System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting information on political beliefs of users; means for matching candidates based on the collected information; means for selecting a candidate to vote for based on the matched candidates; means for simulating social and economic effects when the selected candidate wins; and means for recording the voting behavior and issuing points or coupons under certain conditions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the current electoral system, low voter turnout is a problem because many voters feel they "don't know who to vote for" or "nothing will change no matter what I vote for." As a result, interest in politics declines, and situations where voters' voices are not properly reflected in politics occur frequently. Another issue is that it is difficult for voters to understand how election results will affect society and the economy, which results in a lack of proactive voting behavior. [Means for solving the problem]

[0005] The present invention is a system that includes a means for collecting information about a user's political beliefs and matching candidates based on the collected information, a means for selecting a candidate to vote for based on the matched candidates, a means for simulating the social and economic impact if the selected candidate is elected, and a means for recording the voting behavior and issuing points or coupons under certain conditions.

[0006] The app will confirm users' political beliefs through dialogue and match them with candidates in their voting districts, making it easier for voters to find the candidate that best suits them. The app will also aim to increase voter turnout by setting incentive conditions such as a certain level of voter turnout for the election and a certain range of deviation from the number of votes received by the candidate selected in the app.

[0007] Furthermore, by simulating future policy and economic trends based on the user's voting behavior and political beliefs and presenting them to the user, the system allows the user to visually understand the social and economic impact of voting results. Finally, the system encourages voting behavior by providing users with points and coupons as an incentive to vote, allowing them to use these points before the next election.

[0008] "User" refers to an individual or organization that uses this system.

[0009] "Political beliefs" refer to the political opinions, beliefs, values, or concerns held by an individual or group.

[0010] "Candidate" refers to a politician or an organization authorized by the politician to run for election and seek to be elected.

[0011] "Matching" refers to the process of selecting and presenting suitable candidates based on the user's political beliefs.

[0012] "Candidate for whom you intend to vote" refers to the candidate for whom you intend to vote on Election Day.

[0013] "Simulation" refers to the process of predicting and analyzing the social and economic impacts if the selected candidate were elected.

[0014] "Recording" refers to saving a user's voting behavior as data.

[0015] "Points" refer to a type of incentive given to users for their voting behavior, and are units of value that can be used under certain conditions.

[0016] A "coupon" is a type of incentive given to users in exchange for their voting behavior, and refers to a discount voucher or exchange ticket that can be exchanged for specific products or services.

[0017] "Incentives" refer to rewards or benefits given to encourage users to take certain actions.

[0018] The term "system" refers to a collective term for a series of devices, means, or programs required to carry out the present invention. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] 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.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] 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.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0041] Collection of User Information

[0042] When users install and launch the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and inputs their interests, such as "welfare," "environment," and "education."

[0043] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[0044] Matching with candidates

[0045] The server searches for candidate information in the database based on the generated political belief profile. For example, if a search is performed for candidates who prioritize "welfare," Candidate A and Candidate B will be listed.

[0046] The search results are sent to the terminal, which displays the candidate information to the user. The user checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0047] Simulation of voting results

[0048] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A's election.

[0049] For example, the simulation results predict that if Candidate A is elected, "the welfare budget will increase by 10% and support for the elderly will be strengthened." The server sends this simulation result to the terminal, which then visually displays the result to the user, allowing the user to understand the effects if the selected candidate is elected.

[0050] Incentive distribution

[0051] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[0052] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[0053] This process helps users find candidates who align with their political beliefs, understand the social and economic impact of their voting behavior, and provides incentives to actually vote.

[0054] Specific examples

[0055] For example, if User A uses the system and responds that he or she is interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. User A selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[0056] On election day, if User A actually votes for Candidate C, and Candidate C meets certain criteria and wins, the server will award points to User A, and the device will notify the user. User A can exchange those points for coupons before the next election.

[0057] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[0061] Step 2:

[0062] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[0063] Step 3:

[0064] Terminal: Sends the user's answer information to the server.

[0065] Step 4:

[0066] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[0067] Step 5:

[0068] Server: Based on the generated political belief profile, search for candidate information in the database. Search for candidates who prioritize "welfare" and list Candidate A and Candidate B.

[0069] Step 6:

[0070] Server: Sends candidate information listed as search results to the terminal.

[0071] Step 7:

[0072] Terminal: Displays candidate information to the user.

[0073] Step 8:

[0074] User: Check the displayed candidate information and select the candidate for whom they plan to vote (e.g., Candidate A).

[0075] Step 9:

[0076] Terminal: Sends the user's selection information to the server.

[0077] Step 10:

[0078] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[0079] Step 11:

[0080] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[0081] Step 12:

[0082] Terminal: Visually displays the simulation results to users, allowing them to understand the impact of their chosen candidate if they were elected.

[0083] Step 13:

[0084] Server: Records users' voting behavior.

[0085] Step 14:

[0086] User: On election day, go to the polling station and vote for the candidate of your choice.

[0087] Step 15:

[0088] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[0089] Step 16:

[0090] Server: Sends generated points and coupon information to the terminal.

[0091] Step 17:

[0092] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] Many voters today find it difficult to find candidates who align with their political beliefs. Furthermore, they are often hesitant to vote due to limited means of predicting the impact that election results will have on society and the economy. Furthermore, there is a lack of effective means to encourage voting, resulting in low interest in and participation in elections.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes means for collecting information on a user's political beliefs, means for analyzing the collected information to generate a user's political belief profile, means for searching for and matching candidates based on the generated profile, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact of the selected candidate being elected, means for visually displaying the results of the simulation to the user, and means for recording the voting behavior and issuing points or coupons under certain conditions. This allows users to easily find candidates that match their political beliefs, makes it easier for them to understand the social and economic impact of election results, and encourages actual voting behavior through incentives.

[0098] "Information regarding the user's political beliefs" refers to information that indicates the user's political interests, values, policy priorities, etc.

[0099] A "political profile" is data that represents a user's political leanings and areas of interest, generated based on information about their political beliefs provided by the user.

[0100] "Candidate" means a person or entity running for public office in a particular election.

[0101] "Matching" refers to the act of selecting and providing candidates who are likely to be supported by the user based on the collected information and the generated profile.

[0102] Selecting a "candidate to vote for" is the act of the user selecting the candidate for whom they actually want to vote from among the candidates provided.

[0103] "Simulating" refers to the act of virtually predicting the expected social and economic impact if a selected candidate is elected, using past data, statistical information, and algorithms.

[0104] "Issuing points or coupons" refers to the act of generating and granting benefits or rewards to users in order to encourage their active participation and behavior.

[0105] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0106] Collection of User Information

[0107] When a user installs and launches the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and enters their interests, such as "welfare," "environment," or "education." Once this information is entered, the device sends it to a server.

[0108] Generating a political belief profile

[0109] The server analyzes the information it receives and generates a political profile of the user using Python data analysis libraries (e.g., Pandas) and other statistical analysis methods. The profile includes the user's political interests and is stored in a central database. Based on the profile, the server then creates a list of candidates the user is likely to support.

[0110] Matching with candidates

[0111] The server searches for candidate information in a database based on the generated political belief profile. For example, a search for candidates who prioritize "welfare" results in a list of Candidate A and Candidate B. A database management system such as a NoSQL database (e.g., MongoDB) is used for the search. The search results are sent to the device, which displays the candidate information to the user. The user reviews the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0112] Simulation of voting results

[0113] When the user selects Candidate A, the device sends that information back to the server. The server then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A being elected. A generative AI model (e.g., a TensorFlow-based predictive model) is used for the simulation. For example, the simulation results in a prediction that "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends the results of this simulation to the device, which then visually displays the results to the user. This allows the user to understand the impact that the selected candidate would have if elected.

[0114] Incentive distribution

[0115] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes received after the election exceeds a certain threshold, points are awarded. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0116] Specific examples

[0117] For example, if a newly registered user uses the system and responds that they are interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. The user selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if the user actually votes for Candidate C, and Candidate C meets certain criteria and is elected, the server will award the user points and the device will notify them of this. The user can exchange those points for coupons before the next election.

[0118] Example prompts for generative AI models

[0119] "Please explain in natural language the process of a system that lists appropriate candidates, simulates voting results, and awards incentives based on the user's political beliefs."

[0120] This is a specific embodiment of the present invention. This system makes it easier for users to find candidates who align with their political beliefs and understand the social and economic impacts of their election. It is also expected that incentives will encourage users to vote.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1:

[0123] Collection of User Information

[0124] Input: A user installs and launches an application.

[0125] What it does: The device prompts the user with a survey about their political beliefs, such as the question, "What policy area do you care about most?"

[0126] Output: The user's answer (e.g., "welfare," "environment," "education," etc.) is obtained.

[0127] How it works: The user answers the survey, and the information they enter is encrypted in JSON format and sent to the server using the HTTPS protocol.

[0128] Step 2:

[0129] Generating a political belief profile

[0130] Input: User survey response data.

[0131] How it works: The server analyzes the received data using a Python data analysis library (e.g., Pandas).

[0132] Output: A political profile of the user is generated.

[0133] How it works: The server uses the analyzed data to create a profile of the user's political interests and stores this profile in a central database.

[0134] Step 3:

[0135] Candidate search and matching

[0136] Input: Generated political belief profiles.

[0137] How it works: The server searches for candidate information in a NoSQL database (e.g., MongoDB) based on the user's political profile.

[0138] Output: A list of candidates (e.g., Candidate A, Candidate B) that match the user's political beliefs.

[0139] Specific operation: The server uses a matching algorithm to list candidates that match the profile and sends the results to the terminal.

[0140] Step 4:

[0141] View and select candidate information

[0142] Input: A list of candidates.

[0143] How it works: The device displays information about the candidate to the user, including the candidate's policies and past performance.

[0144] Output: The candidate the user has selected to vote for (e.g., Candidate A).

[0145] Specific operation: Based on the displayed information, the user selects the candidate they plan to vote for, and the selection information is sent from the device to the server.

[0146] Step 5:

[0147] Simulation of voting results

[0148] Input: Candidate information selected by the user.

[0149] How it works: The server uses historical voting data and the current political situation to simulate the social and economic impact of a candidate's election. Generative AI models (e.g., TensorFlow-based predictive models) are used.

[0150] Output: Simulation results (e.g., "The welfare budget will increase by 10% and support for the elderly will be strengthened") are obtained.

[0151] Specific operation: The server performs a simulation using the AI ​​model and sends the results in JSON format to the device, which then visually displays the results to the user.

[0152] Step 6:

[0153] Recording voting behavior and distributing incentives

[0154] Input: User voting behavior and its records.

[0155] How it works: The server records the user's voting behavior and issues points or coupons if certain conditions are met (e.g., candidate A meets certain criteria and wins).

[0156] Output: Notification of points and coupons to the user.

[0157] Specific operation: The server generates points and coupons and sends the information to the terminal. The terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0158] These are the specific processing steps of this system. At each step, the information entered by the user is processed appropriately, and the results are returned to the user.

[0159] (Application example 1)

[0160] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0161] Currently, many brick-and-mortar stores lack the means to improve customer experience, as they do not adequately provide personalized services based on customer interests and purchase history. As a result, customer satisfaction and repeat business rates are low, and sales growth cannot be expected. In addition, there are insufficient means to collect post-purchase feedback and reflect it in product strategies, making efficient marketing and inventory management difficult. There is a need to solve these issues.

[0162] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0163] In this invention, the server includes means for collecting information on user interests, means for matching products based on the collected information, means for selecting products to be purchased based on the matched products, means for simulating the social and economic impact of purchasing the selected products, and means for recording purchasing behavior and issuing points and coupons under certain conditions. This enables personalized product suggestions based on customer interests, and by simulating post-purchase results, it is possible to improve customer satisfaction and enable efficient marketing and inventory management.

[0164] "User" means an individual who utilizes the System to enter interest and purchasing information.

[0165] "Interests" refers to the product categories or service areas in which a user is interested.

[0166] "Means of collecting information" refers to the methods and devices used to input user input such as interests and purchase history into the system.

[0167] "Product matching means" refers to a method for selecting and suggesting suitable products from a database based on collected user interests.

[0168] "Method for selecting products to be purchased" refers to the method used by a user to select the products to actually purchase from the suggested products.

[0169] "Means for simulating social and economic impacts" refers to methods for predicting future changes in social and economic conditions if the selected product is purchased.

[0170] "Means for recording purchasing behavior" refers to a method for recording actual purchasing behavior performed by a user in the system.

[0171] "Means of issuing points or coupons" refers to a method for providing points or coupons as an incentive when a user meets certain conditions.

[0172] "Incentives" refer to rewards or benefits offered to encourage user behavior.

[0173] "Brick and mortar store" refers to a sales location that offers goods or services in an actual physical location.

[0174] "Personalization" refers to customizing products and services to suit the specific interests and needs of individual users.

[0175] "Marketing" refers to all activities involved in bringing products and services to market and selling them to consumers.

[0176] "Inventory management" refers to managing goods so that they are stocked at the right time and in the right quantities and distributed efficiently.

[0177] The present invention relates to a system that proposes products in a physical store based on a user's interests, simulates the impact after purchase, and provides incentives. Specific embodiments of the system are described below.

[0178] Collection of User Information

[0179] When a user installs and launches a smartphone app, the app displays a survey about the user's interests. For example, the question might be, "What product category are you most interested in?" The user answers the survey and enters their interests, such as "home appliances," "fashion," or "food." Once this information is entered, the app sends it to a server. The server analyzes the information it receives and generates a user interest profile. This profile includes the products and categories that interest the user.

[0180] Matching with products

[0181] The server searches for product information in the database based on the generated interest profile. For example, for a user who is primarily searching for "home appliances," products such as "smart refrigerators" and "smart washing machines" are listed. The search results are sent to a smartphone app, which displays the product information to the user. The user then checks the displayed product information and selects the product they wish to purchase (e.g., a smart refrigerator).

[0182] Purchase result simulation

[0183] Once the user selects a product, the app sends that information back to the server. The server then uses past purchase data and current market conditions to simulate the social and economic impact of purchasing the selected product. For example, the simulation may predict that purchasing a smart refrigerator will reduce electricity consumption by 10%, improving household energy efficiency. The server then sends the simulation results to the app, which then visually displays the results to the user. This allows the user to understand the impact of purchasing the selected product.

