aggregation unit" is a function that collects data from various information sources on a communication network and stores it in a memory device within the system. 【0558】 A "communication network" is a network system that enables digital communication, including the internet, and is used for acquiring and transmitting data. 【0559】 A "storage device" is a storage medium or device that holds data within a system and makes it accessible as needed. 【0560】 "Natural language analysis technology" refers to techniques for analyzing meaning from text data and extracting useful information, and includes natural language processing. 【0561】 An "emotional analysis unit" is a function within a system that analyzes user input data to recognize emotional states and psychological tendencies. 【0562】 A "presentation device" is a device or interface that displays information to a user visually or audibly. 【0563】 An "evaluation unit" is a function within a system that evaluates a candidate's past actions and the feasibility of fulfilling their promises, and generates results. 【0564】 A "search unit" is a function that searches for information within a storage device in response to a specific question from the user and retrieves the relevant information. 【0565】 This invention demonstrates a combination of hardware and software that enables the construction of a system that efficiently collects and analyzes candidate pledges and policy information and provides information in accordance with the user's emotions. 【0566】 The server first collects data from internet sources via a communication network. This involves using web crawlers and data acquisition technologies via APIs. The collected data is stored in storage. For natural language processing, open-source natural language processing tools such as NLTK and SpaCy are used to structure the data and extract necessary information. This process yields information on campaign promises and policies, as well as information on candidates' past performance. 【0567】 The server also has an emotion analysis unit that analyzes text data entered by the user through the terminal in real time. This process uses emotion analysis APIs and machine learning models to identify the user's emotional state. For example, it determines the level of interest and stress based on the speed and content of the user's typing. 【0568】 The terminal receives analysis results transmitted from the server and provides them to the user through a display device. In this process, information is visualized using HTML and CSS, and presented in a user-friendly interface. Furthermore, based on data obtained from sentiment analysis, highly relevant information is prioritized and displayed. 【0569】 Furthermore, the system uses a generative AI model to enable users to resolve their questions through prompts. A typical prompt might be something like, "Tell me how your views on tax reform differ from those of the other candidates." Based on this prompt, the AI ​​model scrutinizes the information most useful to the user and generates a response. 【0570】 In this way, the system enables the provision of information that is tailored to the user's interests and emotions, and supports their decision-making. 【0571】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0572】 Step 1: 【0573】 The server collects information about candidates from multiple sources on the internet via a communication network. Using specified keywords and URL lists as input, it extracts relevant data through web crawling techniques. As output, it stores text data containing candidate information in a temporary storage area. 【0574】 Step 2: 【0575】 The server processes the collected information using natural language processing (NLP) techniques. The input is text data, and natural language processing tools are used to tokenize sentences, tag parts of speech, and perform semantic analysis. The output is structured data, such as candidates' pledges, policies, and past achievements. This process includes converting the data into a format that can be stored in a database. 【0576】 Step 3: 【0577】 The terminal accepts queries through the user interface. It receives a request for information on a specified policy or candidate from the user as input, and then queries the server based on that information. The output is a visual presentation of relevant details to the user. Specifically, it uses HTML / CSS to format and display the information clearly. 【0578】 Step 4: 【0579】 The emotion analysis unit continuously monitors user input through the interface. It analyzes user text input and interaction patterns as input, quantifying the emotional state. The output is data regarding the user's level of interest and emotional state, which is used to determine the optimal method of information presentation. 【0580】 Step 5: 【0581】 The server personalizes information presentation based on sentiment analysis results. The input is data from sentiment analysis, and an algorithm is applied to prioritize information that the user is most likely to be interested in. The output is a selection and highlighting of the most relevant information for the user, thereby supporting the user in obtaining the most optimal information from the system. 【0582】 Step 6: 【0583】 The generative AI model generates responses in response to user prompts. It receives prompts as input and uses natural language generation techniques to generate relevant answers. The output is a text response to the user's question, which is presented in real time through the interface. 【0584】 (Application Example 2) 【0585】 Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0586】 In modern elections, voters must sift through a vast amount of information about candidates' promises and policies, and spend considerable time and effort judging whether that information aligns with their interests. Furthermore, because emotions related to the information are not taken into account, there is a high likelihood of anxiety and mismatches of interests. 【0587】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0588】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network and storing it in a database, means for extracting candidates' pledges and policy information from the stored information using natural language processing technology, and means for presenting information tailored to the user's interests and emotions using sentiment analysis results. This makes it possible for users to quickly and easily obtain election information that matches their interests and emotions. 【0589】 An "information processing device" is a device that collects and processes data from multiple information sources via an electronic network. 【0590】 A "data collection method" is a means that has the function of acquiring information through an electronic network and storing it in a database. 【0591】 "Natural language processing technology" is a technology that analyzes human language and extracts information from it. 【0592】 An "evaluation tool" is a means that has the function of evaluating a candidate's past performance and the feasibility of fulfilling their promises based on extracted information. 