System

Abstract

An object of a system according to an embodiment is to enable a voter to easily find a politician suitable for the voter.SOLUTION: A system includes a history provision part, an activity provision part, a belief provision part, a retrieval comparison part, and an election information provision part. The background providing part provides the background of the politician. The activity providing unit provides an activity of a politician. The belief provider provides a belief of the politician. A retrieval and comparison part retrieves and compares information on politicians. The election information providing unit provides information on candidates at the time of election.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, there was an imbalance in information between politicians and voters, making it difficult to find the ideal politician.

[0005] The system according to the embodiment aims to enable voters to easily find politicians who suit them. [Means for solving the problem]

[0006] The system according to the embodiment includes a history providing unit, an activity providing unit, a belief providing unit, a search and comparison unit, and an election information providing unit. The history providing unit provides the history of politicians. The activity providing unit provides the activities of politicians. The belief providing unit provides the beliefs of politicians. The search and comparison unit searches and compares information about politicians. The election information providing unit provides information about candidates during elections. [Effects of the Invention]

[0007] The system according to the embodiment can make it easy for voters to find politicians who suit them. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The politician information provision system according to an embodiment of the present invention is a system that allows voters to easily find a politician who suits them by clearly conveying the careers, activities, and beliefs of politicians. As a result, the politician information provision system can increase the transparency of politics and promote the improvement of its quality.

[0029] A politician information providing system according to an embodiment includes a history providing unit, an activity providing unit, a belief providing unit, a search and comparison unit, and an election information providing unit. The history providing unit provides the history of a politician. For example, the history providing unit provides detailed information about the politician's educational background and work history. The history providing unit can also provide the politician's awards and past political activities. For example, the history providing unit provides information about which university the politician graduated from and what kind of work experience he or she has. The activity providing unit provides the politician's activities. For example, the activity providing unit provides information about what bills the politician has submitted in the past. The activity providing unit can also provide information about what policies the politician has promoted. For example, the activity providing unit provides information about what social issues the politician has addressed. The belief providing unit provides the politician's beliefs. For example, the belief providing unit provides information about the politician's ideals. The belief providing unit can also provide information about what kind of society the politician is aiming for. For example, the belief providing unit provides information about what social justice the politician values. The search and comparison unit searches for and compares information about politicians. For example, the search and comparison unit compares candidates' positions on specific policies. The search and comparison unit can also compare each candidate's position on environmental policy. For example, the search and comparison unit allows a voter who is interested in environmental policy to compare each candidate's position on environmental policy. The election information providing unit provides information about candidates during elections. For example, the election information providing unit provides information summarizing the backgrounds, activities, and beliefs of candidates for each electoral district. The election information providing unit can also display a list of candidate profiles for each electoral district, allowing voters to easily compare candidates. For example, the election information providing unit aggregates candidate information for each electoral district and displays it in a list. In this way, the politician information providing system according to the embodiment can easily convey politicians' backgrounds, activities, and beliefs, allowing voters to easily find a politician who suits them. For example, voters can easily obtain and compare candidate information during elections. Furthermore, making politicians' backgrounds, activities, and beliefs transparent is expected to promote improvements in the quality of politics.

[0030] The career provision unit can use the generation AI to automatically collect data on politicians' careers and filter out only data from highly reliable sources. The career provision unit can, for example, use the generation AI to automatically collect data on politicians' careers and filter out only data from highly reliable sources. For example, it can prioritize collecting information from official websites and reliable news sources and store it in a database. The generation AI can, for example, use a natural language processing model to analyze information on the internet and collect data on politicians' careers. The generation AI can also use a data collection algorithm to filter out only data from highly reliable sources. For example, the generation AI can prioritize collecting data from public institutions and reliable news sources and store it in a database. This makes it possible to provide accurate information to voters by providing only data from highly reliable sources.

[0031] The career providing unit can create an interactive timeline that visually displays a politician's career, allowing a user to intuitively understand it. The career providing unit, for example, creates an interactive timeline that visually displays a politician's career, allowing a user to intuitively understand it. For example, the politician's educational background and work history may be displayed chronologically, with detailed information displayed by a click. The career providing unit can also display the politician's awards and past political activities on the timeline. For example, the career providing unit may display which university a politician graduated from and what kind of work experience he or she has in chronological order, with detailed information displayed by a click. The interactive timeline, for example, has a function that allows a user to click to display detailed information. The interactive timeline can also have a function that allows a user to scroll to check the career. For example, the interactive timeline allows a user to scroll to check the politician's career, with detailed information displayed by a click. This allows a user to intuitively understand the politician's career.

[0032] The career providing unit can provide the career information of politicians in audio or video format, allowing users to obtain the information not only visually but also aurally. For example, the career providing unit can provide the career information of politicians in audio or video format, allowing users to obtain the information not only visually but also aurally. For example, the career providing unit can post interview videos or audio messages of the politicians themselves. The career providing unit can also provide the career information of politicians as audio files. For example, the career providing unit can provide the politician's educational background and work history as audio files, allowing users to obtain the information aurally. For example, the audio file format and video resolution can be specified for the audio and video formats. For example, audio files are provided in MP3 format and videos in HD resolution. This allows users to obtain the information not only visually but also aurally.

[0033] The career providing unit can add a function to compare a politician's career with the careers of other politicians or celebrities, thereby enabling a relative evaluation. The career providing unit can add, for example, a function to compare a politician's career with the careers of other politicians or celebrities, thereby enabling a relative evaluation. For example, the careers of other candidates in the same electoral district can be compared. The career providing unit can also compare with the careers of famous politicians or celebrities. For example, the career providing unit compares the educational backgrounds and work histories of other candidates in the same electoral district and performs a relative evaluation. The careers of other politicians or celebrities can, for example, collect information on candidates in the same electoral district or famous politicians. For example, the career providing unit collects and compares the educational backgrounds and work histories of candidates in the same electoral district. This enables a relative evaluation.