[0184] Incentive distribution

[0185] The server records the user's purchasing behavior and issues points or coupons when certain conditions are met. For example, if a user actually purchases a "smart refrigerator" in a store and then answers a satisfaction survey, points are awarded. The server then sends the generated points and coupon information to the app, which notifies the user. The app displays a message saying, "You can exchange these points for a coupon with your next purchase." This process makes it easier for users to find products that match their interests and understand the social and economic impact of their purchasing behavior. Incentives also encourage actual purchasing behavior.

[0186] Hardware and Software

[0187] The hardware used includes a smartphone and a server. The software used includes the programming language Python and the requests library for sending HTTP requests. Database management uses SQL or NoSQL databases. The simulation engine uses generative AI models.

[0188] Prompt Sentence Examples

[0189] The following prompt sentence is used as an example input to the simulation engine's generative AI model:

[0190] Answer that the user is interested in "home appliances," and suggest related products. Simulate the purchase results of the selected products and output the predicted results regarding reduction in power consumption and improvement in convenience.

[0191] In this way, a smart customer matching system can be built for brick-and-mortar stores. This system can suggest products that match the user's interests and simulate the results of their purchases, improving customer satisfaction and enabling efficient marketing.

[0192] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0193] Step 1:

[0194] A user installs and launches a smartphone app. The app displays a questionnaire about the user's interests, and the user answers it. The information entered is the user's main interests (e.g., "home appliances," "fashion," "food," etc.). This input data forms the basis for building the user's interest profile.

[0195] Step 2:

[0196] The device (smartphone) sends data about the user's interests to the server, which analyzes the data and creates an interest profile for the user. This profile includes categories that reflect the user's interests.

[0197] Step 3:

[0198] The server searches for matching product information from its database based on the generated interest profile. For example, if the user is interested in "home appliances," the server will list product information such as "smart refrigerators" and "smart washing machines." The searched product information is prioritized based on the user's interests.

[0199] Step 4:

[0200] The server sends the search results to the smartphone device, which receives this information and displays the matching product information to the user. The user can then check the displayed product information and select the products they wish to purchase.

[0201] Step 5:

[0202] When a user selects a product they wish to purchase, the device sends the selection back to the server. The server then starts a simulation of the purchase outcome based on the selected product information. The simulation takes into account past purchase data and market conditions to calculate the predicted social and economic impact of the purchase.

[0203] Step 6:

[0204] The server generates simulation results and sends them to the device. The device visually displays the simulation results to the user. For example, it displays a predicted result such as "If you purchase a smart refrigerator, your electricity consumption will decrease by 10%."

[0205] Step 7:

[0206] The server records the user's purchasing behavior. If the user actually purchases a product and then provides a survey or feedback, points or coupons are issued if certain conditions are met. This incentive is intended to encourage purchases.

[0207] Step 8:

[0208] The server sends the generated points and coupon information to the terminal, which notifies the user and displays a message such as "You can use these points for your next purchase." This notification allows the user to use the incentive for their next purchase.

[0209] These are the specific processing steps of this system. At each step, the roles of the user, device, and server are clearly separated, and the input, processing, and output of information are carried out continuously, enabling smart customer matching and incentive provision in physical stores.

[0210] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0211] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. In addition, by combining it with an emotion engine, it takes into account the user's emotional state, selects more appropriate candidates, and presents simulation results.

[0212] Collection of User Information

[0213] When users install and launch the application, the device displays a survey about their political beliefs, including the question, "What policy area are you most interested in?" Users answer the survey and input their interests, such as "welfare," "environment," and "education."

[0214] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[0215] Emotion recognition by emotion engine

[0216] The device collects the user's facial expressions, tone of voice, and input patterns when answering the questionnaire, and analyzes them using an emotion engine. For example, if the user expresses high interest or anxiety about a particular question, this emotional information is collected. The server then adds the results from the emotion engine to the user's profile to generate an overall political belief of the user.

[0217] Emotion-based candidate matching

[0218] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it searches for candidates who prioritize "welfare" and lists Candidate A and Candidate B.

[0219] The search results are sent to the device, which displays the candidate information to the user. The user then checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A). This selection also takes into account the user's emotional information, making it easier for the user to find a candidate they are more comfortable with.

[0220] Simulation of voting results

[0221] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of the selected Candidate A being elected.

[0222] For example, the simulation results predict that if Candidate A is elected, "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends these simulation results to the device, which then visually displays the results to the user. The device also takes into account the user's emotional information and presents the results in a format that is easier to understand. This allows the user to understand the effects that would be expected if the candidate they selected were elected.

[0223] Incentive distribution

[0224] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[0225] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[0226] Specific examples

[0227] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list Candidates D and E, who are focusing on environmental policies. User B selects Candidate E and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[0228] On election day, if User B actually votes for Candidate E, and Candidate E meets certain criteria and wins, the server will award points to User B, and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[0229] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections. Furthermore, the introduction of an emotion engine will enable optimal candidate selection and information presentation that takes into account the user's emotions, improving the accuracy and satisfaction of voting behavior.

[0230] The processing flow will be explained below.

[0231] Step 1:

[0232] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[0233] Step 2:

[0234] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[0235] Step 3:

[0236] Terminal: Sends the user's answer information to the server.

[0237] Step 4:

[0238] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[0239] Step 5:

[0240] Device: Collects emotional data such as facial expressions, tone of voice, and input patterns when users answer surveys.

[0241] Step 6:

[0242] Terminal: Sends collected emotion data to the emotion engine and receives the analysis results.

[0243] Step 7:

[0244] Server: Adds emotional information to the user's political belief profile based on the analysis results from the emotion engine.

[0245] Step 8:

[0246] Server: Searches for candidate information in the database based on the generated political belief profile and emotional information. Searches for candidates who prioritize "welfare" and creates a list of candidates A and B.

[0247] Step 9:

[0248] Server: Sends candidate information listed as search results to the terminal.

[0249] Step 10:

[0250] Terminal: Displays candidate information to the user.

[0251] Step 11:

[0252] User: Check the displayed candidate information and select the candidate they plan to vote for (e.g., Candidate A) based on emotional information.

[0253] Step 12:

[0254] Terminal: Sends the user's selection information to the server.

[0255] Step 13:

[0256] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[0257] Step 14:

[0258] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[0259] Step 15:

[0260] Terminal: Visually displays the simulation results to the user, taking into account the user's emotional state and presenting them in an easy-to-understand format.

[0261] Step 16:

[0262] Server: Records users' voting behavior.

[0263] Step 17:

[0264] User: On election day, go to the polling station and vote for the candidate of your choice.

[0265] Step 18:

[0266] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[0267] Step 19:

[0268] Server: Sends generated points and coupon information to the terminal.

[0269] Step 20:

[0270] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[0271] Example 2

[0272] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0273] Conventional election systems have the problem that it is difficult for users to select the appropriate candidate based on their own political beliefs, and the selection process does not take emotions into consideration. Furthermore, there is a lack of mechanisms to predict the social and economic impact if the candidate selected by the user is elected, and the lack of effective incentives to encourage users to vote is also an issue.

[0274] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0275] In this invention, the server includes: means for collecting information on a user's political beliefs; means for generating a user profile based on the collected information; means for adding emotional information to the profile, which includes an emotion engine for detecting the user's emotional state; means for matching candidates based on the profile and emotional information; means for selecting a candidate to vote for based on the matched candidates; means for simulating the social and economic impact if the selected candidate is elected; and means for recording the voting behavior and issuing points or coupons under certain conditions. This makes it possible to select the optimal candidate taking into account the user's political beliefs and emotional information, and also makes it possible to effectively provide incentives to encourage voting behavior.

[0276] "User information" is data about a user's political beliefs or emotional state.

[0277] A "profile" is a data set generated from collected user information that indicates a user's political interests and attributes.

[0278] An "emotion engine" is an algorithm and system for detecting and analyzing a user's emotional state based on their facial expressions, tone of voice, input patterns, etc.

[0279] "Candidate matching" is the process of identifying suitable candidates among election candidates based on the user's profile and sentiment information.

[0280] "Selecting a candidate to vote for" is the process by which a user ultimately decides which candidate to vote for from among the matched candidates.

[0281] A "simulation" is a computational and modeling tool used to predict the social and economic impacts of a selected candidate being elected.

[0282] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[0283] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also combines an emotion engine to consider the user's emotional state, allowing for more appropriate candidate selection and simulation results. A specific embodiment of this system is described below.

[0284] Collection of User Information

[0285] 1. The device displays a survey about political beliefs to users who have the application installed. The survey includes the question, "What policy area do you care most about?"

[0286] Specific operation: The user enters a policy area of ​​interest, such as "environment" or "welfare."

[0287] 2. The device sends the entered information to the server using the REST API.

[0288] 3. The server analyzes the received information and generates a profile of the user's political beliefs, using an analysis algorithm to categorize responses into profiles such as "environmental" or "welfare."

[0289] Emotion recognition by emotion engine

[0290] 1. The device collects the user's facial expressions, tone of voice, input patterns, etc. when answering the survey. Data is collected using a camera and microphone.

[0291] 2. The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the "environment" question, it adds that emotional information to their profile.

[0292] 3. The server updates the user's overall political beliefs based on the analysis results from the emotion engine.

[0293] Candidate Matching

[0294] 1. The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[0295] 2. The search results are sent to the device, which then displays candidate information to the user, including their profile and policy details.

[0296] 3. The user reviews the displayed candidate information and selects the candidate they plan to vote for. This selection process also takes into account emotional information.

[0297] Simulation of voting results

[0298] 1. When the user selects a candidate, the information is sent to the server, which then uses the REST API to send it again.

[0299] 2. The server uses past voting data and the current political situation to simulate the social and economic impact of the selected candidate's election. The simulation is carried out using big data analysis tools.

[0300] 3. The simulation results are sent to the device, which then displays the results visually to the user, using graphs and charts.

[0301] Incentive distribution

[0302] 1. The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[0303] 2. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user. A notification is displayed saying, "You can exchange these points for coupons before the next election."

[0304] Specific examples

[0305] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list candidates who are focusing on environmental policies. User B selects a candidate and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if User B actually votes for that candidate and that candidate is elected, the server will award User B points and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[0306] Example prompts to input to the generative AI model

[0307] "We want to design a system that suggests the best candidates based on the user's political beliefs and emotional information. If the user expresses a high interest in environmental policy, please explain which candidate would be best to recommend and why."

[0308] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0309] Step 1: Collect user information

[0310] The device will display a survey about political beliefs to users who have the app installed, including the question, "What policy area do you care most about?"

[0311] - Input: User-entered answers regarding political beliefs (e.g., environment, welfare, education)

[0312] - Output: Collected user political belief data

[0313] - Specific behavior: A survey-style interface is displayed, the user enters their answers, and clicks the submit button.

[0314] Step 2: Submit user information

[0315] The device sends the collected user information to the server, which uses a REST API to send the data.

[0316] - Input: User's political beliefs data

[0317] - Output: User information stored on the server

[0318] - Specific operation: The entered data is sent to the server via API and saved in the database.

[0319] Step 3: Generate a profile

[0320] The server analyzes the received user information, generates a profile of the user's political beliefs, and uses an analysis algorithm to categorize the responses.

[0321] - Input: User's political beliefs data

[0322] - Output: User's political belief profile

[0323] - Specific operation: A data analysis algorithm analyzes the responses and classifies them into profiles such as "environment-oriented" or "welfare-oriented."

[0324] Step 4: Collecting emotion data

[0325] The device collects data such as the user's facial expressions, tone of voice, and input patterns when answering the survey. Data is collected using a camera and microphone.

[0326] - Input: User's facial expressions, tone of voice, input patterns

[0327] - Output: Data representing emotional state

[0328] - Specific operation: The camera and microphone will operate and record the user's facial expressions and voice in real time.

[0329] Step 5: Analyze the sentiment data

[0330] The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the question "environment," it adds that emotional information to their profile.

[0331] - Input: User's facial expressions, tone of voice, input patterns

[0332] - Output: Political belief profile with sentiment information

[0333] - What happens: The sentiment analysis algorithm processes the data and generates a sentiment rating, which is added to your profile.

[0334] Step 6: Matching candidate information

[0335] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[0336] - Input: Political belief profile with emotional information

[0337] - Output: Matched candidate list

[0338] - What it does: The database search algorithm will produce a list of candidates who best fit your profile.

[0339] Step 7: View candidate information

[0340] The server sends the search results to the device, which then displays candidate information to the user, including their profile and policy details.

[0341] - Input: Matched candidate list

[0342] - Output: Candidate information displayed to the user

[0343] - Specific behavior: Candidate information is visually displayed in the interface for user confirmation.

[0344] Step 8: Choose the candidate you plan to vote for

[0345] Users review the displayed candidate information and select the candidate they plan to vote for, a selection process that also takes into account emotional information.

[0346] - Input: Displayed candidate information

[0347] - Output: Candidates selected by the user

[0348] - Specific action: The user selects a candidate and clicks the "Next" button.

[0349] Step 9: Simulate the voting results

[0350] The server then receives information about the candidate selected by the user and, based on past voting data and the current political situation, simulates the social and economic impact of the selected candidate being elected.

[0351] - Input: Candidate selected by the user

[0352] - Output: Simulation results

[0353] - Specific actions: Big data analysis tools run simulations and generate results, such as "welfare budgets will increase by 10% and support for the elderly will be strengthened."

[0354] Step 10: Viewing Simulation Results

[0355] The server sends the simulation results to the device, which then visually displays the results to the user using graphs and charts.

[0356] - Input: Simulation results

[0357] - Output: Simulation results displayed to the user

[0358] - Specific operation: Simulation results are visually displayed in the interface for user confirmation.

[0359] Step 11: Record and issue incentives

[0360] The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[0361] - Input: User voting behavior, election results

[0362] - Output: Points or coupons

[0363] - Specific behavior: Voting behavior is logged, and if the conditions are met, points are calculated and awarded.

[0364] Step 12: Incentive Notification

[0365] The server transmits the generated points and coupon information to the terminal, which then notifies the user of the same.