【0593】 "User interface" refers to the screens or consoles that users use to interact with a system. 【0594】 "Emotional analysis tools" are functions that analyze a user's emotional state based on their input and behavior. 【0595】 An "information presentation means" is a means that has the function of presenting collected information to the user in an appropriate format. 【0596】 A "database" is a structure for organizing and storing information so that it can be accessed efficiently. 【0597】 A "search function" is a feature that allows users to quickly retrieve the information they need from a database. 【0598】 This invention is a system for providing election information and is built around an information processing device. The system includes multiple components, each with its own role in processing information. 【0599】 The server collects data about candidates from numerous sources via an electronic network and stores it in a database. The server also uses natural language processing technologies (e.g., spaCy and NLTK) to analyze the information in the database and extract candidate promises and policy information. Based on the extracted data, it evaluates the candidate's past performance and the feasibility of fulfilling their promises. Furthermore, it uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state from their input and behavior. This allows the server to adjust the information presented according to the user's interests and emotions, displaying particularly high-demand information in the user interface. 【0600】 The device displays relevant information to the user through its user interface. Detailed information on policies of interest to the user is presented in a highlighted format. Furthermore, the results of sentiment analysis are used to provide additional information beneficial to the user. In this process, the aim is to improve the user experience by prioritizing the presentation of areas of particular user interest. 【0601】 For example, if a user uses a smartphone app and expresses interest in "environmental policy," the system will prioritize displaying relevant policy information, presenting past success stories and reliable data. Additionally, based on the user's concerns and interests, the system will provide information that alleviates their emotions or piques their specific interest. 【0602】 An example of a prompt might be, "Please describe in detail the candidate's track record, which could be helpful in providing information if the user is feeling anxious." This prompt prompts the system to select and present appropriate information through the user interface. 【0603】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0604】 Step 1: 【0605】 The server collects information about candidates from various sources via an electronic network. The input is data from each source, and the output is data stored in a processable format. A data collection module on the server performs this task, and the resulting data is stored in a database. 【0606】 Step 2: 【0607】 The server uses natural language processing techniques to extract candidate pledges and policy information from the database. The input is raw data from the database, and the output is organized information about pledges and policies. Natural language processing libraries (e.g., spaCy, NLTK) are applied to classify and organize the information. 【0608】 Step 3: 【0609】 The server evaluates the candidate's past performance and the feasibility of fulfilling their promises based on the extracted information. The input is the information obtained in step 2, and the output is the evaluation result. The evaluation algorithm analyzes the feasibility of fulfilling promises using past performance data and generates an evaluation score. 【0610】 Step 4: 【0611】 The sentiment analysis engine analyzes user input via the user interface to recognize the emotional state. The input is real-time data from the user, and the output is analyzed sentiment data. The sentiment analysis engine (e.g., IBM Watson Tone Analyzer) performs this task and outputs the results. 【0612】 Step 5: 【0613】 The device adjusts information based on the user's interests and emotions, using sentiment analysis results. Input consists of output data from the sentiment analysis engine and evaluation results from the server. The device's algorithm analyzes the data and adjusts the information presented based on priority. 【0614】 Step 6: 【0615】 Users review the organized information through the user interface. The input is organized information presented from the device, and the output is useful information to aid in the user's decision-making. The user interface presents highlighted information and relevant data, which the user uses to select candidates. 【0616】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0617】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0618】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0619】 [Fourth Embodiment] 【0620】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0621】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0622】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0623】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0624】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0625】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0626】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0627】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0628】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0629】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0630】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0631】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0632】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0633】 This invention is a system that uses an information processing device to analyze candidates' promises and achievements and provides useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0634】 Server Processing 【0635】 The server is the central hub for data collection, acquiring information about candidates from multiple sources on the electronic network. This includes candidates' official social media accounts and the websites of major news organizations. Crawler programs are run to automatically collect and store this information. Natural language processing is then used on the collected data to extract candidates' pledges and relevant policy information, which is then stored in a database as structured data. 【0636】 To analyze the information stored in the database, the server activates an evaluation algorithm. This algorithm quantifies each candidate's past performance and the likelihood of fulfilling their promises, and calculates an evaluation score. The evaluation score serves as an indicator to help users compare candidates more easily. 【0637】 Furthermore, the server regularly updates the database and tracks the progress of candidates' promises, ensuring that users are always provided with the latest information. 