[0034] The activity provision unit can use the generation AI to automatically analyze a politician's activity history and highlight important activities and achievements. For example, the activity provision unit can automatically analyze a politician's activity history using the generation AI and highlight important activities and achievements. For example, it can automatically extract and highlight achievements such as bill submissions and policy realizations. The generation AI can analyze a politician's activity history using, for example, a natural language processing model. The generation AI can also highlight important activities and achievements using a data collection algorithm. For example, the generation AI can analyze past policy proposals and parliamentary attendance rates to extract important activities. Activity history includes, for example, past policy proposals, parliamentary attendance rates, and local activities. For example, the activity provision unit can analyze a politician's past policy proposals and parliamentary attendance rates to highlight important activities. This makes it easier for voters to understand a politician's achievements by highlighting important activities and achievements.

[0035] The activity providing unit can plot the activities of politicians on a map and visually display the details of their activities for each region. The activity providing unit, for example, plots the activities of politicians on a map and visually displays the details of their activities for each region. For example, the policy implementation status and event participation history in each region are displayed on the map. The activity providing unit can also build a system that visually displays the details of activities for each region. For example, the activity providing unit displays the policy implementation status and event participation history in each region on a map, and users can click to display detailed information. Plotting on a map can be done, for example, using GIS technology. For example, GIS technology can be used to display the policy implementation status and event participation history in each region on a map. This makes it easier for voters to understand politicians' activities by visually displaying the details of activities for each region.

[0036] The activity providing unit can add a function to compare a politician's activities with those of other politicians or organizations and perform a relative evaluation. The activity providing unit, for example, adds a function to compare a politician's activities with those of other politicians or organizations and perform a relative evaluation. For example, activity performance in the same policy field is compared. The activity providing unit can also compare with the activities of well-known politicians or organizations. For example, the activity providing unit compares activity performance in the same policy field and performs a relative evaluation. The activities of other politicians and organizations can, for example, collect information on candidates in the same electoral district or well-known organizations. For example, the activity providing unit collects and compares the activity performance of candidates in the same electoral district. This allows for a relative evaluation.

[0037] The activity providing unit can collect user feedback regarding politicians' activities and automatically generate improvement proposals for the activities using a generation AI. The activity providing unit, for example, collects user feedback regarding politicians' activities and automatically generates improvement proposals for the activities using a generation AI. For example, it proposes improvements to the activities based on user opinions. The activity providing unit can also analyze user feedback using a generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement proposals for the activities. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the activity providing unit collects user feedback through questionnaire surveys or online reviews and analyzes it using a generation AI. This makes it possible to automatically generate improvement proposals for the activities based on user feedback.

[0038] The belief providing unit can use the generation AI to analyze the politician's beliefs and values ​​and visually display the consistency and changes in beliefs. The belief providing unit, for example, uses the generation AI to analyze the politician's beliefs and values ​​and visually display the consistency and changes in beliefs. For example, it displays the changes in beliefs in timeline format based on past statements and actions. The generation AI, for example, uses a natural language processing model to analyze the politician's beliefs and values. The generation AI can also visually display the consistency and changes in beliefs using a data collection algorithm. For example, the generation AI analyzes past statements and actions and displays the changes in beliefs in timeline format. The consistency and changes in beliefs can be determined, for example, by analyzing time series data and displaying them in graphs. For example, the belief providing unit analyzes time series data and displays the changes in beliefs in graphs. In this way, the consistency and changes in beliefs can be visually displayed, making it easier for voters to understand the politician's beliefs.

[0039] The belief providing unit can automatically collect past statements and actions related to a politician's beliefs and provide data that supports the beliefs. The belief providing unit, for example, automatically collects past statements and actions related to a politician's beliefs and provides data that supports the beliefs. For example, past speeches and interview articles may be automatically collected to confirm the consistency of beliefs. The belief providing unit can also use a data collection algorithm to provide data that supports the beliefs. For example, the belief providing unit collects parliamentary records and media reports to provide data that supports the beliefs. Past statements and actions can be collected, for example, through parliamentary records and media reports. For example, the belief providing unit collects parliamentary records and media reports to provide data that supports the beliefs. In this way, by providing data that supports the beliefs, voters can gain a deeper understanding of the politician's beliefs.

[0040] The belief providing unit can add a function to compare a politician's beliefs with the beliefs of other politicians or celebrities and perform a relative evaluation. The belief providing unit can add a function to compare a politician's beliefs with the beliefs of other politicians or celebrities and perform a relative evaluation. For example, it can compare differences in beliefs in the same policy area. The belief providing unit can also compare with the beliefs of famous politicians or celebrities. For example, it can compare differences in beliefs in the same policy area and perform a relative evaluation. The beliefs of other politicians or celebrities can, for example, collect information about candidates in the same electoral district or famous politicians. For example, the belief providing unit can collect and compare the beliefs of candidates in the same electoral district. This allows for a relative evaluation.

[0041] The belief providing unit can collect user feedback regarding the politician's beliefs and automatically generate improvement suggestions for the belief content using the generation AI. The belief providing unit, for example, collects user feedback regarding the politician's beliefs and automatically generates improvement suggestions for the belief content using the generation AI. For example, it suggests improvements to the beliefs based on the user's opinions. The belief providing unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement suggestions for the belief content. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the belief providing unit collects user feedback through questionnaire surveys or online reviews and analyzes it using the generation AI. In this way, improvement suggestions for the belief content can be automatically generated based on the user feedback.

[0042] The search comparison unit can analyze search results using a generation AI and provide customized information based on the user's interests. The search comparison unit, for example, analyzes search results using a generation AI and provides customized information based on the user's interests. For example, related information is prioritized and displayed based on the user's past search history. The search comparison unit can also analyze the user's interests using a generation AI. For example, the generation AI analyzes the user's search history and click history and provides information based on the interests. Customized information includes, for example, a news feed and personalized recommendations based on the user's interests. For example, the search comparison unit provides a news feed based on the user's interests and prioritizes related information. This makes it possible to provide customized information based on the user's interests.