[0366] - Input: Points or coupon information

[0367] - Output: Incentive notification distributed to users

[0368] - Specific operation: A notification will appear on the device saying, "You can exchange these points for coupons before the next election."

[0369] (Application example 2)

[0370] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0371] Conventional voting systems did not adequately match candidates based on users' political beliefs or promote voting behavior. Furthermore, it was difficult to select the optimal candidate and present information based on the user's emotional state, and the management and coordination of points and coupons given as incentives was insufficient. This resulted in low voter engagement and a decline in voter motivation to participate in elections.

[0372] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0373] In this invention, the server includes means for collecting information on the user's political beliefs, means for matching candidates based on the collected information and the user's emotional state, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact if the selected candidate is elected, and means for recording the voting behavior, issuing points or coupons under certain conditions, and linking with an electronic payment service. This enables the selection of the optimal candidate taking the user's emotional state into consideration, promotes voting behavior, and enables incentive management linked with an electronic payment service.

[0374] A "user" is someone who uses the system to provide information about their political beliefs, select candidates, and vote.

[0375] "Political beliefs" refers to information that refers to a user's political opinions, values, and interests.

[0376] "Emotional state" refers to the emotional response state recognized from the facial expressions, tone of voice, input patterns, etc. shown by the user when answering a questionnaire or using the system.

[0377] "Candidates" refers to people or organizations running for office, who are matched based on users' political beliefs.

[0378] "Matching" is the process of comparing the user's political beliefs and emotional state with the candidates' policies and positions to select the most suitable candidate.

[0379] "Selection" refers to the act of a user deciding which candidate they intend to vote for from among the matched candidates.

[0380] "Simulation" is the process of calculation and analysis that predicts the social and economic impacts if the selected candidate is elected.

[0381] "Voting behavior" refers to the entire act of a user actually voting for the selected candidate at a polling station.

[0382] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[0383] An "electronic payment service" is a payment system that uses the Internet and electronic devices, and supports the management and use of points and coupons.

[0384] This invention is a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also uses emotion recognition technology to consider the user's emotional state, selecting more appropriate candidates and presenting simulation results. Furthermore, by linking with electronic payment services, it is possible to smoothly manage incentives according to voting behavior.

[0385] Specifically, users answer a questionnaire about their political beliefs through an application installed on their smartphone. Emotional data, such as the user's facial expressions, tone of voice, and input patterns, is collected while answering the questionnaire and analyzed by an emotion engine. The server generates a political belief profile for the user based on the collected information and emotional data, and compares it with candidate information in a database to match the most suitable candidate.

[0386] When a user checks the candidate information provided and selects the candidate they plan to vote for, the server simulates the social and economic impact if the selected candidate is elected. The simulation results are presented to the user in a visually easy-to-understand format. For example, if a user interested in the environment selects a candidate who is focusing on environmental policies, the server will display a forecast showing the increased adoption of renewable energy.

[0387] Furthermore, if a user actually votes and their actions meet certain conditions, points or coupons are issued in cooperation with an electronic payment service. This allows users to exchange their points for coupons before the next election. Incentive conditions can be set, for example, if the voter turnout for the election is above a certain level, or if the number of votes received by the candidate selected in the application is within a certain range.

[0388] Hardware: Smartphone

[0389] Software: Python, emotion recognition library (emotion_recognition), candidate matching algorithm (match_candidates)

[0390] An example prompt is:

[0391] "The system analyzes the emotions expressed when users answer surveys and matches them with the most suitable candidates based on their political beliefs. It visually displays the simulation results of what would happen if the candidate were elected, and awards incentives (points or coupons) based on voting behavior."

[0392] This system makes it possible to select the most appropriate candidate taking into account the user's emotional state, encouraging voting behavior and facilitating incentive management in conjunction with electronic payment services.

[0393] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0394] Step 1:

[0395] The user launches an application installed on their smartphone and answers a questionnaire about their political beliefs.

[0396] Input: Survey response about user's political beliefs

[0397] Output: Response data

[0398] Specific operation: The user launches the application and enters their interests, such as "welfare" or "environment," in response to the questions that appear.

[0399] Step 2:

[0400] Emotional data such as facial expressions, tone of voice, and input patterns of users when answering surveys are collected.

[0401] Input: User facial expressions, tone of voice, and input patterns while answering the survey

[0402] Output: Emotion data

[0403] Specific operation: Using the device's camera and microphone, the user's facial expressions and tone of voice are captured and analyzed using an emotion engine.

[0404] Step 3:

[0405] The server receives the collected political belief information and emotional data and generates a political belief profile for the user.

[0406] Input: Survey response data, emotion data

[0407] Output: Political profile

[0408] What it does: The server analyzes the data it receives and creates a profile of the user that combines their political interests and emotional state.

[0409] Step 4:

[0410] The server matches the most suitable candidate based on the political belief profile with candidate information in the database.

[0411] Input: Political profile, candidate information in database

[0412] Output: A list of matched candidates

[0413] Specific operation: The server matches the user's profile with the policies of each candidate and identifies the most suitable candidate.

[0414] Step 5:

[0415] Information about matched candidates is sent to the terminal and displayed to the user.

[0416] Input: List of matched candidates

[0417] Output: Candidates selected by the user

[0418] Specific operation: Candidate information is displayed on the device, and the user is asked to confirm and select the candidate they plan to vote for.

[0419] Step 6:

[0420] Information about the candidate selected by the user is sent to a server, and the social and economic impact of the selected candidate being elected is simulated.

[0421] Input: Candidate information selected by the user

[0422] Output: Simulation results

[0423] Specific operation: The server calculates the impact of winning based on past data and the current political situation and generates the results.

[0424] Step 7:

[0425] The simulation results are sent to the terminal and displayed visually to the user.

[0426] Input: Simulation results

[0427] Output: Displaying results in a user-friendly format

[0428] Specific operation: The simulation results are displayed on the terminal in a visually easy-to-understand format for the user to confirm.

[0429] Step 8:

[0430] After a user actually votes, their voting behavior is recorded, and if specified conditions are met, points or coupons are generated and distributed via an electronic payment service.

[0431] Input: Voting records, election results, incentive conditions

[0432] Output: Points or coupons

[0433] Specific operation: The server checks the user's voting behavior and determines whether the incentive conditions are met, then generates points or coupons and provides them to the user via an electronic payment service.

[0434] 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.

[0435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0436] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0437] [Second embodiment]

[0438] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0439] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0440] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0441] 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.

[0442] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0443] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0444] 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.

[0445] 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.

[0446] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0447] 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.

[0448] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0449] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0450] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0451] Collection of User Information

[0452] When users install and launch the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and inputs their interests, such as "welfare," "environment," and "education."

[0453] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[0454] Matching with candidates

[0455] The server searches for candidate information in the database based on the generated political belief profile. For example, if a search is performed for candidates who prioritize "welfare," Candidate A and Candidate B will be listed.

[0456] The search results are sent to the terminal, which displays the candidate information to the user. The user checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0457] Simulation of voting results

[0458] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A's election.

[0459] For example, the simulation results predict that if Candidate A is elected, "the welfare budget will increase by 10% and support for the elderly will be strengthened." The server sends this simulation result to the terminal, which then visually displays the result to the user, allowing the user to understand the effects if the selected candidate is elected.

[0460] Incentive distribution

[0461] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[0462] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[0463] This process helps users find candidates who align with their political beliefs, understand the social and economic impact of their voting behavior, and provides incentives to actually vote.

[0464] Specific examples

[0465] For example, if User A uses the system and responds that he or she is interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. User A selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[0466] On election day, if User A actually votes for Candidate C, and Candidate C meets certain criteria and wins, the server will award points to User A, and the device will notify the user. User A can exchange those points for coupons before the next election.

[0467] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections.

[0468] The processing flow will be explained below.

[0469] Step 1:

[0470] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[0471] Step 2:

[0472] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[0473] Step 3:

[0474] Terminal: Sends the user's answer information to the server.

[0475] Step 4:

[0476] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[0477] Step 5:

[0478] Server: Based on the generated political belief profile, search for candidate information in the database. Search for candidates who prioritize "welfare" and list Candidate A and Candidate B.

[0479] Step 6:

[0480] Server: Sends candidate information listed as search results to the terminal.

[0481] Step 7:

[0482] Terminal: Displays candidate information to the user.

[0483] Step 8:

[0484] User: Check the displayed candidate information and select the candidate for whom they plan to vote (e.g., Candidate A).

[0485] Step 9:

[0486] Terminal: Sends the user's selection information to the server.

[0487] Step 10:

[0488] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[0489] Step 11:

[0490] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[0491] Step 12:

[0492] Terminal: Visually displays the simulation results to users, allowing them to understand the impact of their chosen candidate if they were elected.

[0493] Step 13:

[0494] Server: Records users' voting behavior.

[0495] Step 14:

[0496] User: On election day, go to the polling station and vote for the candidate of your choice.

[0497] Step 15:

[0498] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[0499] Step 16:

[0500] Server: Sends generated points and coupon information to the terminal.

[0501] Step 17:

[0502] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[0503] Example 1

[0504] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0505] Many voters today find it difficult to find candidates who align with their political beliefs. Furthermore, they are often hesitant to vote due to limited means of predicting the impact that election results will have on society and the economy. Furthermore, there is a lack of effective means to encourage voting, resulting in low interest in and participation in elections.

[0506] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0507] In this invention, the server includes means for collecting information on a user's political beliefs, means for analyzing the collected information to generate a user's political belief profile, means for searching for and matching candidates based on the generated profile, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact of the selected candidate being elected, means for visually displaying the results of the simulation to the user, and means for recording the voting behavior and issuing points or coupons under certain conditions. This allows users to easily find candidates that match their political beliefs, makes it easier for them to understand the social and economic impact of election results, and encourages actual voting behavior through incentives.

[0508] "Information regarding the user's political beliefs" refers to information that indicates the user's political interests, values, policy priorities, etc.

[0509] A "political profile" is data that represents a user's political leanings and areas of interest, generated based on information about their political beliefs provided by the user.

[0510] "Candidate" means a person or entity running for public office in a particular election.

[0511] "Matching" refers to the act of selecting and providing candidates who are likely to be supported by the user based on the collected information and the generated profile.

[0512] Selecting a "candidate to vote for" is the act of the user selecting the candidate for whom they actually want to vote from among the candidates provided.

[0513] "Simulating" refers to the act of virtually predicting the expected social and economic impact if a selected candidate is elected, using past data, statistical information, and algorithms.

[0514] "Issuing points or coupons" refers to the act of generating and granting benefits or rewards to users in order to encourage their active participation and behavior.

[0515] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0516] Collection of User Information

[0517] When a user installs and launches the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and enters their interests, such as "welfare," "environment," or "education." Once this information is entered, the device sends it to a server.

[0518] Generating a political belief profile

[0519] The server analyzes the information it receives and generates a political profile of the user using Python data analysis libraries (e.g., Pandas) and other statistical analysis methods. The profile includes the user's political interests and is stored in a central database. Based on the profile, the server then creates a list of candidates the user is likely to support.

[0520] Matching with candidates

[0521] The server searches for candidate information in a database based on the generated political belief profile. For example, a search for candidates who prioritize "welfare" results in a list of Candidate A and Candidate B. A database management system such as a NoSQL database (e.g., MongoDB) is used for the search. The search results are sent to the device, which displays the candidate information to the user. The user reviews the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0522] Simulation of voting results

[0523] When the user selects Candidate A, the device sends that information back to the server. The server then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A being elected. A generative AI model (e.g., a TensorFlow-based predictive model) is used for the simulation. For example, the simulation results in a prediction that "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends the results of this simulation to the device, which then visually displays the results to the user. This allows the user to understand the impact that the selected candidate would have if elected.

[0524] Incentive distribution

[0525] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes received after the election exceeds a certain threshold, points are awarded. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0526] Specific examples

[0527] For example, if a newly registered user uses the system and responds that they are interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. The user selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if the user actually votes for Candidate C, and Candidate C meets certain criteria and is elected, the server will award the user points and the device will notify them of this. The user can exchange those points for coupons before the next election.

[0528] Example prompts for generative AI models

[0529] "Please explain in natural language the process of a system that lists appropriate candidates, simulates voting results, and awards incentives based on the user's political beliefs."

[0530] This is a specific embodiment of the present invention. This system makes it easier for users to find candidates who align with their political beliefs and understand the social and economic impacts of their election. It is also expected that incentives will encourage users to vote.

[0531] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0532] Step 1:

[0533] Collection of User Information

[0534] Input: A user installs and launches an application.

[0535] What it does: The device prompts the user with a survey about their political beliefs, such as the question, "What policy area do you care about most?"

[0536] Output: The user's answer (e.g., "welfare," "environment," "education," etc.) is obtained.

[0537] How it works: The user answers the survey, and the information they enter is encrypted in JSON format and sent to the server using the HTTPS protocol.

[0538] Step 2:

[0539] Generating a political belief profile

[0540] Input: User survey response data.

[0541] How it works: The server analyzes the received data using a Python data analysis library (e.g., Pandas).

[0542] Output: A political profile of the user is generated.

[0543] How it works: The server uses the analyzed data to create a profile of the user's political interests and stores this profile in a central database.

[0544] Step 3:

[0545] Candidate search and matching

[0546] Input: Generated political belief profiles.

[0547] How it works: The server searches for candidate information in a NoSQL database (e.g., MongoDB) based on the user's political profile.

[0548] Output: A list of candidates (e.g., Candidate A, Candidate B) that match the user's political beliefs.

[0549] Specific operation: The server uses a matching algorithm to list candidates that match the profile and sends the results to the terminal.

[0550] Step 4:

[0551] View and select candidate information

[0552] Input: A list of candidates.

[0553] How it works: The device displays information about the candidate to the user, including the candidate's policies and past performance.

[0554] Output: The candidate the user has selected to vote for (e.g., Candidate A).

[0555] Specific operation: Based on the displayed information, the user selects the candidate they plan to vote for, and the selection information is sent from the device to the server.

[0556] Step 5:

[0557] Simulation of voting results

[0558] Input: Candidate information selected by the user.