【0638】 Terminal processing 【0639】 The terminal provides information to the user through a user interface. When the user operates the terminal and selects a specific electoral district or candidate, the terminal sends a query to the server and retrieves the corresponding information. Based on the retrieved data, a list of candidates, details of their pledges, and information on their past performance are displayed. This information is visualized in tables and graphs to make it easy for the user to understand. 【0640】 User actions 【0641】 Users can use their devices to select candidates they are interested in and view detailed information. For example, if a user is interested in "building a medical center in front of the train station," they can search for information related to that policy and see the positions of both proponents and opponents displayed on their device. 【0642】 This system will enable users to make informed decisions and support their decision-making when participating in elections. 【0643】 The following describes the processing flow. 【0644】 Step 1: 【0645】 The server launches a crawler program to collect information related to the candidate from multiple sources on the electronic network. It retrieves the latest posts and articles from official social media accounts and news organizations' websites and saves them as text data. 【0646】 Step 2: 【0647】 The server runs a natural language processing algorithm on the stored text data. The algorithm analyzes and extracts candidate promises and policy information. The extracted information is stored in a database as structured data. 【0648】 Step 3: 【0649】 The server uses information from the database to evaluate each candidate's past performance and the likelihood of fulfilling their promises. An evaluation algorithm is executed, and a score is calculated for each candidate. This score is determined based on the quality and reliability of the information. 【0650】 Step 4: 【0651】 The server updates the database at regular intervals. When new information is collected, it updates the existing data and tracks the progress of the commitments. This ensures that users are provided with the most up-to-date information. 【0652】 Step 5: 【0653】 The terminal displays the user interface and prepares to receive the user. If the user selects details about a specific candidate or policy, the terminal sends a query to the server. 【0654】 Step 6: 【0655】 The server receives queries from the terminal, searches the database for the relevant data, and then sends the information back to the terminal. 【0656】 Step 7: 【0657】 The terminal displays candidate lists, detailed pledges, and comparable visual information on its screen based on data received from the server. Information is presented in tables and graphs on the user interface, making it easy for users to understand. 【0658】 Step 8: 【0659】 Users view information provided on their devices and research candidates and policies that interest them in detail. They find candidates that meet their criteria and make voting decisions based on that information. 【0660】 (Example 1) 【0661】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0662】 In recent years, it has become crucial for voters to make informed and informed decisions in elections. However, information about candidates is vast and fragmented, making its analysis and understanding extremely difficult. Furthermore, there are insufficient means to track the progress and feasibility of candidates' promises, and a comprehensive system to assist voters in making informed decisions does not exist. Addressing these challenges is essential. 【0663】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0664】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing the information in a data storage medium; means for extracting candidates' pledges and policy information from the information stored in the data storage medium using natural language processing technology; and means for generating evaluation scores for candidates and using the scores as evaluation indicators. This enables users to compare candidates based on quantitative evaluations. Furthermore, by including means for creating prompt sentences for a generative AI model and presenting them to the user, flexible responses to a variety of questions become possible. 【0665】 An "information processing device" is an electronic device used for collecting, analyzing, storing, and presenting data. 【0666】 "Data collection means" refers to technology that has the function of automatically acquiring target information from multiple information sources on an electronic network. 【0667】 A "data storage medium" is a physical or electronic storage device used to record and retain acquired information over a long period of time. 【0668】 "Natural language processing technology" refers to computational techniques that analyze text data written in human language to extract or understand specific information. 【0669】 "Evaluation means" refers to an algorithm or method for quantifying or scoring a specific object based on acquired information. 【0670】 A "display device" is a digital screen or related device used to visually present information to a user. 【0671】 An "evaluation score" is a value calculated using an evaluation method and is a numerical value used as a comparable indicator. 【0672】 A "generative AI model" is a computer program or system that uses artificial intelligence to generate output from specific input data. 【0673】 A "prompt statement" is a form of instruction or question input to a generative AI model to elicit a specific response. 【0674】 This invention relates to a system that uses an information processing device to collect and analyze diverse information about candidates and provide useful information to voters. This system consists of three components: a server, a terminal, and a user. 【0675】 The server is the central device for data collection. The server runs a crawler program to automatically retrieve candidate information from multiple sources on the electronic network. This crawler program, built using, for example, Python, downloads data from candidates' official social media accounts and news organizations' websites. The retrieved text data is analyzed using natural language processing tools (e.g., NLTK or SpaCy) to extract keywords related to the candidates' pledges and policies. The analyzed data is stored in a structured format in a database. 【0676】 The terminal plays the role of providing information to the user through an interface. When a user requests information about a specific electoral district or candidate, the terminal sends a query to the server, retrieves the relevant information, and displays it. The displayed information is then formatted into a visualized form, such as a table or graph, to facilitate comparison and understanding. 【0677】 Users can select candidates they are interested in via their device and view detailed information. For example, if a user expresses interest in "building a medical center in front of the train station," they can search for information related to that policy and check the positions of candidates who support and oppose it. It is also possible to use generative AI models to create prompts for specific questions, and the AI ​​can organize and present information about the candidates. 