[0043] The search comparison unit can create an interactive dashboard that allows the user to visually compare search results, thereby enabling an intuitive understanding by the user. The search comparison unit, for example, creates an interactive dashboard that allows the user to visually compare search results, thereby enabling an intuitive understanding by the user. For example, the search comparison unit displays information about each candidate in a graph or chart. The search comparison unit can also provide a function that allows the user to click to display detailed information using the interactive dashboard. For example, the search comparison unit displays information about each candidate in a graph or chart, and the user clicks to display detailed information. The interactive dashboard, for example, has a function that allows the user to click to display detailed information. The interactive dashboard can also have a function that allows the user to scroll to check information. For example, the interactive dashboard allows the user to scroll to check information about each candidate, and click to display detailed information. This allows the user to intuitively understand the search results.

[0044] The search comparison unit can add a function to compare search results with search results of other users and perform a relative evaluation. The search comparison unit can add a function to compare search results with search results of other users and perform a relative evaluation, for example. For example, it can display other users' evaluations for the same search keyword. The search comparison unit can also collect and compare search results of other users. For example, the search comparison unit collects and compares search results for the same keyword or similar search queries. The search results of other users include, for example, search results for the same keyword or similar search queries. For example, the search comparison unit collects and compares search results for the same keyword or similar search queries. This allows for a relative evaluation.

[0045] The search comparison unit can collect user feedback on search results and automatically generate improvement suggestions for the search algorithm using the generation AI. The search comparison unit, for example, collects user feedback on search results and automatically generates improvement suggestions for the search algorithm using the generation AI. For example, the search comparison unit adjusts the display order of search results based on user opinions. The search comparison unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement suggestions for the search algorithm. Feedback can be collected, for example, through surveys or online reviews. For example, the search comparison unit collects user feedback through surveys or online reviews and analyzes it using the generation AI. This makes it possible to automatically generate improvement suggestions for the search algorithm based on user feedback.

[0046] The election information provision unit can automatically aggregate candidate information during elections using generation AI and filter only data from highly reliable sources. The election information provision unit, for example, can automatically aggregate candidate information during elections using generation AI and filter only data from highly reliable sources. For example, it can prioritize collecting information from official websites and reliable news sources and store it in a database. The generation AI can, for example, use a natural language processing model to analyze information on the internet and collect candidate information. The generation AI can also use a data collection algorithm to filter only data from highly reliable sources. For example, the generation AI can prioritize collecting data from public institutions and reliable news sources and store it in a database. This makes it possible to provide accurate candidate information to voters by providing only data from highly reliable sources.

[0047] The election information providing unit can create an interactive map that visually displays candidate information during an election, allowing a user to intuitively understand the information. The election information providing unit, for example, creates an interactive map that visually displays candidate information during an election, allowing a user to intuitively understand the information. For example, candidate information for each electoral district can be displayed on a map, and detailed information can be displayed by clicking. The election information providing unit can also provide a function that allows a user to click to display detailed information using the interactive map. For example, the election information providing unit displays candidate information for each electoral district on a map, and detailed information can be displayed by clicking. The interactive map, for example, has a function that allows a user to click to display detailed information. The interactive map can also have a function that allows a user to scroll to check information. For example, the interactive map allows a user to scroll to check information for each candidate, and detailed information can be displayed by clicking. This allows a user to intuitively understand candidate information.

[0048] The election information providing unit can add a function to compare candidate information at the time of an election with information on other electoral districts and perform a relative evaluation. The election information providing unit can add a function to compare candidate information at the time of an election with information on other electoral districts and perform a relative evaluation. For example, the positions of candidates in the same policy area are compared. The election information providing unit can also collect and compare information on other electoral districts. For example, the election information providing unit compares the positions of candidates in the same policy area and performs a relative evaluation. Information on other electoral districts includes, for example, the candidate's profile, policies, and campaign promises. For example, the election information providing unit collects and compares the profiles, policies, and campaign promises of candidates in other electoral districts. This allows for a relative evaluation.

[0049] The election information provision unit can collect user feedback regarding candidate information during elections and automatically generate improvement proposals for information provision using the generation AI. The election information provision unit, for example, collects user feedback regarding candidate information during elections and automatically generates improvement proposals for information provision using the generation AI. For example, it proposes improvements to the information based on user opinions. The election information provision unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement proposals for information provision. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the election information provision unit collects user feedback through questionnaire surveys or online reviews and analyzes it using the generation AI. This makes it possible to automatically generate improvement proposals for information provision based on user feedback.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The politician information provision system can further include a news provision unit that provides a news feed based on the user's interests. The news provision unit, for example, analyzes the user's past search history and click history and preferentially displays news based on the user's interests. The news provision unit can also analyze the user's interests using a generation AI. For example, the generation AI analyzes the user's search history and click history and provides news based on the user's interests. This makes it possible to provide a customized news feed based on the user's interests.

[0052] The politician information provision system can further include a feedback collection unit that collects user feedback and automatically generates system improvement proposals using a generation AI. The feedback collection unit collects user feedback, for example, through questionnaire surveys or online reviews, and analyzes it using a generation AI. The feedback collection unit can also suggest system improvements based on user opinions. This allows system improvement proposals to be automatically generated based on user feedback.

[0053] The politician information provision system can further include a recommendation unit that provides recommendations based on the user's interests. For example, the recommendation unit analyzes the user's past search history and click history to recommend candidates and policies based on the user's interests. The recommendation unit can also use generation AI to analyze the user's interests. This allows the system to provide customized recommendations based on the user's interests.

[0054] The politician information provision system can further include a feedback collection unit that collects user feedback and automatically generates system improvement proposals using a generation AI. The feedback collection unit collects user feedback, for example, through questionnaire surveys or online reviews, and analyzes it using a generation AI. The feedback collection unit can also suggest system improvements based on user opinions. This allows system improvement proposals to be automatically generated based on user feedback.