[0559] How it works: The server uses historical voting data and the current political situation to simulate the social and economic impact of a candidate's election. Generative AI models (e.g., TensorFlow-based predictive models) are used.

[0560] Output: Simulation results (e.g., "The welfare budget will increase by 10% and support for the elderly will be strengthened") are obtained.

[0561] Specific operation: The server performs a simulation using the AI ​​model and sends the results in JSON format to the device, which then visually displays the results to the user.

[0562] Step 6:

[0563] Recording voting behavior and distributing incentives

[0564] Input: User voting behavior and its records.

[0565] How it works: The server records the user's voting behavior and issues points or coupons if certain conditions are met (e.g., candidate A meets certain criteria and wins).

[0566] Output: Notification of points and coupons to the user.

[0567] Specific operation: The server generates points and coupons and sends the information to the terminal. The terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0568] These are the specific processing steps of this system. At each step, the information entered by the user is processed appropriately, and the results are returned to the user.

[0569] (Application example 1)

[0570] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0571] Currently, many brick-and-mortar stores lack the means to improve customer experience, as they do not adequately provide personalized services based on customer interests and purchase history. As a result, customer satisfaction and repeat business rates are low, and sales growth cannot be expected. In addition, there are insufficient means to collect post-purchase feedback and reflect it in product strategies, making efficient marketing and inventory management difficult. There is a need to solve these issues.

[0572] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0573] In this invention, the server includes means for collecting information on user interests, means for matching products based on the collected information, means for selecting products to be purchased based on the matched products, means for simulating the social and economic impact of purchasing the selected products, and means for recording purchasing behavior and issuing points and coupons under certain conditions. This enables personalized product suggestions based on customer interests, and by simulating post-purchase results, it is possible to improve customer satisfaction and enable efficient marketing and inventory management.

[0574] "User" means an individual who utilizes the System to enter interest and purchasing information.

[0575] "Interests" refers to the product categories or service areas in which a user is interested.

[0576] "Means of collecting information" refers to the methods and devices used to input user input such as interests and purchase history into the system.

[0577] "Product matching means" refers to a method for selecting and suggesting suitable products from a database based on collected user interests.

[0578] "Method for selecting products to be purchased" refers to the method used by a user to select the products to actually purchase from the suggested products.

[0579] "Means for simulating social and economic impacts" refers to methods for predicting future changes in social and economic conditions if the selected product is purchased.

[0580] "Means for recording purchasing behavior" refers to a method for recording actual purchasing behavior performed by a user in the system.

[0581] "Means of issuing points or coupons" refers to a method for providing points or coupons as an incentive when a user meets certain conditions.

[0582] "Incentives" refer to rewards or benefits offered to encourage user behavior.

[0583] "Brick and mortar store" refers to a sales location that offers goods or services in an actual physical location.

[0584] "Personalization" refers to customizing products and services to suit the specific interests and needs of individual users.

[0585] "Marketing" refers to all activities involved in bringing products and services to market and selling them to consumers.

[0586] "Inventory management" refers to managing goods so that they are stocked at the right time and in the right quantities and distributed efficiently.

[0587] The present invention relates to a system that proposes products in a physical store based on a user's interests, simulates the impact after purchase, and provides incentives. Specific embodiments of the system are described below.

[0588] Collection of User Information

[0589] When a user installs and launches a smartphone app, the app displays a survey about the user's interests. For example, the question might be, "What product category are you most interested in?" The user answers the survey and enters their interests, such as "home appliances," "fashion," or "food." Once this information is entered, the app sends it to a server. The server analyzes the information it receives and generates a user interest profile. This profile includes the products and categories that interest the user.

[0590] Matching with products

[0591] The server searches for product information in the database based on the generated interest profile. For example, for a user who is primarily searching for "home appliances," products such as "smart refrigerators" and "smart washing machines" are listed. The search results are sent to a smartphone app, which displays the product information to the user. The user then checks the displayed product information and selects the product they wish to purchase (e.g., a smart refrigerator).

[0592] Purchase result simulation

[0593] Once the user selects a product, the app sends that information back to the server. The server then uses past purchase data and current market conditions to simulate the social and economic impact of purchasing the selected product. For example, the simulation may predict that purchasing a smart refrigerator will reduce electricity consumption by 10%, improving household energy efficiency. The server then sends the simulation results to the app, which then visually displays the results to the user. This allows the user to understand the impact of purchasing the selected product.

[0594] Incentive distribution

[0595] The server records the user's purchasing behavior and issues points or coupons when certain conditions are met. For example, if a user actually purchases a "smart refrigerator" in a store and then answers a satisfaction survey, points are awarded. The server then sends the generated points and coupon information to the app, which notifies the user. The app displays a message saying, "You can exchange these points for a coupon with your next purchase." This process makes it easier for users to find products that match their interests and understand the social and economic impact of their purchasing behavior. Incentives also encourage actual purchasing behavior.

[0596] Hardware and Software

[0597] The hardware used includes a smartphone and a server. The software used includes the programming language Python and the requests library for sending HTTP requests. Database management uses SQL or NoSQL databases. The simulation engine uses generative AI models.

[0598] Prompt Sentence Examples

[0599] The following prompt sentence is used as an example input to the simulation engine's generative AI model:

[0600] Answer that the user is interested in "home appliances," and suggest related products. Simulate the purchase results of the selected products and output the predicted results regarding reduction in power consumption and improvement in convenience.

[0601] In this way, a smart customer matching system can be built for brick-and-mortar stores. This system can suggest products that match the user's interests and simulate the results of their purchases, improving customer satisfaction and enabling efficient marketing.

[0602] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0603] Step 1:

[0604] A user installs and launches a smartphone app. The app displays a questionnaire about the user's interests, and the user answers it. The information entered is the user's main interests (e.g., "home appliances," "fashion," "food," etc.). This input data forms the basis for building the user's interest profile.

[0605] Step 2:

[0606] The device (smartphone) sends data about the user's interests to the server, which analyzes the data and creates an interest profile for the user. This profile includes categories that reflect the user's interests.

[0607] Step 3:

[0608] The server searches for matching product information from its database based on the generated interest profile. For example, if the user is interested in "home appliances," the server will list product information such as "smart refrigerators" and "smart washing machines." The searched product information is prioritized based on the user's interests.

[0609] Step 4:

[0610] The server sends the search results to the smartphone device, which receives this information and displays the matching product information to the user. The user can then check the displayed product information and select the products they wish to purchase.

[0611] Step 5:

[0612] When a user selects a product they wish to purchase, the device sends the selection back to the server. The server then starts a simulation of the purchase outcome based on the selected product information. The simulation takes into account past purchase data and market conditions to calculate the predicted social and economic impact of the purchase.

[0613] Step 6:

[0614] The server generates simulation results and sends them to the device. The device visually displays the simulation results to the user. For example, it displays a predicted result such as "If you purchase a smart refrigerator, your electricity consumption will decrease by 10%."

[0615] Step 7:

[0616] The server records the user's purchasing behavior. If the user actually purchases a product and then provides a survey or feedback, points or coupons are issued if certain conditions are met. This incentive is intended to encourage purchases.

[0617] Step 8:

[0618] The server sends the generated points and coupon information to the terminal, which notifies the user and displays a message such as "You can use these points for your next purchase." This notification allows the user to use the incentive for their next purchase.

[0619] These are the specific processing steps of this system. At each step, the roles of the user, device, and server are clearly separated, and the input, processing, and output of information are carried out continuously, enabling smart customer matching and incentive provision in physical stores.

[0620] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0621] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. In addition, by combining it with an emotion engine, it takes into account the user's emotional state, selects more appropriate candidates, and presents simulation results.

[0622] Collection of User Information

[0623] When users install and launch the application, the device displays a survey about their political beliefs, including the question, "What policy area are you most interested in?" Users answer the survey and input their interests, such as "welfare," "environment," and "education."

[0624] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[0625] Emotion recognition by emotion engine

[0626] The device collects the user's facial expressions, tone of voice, and input patterns when answering the questionnaire, and analyzes them using an emotion engine. For example, if the user expresses high interest or anxiety about a particular question, this emotional information is collected. The server then adds the results from the emotion engine to the user's profile to generate an overall political belief of the user.

[0627] Emotion-based candidate matching

[0628] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it searches for candidates who prioritize "welfare" and lists Candidate A and Candidate B.

[0629] The search results are sent to the device, which displays the candidate information to the user. The user then checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A). This selection also takes into account the user's emotional information, making it easier for the user to find a candidate they are more comfortable with.

[0630] Simulation of voting results

[0631] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of the selected Candidate A being elected.

[0632] For example, the simulation results predict that if Candidate A is elected, "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends these simulation results to the device, which then visually displays the results to the user. The device also takes into account the user's emotional information and presents the results in a format that is easier to understand. This allows the user to understand the effects that would be expected if the candidate they selected were elected.

[0633] Incentive distribution

[0634] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[0635] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[0636] Specific examples

[0637] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list Candidates D and E, who are focusing on environmental policies. User B selects Candidate E and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[0638] On election day, if User B actually votes for Candidate E, and Candidate E meets certain criteria and wins, the server will award points to User B, and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[0639] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections. Furthermore, the introduction of an emotion engine will enable optimal candidate selection and information presentation that takes into account the user's emotions, improving the accuracy and satisfaction of voting behavior.

[0640] The processing flow will be explained below.

[0641] Step 1:

[0642] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[0643] Step 2:

[0644] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[0645] Step 3:

[0646] Terminal: Sends the user's answer information to the server.

[0647] Step 4:

[0648] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[0649] Step 5:

[0650] Device: Collects emotional data such as facial expressions, tone of voice, and input patterns when users answer surveys.

[0651] Step 6:

[0652] Terminal: Sends collected emotion data to the emotion engine and receives the analysis results.

[0653] Step 7:

[0654] Server: Adds emotional information to the user's political belief profile based on the analysis results from the emotion engine.

[0655] Step 8:

[0656] Server: Searches for candidate information in the database based on the generated political belief profile and emotional information. Searches for candidates who prioritize "welfare" and creates a list of candidates A and B.

[0657] Step 9:

[0658] Server: Sends candidate information listed as search results to the terminal.

[0659] Step 10:

[0660] Terminal: Displays candidate information to the user.

[0661] Step 11:

[0662] User: Check the displayed candidate information and select the candidate they plan to vote for (e.g., Candidate A) based on emotional information.

[0663] Step 12:

[0664] Terminal: Sends the user's selection information to the server.

[0665] Step 13:

[0666] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[0667] Step 14:

[0668] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[0669] Step 15:

[0670] Terminal: Visually displays the simulation results to the user, taking into account the user's emotional state and presenting them in an easy-to-understand format.

[0671] Step 16:

[0672] Server: Records users' voting behavior.

[0673] Step 17:

[0674] User: On election day, go to the polling station and vote for the candidate of your choice.

[0675] Step 18:

[0676] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[0677] Step 19:

[0678] Server: Sends generated points and coupon information to the terminal.

[0679] Step 20:

[0680] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[0681] Example 2

[0682] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0683] Conventional election systems have the problem that it is difficult for users to select the appropriate candidate based on their own political beliefs, and the selection process does not take emotions into consideration. Furthermore, there is a lack of mechanisms to predict the social and economic impact if the candidate selected by the user is elected, and the lack of effective incentives to encourage users to vote is also an issue.

[0684] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0685] In this invention, the server includes: means for collecting information on a user's political beliefs; means for generating a user profile based on the collected information; means for adding emotional information to the profile, which includes an emotion engine for detecting the user's emotional state; means for matching candidates based on the profile and emotional information; means for selecting a candidate to vote for based on the matched candidates; means for simulating the social and economic impact if the selected candidate is elected; and means for recording the voting behavior and issuing points or coupons under certain conditions. This makes it possible to select the optimal candidate taking into account the user's political beliefs and emotional information, and also makes it possible to effectively provide incentives to encourage voting behavior.

[0686] "User information" is data about a user's political beliefs or emotional state.

[0687] A "profile" is a data set generated from collected user information that indicates a user's political interests and attributes.

[0688] An "emotion engine" is an algorithm and system for detecting and analyzing a user's emotional state based on their facial expressions, tone of voice, input patterns, etc.

[0689] "Candidate matching" is the process of identifying suitable candidates among election candidates based on the user's profile and sentiment information.

[0690] "Selecting a candidate to vote for" is the process by which a user ultimately decides which candidate to vote for from among the matched candidates.

[0691] A "simulation" is a computational and modeling tool used to predict the social and economic impacts of a selected candidate being elected.

[0692] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[0693] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also combines an emotion engine to consider the user's emotional state, allowing for more appropriate candidate selection and simulation results. A specific embodiment of this system is described below.

[0694] Collection of User Information

[0695] 1. The device displays a survey about political beliefs to users who have the application installed. The survey includes the question, "What policy area do you care most about?"

[0696] Specific operation: The user enters a policy area of ​​interest, such as "environment" or "welfare."

[0697] 2. The device sends the entered information to the server using the REST API.

[0698] 3. The server analyzes the received information and generates a profile of the user's political beliefs, using an analysis algorithm to categorize responses into profiles such as "environmental" or "welfare."

[0699] Emotion recognition by emotion engine

[0700] 1. The device collects the user's facial expressions, tone of voice, input patterns, etc. when answering the survey. Data is collected using a camera and microphone.

[0701] 2. The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the "environment" question, it adds that emotional information to their profile.

[0702] 3. The server updates the user's overall political beliefs based on the analysis results from the emotion engine.

[0703] Candidate Matching

[0704] 1. The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[0705] 2. The search results are sent to the device, which then displays candidate information to the user, including their profile and policy details.

[0706] 3. The user reviews the displayed candidate information and selects the candidate they plan to vote for. This selection process also takes into account emotional information.

[0707] Simulation of voting results

[0708] 1. When the user selects a candidate, the information is sent to the server, which then uses the REST API to send it again.

[0709] 2. The server uses past voting data and the current political situation to simulate the social and economic impact of the selected candidate's election. The simulation is carried out using big data analysis tools.

[0710] 3. The simulation results are sent to the device, which then displays the results visually to the user, using graphs and charts.

[0711] Incentive distribution

[0712] 1. The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[0713] 2. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user. A notification is displayed saying, "You can exchange these points for coupons before the next election."