【0678】 For example, if a user wants to know "the candidates' opinions on the greening project," they can efficiently obtain the desired information by inputting a prompt into the AI ​​model that says, "Compare the promises and achievements of the candidates promoting the greening project." In this way, the present invention functions as an advanced information provision system that supports decision-making in elections. 【0679】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0680】 Step 1: 【0681】 The server uses data collection tools to obtain information about candidates from multiple sources on the electronic network. It receives a list of URLs for candidates' official social media accounts and news organizations as input, and executes a crawler program (e.g., Python's Scrapy) based on this. Specifically, the server sends an HTTP request to each URL and downloads HTML content from the web pages. The output is a collection of raw text data. 【0682】 Step 2: 【0683】 The server performs natural language processing on the acquired text data. It receives the text data obtained in step 1 as input. The server tokenizes the text using Python's NLTK or SpaCy and extracts important keywords and phrases. Specific operations include morphological analysis and keyword matching. The output is structured data containing candidate pledges and policy information. 【0684】 Step 3: 【0685】 The server applies an evaluation algorithm based on the extracted information. It receives the structured data generated in step 2 as input. The evaluation algorithm calculates an evaluation score for each candidate based on the feasibility of fulfilling their promises and their past performance. Specifically, it performs numerical scoring and applies statistical models. The output is a list of candidates assigned evaluation scores. 【0686】 Step 4: 【0687】 The terminal sends queries to the server based on user requests to retrieve candidate information. The input consists of the electoral district and candidate criteria specified by the user. The terminal processes the retrieved information and generates tables and graphs for visual presentation to the user. Specific operations include sending and receiving SQL queries to and from the database and formatting the information. The output is detailed information that the user can view on the terminal. 【0688】 Step 5: 【0689】 Users use their devices to view detailed information about candidates and policies they are interested in and ask questions to a generative AI model. For example, a user might input the prompt, "Please tell me the latest pledges of candidates who focus on environmental policy and their evaluation scores," and the model would then present the corresponding information. The input consists of the user's questions and filter conditions, while the output is candidate information and proposals organized by the generative AI model. 【0690】 (Application Example 1) 【0691】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0692】 In modern elections, a challenge exists in that voters find it difficult to fully understand candidates' promises and track records, and to make appropriate comparisons and evaluations. They are often overwhelmed by the sheer volume of information and the complexity of the policies, resulting in an inability to make informed decisions. Furthermore, voters want to efficiently obtain information directly relevant to their interests, but existing methods are insufficient to do so. 【0693】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0694】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic communication network and storing it in an information aggregator; means for extracting pledges and policy information from the stored information using natural language processing technology; and means for analyzing the similarities between candidates and highlighting and visualizing the most relevant information in order to provide information based on the user's interests. This enables voters to efficiently compare information on each candidate and make informed decisions. 【0695】 An "information processing device" is an electronic device used to collect data, perform analysis based on that data, and provide information to users. 【0696】 An "electronic communication network" is a communication infrastructure that enables the exchange of information via the internet and other means. 【0697】 "Information sources" refer to various media outlets, such as websites, official accounts, and news organizations, that provide information about the candidates. 【0698】 "Information aggregation" refers to a database that centrally stores acquired data to prepare it for later analysis and retrieval. 【0699】 "Natural language processing technology" is a technique for extracting useful information from text data and converting it into a format that humans can understand. 【0700】 A "campaign promise" is a set of policy promises that an election candidate makes to voters during their campaign. 【0701】 "Policy information" refers to data on specific policies related to campaign promises, as well as past performance. 【0702】 An "evaluation tool" is a system for quantifying the feasibility of a candidate's promises and achievements and conducting comparative analysis. 【0703】 A "user interface" refers to screens and output methods that allow users to visually understand the collected data and evaluation results. 【0704】 "Similarity analysis" is a method for identifying similarities in policies and promises among different candidates and visualizing their relative positions. 【0705】 This invention is centered around an information processing device and is realized with three main components: a server, a terminal, and a user. 【0706】 First, the server collects information about candidates from multiple sources via an electronic communication network. A crawler program is used to automatically retrieve data, which is then stored in an information repository. The stored information is effectively managed using Python libraries such as BeautifulSoup and requests. Next, natural language processing techniques are used to extract candidate pledges and policy information from the stored data. Specifically, TfidfVectorizer is used to vectorize text data, and then information summarization and semantic analysis are performed. 【0707】 The terminal is responsible for displaying information via a user interface based on the provided data. Based on the extracted information, it evaluates the candidates' past performance and the feasibility of fulfilling their promises. This evaluation process uses technologies such as cosine_similarity to analyze the similarities of policies among candidates and highlights more relevant information. This visualized information is presented in graphs and tables, making it easy for users to understand. 【0708】 Users interact with their devices to obtain information based on their interests. For example, when seeking information on candidates with pledges related to "environmental policy," they use prompts to request specific information from the server. A concrete example of such a prompt might be: "Please collect information on candidates with pledges focused on environmental policy and generate an evaluation score." 