[0055] The politician information provision system can further include a news provision unit that provides a news feed based on the user's interests. The news provision unit, for example, analyzes the user's past search history and click history and prioritizes displaying news based on the user's interests. The news provision unit can also use generation AI to analyze the user's interests. This makes it possible to provide a customized news feed based on the user's interests.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The career provider provides the politician's career history. For example, the career provider provides details of the politician's educational background, work history, awards, and past political activities. Specifically, it provides information on which university the politician graduated from and what kind of work experience he or she has. Step 2: The activity provider provides information on the politician's activities. For example, the activity provider provides information on what bills the politician has submitted in the past, what policies he or she has promoted, and what social issues he or she has addressed. Step 3: The belief provider provides the politician's beliefs. For example, the belief provider provides information about the politician's ideals, the type of society they are aiming for, and the social justice they value. Step 4: The search and compare unit searches and compares information about politicians. For example, the search and compare unit can compare candidates' positions on specific policies or each candidate's stance on environmental policy. This allows voters to easily compare each candidate's position. Step 5: The Election Information Provider provides information on candidates at the time of election. For example, the Election Information Provider provides information summarizing the backgrounds, activities, and beliefs of candidates for each electoral district, and displays candidate profiles in a list. This allows voters to easily compare information on candidates.

[0058] (Example 2) The politician information provision system according to an embodiment of the present invention is a system that allows voters to easily find a politician who suits them by clearly conveying the careers, activities, and beliefs of politicians. As a result, the politician information provision system can increase the transparency of politics and promote the improvement of its quality.

[0059] A politician information providing system according to an embodiment includes a history providing unit, an activity providing unit, a belief providing unit, a search and comparison unit, and an election information providing unit. The history providing unit provides the history of a politician. For example, the history providing unit provides detailed information about the politician's educational background and work history. The history providing unit can also provide the politician's awards and past political activities. For example, the history providing unit provides information about which university the politician graduated from and what kind of work experience he or she has. The activity providing unit provides the politician's activities. For example, the activity providing unit provides information about what bills the politician has submitted in the past. The activity providing unit can also provide information about what policies the politician has promoted. For example, the activity providing unit provides information about what social issues the politician has addressed. The belief providing unit provides the politician's beliefs. For example, the belief providing unit provides information about the politician's ideals. The belief providing unit can also provide information about what kind of society the politician is aiming for. For example, the belief providing unit provides information about what social justice the politician values. The search and comparison unit searches for and compares information about politicians. For example, the search and comparison unit compares candidates' positions on specific policies. The search and comparison unit can also compare each candidate's position on environmental policy. For example, the search and comparison unit allows a voter who is interested in environmental policy to compare each candidate's position on environmental policy. The election information providing unit provides information about candidates during elections. For example, the election information providing unit provides information summarizing the backgrounds, activities, and beliefs of candidates for each electoral district. The election information providing unit can also display a list of candidate profiles for each electoral district, allowing voters to easily compare candidates. For example, the election information providing unit aggregates candidate information for each electoral district and displays it in a list. In this way, the politician information providing system according to the embodiment can easily convey politicians' backgrounds, activities, and beliefs, allowing voters to easily find a politician who suits them. For example, voters can easily obtain and compare candidate information during elections. Furthermore, making politicians' backgrounds, activities, and beliefs transparent is expected to promote improvements in the quality of politics.

[0060] The career provision unit can use the generation AI to automatically collect data on politicians' careers and filter out only data from highly reliable sources. The career provision unit can, for example, use the generation AI to automatically collect data on politicians' careers and filter out only data from highly reliable sources. For example, it can prioritize collecting information from official websites and reliable news sources and store it in a database. The generation AI can, for example, use a natural language processing model to analyze information on the internet and collect data on politicians' careers. The generation AI can also use a data collection algorithm to filter out only data from highly reliable sources. For example, the generation AI can prioritize collecting data from public institutions and reliable news sources and store it in a database. This makes it possible to provide accurate information to voters by providing only data from highly reliable sources.

[0061] The career providing unit can create an interactive timeline that visually displays a politician's career, allowing a user to intuitively understand it. The career providing unit, for example, creates an interactive timeline that visually displays a politician's career, allowing a user to intuitively understand it. For example, the politician's educational background and work history may be displayed chronologically, with detailed information displayed by a click. The career providing unit can also display the politician's awards and past political activities on the timeline. For example, the career providing unit may display which university a politician graduated from and what kind of work experience he or she has in chronological order, with detailed information displayed by a click. The interactive timeline, for example, has a function that allows a user to click to display detailed information. The interactive timeline can also have a function that allows a user to scroll to check the career. For example, the interactive timeline allows a user to scroll to check the politician's career, with detailed information displayed by a click. This allows a user to intuitively understand the politician's career.

[0062] The career providing unit can use the emotion estimation function to analyze voters' emotional reactions to a politician's career and suggest key points in the career that will elicit a positive reaction. The career providing unit, for example, uses the emotion estimation function to analyze voters' emotional reactions to a politician's career and suggest key points in the career that will elicit a positive reaction. For example, the career providing unit highlights a specific career based on a user's emotion score. The career providing unit can also analyze users' emotional reactions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes a user's facial expressions and voice to calculate an emotion score. The emotion estimation function, for example, uses an emotion analysis algorithm to analyze users' emotional reactions. The emotion estimation function can also collect users' emotional reactions using a data collection method. For example, the emotion estimation function analyzes a user's facial expressions and voice to calculate an emotion score. As a result, key points in the career that will elicit a positive reaction are suggested based on voters' emotional reactions.