[0714] Specific examples

[0715] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list candidates who are focusing on environmental policies. User B selects a candidate and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if User B actually votes for that candidate and that candidate is elected, the server will award User B points and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[0716] Example prompts to input to the generative AI model

[0717] "We want to design a system that suggests the best candidates based on the user's political beliefs and emotional information. If the user expresses a high interest in environmental policy, please explain which candidate would be best to recommend and why."

[0718] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0719] Step 1: Collect user information

[0720] The device will display a survey about political beliefs to users who have the app installed, including the question, "What policy area do you care most about?"

[0721] - Input: User-entered answers regarding political beliefs (e.g., environment, welfare, education)

[0722] - Output: Collected user political belief data

[0723] - Specific behavior: A survey-style interface is displayed, the user enters their answers, and clicks the submit button.

[0724] Step 2: Submit user information

[0725] The device sends the collected user information to the server, which uses a REST API to send the data.

[0726] - Input: User's political beliefs data

[0727] - Output: User information stored on the server

[0728] - Specific operation: The entered data is sent to the server via API and saved in the database.

[0729] Step 3: Generate a profile

[0730] The server analyzes the received user information, generates a profile of the user's political beliefs, and uses an analysis algorithm to categorize the responses.

[0731] - Input: User's political beliefs data

[0732] - Output: User's political belief profile

[0733] - Specific operation: A data analysis algorithm analyzes the responses and classifies them into profiles such as "environment-oriented" or "welfare-oriented."

[0734] Step 4: Collecting emotion data

[0735] The device collects data such as the user's facial expressions, tone of voice, and input patterns when answering the survey. Data is collected using a camera and microphone.

[0736] - Input: User's facial expressions, tone of voice, input patterns

[0737] - Output: Data representing emotional state

[0738] - Specific operation: The camera and microphone will operate and record the user's facial expressions and voice in real time.

[0739] Step 5: Analyze the sentiment data

[0740] The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the question "environment," it adds that emotional information to their profile.

[0741] - Input: User's facial expressions, tone of voice, input patterns

[0742] - Output: Political belief profile with sentiment information

[0743] - What happens: The sentiment analysis algorithm processes the data and generates a sentiment rating, which is added to your profile.

[0744] Step 6: Matching candidate information

[0745] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[0746] - Input: Political belief profile with emotional information

[0747] - Output: Matched candidate list

[0748] - What it does: The database search algorithm will produce a list of candidates who best fit your profile.

[0749] Step 7: View candidate information

[0750] The server sends the search results to the device, which then displays candidate information to the user, including their profile and policy details.

[0751] - Input: Matched candidate list

[0752] - Output: Candidate information displayed to the user

[0753] - Specific behavior: Candidate information is visually displayed in the interface for user confirmation.

[0754] Step 8: Choose the candidate you plan to vote for

[0755] Users review the displayed candidate information and select the candidate they plan to vote for, a selection process that also takes into account emotional information.

[0756] - Input: Displayed candidate information

[0757] - Output: Candidates selected by the user

[0758] - Specific action: The user selects a candidate and clicks the "Next" button.

[0759] Step 9: Simulate the voting results

[0760] The server then receives information about the candidate selected by the user and, based on past voting data and the current political situation, simulates the social and economic impact of the selected candidate being elected.

[0761] - Input: Candidate selected by the user

[0762] - Output: Simulation results

[0763] - Specific actions: Big data analysis tools run simulations and generate results, such as "welfare budgets will increase by 10% and support for the elderly will be strengthened."

[0764] Step 10: Viewing Simulation Results

[0765] The server sends the simulation results to the device, which then visually displays the results to the user using graphs and charts.

[0766] - Input: Simulation results

[0767] - Output: Simulation results displayed to the user

[0768] - Specific operation: Simulation results are visually displayed in the interface for user confirmation.

[0769] Step 11: Record and issue incentives

[0770] The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[0771] - Input: User voting behavior, election results

[0772] - Output: Points or coupons

[0773] - Specific behavior: Voting behavior is logged, and if the conditions are met, points are calculated and awarded.

[0774] Step 12: Incentive Notification

[0775] The server transmits the generated points and coupon information to the terminal, which then notifies the user of the same.

[0776] - Input: Points or coupon information

[0777] - Output: Incentive notification distributed to users

[0778] - Specific operation: A notification will appear on the device saying, "You can exchange these points for coupons before the next election."

[0779] (Application example 2)

[0780] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0781] Conventional voting systems did not adequately match candidates based on users' political beliefs or promote voting behavior. Furthermore, it was difficult to select the optimal candidate and present information based on the user's emotional state, and the management and coordination of points and coupons given as incentives was insufficient. This resulted in low voter engagement and a decline in voter motivation to participate in elections.

[0782] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0783] In this invention, the server includes means for collecting information on the user's political beliefs, means for matching candidates based on the collected information and the user's emotional state, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact if the selected candidate is elected, and means for recording the voting behavior, issuing points or coupons under certain conditions, and linking with an electronic payment service. This enables the selection of the optimal candidate taking the user's emotional state into consideration, promotes voting behavior, and enables incentive management linked with an electronic payment service.

[0784] A "user" is someone who uses the system to provide information about their political beliefs, select candidates, and vote.

[0785] "Political beliefs" refers to information that refers to a user's political opinions, values, and interests.

[0786] "Emotional state" refers to the emotional response state recognized from the facial expressions, tone of voice, input patterns, etc. shown by the user when answering a questionnaire or using the system.

[0787] "Candidates" refers to people or organizations running for office, who are matched based on users' political beliefs.

[0788] "Matching" is the process of comparing the user's political beliefs and emotional state with the candidates' policies and positions to select the most suitable candidate.

[0789] "Selection" refers to the act of a user deciding which candidate they intend to vote for from among the matched candidates.

[0790] "Simulation" is the process of calculation and analysis that predicts the social and economic impacts if the selected candidate is elected.

[0791] "Voting behavior" refers to the entire act of a user actually voting for the selected candidate at a polling station.

[0792] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[0793] An "electronic payment service" is a payment system that uses the Internet and electronic devices, and supports the management and use of points and coupons.

[0794] This invention is a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also uses emotion recognition technology to consider the user's emotional state, selecting more appropriate candidates and presenting simulation results. Furthermore, by linking with electronic payment services, it is possible to smoothly manage incentives according to voting behavior.

[0795] Specifically, users answer a questionnaire about their political beliefs through an application installed on their smartphone. Emotional data, such as the user's facial expressions, tone of voice, and input patterns, is collected while answering the questionnaire and analyzed by an emotion engine. The server generates a political belief profile for the user based on the collected information and emotional data, and compares it with candidate information in a database to match the most suitable candidate.

[0796] When a user checks the candidate information provided and selects the candidate they plan to vote for, the server simulates the social and economic impact if the selected candidate is elected. The simulation results are presented to the user in a visually easy-to-understand format. For example, if a user interested in the environment selects a candidate who is focusing on environmental policies, the server will display a forecast showing the increased adoption of renewable energy.

[0797] Furthermore, if a user actually votes and their actions meet certain conditions, points or coupons are issued in cooperation with an electronic payment service. This allows users to exchange their points for coupons before the next election. Incentive conditions can be set, for example, if the voter turnout for the election is above a certain level, or if the number of votes received by the candidate selected in the application is within a certain range.

[0798] Hardware: Smartphone

[0799] Software: Python, emotion recognition library (emotion_recognition), candidate matching algorithm (match_candidates)

[0800] An example prompt is:

[0801] "The system analyzes the emotions expressed when users answer surveys and matches them with the most suitable candidates based on their political beliefs. It visually displays the simulation results of what would happen if the candidate were elected, and awards incentives (points or coupons) based on voting behavior."

[0802] This system makes it possible to select the most appropriate candidate taking into account the user's emotional state, encouraging voting behavior and facilitating incentive management in conjunction with electronic payment services.

[0803] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0804] Step 1:

[0805] The user launches an application installed on their smartphone and answers a questionnaire about their political beliefs.

[0806] Input: Survey response about user's political beliefs

[0807] Output: Response data

[0808] Specific operation: The user launches the application and enters their interests, such as "welfare" or "environment," in response to the questions that appear.

[0809] Step 2:

[0810] Emotional data such as facial expressions, tone of voice, and input patterns of users when answering surveys are collected.

[0811] Input: User facial expressions, tone of voice, and input patterns while answering the survey

[0812] Output: Emotion data

[0813] Specific operation: Using the device's camera and microphone, the user's facial expressions and tone of voice are captured and analyzed using an emotion engine.

[0814] Step 3:

[0815] The server receives the collected political belief information and emotional data and generates a political belief profile for the user.

[0816] Input: Survey response data, emotion data

[0817] Output: Political profile

[0818] What it does: The server analyzes the data it receives and creates a profile of the user that combines their political interests and emotional state.

[0819] Step 4:

[0820] The server matches the most suitable candidate based on the political belief profile with candidate information in the database.

[0821] Input: Political profile, candidate information in database

[0822] Output: A list of matched candidates

[0823] Specific operation: The server matches the user's profile with the policies of each candidate and identifies the most suitable candidate.

[0824] Step 5:

[0825] Information about matched candidates is sent to the terminal and displayed to the user.

[0826] Input: List of matched candidates

[0827] Output: Candidates selected by the user

[0828] Specific operation: Candidate information is displayed on the device, and the user is asked to confirm and select the candidate they plan to vote for.

[0829] Step 6:

[0830] Information about the candidate selected by the user is sent to a server, and the social and economic impact of the selected candidate being elected is simulated.

[0831] Input: Candidate information selected by the user

[0832] Output: Simulation results

[0833] Specific operation: The server calculates the impact of winning based on past data and the current political situation and generates the results.

[0834] Step 7:

[0835] The simulation results are sent to the terminal and displayed visually to the user.

[0836] Input: Simulation results

[0837] Output: Displaying results in a user-friendly format

[0838] Specific operation: The simulation results are displayed on the terminal in a visually easy-to-understand format for the user to confirm.

[0839] Step 8:

[0840] After a user actually votes, their voting behavior is recorded, and if specified conditions are met, points or coupons are generated and distributed via an electronic payment service.

[0841] Input: Voting records, election results, incentive conditions

[0842] Output: Points or coupons

[0843] Specific operation: The server checks the user's voting behavior and determines whether the incentive conditions are met, then generates points or coupons and provides them to the user via an electronic payment service.

[0844] 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.

[0845] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0846] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0847] [Third embodiment]

[0848] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0849] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0850] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0851] 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.

[0852] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0853] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0854] 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.

[0855] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0856] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0857] 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.

[0858] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0859] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0860] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0861] Collection of User Information

[0862] When users install and launch the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and inputs their interests, such as "welfare," "environment," and "education."

[0863] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[0864] Matching with candidates

[0865] The server searches for candidate information in the database based on the generated political belief profile. For example, if a search is performed for candidates who prioritize "welfare," Candidate A and Candidate B will be listed.

[0866] The search results are sent to the terminal, which displays the candidate information to the user. The user checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0867] Simulation of voting results

[0868] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A's election.

[0869] For example, the simulation results predict that if Candidate A is elected, "the welfare budget will increase by 10% and support for the elderly will be strengthened." The server sends this simulation result to the terminal, which then visually displays the result to the user, allowing the user to understand the effects if the selected candidate is elected.

[0870] Incentive distribution

[0871] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[0872] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[0873] This process helps users find candidates who align with their political beliefs, understand the social and economic impact of their voting behavior, and provides incentives to actually vote.

[0874] Specific examples

[0875] For example, if User A uses the system and responds that he or she is interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. User A selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[0876] On election day, if User A actually votes for Candidate C, and Candidate C meets certain criteria and wins, the server will award points to User A, and the device will notify the user. User A can exchange those points for coupons before the next election.

[0877] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections.

[0878] The processing flow will be explained below.

[0879] Step 1:

[0880] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[0881] Step 2:

[0882] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[0883] Step 3:

[0884] Terminal: Sends the user's answer information to the server.

[0885] Step 4:

[0886] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[0887] Step 5:

[0888] Server: Based on the generated political belief profile, search for candidate information in the database. Search for candidates who prioritize "welfare" and list Candidate A and Candidate B.

[0889] Step 6:

[0890] Server: Sends candidate information listed as search results to the terminal.

[0891] Step 7:

[0892] Terminal: Displays candidate information to the user.

[0893] Step 8:

[0894] User: Check the displayed candidate information and select the candidate for whom they plan to vote (e.g., Candidate A).

[0895] Step 9:

[0896] Terminal: Sends the user's selection information to the server.

[0897] Step 10:

[0898] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[0899] Step 11:

[0900] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[0901] Step 12:

[0902] Terminal: Visually displays the simulation results to users, allowing them to understand the impact of their chosen candidate if they were elected.

[0903] Step 13:

[0904] Server: Records users' voting behavior.

[0905] Step 14:

[0906] User: On election day, go to the polling station and vote for the candidate of your choice.

[0907] Step 15:

[0908] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[0909] Step 16:

[0910] Server: Sends generated points and coupon information to the terminal.

[0911] Step 17:

[0912] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[0913] Example 1

[0914] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0915] Many voters today find it difficult to find candidates who align with their political beliefs. Furthermore, they are often hesitant to vote due to limited means of predicting the impact that election results will have on society and the economy. Furthermore, there is a lack of effective means to encourage voting, resulting in low interest in and participation in elections.

[0916] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0917] In this invention, the server includes means for collecting information on a user's political beliefs, means for analyzing the collected information to generate a user's political belief profile, means for searching for and matching candidates based on the generated profile, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact of the selected candidate being elected, means for visually displaying the results of the simulation to the user, and means for recording the voting behavior and issuing points or coupons under certain conditions. This allows users to easily find candidates that match their political beliefs, makes it easier for them to understand the social and economic impact of election results, and encourages actual voting behavior through incentives.

[0918] "Information regarding the user's political beliefs" refers to information that indicates the user's political interests, values, policy priorities, etc.

[0919] A "political profile" is data that represents a user's political leanings and areas of interest, generated based on information about their political beliefs provided by the user.

[0920] "Candidate" means a person or entity running for public office in a particular election.