【0709】 This allows users to efficiently compare the promises and track records of multiple candidates and make informed decisions. The entire system aims to support voters in elections by processing data quickly and accurately. 【0710】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0711】 Step 1: 【0712】 The server collects information about candidates from multiple sources via an electronic communication network. The input is a list of website URLs. The server accesses the web pages using the requests library and parses the HTML structure using BeautifulSoup. The parsed data is stored in an information repository. The output is a structured list of candidate information. 【0713】 Step 2: 【0714】 The server applies natural language processing techniques to the stored information. Specifically, it uses the text data acquired as input and vectorizes it using TfidfVectorizer. This process extracts pledges and policy information. As output, data is generated in which the topics of the text have been vectorized. 【0715】 Step 3: 【0716】 The server evaluates candidates' pledges and past performance based on vectorized data. It uses `cosine_similarity` to calculate textual similarity. The input data consists of vectorized policy information for each candidate. The output generates a matrix of similarity scores, enabling comparative analysis of candidates. 【0717】 Step 4: 【0718】 The terminal displays the evaluation results received from the server on the user interface. Similarity scores and evaluation scores obtained from the server are provided as input. The terminal visualizes the results in graph and table format and provides them to the user. The visualized data is displayed on the screen as output, converted into a format easily understandable to the user. 【0719】 Step 5: 【0720】 Users search for information about campaign promises and policies that interest them through their terminal. Prompts related to specific policies are used as input. Based on the user's interests, the terminal sends queries to the server. The output displayed on the terminal includes relevant candidate information and evaluation scores. 【0721】 Step 6: 【0722】 Users compare candidates' policies and make decisions based on the information presented. They utilize visualized information and reliable data as input. The output is a decision based on the user's selection, which is then used as a basis for their election participation decisions. 【0723】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0724】 This invention combines a system that provides information based on candidates' promises and policies with an emotion engine that analyzes user emotions. The system comprises an information processing device, a user interface, and an emotion engine. 【0725】 Server Processing 【0726】 The server efficiently collects information related to candidates from the electronic network and uses natural language processing to extract candidates' pledges and policies into a database. Furthermore, it evaluates candidates' past performance and the feasibility of fulfilling their pledges, and generates data to present the evaluation results in the user interface. 【0727】 Emotional Engine Processing 【0728】 The emotion engine analyzes user input through the user interface and recognizes their emotional state. For example, it determines the user's level of interest and stress when researching information about election candidates. This data is received by the server and used to adjust how information is presented in the user interface. 【0729】 Terminal processing 【0730】 The terminal provides a user interface, displaying detailed information about candidates and offering information tailored to the user's emotions. After data from the emotion engine is analyzed by the server, the terminal prioritizes and displays the information most relevant to that user. For example, if a user expresses interest in a particular policy, it highlights and displays information about relevant candidates. 【0731】 The device also uses an emotion engine to recognize the user's emotions in response to a question. For example, if the user indicates anxiety, the device will present information to alleviate that anxiety or data on the candidate's trustworthiness. 【0732】 User actions 【0733】 Users can research specific candidates and policies through the device's user interface. By recognizing the user's emotions through an emotion engine, the system can provide personalized information tailored to the user, increasing their interest in the election campaign and helping them make more informed decisions. This allows users to participate more actively in the election. 【0734】 The following describes the processing flow. 【0735】 Step 1: 【0736】 The server uses a crawler program to collect data about candidates from multiple sources on the electronic network. This includes the candidates' official social media accounts and the websites of major news organizations. The collected information is stored on the server in text format. 【0737】 Step 2: 【0738】 The server uses natural language processing algorithms to analyze the stored text data. The algorithms extract pledges and policy information from the text and store this information in a database as structured data. 【0739】 Step 3: 【0740】 The server runs an evaluation algorithm that assesses candidates' past performance and the feasibility of fulfilling their promises based on a database. The evaluation results are calculated as a score that facilitates comparison between candidates. 【0741】 Step 4: 【0742】 The emotion engine built into the server receives input from the user and analyzes the user's emotional state. In this process, it evaluates the user's level of interest and stress based on the words used and the information selected. 【0743】 Step 5: 【0744】 The terminal receives evaluation results and sentiment engine analysis data from the server via the user interface. The user interface is adjusted according to the user's emotions and prioritizes the presentation of relevant candidate information. 【0745】 Step 6: 【0746】 Users interact with the device to express interest in candidates and policies and view detailed information. For example, if a user expresses interest in a particular policy, the device will highlight the positions and evaluations of candidates related to that policy. 【0747】 Step 7: 【0748】 When a user makes a query on their device, the sentiment engine recognizes the user's emotion in response to that question. The server then presents information about candidates and policies that address the question, taking the user's emotional state into consideration. 【0749】 Step 8: 【0750】 The device optimizes the information displayed on the screen based on updated information and user sentiment analysis results. This allows users to receive more accurate and personalized information to help them make informed decisions. 