[0063] The career providing unit can provide the career information of politicians in audio or video format, allowing users to obtain the information not only visually but also aurally. For example, the career providing unit can provide the career information of politicians in audio or video format, allowing users to obtain the information not only visually but also aurally. For example, the career providing unit can post interview videos or audio messages of the politicians themselves. The career providing unit can also provide the career information of politicians as audio files. For example, the career providing unit can provide the politician's educational background and work history as audio files, allowing users to obtain the information aurally. For example, the audio file format and video resolution can be specified for the audio and video formats. For example, audio files are provided in MP3 format and videos in HD resolution. This allows users to obtain the information not only visually but also aurally.

[0064] The career providing unit can add a function to compare a politician's career with the careers of other politicians or celebrities, thereby enabling a relative evaluation. The career providing unit can add, for example, a function to compare a politician's career with the careers of other politicians or celebrities, thereby enabling a relative evaluation. For example, the careers of other candidates in the same electoral district can be compared. The career providing unit can also compare with the careers of famous politicians or celebrities. For example, the career providing unit compares the educational backgrounds and work histories of other candidates in the same electoral district and performs a relative evaluation. The careers of other politicians or celebrities can, for example, collect information on candidates in the same electoral district or famous politicians. For example, the career providing unit collects and compares the educational backgrounds and work histories of candidates in the same electoral district. This enables a relative evaluation.

[0065] The career providing unit can use an emotion estimation function to monitor users' emotions toward a politician's career in real time and dynamically change the way the career is displayed. The career providing unit, for example, uses the emotion estimation function to monitor users' emotions toward a politician's career in real time and dynamically change the way the career is displayed. For example, careers with strong positive emotions are highlighted. The career providing unit can also analyze users' emotions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice and calculates an emotion score. Real-time monitoring can be performed, for example, using real-time data collection and analysis algorithms. For example, real-time data collection involves collecting the user's facial expressions and voice in real time and analyzing them using an emotion estimation algorithm. This allows the way the career is displayed to be dynamically changed depending on the user's emotions.

[0066] The activity provision unit can use the generation AI to automatically analyze a politician's activity history and highlight important activities and achievements. For example, the activity provision unit can automatically analyze a politician's activity history using the generation AI and highlight important activities and achievements. For example, it can automatically extract and highlight achievements such as bill submissions and policy realizations. The generation AI can analyze a politician's activity history using, for example, a natural language processing model. The generation AI can also highlight important activities and achievements using a data collection algorithm. For example, the generation AI can analyze past policy proposals and parliamentary attendance rates to extract important activities. Activity history includes, for example, past policy proposals, parliamentary attendance rates, and local activities. For example, the activity provision unit can analyze a politician's past policy proposals and parliamentary attendance rates to highlight important activities. This makes it easier for voters to understand a politician's achievements by highlighting important activities and achievements.

[0067] The activity providing unit can plot the activities of politicians on a map and visually display the details of their activities for each region. The activity providing unit, for example, plots the activities of politicians on a map and visually displays the details of their activities for each region. For example, the policy implementation status and event participation history in each region are displayed on the map. The activity providing unit can also build a system that visually displays the details of activities for each region. For example, the activity providing unit displays the policy implementation status and event participation history in each region on a map, and users can click to display detailed information. Plotting on a map can be done, for example, using GIS technology. For example, GIS technology can be used to display the policy implementation status and event participation history in each region on a map. This makes it easier for voters to understand politicians' activities by visually displaying the details of activities for each region.

[0068] The activity providing unit can use the emotion estimation function to analyze voters' emotional reactions to a politician's activities and highlight positive activities. The activity providing unit, for example, uses the emotion estimation function to analyze voters' emotional reactions to a politician's activities and highlight positive activities. For example, activities with a high emotion score are automatically highlighted. The activity providing unit can also use an emotion estimation algorithm to analyze users' emotional reactions in real time. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice to calculate an emotion score. Positive activities include, for example, social contribution activities and successful policy proposals. For example, the activity providing unit highlights social contribution activities and successful policy proposals. In this way, by highlighting positive activities based on voters' emotional reactions, understanding of the politician's activities is deepened.

[0069] The activity providing unit can add a function to compare a politician's activities with those of other politicians or organizations and perform a relative evaluation. The activity providing unit, for example, adds a function to compare a politician's activities with those of other politicians or organizations and perform a relative evaluation. For example, activity performance in the same policy field is compared. The activity providing unit can also compare with the activities of well-known politicians or organizations. For example, the activity providing unit compares activity performance in the same policy field and performs a relative evaluation. The activities of other politicians and organizations can, for example, collect information on candidates in the same electoral district or well-known organizations. For example, the activity providing unit collects and compares the activity performance of candidates in the same electoral district. This allows for a relative evaluation.

[0070] The activity providing unit can collect user feedback regarding politicians' activities and automatically generate improvement proposals for the activities using a generation AI. The activity providing unit, for example, collects user feedback regarding politicians' activities and automatically generates improvement proposals for the activities using a generation AI. For example, it proposes improvements to the activities based on user opinions. The activity providing unit can also analyze user feedback using a generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement proposals for the activities. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the activity providing unit collects user feedback through questionnaire surveys or online reviews and analyzes it using a generation AI. This makes it possible to automatically generate improvement proposals for the activities based on user feedback.

[0071] The activity providing unit can use the emotion estimation function to monitor the user's emotions toward the politician's activities in real time and dynamically change the way the activities are displayed. The activity providing unit, for example, uses the emotion estimation function to monitor the user's emotions toward the politician's activities in real time and dynamically change the way the activities are displayed. For example, activities with strong positive emotions are highlighted. The activity providing unit can also analyze the user's emotions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice and calculates an emotion score. Real-time monitoring can be performed, for example, using real-time data collection and analysis algorithms. For example, real-time data collection collects the user's facial expressions and voice in real time and analyzes them using an emotion estimation algorithm. This makes it possible to dynamically change the way the activities are displayed depending on the user's emotions.