[0921] "Matching" refers to the act of selecting and providing candidates who are likely to be supported by the user based on the collected information and the generated profile.

[0922] Selecting a "candidate to vote for" is the act of the user selecting the candidate for whom they actually want to vote from among the candidates provided.

[0923] "Simulating" refers to the act of virtually predicting the expected social and economic impact if a selected candidate is elected, using past data, statistical information, and algorithms.

[0924] "Issuing points or coupons" refers to the act of generating and granting benefits or rewards to users in order to encourage their active participation and behavior.

[0925] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[0926] Collection of User Information

[0927] When a user installs and launches the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and enters their interests, such as "welfare," "environment," or "education." Once this information is entered, the device sends it to a server.

[0928] Generating a political belief profile

[0929] The server analyzes the information it receives and generates a political profile of the user using Python data analysis libraries (e.g., Pandas) and other statistical analysis methods. The profile includes the user's political interests and is stored in a central database. Based on the profile, the server then creates a list of candidates the user is likely to support.

[0930] Matching with candidates

[0931] The server searches for candidate information in a database based on the generated political belief profile. For example, a search for candidates who prioritize "welfare" results in a list of Candidate A and Candidate B. A database management system such as a NoSQL database (e.g., MongoDB) is used for the search. The search results are sent to the device, which displays the candidate information to the user. The user reviews the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[0932] Simulation of voting results

[0933] When the user selects Candidate A, the device sends that information back to the server. The server then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A being elected. A generative AI model (e.g., a TensorFlow-based predictive model) is used for the simulation. For example, the simulation results in a prediction that "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends the results of this simulation to the device, which then visually displays the results to the user. This allows the user to understand the impact that the selected candidate would have if elected.

[0934] Incentive distribution

[0935] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes received after the election exceeds a certain threshold, points are awarded. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0936] Specific examples

[0937] For example, if a newly registered user uses the system and responds that they are interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. The user selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if the user actually votes for Candidate C, and Candidate C meets certain criteria and is elected, the server will award the user points and the device will notify them of this. The user can exchange those points for coupons before the next election.

[0938] Example prompts for generative AI models

[0939] "Please explain in natural language the process of a system that lists appropriate candidates, simulates voting results, and awards incentives based on the user's political beliefs."

[0940] This is a specific embodiment of the present invention. This system makes it easier for users to find candidates who align with their political beliefs and understand the social and economic impacts of their election. It is also expected that incentives will encourage users to vote.

[0941] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0942] Step 1:

[0943] Collection of User Information

[0944] Input: A user installs and launches an application.

[0945] What it does: The device prompts the user with a survey about their political beliefs, such as the question, "What policy area do you care about most?"

[0946] Output: The user's answer (e.g., "welfare," "environment," "education," etc.) is obtained.

[0947] How it works: The user answers the survey, and the information they enter is encrypted in JSON format and sent to the server using the HTTPS protocol.

[0948] Step 2:

[0949] Generating a political belief profile

[0950] Input: User survey response data.

[0951] How it works: The server analyzes the received data using a Python data analysis library (e.g., Pandas).

[0952] Output: A political profile of the user is generated.

[0953] How it works: The server uses the analyzed data to create a profile of the user's political interests and stores this profile in a central database.

[0954] Step 3:

[0955] Candidate search and matching

[0956] Input: Generated political belief profiles.

[0957] How it works: The server searches for candidate information in a NoSQL database (e.g., MongoDB) based on the user's political profile.

[0958] Output: A list of candidates (e.g., Candidate A, Candidate B) that match the user's political beliefs.

[0959] Specific operation: The server uses a matching algorithm to list candidates that match the profile and sends the results to the terminal.

[0960] Step 4:

[0961] View and select candidate information

[0962] Input: A list of candidates.

[0963] How it works: The device displays information about the candidate to the user, including the candidate's policies and past performance.

[0964] Output: The candidate the user has selected to vote for (e.g., Candidate A).

[0965] Specific operation: Based on the displayed information, the user selects the candidate they plan to vote for, and the selection information is sent from the device to the server.

[0966] Step 5:

[0967] Simulation of voting results

[0968] Input: Candidate information selected by the user.

[0969] How it works: The server uses historical voting data and the current political situation to simulate the social and economic impact of a candidate's election. Generative AI models (e.g., TensorFlow-based predictive models) are used.

[0970] Output: Simulation results (e.g., "The welfare budget will increase by 10% and support for the elderly will be strengthened") are obtained.

[0971] Specific operation: The server performs a simulation using the AI ​​model and sends the results in JSON format to the device, which then visually displays the results to the user.

[0972] Step 6:

[0973] Recording voting behavior and distributing incentives

[0974] Input: User voting behavior and its records.

[0975] How it works: The server records the user's voting behavior and issues points or coupons if certain conditions are met (e.g., candidate A meets certain criteria and wins).

[0976] Output: Notification of points and coupons to the user.

[0977] Specific operation: The server generates points and coupons and sends the information to the terminal. The terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[0978] These are the specific processing steps of this system. At each step, the information entered by the user is processed appropriately, and the results are returned to the user.

[0979] (Application example 1)

[0980] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0981] Currently, many brick-and-mortar stores lack the means to improve customer experience, as they do not adequately provide personalized services based on customer interests and purchase history. As a result, customer satisfaction and repeat business rates are low, and sales growth cannot be expected. In addition, there are insufficient means to collect post-purchase feedback and reflect it in product strategies, making efficient marketing and inventory management difficult. There is a need to solve these issues.

[0982] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0983] In this invention, the server includes means for collecting information on user interests, means for matching products based on the collected information, means for selecting products to be purchased based on the matched products, means for simulating the social and economic impact of purchasing the selected products, and means for recording purchasing behavior and issuing points and coupons under certain conditions. This enables personalized product suggestions based on customer interests, and by simulating post-purchase results, it is possible to improve customer satisfaction and enable efficient marketing and inventory management.

[0984] "User" means an individual who utilizes the System to enter interest and purchasing information.

[0985] "Interests" refers to the product categories or service areas in which a user is interested.

[0986] "Means of collecting information" refers to the methods and devices used to input user input such as interests and purchase history into the system.

[0987] "Product matching means" refers to a method for selecting and suggesting suitable products from a database based on collected user interests.

[0988] "Method for selecting products to be purchased" refers to the method used by a user to select the products to actually purchase from the suggested products.

[0989] "Means for simulating social and economic impacts" refers to methods for predicting future changes in social and economic conditions if the selected product is purchased.

[0990] "Means for recording purchasing behavior" refers to a method for recording actual purchasing behavior performed by a user in the system.

[0991] "Means of issuing points or coupons" refers to a method for providing points or coupons as an incentive when a user meets certain conditions.

[0992] "Incentives" refer to rewards or benefits offered to encourage user behavior.

[0993] "Brick and mortar store" refers to a sales location that offers goods or services in an actual physical location.

[0994] "Personalization" refers to customizing products and services to suit the specific interests and needs of individual users.

[0995] "Marketing" refers to all activities involved in bringing products and services to market and selling them to consumers.

[0996] "Inventory management" refers to managing goods so that they are stocked at the right time and in the right quantities and distributed efficiently.

[0997] The present invention relates to a system that proposes products in a physical store based on a user's interests, simulates the impact after purchase, and provides incentives. Specific embodiments of the system are described below.

[0998] Collection of User Information

[0999] When a user installs and launches a smartphone app, the app displays a survey about the user's interests. For example, the question might be, "What product category are you most interested in?" The user answers the survey and enters their interests, such as "home appliances," "fashion," or "food." Once this information is entered, the app sends it to a server. The server analyzes the information it receives and generates a user interest profile. This profile includes the products and categories that interest the user.

[1000] Matching with products

[1001] The server searches for product information in the database based on the generated interest profile. For example, for a user who is primarily searching for "home appliances," products such as "smart refrigerators" and "smart washing machines" are listed. The search results are sent to a smartphone app, which displays the product information to the user. The user then checks the displayed product information and selects the product they wish to purchase (e.g., a smart refrigerator).

[1002] Purchase result simulation

[1003] Once the user selects a product, the app sends that information back to the server. The server then uses past purchase data and current market conditions to simulate the social and economic impact of purchasing the selected product. For example, the simulation may predict that purchasing a smart refrigerator will reduce electricity consumption by 10%, improving household energy efficiency. The server then sends the simulation results to the app, which then visually displays the results to the user. This allows the user to understand the impact of purchasing the selected product.

[1004] Incentive distribution

[1005] The server records the user's purchasing behavior and issues points or coupons when certain conditions are met. For example, if a user actually purchases a "smart refrigerator" in a store and then answers a satisfaction survey, points are awarded. The server then sends the generated points and coupon information to the app, which notifies the user. The app displays a message saying, "You can exchange these points for a coupon with your next purchase." This process makes it easier for users to find products that match their interests and understand the social and economic impact of their purchasing behavior. Incentives also encourage actual purchasing behavior.

[1006] Hardware and Software

[1007] The hardware used includes a smartphone and a server. The software used includes the programming language Python and the requests library for sending HTTP requests. Database management uses SQL or NoSQL databases. The simulation engine uses generative AI models.

[1008] Prompt Sentence Examples

[1009] The following prompt sentence is used as an example input to the simulation engine's generative AI model:

[1010] Answer that the user is interested in "home appliances," and suggest related products. Simulate the purchase results of the selected products and output the predicted results regarding reduction in power consumption and improvement in convenience.

[1011] In this way, a smart customer matching system can be built for brick-and-mortar stores. This system can suggest products that match the user's interests and simulate the results of their purchases, improving customer satisfaction and enabling efficient marketing.

[1012] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1013] Step 1:

[1014] A user installs and launches a smartphone app. The app displays a questionnaire about the user's interests, and the user answers it. The information entered is the user's main interests (e.g., "home appliances," "fashion," "food," etc.). This input data forms the basis for building the user's interest profile.

[1015] Step 2:

[1016] The device (smartphone) sends data about the user's interests to the server, which analyzes the data and creates an interest profile for the user. This profile includes categories that reflect the user's interests.

[1017] Step 3:

[1018] The server searches for matching product information from its database based on the generated interest profile. For example, if the user is interested in "home appliances," the server will list product information such as "smart refrigerators" and "smart washing machines." The searched product information is prioritized based on the user's interests.

[1019] Step 4:

[1020] The server sends the search results to the smartphone device, which receives this information and displays the matching product information to the user. The user can then check the displayed product information and select the products they wish to purchase.

[1021] Step 5:

[1022] When a user selects a product they wish to purchase, the device sends the selection back to the server. The server then starts a simulation of the purchase outcome based on the selected product information. The simulation takes into account past purchase data and market conditions to calculate the predicted social and economic impact of the purchase.

[1023] Step 6:

[1024] The server generates simulation results and sends them to the device. The device visually displays the simulation results to the user. For example, it displays a predicted result such as "If you purchase a smart refrigerator, your electricity consumption will decrease by 10%."

[1025] Step 7:

[1026] The server records the user's purchasing behavior. If the user actually purchases a product and then provides a survey or feedback, points or coupons are issued if certain conditions are met. This incentive is intended to encourage purchases.

[1027] Step 8:

[1028] The server sends the generated points and coupon information to the terminal, which notifies the user and displays a message such as "You can use these points for your next purchase." This notification allows the user to use the incentive for their next purchase.

[1029] These are the specific processing steps of this system. At each step, the roles of the user, device, and server are clearly separated, and the input, processing, and output of information are carried out continuously, enabling smart customer matching and incentive provision in physical stores.

[1030] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1031] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. In addition, by combining it with an emotion engine, it takes into account the user's emotional state, selects more appropriate candidates, and presents simulation results.

[1032] Collection of User Information

[1033] When users install and launch the application, the device displays a survey about their political beliefs, including the question, "What policy area are you most interested in?" Users answer the survey and input their interests, such as "welfare," "environment," and "education."

[1034] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[1035] Emotion recognition by emotion engine

[1036] The device collects the user's facial expressions, tone of voice, and input patterns when answering the questionnaire, and analyzes them using an emotion engine. For example, if the user expresses high interest or anxiety about a particular question, this emotional information is collected. The server then adds the results from the emotion engine to the user's profile to generate an overall political belief of the user.

[1037] Emotion-based candidate matching

[1038] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it searches for candidates who prioritize "welfare" and lists Candidate A and Candidate B.

[1039] The search results are sent to the device, which displays the candidate information to the user. The user then checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A). This selection also takes into account the user's emotional information, making it easier for the user to find a candidate they are more comfortable with.

[1040] Simulation of voting results

[1041] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of the selected Candidate A being elected.

[1042] For example, the simulation results predict that if Candidate A is elected, "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends these simulation results to the device, which then visually displays the results to the user. The device also takes into account the user's emotional information and presents the results in a format that is easier to understand. This allows the user to understand the effects that would be expected if the candidate they selected were elected.

[1043] Incentive distribution

[1044] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[1045] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[1046] Specific examples

[1047] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list Candidates D and E, who are focusing on environmental policies. User B selects Candidate E and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[1048] On election day, if User B actually votes for Candidate E, and Candidate E meets certain criteria and wins, the server will award points to User B, and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[1049] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections. Furthermore, the introduction of an emotion engine will enable optimal candidate selection and information presentation that takes into account the user's emotions, improving the accuracy and satisfaction of voting behavior.

[1050] The processing flow will be explained below.

[1051] Step 1:

[1052] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[1053] Step 2:

[1054] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[1055] Step 3:

[1056] Terminal: Sends the user's answer information to the server.

[1057] Step 4:

[1058] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[1059] Step 5:

[1060] Device: Collects emotional data such as facial expressions, tone of voice, and input patterns when users answer surveys.

[1061] Step 6:

[1062] Terminal: Sends collected emotion data to the emotion engine and receives the analysis results.

[1063] Step 7:

[1064] Server: Adds emotional information to the user's political belief profile based on the analysis results from the emotion engine.

[1065] Step 8:

[1066] Server: Searches for candidate information in the database based on the generated political belief profile and emotional information. Searches for candidates who prioritize "welfare" and creates a list of candidates A and B.

[1067] Step 9:

[1068] Server: Sends candidate information listed as search results to the terminal.