【0751】 (Example 2) 【0752】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0753】 In modern election campaigns, it is crucial for voters to make informed decisions based on candidates' promises and achievements. However, efficiently obtaining useful information from a vast amount of data is difficult. Furthermore, providing information tailored to each voter's emotional state and maintaining their interest is also challenging. Therefore, there is a need for a system that personalizes information based on the emotions and interests of individual users, providing higher-quality information. 【0754】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0755】 In this invention, the server includes means for acquiring information from information sources on a communication network, which serve as an information aggregation unit; means for extracting information using natural language processing technology; and means for recognizing the user's emotional state, which are equipped with an emotion analysis unit. This enables the user to receive information that is tailored to their emotions and interests quickly and accurately. 【0756】 An "information aggregation unit" is a function that collects data from various information sources on a communication network and stores it in a memory device within the system. 【0757】 A "communication network" is a network system that enables digital communication, including the internet, and is used for acquiring and transmitting data. 【0758】 A "storage device" is a storage medium or device that holds data within a system and makes it accessible as needed. 【0759】 "Natural language analysis technology" refers to techniques for analyzing meaning from text data and extracting useful information, and includes natural language processing. 【0760】 An "emotional analysis unit" is a function within a system that analyzes user input data to recognize emotional states and psychological tendencies. 【0761】 A "presentation device" is a device or interface that displays information to a user visually or audibly. 【0762】 An "evaluation unit" is a function within a system that evaluates a candidate's past actions and the feasibility of fulfilling their promises, and generates results. 【0763】 A "search unit" is a function that searches for information within a storage device in response to a specific question from the user and retrieves the relevant information. 【0764】 This invention demonstrates a combination of hardware and software that enables the construction of a system that efficiently collects and analyzes candidate pledges and policy information and provides information in accordance with the user's emotions. 【0765】 The server first collects data from internet sources via a communication network. This involves using web crawlers and data acquisition technologies via APIs. The collected data is stored in storage. For natural language processing, open-source natural language processing tools such as NLTK and SpaCy are used to structure the data and extract necessary information. This process yields information on campaign promises and policies, as well as information on candidates' past performance. 【0766】 The server also has an emotion analysis unit that analyzes text data entered by the user through the terminal in real time. This process uses emotion analysis APIs and machine learning models to identify the user's emotional state. For example, it determines the level of interest and stress based on the speed and content of the user's typing. 【0767】 The terminal receives analysis results transmitted from the server and provides them to the user through a display device. In this process, information is visualized using HTML and CSS, and presented in a user-friendly interface. Furthermore, based on data obtained from sentiment analysis, highly relevant information is prioritized and displayed. 【0768】 Furthermore, the system uses a generative AI model to enable users to resolve their questions through prompts. A typical prompt might be something like, "Tell me how your views on tax reform differ from those of the other candidates." Based on this prompt, the AI ​​model scrutinizes the information most useful to the user and generates a response. 【0769】 In this way, the system enables the provision of information that is tailored to the user's interests and emotions, and supports their decision-making. 【0770】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0771】 Step 1: 【0772】 The server collects information about candidates from multiple sources on the internet via a communication network. Using specified keywords and URL lists as input, it extracts relevant data through web crawling techniques. As output, it stores text data containing candidate information in a temporary storage area. 【0773】 Step 2: 【0774】 The server processes the collected information using natural language processing (NLP) techniques. The input is text data, and natural language processing tools are used to tokenize sentences, tag parts of speech, and perform semantic analysis. The output is structured data, such as candidates' pledges, policies, and past achievements. This process includes converting the data into a format that can be stored in a database. 【0775】 Step 3: 【0776】 The terminal accepts queries through the user interface. It receives a request for information on a specified policy or candidate from the user as input, and then queries the server based on that information. The output is a visual presentation of relevant details to the user. Specifically, it uses HTML / CSS to format and display the information clearly. 【0777】 Step 4: 【0778】 The emotion analysis unit continuously monitors user input through the interface. It analyzes user text input and interaction patterns as input, quantifying the emotional state. The output is data regarding the user's level of interest and emotional state, which is used to determine the optimal method of information presentation. 【0779】 Step 5: 【0780】 The server personalizes information presentation based on sentiment analysis results. The input is data from sentiment analysis, and an algorithm is applied to prioritize information that the user is most likely to be interested in. The output is a selection and highlighting of the most relevant information for the user, thereby supporting the user in obtaining the most optimal information from the system. 【0781】 Step 6: 【0782】 The generative AI model generates responses in response to user prompts. It receives prompts as input and uses natural language generation techniques to generate relevant answers. The output is a text response to the user's question, which is presented in real time through the interface. 【0783】 (Application Example 2) 【0784】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0785】 In modern elections, voters must sift through a vast amount of information about candidates' promises and policies, and spend considerable time and effort judging whether that information aligns with their interests. Furthermore, because emotions related to the information are not taken into account, there is a high likelihood of anxiety and mismatches of interests. 