[0072] The belief providing unit can use the generation AI to analyze the politician's beliefs and values ​​and visually display the consistency and changes in beliefs. The belief providing unit, for example, uses the generation AI to analyze the politician's beliefs and values ​​and visually display the consistency and changes in beliefs. For example, it displays the changes in beliefs in timeline format based on past statements and actions. The generation AI, for example, uses a natural language processing model to analyze the politician's beliefs and values. The generation AI can also visually display the consistency and changes in beliefs using a data collection algorithm. For example, the generation AI analyzes past statements and actions and displays the changes in beliefs in timeline format. The consistency and changes in beliefs can be determined, for example, by analyzing time series data and displaying them in graphs. For example, the belief providing unit analyzes time series data and displays the changes in beliefs in graphs. In this way, the consistency and changes in beliefs can be visually displayed, making it easier for voters to understand the politician's beliefs.

[0073] The belief providing unit can automatically collect past statements and actions related to a politician's beliefs and provide data that supports the beliefs. The belief providing unit, for example, automatically collects past statements and actions related to a politician's beliefs and provides data that supports the beliefs. For example, past speeches and interview articles may be automatically collected to confirm the consistency of beliefs. The belief providing unit can also use a data collection algorithm to provide data that supports the beliefs. For example, the belief providing unit collects parliamentary records and media reports to provide data that supports the beliefs. Past statements and actions can be collected, for example, through parliamentary records and media reports. For example, the belief providing unit collects parliamentary records and media reports to provide data that supports the beliefs. In this way, by providing data that supports the beliefs, voters can gain a deeper understanding of the politician's beliefs.

[0074] The belief providing unit can use the emotion estimation function to analyze voters' emotional reactions to politicians' beliefs and emphasize positive beliefs. The belief providing unit, for example, uses the emotion estimation function to analyze voters' emotional reactions to politicians' beliefs and emphasize positive beliefs. For example, it automatically highlights beliefs with high emotion scores. The belief providing unit can also analyze users' emotional reactions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice to calculate an emotion score. Positive beliefs include, for example, social justice and environmental protection. For example, the belief providing unit highlights beliefs related to social justice and environmental protection. In this way, by emphasizing positive beliefs based on voters' emotional reactions, understanding of politicians' beliefs is deepened.

[0075] The belief providing unit can add a function to compare a politician's beliefs with the beliefs of other politicians or celebrities and perform a relative evaluation. The belief providing unit can add a function to compare a politician's beliefs with the beliefs of other politicians or celebrities and perform a relative evaluation. For example, it can compare differences in beliefs in the same policy area. The belief providing unit can also compare with the beliefs of famous politicians or celebrities. For example, it can compare differences in beliefs in the same policy area and perform a relative evaluation. The beliefs of other politicians or celebrities can, for example, collect information about candidates in the same electoral district or famous politicians. For example, the belief providing unit can collect and compare the beliefs of candidates in the same electoral district. This allows for a relative evaluation.

[0076] The belief providing unit can collect user feedback regarding the politician's beliefs and automatically generate improvement suggestions for the belief content using the generation AI. The belief providing unit, for example, collects user feedback regarding the politician's beliefs and automatically generates improvement suggestions for the belief content using the generation AI. For example, it suggests improvements to the beliefs based on the user's opinions. The belief providing unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement suggestions for the belief content. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the belief providing unit collects user feedback through questionnaire surveys or online reviews and analyzes it using the generation AI. In this way, improvement suggestions for the belief content can be automatically generated based on the user feedback.

[0077] The belief providing unit can use an emotion estimation function to monitor the user's emotions toward the politician's beliefs in real time and dynamically change the way the beliefs are displayed. The belief providing unit, for example, uses the emotion estimation function to monitor the user's emotions toward the politician's beliefs in real time and dynamically change the way the beliefs are displayed. For example, beliefs with strong positive emotions are highlighted. The belief providing unit can also analyze the user's emotions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice and calculates an emotion score. Real-time monitoring can be performed, for example, using real-time data collection and analysis algorithms. For example, real-time data collection involves collecting the user's facial expressions and voice in real time and analyzing them with an emotion estimation algorithm. This makes it possible to dynamically change the way the beliefs are displayed depending on the user's emotions.

[0078] The search comparison unit can analyze search results using a generation AI and provide customized information based on the user's interests. The search comparison unit, for example, analyzes search results using a generation AI and provides customized information based on the user's interests. For example, related information is prioritized and displayed based on the user's past search history. The search comparison unit can also analyze the user's interests using a generation AI. For example, the generation AI analyzes the user's search history and click history and provides information based on the interests. Customized information includes, for example, a news feed and personalized recommendations based on the user's interests. For example, the search comparison unit provides a news feed based on the user's interests and prioritizes related information. This makes it possible to provide customized information based on the user's interests.

[0079] The search comparison unit can create an interactive dashboard that allows the user to visually compare search results, thereby enabling an intuitive understanding by the user. The search comparison unit, for example, creates an interactive dashboard that allows the user to visually compare search results, thereby enabling an intuitive understanding by the user. For example, the search comparison unit displays information about each candidate in a graph or chart. The search comparison unit can also provide a function that allows the user to click to display detailed information using the interactive dashboard. For example, the search comparison unit displays information about each candidate in a graph or chart, and the user clicks to display detailed information. The interactive dashboard, for example, has a function that allows the user to click to display detailed information. The interactive dashboard can also have a function that allows the user to scroll to check information. For example, the interactive dashboard allows the user to scroll to check information about each candidate, and click to display detailed information. This allows the user to intuitively understand the search results.

[0080] The search comparison unit can use an emotion estimation function to analyze voters' emotional responses to search results and prioritize displaying positive information. The search comparison unit, for example, uses the emotion estimation function to analyze voters' emotional responses to search results and prioritize displaying positive information. For example, information with a high emotion score is displayed at the top. The search comparison unit can also analyze users' emotional responses in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice to calculate an emotion score. Positive information includes, for example, success stories and positive reviews. For example, the search comparison unit prioritizes displaying success stories and positive reviews. This improves user satisfaction by preferentially displaying positive information based on voters' emotional responses.