[1069] Step 10:

[1070] Terminal: Displays candidate information to the user.

[1071] Step 11:

[1072] User: Check the displayed candidate information and select the candidate they plan to vote for (e.g., Candidate A) based on emotional information.

[1073] Step 12:

[1074] Terminal: Sends the user's selection information to the server.

[1075] Step 13:

[1076] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[1077] Step 14:

[1078] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[1079] Step 15:

[1080] Terminal: Visually displays the simulation results to the user, taking into account the user's emotional state and presenting them in an easy-to-understand format.

[1081] Step 16:

[1082] Server: Records users' voting behavior.

[1083] Step 17:

[1084] User: On election day, go to the polling station and vote for the candidate of your choice.

[1085] Step 18:

[1086] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[1087] Step 19:

[1088] Server: Sends generated points and coupon information to the terminal.

[1089] Step 20:

[1090] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[1091] Example 2

[1092] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1093] Conventional election systems have the problem that it is difficult for users to select the appropriate candidate based on their own political beliefs, and the selection process does not take emotions into consideration. Furthermore, there is a lack of mechanisms to predict the social and economic impact if the candidate selected by the user is elected, and the lack of effective incentives to encourage users to vote is also an issue.

[1094] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1095] In this invention, the server includes: means for collecting information on a user's political beliefs; means for generating a user profile based on the collected information; means for adding emotional information to the profile, which includes an emotion engine for detecting the user's emotional state; means for matching candidates based on the profile and emotional information; means for selecting a candidate to vote for based on the matched candidates; means for simulating the social and economic impact if the selected candidate is elected; and means for recording the voting behavior and issuing points or coupons under certain conditions. This makes it possible to select the optimal candidate taking into account the user's political beliefs and emotional information, and also makes it possible to effectively provide incentives to encourage voting behavior.

[1096] "User information" is data about a user's political beliefs or emotional state.

[1097] A "profile" is a data set generated from collected user information that indicates a user's political interests and attributes.

[1098] An "emotion engine" is an algorithm and system for detecting and analyzing a user's emotional state based on their facial expressions, tone of voice, input patterns, etc.

[1099] "Candidate matching" is the process of identifying suitable candidates among election candidates based on the user's profile and sentiment information.

[1100] "Selecting a candidate to vote for" is the process by which a user ultimately decides which candidate to vote for from among the matched candidates.

[1101] A "simulation" is a computational and modeling tool used to predict the social and economic impacts of a selected candidate being elected.

[1102] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[1103] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also combines an emotion engine to consider the user's emotional state, allowing for more appropriate candidate selection and simulation results. A specific embodiment of this system is described below.

[1104] Collection of User Information

[1105] 1. The device displays a survey about political beliefs to users who have the application installed. The survey includes the question, "What policy area do you care most about?"

[1106] Specific operation: The user enters a policy area of ​​interest, such as "environment" or "welfare."

[1107] 2. The device sends the entered information to the server using the REST API.

[1108] 3. The server analyzes the received information and generates a profile of the user's political beliefs, using an analysis algorithm to categorize responses into profiles such as "environmental" or "welfare."

[1109] Emotion recognition by emotion engine

[1110] 1. The device collects the user's facial expressions, tone of voice, input patterns, etc. when answering the survey. Data is collected using a camera and microphone.

[1111] 2. The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the "environment" question, it adds that emotional information to their profile.

[1112] 3. The server updates the user's overall political beliefs based on the analysis results from the emotion engine.

[1113] Candidate Matching

[1114] 1. The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[1115] 2. The search results are sent to the device, which then displays candidate information to the user, including their profile and policy details.

[1116] 3. The user reviews the displayed candidate information and selects the candidate they plan to vote for. This selection process also takes into account emotional information.

[1117] Simulation of voting results

[1118] 1. When the user selects a candidate, the information is sent to the server, which then uses the REST API to send it again.

[1119] 2. The server uses past voting data and the current political situation to simulate the social and economic impact of the selected candidate's election. The simulation is carried out using big data analysis tools.

[1120] 3. The simulation results are sent to the device, which then displays the results visually to the user, using graphs and charts.

[1121] Incentive distribution

[1122] 1. The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[1123] 2. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user. A notification is displayed saying, "You can exchange these points for coupons before the next election."

[1124] Specific examples

[1125] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list candidates who are focusing on environmental policies. User B selects a candidate and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if User B actually votes for that candidate and that candidate is elected, the server will award User B points and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[1126] Example prompts to input to the generative AI model

[1127] "We want to design a system that suggests the best candidates based on the user's political beliefs and emotional information. If the user expresses a high interest in environmental policy, please explain which candidate would be best to recommend and why."

[1128] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1129] Step 1: Collect user information

[1130] The device will display a survey about political beliefs to users who have the app installed, including the question, "What policy area do you care most about?"

[1131] - Input: User-entered answers regarding political beliefs (e.g., environment, welfare, education)

[1132] - Output: Collected user political belief data

[1133] - Specific behavior: A survey-style interface is displayed, the user enters their answers, and clicks the submit button.

[1134] Step 2: Submit user information

[1135] The device sends the collected user information to the server, which uses a REST API to send the data.

[1136] - Input: User's political beliefs data

[1137] - Output: User information stored on the server

[1138] - Specific operation: The entered data is sent to the server via API and saved in the database.

[1139] Step 3: Generate a profile

[1140] The server analyzes the received user information, generates a profile of the user's political beliefs, and uses an analysis algorithm to categorize the responses.

[1141] - Input: User's political beliefs data

[1142] - Output: User's political belief profile

[1143] - Specific operation: A data analysis algorithm analyzes the responses and classifies them into profiles such as "environment-oriented" or "welfare-oriented."

[1144] Step 4: Collecting emotion data

[1145] The device collects data such as the user's facial expressions, tone of voice, and input patterns when answering the survey. Data is collected using a camera and microphone.

[1146] - Input: User's facial expressions, tone of voice, input patterns

[1147] - Output: Data representing emotional state

[1148] - Specific operation: The camera and microphone will operate and record the user's facial expressions and voice in real time.

[1149] Step 5: Analyze the sentiment data

[1150] The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the question "environment," it adds that emotional information to their profile.

[1151] - Input: User's facial expressions, tone of voice, input patterns

[1152] - Output: Political belief profile with sentiment information

[1153] - What happens: The sentiment analysis algorithm processes the data and generates a sentiment rating, which is added to your profile.

[1154] Step 6: Matching candidate information

[1155] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[1156] - Input: Political belief profile with emotional information

[1157] - Output: Matched candidate list

[1158] - What it does: The database search algorithm will produce a list of candidates who best fit your profile.

[1159] Step 7: View candidate information

[1160] The server sends the search results to the device, which then displays candidate information to the user, including their profile and policy details.

[1161] - Input: Matched candidate list

[1162] - Output: Candidate information displayed to the user

[1163] - Specific behavior: Candidate information is visually displayed in the interface for user confirmation.

[1164] Step 8: Choose the candidate you plan to vote for

[1165] Users review the displayed candidate information and select the candidate they plan to vote for, a selection process that also takes into account emotional information.

[1166] - Input: Displayed candidate information

[1167] - Output: Candidates selected by the user

[1168] - Specific action: The user selects a candidate and clicks the "Next" button.

[1169] Step 9: Simulate the voting results

[1170] The server then receives information about the candidate selected by the user and, based on past voting data and the current political situation, simulates the social and economic impact of the selected candidate being elected.

[1171] - Input: Candidate selected by the user

[1172] - Output: Simulation results

[1173] - Specific actions: Big data analysis tools run simulations and generate results, such as "welfare budgets will increase by 10% and support for the elderly will be strengthened."

[1174] Step 10: Viewing Simulation Results

[1175] The server sends the simulation results to the device, which then visually displays the results to the user using graphs and charts.

[1176] - Input: Simulation results

[1177] - Output: Simulation results displayed to the user

[1178] - Specific operation: Simulation results are visually displayed in the interface for user confirmation.

[1179] Step 11: Record and issue incentives

[1180] The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[1181] - Input: User voting behavior, election results

[1182] - Output: Points or coupons

[1183] - Specific behavior: Voting behavior is logged, and if the conditions are met, points are calculated and awarded.

[1184] Step 12: Incentive Notification

[1185] The server transmits the generated points and coupon information to the terminal, which then notifies the user of the same.

[1186] - Input: Points or coupon information

[1187] - Output: Incentive notification distributed to users

[1188] - Specific operation: A notification will appear on the device saying, "You can exchange these points for coupons before the next election."

[1189] (Application example 2)

[1190] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1191] Conventional voting systems did not adequately match candidates based on users' political beliefs or promote voting behavior. Furthermore, it was difficult to select the optimal candidate and present information based on the user's emotional state, and the management and coordination of points and coupons given as incentives was insufficient. This resulted in low voter engagement and a decline in voter motivation to participate in elections.

[1192] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1193] In this invention, the server includes means for collecting information on the user's political beliefs, means for matching candidates based on the collected information and the user's emotional state, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact if the selected candidate is elected, and means for recording the voting behavior, issuing points or coupons under certain conditions, and linking with an electronic payment service. This enables the selection of the optimal candidate taking the user's emotional state into consideration, promotes voting behavior, and enables incentive management linked with an electronic payment service.

[1194] A "user" is someone who uses the system to provide information about their political beliefs, select candidates, and vote.

[1195] "Political beliefs" refers to information that refers to a user's political opinions, values, and interests.

[1196] "Emotional state" refers to the emotional response state recognized from the facial expressions, tone of voice, input patterns, etc. shown by the user when answering a questionnaire or using the system.

[1197] "Candidates" refers to people or organizations running for office, who are matched based on users' political beliefs.

[1198] "Matching" is the process of comparing the user's political beliefs and emotional state with the candidates' policies and positions to select the most suitable candidate.

[1199] "Selection" refers to the act of a user deciding which candidate they intend to vote for from among the matched candidates.

[1200] "Simulation" is the process of calculation and analysis that predicts the social and economic impacts if the selected candidate is elected.

[1201] "Voting behavior" refers to the entire act of a user actually voting for the selected candidate at a polling station.

[1202] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[1203] An "electronic payment service" is a payment system that uses the Internet and electronic devices, and supports the management and use of points and coupons.

[1204] This invention is a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also uses emotion recognition technology to consider the user's emotional state, selecting more appropriate candidates and presenting simulation results. Furthermore, by linking with electronic payment services, it is possible to smoothly manage incentives according to voting behavior.

[1205] Specifically, users answer a questionnaire about their political beliefs through an application installed on their smartphone. Emotional data, such as the user's facial expressions, tone of voice, and input patterns, is collected while answering the questionnaire and analyzed by an emotion engine. The server generates a political belief profile for the user based on the collected information and emotional data, and compares it with candidate information in a database to match the most suitable candidate.

[1206] When a user checks the candidate information provided and selects the candidate they plan to vote for, the server simulates the social and economic impact if the selected candidate is elected. The simulation results are presented to the user in a visually easy-to-understand format. For example, if a user interested in the environment selects a candidate who is focusing on environmental policies, the server will display a forecast showing the increased adoption of renewable energy.

[1207] Furthermore, if a user actually votes and their actions meet certain conditions, points or coupons are issued in cooperation with an electronic payment service. This allows users to exchange their points for coupons before the next election. Incentive conditions can be set, for example, if the voter turnout for the election is above a certain level, or if the number of votes received by the candidate selected in the application is within a certain range.

[1208] Hardware: Smartphone

[1209] Software: Python, emotion recognition library (emotion_recognition), candidate matching algorithm (match_candidates)

[1210] An example prompt is:

[1211] "The system analyzes the emotions expressed when users answer surveys and matches them with the most suitable candidates based on their political beliefs. It visually displays the simulation results of what would happen if the candidate were elected, and awards incentives (points or coupons) based on voting behavior."

[1212] This system makes it possible to select the most appropriate candidate taking into account the user's emotional state, encouraging voting behavior and facilitating incentive management in conjunction with electronic payment services.

[1213] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1214] Step 1:

[1215] The user launches an application installed on their smartphone and answers a questionnaire about their political beliefs.

[1216] Input: Survey response about user's political beliefs

[1217] Output: Response data

[1218] Specific operation: The user launches the application and enters their interests, such as "welfare" or "environment," in response to the questions that appear.

[1219] Step 2:

[1220] Emotional data such as facial expressions, tone of voice, and input patterns of users when answering surveys are collected.

[1221] Input: User facial expressions, tone of voice, and input patterns while answering the survey

[1222] Output: Emotion data

[1223] Specific operation: Using the device's camera and microphone, the user's facial expressions and tone of voice are captured and analyzed using an emotion engine.

[1224] Step 3:

[1225] The server receives the collected political belief information and emotional data and generates a political belief profile for the user.

[1226] Input: Survey response data, emotion data

[1227] Output: Political profile

[1228] What it does: The server analyzes the data it receives and creates a profile of the user that combines their political interests and emotional state.

[1229] Step 4:

[1230] The server matches the most suitable candidate based on the political belief profile with candidate information in the database.

[1231] Input: Political profile, candidate information in database

[1232] Output: A list of matched candidates

[1233] Specific operation: The server matches the user's profile with the policies of each candidate and identifies the most suitable candidate.

[1234] Step 5:

[1235] Information about matched candidates is sent to the terminal and displayed to the user.

[1236] Input: List of matched candidates

[1237] Output: Candidates selected by the user

[1238] Specific operation: Candidate information is displayed on the device, and the user is asked to confirm and select the candidate they plan to vote for.

[1239] Step 6:

[1240] Information about the candidate selected by the user is sent to a server, and the social and economic impact of the selected candidate being elected is simulated.

[1241] Input: Candidate information selected by the user

[1242] Output: Simulation results

[1243] Specific operation: The server calculates the impact of winning based on past data and the current political situation and generates the results.

[1244] Step 7:

[1245] The simulation results are sent to the terminal and displayed visually to the user.

[1246] Input: Simulation results

[1247] Output: Displaying results in a user-friendly format

[1248] Specific operation: The simulation results are displayed on the terminal in a visually easy-to-understand format for the user to confirm.