【0786】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0787】 In this invention, the server includes means for acquiring information about candidates from multiple information sources on an electronic network and storing it in a database, means for extracting candidates' pledges and policy information from the stored information using natural language processing technology, and means for presenting information tailored to the user's interests and emotions using sentiment analysis results. This makes it possible for users to quickly and easily obtain election information that matches their interests and emotions. 【0788】 An "information processing device" is a device that collects and processes data from multiple information sources via an electronic network. 【0789】 A "data collection method" is a means that has the function of acquiring information through an electronic network and storing it in a database. 【0790】 "Natural language processing technology" is a technology that analyzes human language and extracts information from it. 【0791】 An "evaluation tool" is a means that has the function of evaluating a candidate's past performance and the feasibility of fulfilling their promises based on extracted information. 【0792】 "User interface" refers to the screens or consoles that users use to interact with a system. 【0793】 "Emotional analysis tools" are functions that analyze a user's emotional state based on their input and behavior. 【0794】 An "information presentation means" is a means that has the function of presenting collected information to the user in an appropriate format. 【0795】 A "database" is a structure for organizing and storing information so that it can be accessed efficiently. 【0796】 A "search function" is a feature that allows users to quickly retrieve the information they need from a database. 【0797】 This invention is a system for providing election information and is built around an information processing device. The system includes multiple components, each with its own role in processing information. 【0798】 The server collects data about candidates from numerous sources via an electronic network and stores it in a database. The server also uses natural language processing technologies (e.g., spaCy and NLTK) to analyze the information in the database and extract candidate promises and policy information. Based on the extracted data, it evaluates the candidate's past performance and the feasibility of fulfilling their promises. Furthermore, it uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state from their input and behavior. This allows the server to adjust the information presented according to the user's interests and emotions, displaying particularly high-demand information in the user interface. 【0799】 The device displays relevant information to the user through its user interface. Detailed information on policies of interest to the user is presented in a highlighted format. Furthermore, the results of sentiment analysis are used to provide additional information beneficial to the user. In this process, the aim is to improve the user experience by prioritizing the presentation of areas of particular user interest. 【0800】 For example, if a user uses a smartphone app and expresses interest in "environmental policy," the system will prioritize displaying relevant policy information, presenting past success stories and reliable data. Additionally, based on the user's concerns and interests, the system will provide information that alleviates their emotions or piques their specific interest. 【0801】 An example of a prompt might be, "Please describe in detail the candidate's track record, which could be helpful in providing information if the user is feeling anxious." This prompt prompts the system to select and present appropriate information through the user interface. 【0802】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0803】 Step 1: 【0804】 The server collects information about candidates from various sources via an electronic network. The input is data from each source, and the output is data stored in a processable format. A data collection module on the server performs this task, and the resulting data is stored in a database. 【0805】 Step 2: 【0806】 The server uses natural language processing techniques to extract candidate pledges and policy information from the database. The input is raw data from the database, and the output is organized information about pledges and policies. Natural language processing libraries (e.g., spaCy, NLTK) are applied to classify and organize the information. 【0807】 Step 3: 【0808】 The server evaluates the candidate's past performance and the feasibility of fulfilling their promises based on the extracted information. The input is the information obtained in step 2, and the output is the evaluation result. The evaluation algorithm analyzes the feasibility of fulfilling promises using past performance data and generates an evaluation score. 【0809】 Step 4: 【0810】 The sentiment analysis engine analyzes user input via the user interface to recognize the emotional state. The input is real-time data from the user, and the output is analyzed sentiment data. The sentiment analysis engine (e.g., IBM Watson Tone Analyzer) performs this task and outputs the results. 【0811】 Step 5: 【0812】 The device adjusts information based on the user's interests and emotions, using sentiment analysis results. Input consists of output data from the sentiment analysis engine and evaluation results from the server. The device's algorithm analyzes the data and adjusts the information presented based on priority. 【0813】 Step 6: 【0814】 Users review the organized information through the user interface. The input is organized information presented from the device, and the output is useful information to aid in the user's decision-making. The user interface presents highlighted information and relevant data, which the user uses to select candidates. 【0815】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0816】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0817】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0818】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0819】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0820】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0821】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0822】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0823】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0824】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0825】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0826】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0827】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0828】 Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12. 【0829】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0830】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0831】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0832】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0833】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0834】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0835】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0836】 The following is further disclosed regarding the embodiments described above. 