[0081] The search comparison unit can add a function to compare search results with search results of other users and perform a relative evaluation. The search comparison unit can add a function to compare search results with search results of other users and perform a relative evaluation, for example. For example, it can display other users' evaluations for the same search keyword. The search comparison unit can also collect and compare search results of other users. For example, the search comparison unit collects and compares search results for the same keyword or similar search queries. The search results of other users include, for example, search results for the same keyword or similar search queries. For example, the search comparison unit collects and compares search results for the same keyword or similar search queries. This allows for a relative evaluation.

[0082] The search comparison unit can collect user feedback on search results and automatically generate improvement suggestions for the search algorithm using the generation AI. The search comparison unit, for example, collects user feedback on search results and automatically generates improvement suggestions for the search algorithm using the generation AI. For example, the search comparison unit adjusts the display order of search results based on user opinions. The search comparison unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement suggestions for the search algorithm. Feedback can be collected, for example, through surveys or online reviews. For example, the search comparison unit collects user feedback through surveys or online reviews and analyzes it using the generation AI. This makes it possible to automatically generate improvement suggestions for the search algorithm based on user feedback.

[0083] The search comparison unit can use an emotion estimation function to monitor the user's emotion regarding the search results in real time and dynamically change the display method of the search results. The search comparison unit, for example, uses the emotion estimation function to monitor the user's emotion regarding the search results in real time and dynamically change the display method of the search results. For example, it can highlight information with strong positive emotions. The search comparison unit can also analyze the user's emotion in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice and calculates an emotion score. Real-time monitoring can be performed, for example, using real-time data collection and analysis algorithms. For example, real-time data collection collects the user's facial expressions and voice in real time and analyzes them using an emotion estimation algorithm. This allows the display method of the search results to be dynamically changed depending on the user's emotion.

[0084] The election information provision unit can automatically aggregate candidate information during elections using generation AI and filter only data from highly reliable sources. The election information provision unit, for example, can automatically aggregate candidate information during elections using generation AI and filter only data from highly reliable sources. For example, it can prioritize collecting information from official websites and reliable news sources and store it in a database. The generation AI can, for example, use a natural language processing model to analyze information on the internet and collect candidate information. The generation AI can also use a data collection algorithm to filter only data from highly reliable sources. For example, the generation AI can prioritize collecting data from public institutions and reliable news sources and store it in a database. This makes it possible to provide accurate candidate information to voters by providing only data from highly reliable sources.

[0085] The election information providing unit can create an interactive map that visually displays candidate information during an election, allowing a user to intuitively understand the information. The election information providing unit, for example, creates an interactive map that visually displays candidate information during an election, allowing a user to intuitively understand the information. For example, candidate information for each electoral district can be displayed on a map, and detailed information can be displayed by clicking. The election information providing unit can also provide a function that allows a user to click to display detailed information using the interactive map. For example, the election information providing unit displays candidate information for each electoral district on a map, and detailed information can be displayed by clicking. The interactive map, for example, has a function that allows a user to click to display detailed information. The interactive map can also have a function that allows a user to scroll to check information. For example, the interactive map allows a user to scroll to check information for each candidate, and detailed information can be displayed by clicking. This allows a user to intuitively understand candidate information.

[0086] The election information providing unit can use the emotion estimation function to analyze voters' emotional reactions to candidate information during an election and emphasize positive information. The election information providing unit, for example, uses the emotion estimation function to analyze voters' emotional reactions to candidate information during an election and emphasize positive information. For example, it automatically highlights information with a high emotion score. The election information providing unit can also analyze users' emotional reactions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice to calculate an emotion score. Positive information includes, for example, success stories and positive reviews. For example, the election information providing unit highlights success stories and positive reviews. In this way, emphasizing positive information based on voters' emotional reactions deepens understanding of candidate information.

[0087] The election information providing unit can add a function to compare candidate information at the time of an election with information on other electoral districts and perform a relative evaluation. The election information providing unit can add a function to compare candidate information at the time of an election with information on other electoral districts and perform a relative evaluation. For example, the positions of candidates in the same policy area are compared. The election information providing unit can also collect and compare information on other electoral districts. For example, the election information providing unit compares the positions of candidates in the same policy area and performs a relative evaluation. Information on other electoral districts includes, for example, the candidate's profile, policies, and campaign promises. For example, the election information providing unit collects and compares the profiles, policies, and campaign promises of candidates in other electoral districts. This allows for a relative evaluation.

[0088] The election information provision unit can collect user feedback regarding candidate information during elections and automatically generate improvement proposals for information provision using the generation AI. The election information provision unit, for example, collects user feedback regarding candidate information during elections and automatically generates improvement proposals for information provision using the generation AI. For example, it proposes improvements to the information based on user opinions. The election information provision unit can also analyze user feedback using the generation AI. For example, the generation AI analyzes user feedback and automatically generates improvement proposals for information provision. Feedback can be collected, for example, through questionnaire surveys or online reviews. For example, the election information provision unit collects user feedback through questionnaire surveys or online reviews and analyzes it using the generation AI. This makes it possible to automatically generate improvement proposals for information provision based on user feedback.

[0089] The election information providing unit can use an emotion estimation function to monitor users' emotions toward candidate information during an election in real time and dynamically change the way the information is displayed. The election information providing unit, for example, uses the emotion estimation function to monitor users' emotions toward candidate information during an election in real time and dynamically change the way the information is displayed. For example, information with strong positive emotions is highlighted. The election information providing unit can also analyze users' emotions in real time using an emotion estimation algorithm. For example, the emotion estimation algorithm analyzes the user's facial expressions and voice and calculates an emotion score. Real-time monitoring can be performed, for example, using real-time data collection and analysis algorithms. For example, real-time data collection involves collecting the user's facial expressions and voice in real time and analyzing them using an emotion estimation algorithm. This makes it possible to dynamically change the way the information is displayed depending on the user's emotions.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The politician information provision system can further include a news provision unit that provides a news feed based on the user's interests. The news provision unit, for example, analyzes the user's past search history and click history and preferentially displays news based on the user's interests. The news provision unit can also analyze the user's interests using a generation AI. For example, the generation AI analyzes the user's search history and click history and provides news based on the user's interests. This makes it possible to provide a customized news feed based on the user's interests.