【0837】 (Claim 1) 【0838】 The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing said information in a database, 【0839】 A means for extracting candidate pledges and policy information from the information stored in the database using natural language processing technology, 【0840】 An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, 【0841】 A means for presenting the aforementioned evaluation results via a user interface, 【0842】 A system that includes this. 【0843】 (Claim 2) 【0844】 The system according to claim 1, further comprising means for continuously tracking the progress of candidates' pledges and updating the database. 【0845】 (Claim 3) 【0846】 The system according to claim 1, further comprising a search means for searching the database based on a user's question about a specific policy or candidate and presenting information corresponding to the question. 【0847】 "Example 1" 【0848】 (Claim 1) 【0849】 The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means, and means for storing said information on a data storage medium. 【0850】 A means for extracting candidate pledges and policy information from information stored in the data storage medium using natural language processing technology, 【0851】 An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, 【0852】 Means for presenting the evaluation results via a display device, 【0853】 A means for generating an evaluation score for a candidate and using the score as an evaluation metric, 【0854】 A means of creating prompts for a generative AI model and presenting them to the user, 【0855】 A system that includes this. 【0856】 (Claim 2) 【0857】 The system according to claim 1, comprising means for continuously tracking the progress of a candidate's pledges and updating the data storage medium. 【0858】 (Claim 3) 【0859】 The system according to claim 1, comprising a search means for searching the data storage medium based on a question from a user regarding a specific policy or candidate, and for presenting information corresponding to the question. 【0860】 "Application Example 1" 【0861】 (Claim 1) 【0862】 The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic communication network as a data collection means, and means for storing said information in an information aggregate. 【0863】 A means for extracting candidate pledges and policy information from the information stored in the aforementioned information collection using natural language processing technology, 【0864】 An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, 【0865】 A means for presenting the aforementioned evaluation results via a user interface, 【0866】 To provide information based on user interests, a means of analyzing the similarities between candidates and visualizing and highlighting the most relevant information, 【0867】 A system that includes this. 【0868】 (Claim 2) 【0869】 The system according to claim 1, further comprising means for continuously tracking the progress of candidates' pledges and updating the information collection. 【0870】 (Claim 3) 【0871】 The system according to claim 1, further comprising a search means for searching the information collection based on inquiries from users regarding specific policies or candidates, and for presenting information in response to said inquiries. 【0872】 "Example 2 of combining an emotion engine" 【0873】 (Claim 1) 【0874】 An information processing system is a unit that, as an information aggregation unit, acquires information related to a candidate from multiple information sources on a communication network and stores that information in a storage device. 【0875】 A unit that uses natural language processing technology to extract candidate promises and policy information from the information stored in the memory device, 【0876】 Based on the extracted information, an evaluation unit is used to assess the candidate's past actions and the feasibility of fulfilling their promises, 【0877】 The unit that presents the aforementioned evaluation result via the display device, 【0878】 It is equipped with an emotion analysis unit, which analyzes user input and recognizes the emotional state, 【0879】 A unit that adjusts information presentation based on the user's emotional state and prioritizes the presentation of highly relevant information, 【0880】 A system that includes this. 【0881】 (Claim 2) 【0882】 The system according to claim 1, comprising a unit for continuously tracking the progress of candidate commitments and updating the storage device. 【0883】 (Claim 3) 【0884】 The system according to claim 1, further comprising a search unit that searches the storage device based on a question from a user regarding a specific strategy or candidate, and presents information corresponding to the question. 【0885】 "Application example 2 when combining with an emotional engine" 【0886】 (Claim 1) 【0887】 The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing said information in a database, 【0888】 A means for extracting candidate pledges and policy information from the information stored in the database using natural language processing technology, 【0889】 An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, 【0890】 A sentiment analysis means that adjusts the content of information presented based on the user's emotional state, 【0891】 A means for presenting information tailored to the user's interests and emotions via a user interface, using the aforementioned emotion analysis results, 【0892】 A system that includes this. 【0893】 (Claim 2) 【0894】 The system according to claim 1, comprising means for continuously tracking the progress of a candidate's pledges and updating the database, and using sentiment analysis means to provide emotional responses tailored to the user's questions. 【0895】 (Claim 3) 【0896】 The system according to claim 1, comprising a search means for searching the database based on a user's question about a specific policy or candidate and presenting information corresponding to the question, and further comprising a means for highlighting highly reliable information based on sentiment analysis results. [Explanation of symbols] 【0897】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] The information processing device includes means for acquiring information about candidates from multiple information sources on an electronic network as a data collection means and storing said information in a database, A means for extracting candidate pledges and policy information from the information stored in the database using natural language processing technology, An evaluation method that assesses the candidate's past performance and the feasibility of fulfilling their promises based on extracted information, A means for presenting the aforementioned evaluation results via a user interface, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for continuously tracking the progress of candidates' pledges and updating the database. [Claim 3] The system according to claim 1, further comprising a search means for searching the database based on a user's question about a specific policy or candidate and presenting information corresponding to the question.

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