[0092] The politician information provision system can further include a feedback collection unit that collects user feedback and automatically generates system improvement proposals using a generation AI. The feedback collection unit collects user feedback, for example, through questionnaire surveys or online reviews, and analyzes it using a generation AI. The feedback collection unit can also suggest system improvements based on user opinions. This allows system improvement proposals to be automatically generated based on user feedback.

[0093] The politician information provision system can further include an emotion monitoring unit that monitors the user's emotions in real time and dynamically changes the system's display method. The emotion monitoring unit, for example, collects the user's facial expressions and voice in real time and analyzes them using an emotion estimation algorithm. The emotion monitoring unit can also dynamically change the system's display method according to the user's emotions. This allows the system's display method to be dynamically changed according to the user's emotions.

[0094] The politician information provision system can further include a sentiment analysis unit that analyzes the user's emotional response and emphasizes positive information. The sentiment analysis unit, for example, analyzes the user's facial expressions and voice and calculates an emotional score. The sentiment analysis unit can also automatically highlight information with a high emotional score. This makes it possible to enhance user satisfaction with the system by emphasizing positive information based on the user's emotional response.

[0095] The politician information provision system can further include a recommendation unit that provides recommendations based on the user's interests. For example, the recommendation unit analyzes the user's past search history and click history to recommend candidates and policies based on the user's interests. The recommendation unit can also use generation AI to analyze the user's interests. This allows the system to provide customized recommendations based on the user's interests.

[0096] The politician information provision system can further include an emotion monitoring unit that monitors the user's emotional reactions in real time and dynamically changes the system's display method. The emotion monitoring unit, for example, collects the user's facial expressions and voice in real time and analyzes them using an emotion estimation algorithm. The emotion monitoring unit can also dynamically change the system's display method according to the user's emotions. This allows the system's display method to be dynamically changed according to the user's emotions.

[0097] The politician information provision system can further include a feedback collection unit that collects user feedback and automatically generates system improvement proposals using a generation AI. The feedback collection unit collects user feedback, for example, through questionnaire surveys or online reviews, and analyzes it using a generation AI. The feedback collection unit can also suggest system improvements based on user opinions. This allows system improvement proposals to be automatically generated based on user feedback.

[0098] The politician information provision system can further include a sentiment analysis unit that analyzes the user's emotional response and emphasizes positive information. The sentiment analysis unit, for example, analyzes the user's facial expressions and voice and calculates an emotional score. The sentiment analysis unit can also automatically highlight information with a high emotional score. This makes it possible to enhance user satisfaction with the system by emphasizing positive information based on the user's emotional response.

[0099] The politician information provision system can further include a news provision unit that provides a news feed based on the user's interests. The news provision unit, for example, analyzes the user's past search history and click history and prioritizes displaying news based on the user's interests. The news provision unit can also use generation AI to analyze the user's interests. This makes it possible to provide a customized news feed based on the user's interests.

[0100] The politician information provision system can further include an emotion monitoring unit that monitors the user's emotional reactions in real time and dynamically changes the system's display method. The emotion monitoring unit, for example, collects the user's facial expressions and voice in real time and analyzes them using an emotion estimation algorithm. The emotion monitoring unit can also dynamically change the system's display method according to the user's emotions. This allows the system's display method to be dynamically changed according to the user's emotions.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The career provider provides the politician's career history. For example, the career provider provides details of the politician's educational background, work history, awards, and past political activities. Specifically, it provides information on which university the politician graduated from and what kind of work experience he or she has. Step 2: The activity provider provides information on the politician's activities. For example, the activity provider provides information on what bills the politician has submitted in the past, what policies he or she has promoted, and what social issues he or she has addressed. Step 3: The belief provider provides the politician's beliefs. For example, the belief provider provides information about the politician's ideals, the type of society they are aiming for, and the social justice they value. Step 4: The search and compare unit searches and compares information about politicians. For example, the search and compare unit can compare candidates' positions on specific policies or each candidate's stance on environmental policy. This allows voters to easily compare each candidate's position. Step 5: The Election Information Provider provides information on candidates at the time of election. For example, the Election Information Provider provides information summarizing the backgrounds, activities, and beliefs of candidates for each electoral district, and displays candidate profiles in a list. This allows voters to easily compare information on candidates.

[0103] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0104] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0105] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0109] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0110] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0111] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0112] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0113] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0114] 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.

[0115] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0117] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0118] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0119] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0120] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0124] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0125] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0126] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0127] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0128] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0129] 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.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0131] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0135] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0139] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0140] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0141] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0142] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0143] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0144] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0145] 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.

[0146] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0147] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0148] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0149] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0150] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0151] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0152] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0154] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0155] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0156] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0159] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0160] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0161] 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.

[0162] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0163] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0164] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0165] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0166] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0167] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0168] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0169] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A career information department that provides career histories of politicians; The Activities Providing Department provides activities for politicians, The Belief Providing Department provides politicians with their beliefs. a search and comparison section that searches and compares information on politicians; An election information providing unit that provides information on candidates during elections. A system characterized by:

2. The activity providing unit Using generative AI, the politician's activity history is automatically analyzed and important activities and achievements are highlighted. The system of claim 1 .

3. The belief providing unit: Analyze the politician's beliefs and values ​​using generative AI and visually display the consistency and changes in those beliefs. The system of claim 1 .

4. The search and comparison unit Analyze search results with AI and provide customized information based on user interests. The system of claim 1 .

5. The election information providing unit Using emotion estimation, the system analyzes voters' emotional responses to candidate information during the election and emphasizes positive information. The system of claim 1 .

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