[1249] Step 8:

[1250] After a user actually votes, their voting behavior is recorded, and if specified conditions are met, points or coupons are generated and distributed via an electronic payment service.

[1251] Input: Voting records, election results, incentive conditions

[1252] Output: Points or coupons

[1253] Specific operation: The server checks the user's voting behavior and determines whether the incentive conditions are met, then generates points or coupons and provides them to the user via an electronic payment service.

[1254] 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.

[1255] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1256] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1257] [Fourth embodiment]

[1258] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1259] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1260] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1261] 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.

[1262] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1263] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1264] 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.

[1265] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1266] 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.

[1267] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1268] 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.

[1269] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1270] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1271] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[1272] Collection of User Information

[1273] When users install and launch the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and inputs their interests, such as "welfare," "environment," and "education."

[1274] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[1275] Matching with candidates

[1276] The server searches for candidate information in the database based on the generated political belief profile. For example, if a search is performed for candidates who prioritize "welfare," Candidate A and Candidate B will be listed.

[1277] The search results are sent to the terminal, which displays the candidate information to the user. The user checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[1278] Simulation of voting results

[1279] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A's election.

[1280] For example, the simulation results predict that if Candidate A is elected, "the welfare budget will increase by 10% and support for the elderly will be strengthened." The server sends this simulation result to the terminal, which then visually displays the result to the user, allowing the user to understand the effects if the selected candidate is elected.

[1281] Incentive distribution

[1282] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[1283] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[1284] This process helps users find candidates who align with their political beliefs, understand the social and economic impact of their voting behavior, and provides incentives to actually vote.

[1285] Specific examples

[1286] For example, if User A uses the system and responds that he or she is interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. User A selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[1287] On election day, if User A actually votes for Candidate C, and Candidate C meets certain criteria and wins, the server will award points to User A, and the device will notify the user. User A can exchange those points for coupons before the next election.

[1288] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections.

[1289] The processing flow will be explained below.

[1290] Step 1:

[1291] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[1292] Step 2:

[1293] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[1294] Step 3:

[1295] Terminal: Sends the user's answer information to the server.

[1296] Step 4:

[1297] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[1298] Step 5:

[1299] Server: Based on the generated political belief profile, search for candidate information in the database. Search for candidates who prioritize "welfare" and list Candidate A and Candidate B.

[1300] Step 6:

[1301] Server: Sends candidate information listed as search results to the terminal.

[1302] Step 7:

[1303] Terminal: Displays candidate information to the user.

[1304] Step 8:

[1305] User: Check the displayed candidate information and select the candidate for whom they plan to vote (e.g., Candidate A).

[1306] Step 9:

[1307] Terminal: Sends the user's selection information to the server.

[1308] Step 10:

[1309] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[1310] Step 11:

[1311] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[1312] Step 12:

[1313] Terminal: Visually displays the simulation results to users, allowing them to understand the impact of their chosen candidate if they were elected.

[1314] Step 13:

[1315] Server: Records users' voting behavior.

[1316] Step 14:

[1317] User: On election day, go to the polling station and vote for the candidate of your choice.

[1318] Step 15:

[1319] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[1320] Step 16:

[1321] Server: Sends generated points and coupon information to the terminal.

[1322] Step 17:

[1323] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[1324] Example 1

[1325] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1326] Many voters today find it difficult to find candidates who align with their political beliefs. Furthermore, they are often hesitant to vote due to limited means of predicting the impact that election results will have on society and the economy. Furthermore, there is a lack of effective means to encourage voting, resulting in low interest in and participation in elections.

[1327] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1328] In this invention, the server includes means for collecting information on a user's political beliefs, means for analyzing the collected information to generate a user's political belief profile, means for searching for and matching candidates based on the generated profile, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact of the selected candidate being elected, means for visually displaying the results of the simulation to the user, and means for recording the voting behavior and issuing points or coupons under certain conditions. This allows users to easily find candidates that match their political beliefs, makes it easier for them to understand the social and economic impact of election results, and encourages actual voting behavior through incentives.

[1329] "Information regarding the user's political beliefs" refers to information that indicates the user's political interests, values, policy priorities, etc.

[1330] A "political profile" is data that represents a user's political leanings and areas of interest, generated based on information about their political beliefs provided by the user.

[1331] "Candidate" means a person or entity running for public office in a particular election.

[1332] "Matching" refers to the act of selecting and providing candidates who are likely to be supported by the user based on the collected information and the generated profile.

[1333] Selecting a "candidate to vote for" is the act of the user selecting the candidate for whom they actually want to vote from among the candidates provided.

[1334] "Simulating" refers to the act of virtually predicting the expected social and economic impact if a selected candidate is elected, using past data, statistical information, and algorithms.

[1335] "Issuing points or coupons" refers to the act of generating and granting benefits or rewards to users in order to encourage their active participation and behavior.

[1336] The present invention relates to a system for matching candidates based on a user's political beliefs and encouraging voting behavior. Specific embodiments of the system are described below.

[1337] Collection of User Information

[1338] When a user installs and launches the application, the device displays a questionnaire about their political beliefs. For example, the device displays a question such as, "What policy area are you most interested in?" The user answers the questionnaire and enters their interests, such as "welfare," "environment," or "education." Once this information is entered, the device sends it to a server.

[1339] Generating a political belief profile

[1340] The server analyzes the information it receives and generates a political profile of the user using Python data analysis libraries (e.g., Pandas) and other statistical analysis methods. The profile includes the user's political interests and is stored in a central database. Based on the profile, the server then creates a list of candidates the user is likely to support.

[1341] Matching with candidates

[1342] The server searches for candidate information in a database based on the generated political belief profile. For example, a search for candidates who prioritize "welfare" results in a list of Candidate A and Candidate B. A database management system such as a NoSQL database (e.g., MongoDB) is used for the search. The search results are sent to the device, which displays the candidate information to the user. The user reviews the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A).

[1343] Simulation of voting results

[1344] When the user selects Candidate A, the device sends that information back to the server. The server then uses past voting data and the current political situation to simulate the social and economic impacts of Candidate A being elected. A generative AI model (e.g., a TensorFlow-based predictive model) is used for the simulation. For example, the simulation results in a prediction that "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends the results of this simulation to the device, which then visually displays the results to the user. This allows the user to understand the impact that the selected candidate would have if elected.

[1345] Incentive distribution

[1346] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes received after the election exceeds a certain threshold, points are awarded. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[1347] Specific examples

[1348] For example, if a newly registered user uses the system and responds that they are interested in the "environment," the server will list Candidate C, who is focusing on environmental policies. The user selects Candidate C and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if the user actually votes for Candidate C, and Candidate C meets certain criteria and is elected, the server will award the user points and the device will notify them of this. The user can exchange those points for coupons before the next election.

[1349] Example prompts for generative AI models

[1350] "Please explain in natural language the process of a system that lists appropriate candidates, simulates voting results, and awards incentives based on the user's political beliefs."

[1351] This is a specific embodiment of the present invention. This system makes it easier for users to find candidates who align with their political beliefs and understand the social and economic impacts of their election. It is also expected that incentives will encourage users to vote.

[1352] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1353] Step 1:

[1354] Collection of User Information

[1355] Input: A user installs and launches an application.

[1356] What it does: The device prompts the user with a survey about their political beliefs, such as the question, "What policy area do you care about most?"

[1357] Output: The user's answer (e.g., "welfare," "environment," "education," etc.) is obtained.

[1358] How it works: The user answers the survey, and the information they enter is encrypted in JSON format and sent to the server using the HTTPS protocol.

[1359] Step 2:

[1360] Generating a political belief profile

[1361] Input: User survey response data.

[1362] How it works: The server analyzes the received data using a Python data analysis library (e.g., Pandas).

[1363] Output: A political profile of the user is generated.

[1364] How it works: The server uses the analyzed data to create a profile of the user's political interests and stores this profile in a central database.

[1365] Step 3:

[1366] Candidate search and matching

[1367] Input: Generated political belief profiles.

[1368] How it works: The server searches for candidate information in a NoSQL database (e.g., MongoDB) based on the user's political profile.

[1369] Output: A list of candidates (e.g., Candidate A, Candidate B) that match the user's political beliefs.

[1370] Specific operation: The server uses a matching algorithm to list candidates that match the profile and sends the results to the terminal.

[1371] Step 4:

[1372] View and select candidate information

[1373] Input: A list of candidates.

[1374] How it works: The device displays information about the candidate to the user, including the candidate's policies and past performance.

[1375] Output: The candidate the user has selected to vote for (e.g., Candidate A).

[1376] Specific operation: Based on the displayed information, the user selects the candidate they plan to vote for, and the selection information is sent from the device to the server.

[1377] Step 5:

[1378] Simulation of voting results

[1379] Input: Candidate information selected by the user.

[1380] How it works: The server uses historical voting data and the current political situation to simulate the social and economic impact of a candidate's election. Generative AI models (e.g., TensorFlow-based predictive models) are used.

[1381] Output: Simulation results (e.g., "The welfare budget will increase by 10% and support for the elderly will be strengthened") are obtained.

[1382] Specific operation: The server performs a simulation using the AI ​​model and sends the results in JSON format to the device, which then visually displays the results to the user.

[1383] Step 6:

[1384] Recording voting behavior and distributing incentives

[1385] Input: User voting behavior and its records.

[1386] How it works: The server records the user's voting behavior and issues points or coupons if certain conditions are met (e.g., candidate A meets certain criteria and wins).

[1387] Output: Notification of points and coupons to the user.

[1388] Specific operation: The server generates points and coupons and sends the information to the terminal. The terminal notifies the user, for example, "You can exchange these points for coupons before the next election."

[1389] These are the specific processing steps of this system. At each step, the information entered by the user is processed appropriately, and the results are returned to the user.

[1390] (Application example 1)

[1391] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1392] Currently, many brick-and-mortar stores lack the means to improve customer experience, as they do not adequately provide personalized services based on customer interests and purchase history. As a result, customer satisfaction and repeat business rates are low, and sales growth cannot be expected. In addition, there are insufficient means to collect post-purchase feedback and reflect it in product strategies, making efficient marketing and inventory management difficult. There is a need to solve these issues.

[1393] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1394] In this invention, the server includes means for collecting information on user interests, means for matching products based on the collected information, means for selecting products to be purchased based on the matched products, means for simulating the social and economic impact of purchasing the selected products, and means for recording purchasing behavior and issuing points and coupons under certain conditions. This enables personalized product suggestions based on customer interests, and by simulating post-purchase results, it is possible to improve customer satisfaction and enable efficient marketing and inventory management.

[1395] "User" means an individual who utilizes the System to enter interest and purchasing information.

[1396] "Interests" refers to the product categories or service areas in which a user is interested.

[1397] "Means of collecting information" refers to the methods and devices used to input user input such as interests and purchase history into the system.

[1398] "Product matching means" refers to a method for selecting and suggesting suitable products from a database based on collected user interests.

[1399] "Method for selecting products to be purchased" refers to the method used by a user to select the products to actually purchase from the suggested products.

[1400] "Means for simulating social and economic impacts" refers to methods for predicting future changes in social and economic conditions if the selected product is purchased.

[1401] "Means for recording purchasing behavior" refers to a method for recording actual purchasing behavior performed by a user in the system.

[1402] "Means of issuing points or coupons" refers to a method for providing points or coupons as an incentive when a user meets certain conditions.

[1403] "Incentives" refer to rewards or benefits offered to encourage user behavior.

[1404] "Brick and mortar store" refers to a sales location that offers goods or services in an actual physical location.

[1405] "Personalization" refers to customizing products and services to suit the specific interests and needs of individual users.

[1406] "Marketing" refers to all activities involved in bringing products and services to market and selling them to consumers.

[1407] "Inventory management" refers to managing goods so that they are stocked at the right time and in the right quantities and distributed efficiently.

[1408] The present invention relates to a system that proposes products in a physical store based on a user's interests, simulates the impact after purchase, and provides incentives. Specific embodiments of the system are described below.

[1409] Collection of User Information

[1410] When a user installs and launches a smartphone app, the app displays a survey about the user's interests. For example, the question might be, "What product category are you most interested in?" The user answers the survey and enters their interests, such as "home appliances," "fashion," or "food." Once this information is entered, the app sends it to a server. The server analyzes the information it receives and generates a user interest profile. This profile includes the products and categories that interest the user.

[1411] Matching with products

[1412] The server searches for product information in the database based on the generated interest profile. For example, for a user who is primarily searching for "home appliances," products such as "smart refrigerators" and "smart washing machines" are listed. The search results are sent to a smartphone app, which displays the product information to the user. The user then checks the displayed product information and selects the product they wish to purchase (e.g., a smart refrigerator).

[1413] Purchase result simulation

[1414] Once the user selects a product, the app sends that information back to the server. The server then uses past purchase data and current market conditions to simulate the social and economic impact of purchasing the selected product. For example, the simulation may predict that purchasing a smart refrigerator will reduce electricity consumption by 10%, improving household energy efficiency. The server then sends the simulation results to the app, which then visually displays the results to the user. This allows the user to understand the impact of purchasing the selected product.

[1415] Incentive distribution

[1416] The server records the user's purchasing behavior and issues points or coupons when certain conditions are met. For example, if a user actually purchases a "smart refrigerator" in a store and then answers a satisfaction survey, points are awarded. The server then sends the generated points and coupon information to the app, which notifies the user. The app displays a message saying, "You can exchange these points for a coupon with your next purchase." This process makes it easier for users to find products that match their interests and understand the social and economic impact of their purchasing behavior. Incentives also encourage actual purchasing behavior.

[1417] Hardware and Software

[1418] The hardware used includes a smartphone and a server. The software used includes the programming language Python and the requests library for sending HTTP requests. Database management uses SQL or NoSQL databases. The simulation engine uses generative AI models.

[1419] Prompt Sentence Examples

[1420] The following prompt sentence is used as an example input to the simulation engine's generative AI model:

[1421] Answer that the user is interested in "home appliances," and suggest related products. Simulate the purchase results of the selected products and output the predicted results regarding reduction in power consumption and improvement in convenience.

[1422] In this way, a smart customer matching system can be built for brick-and-mortar stores. This system can suggest products that match the user's interests and simulate the results of their purchases, improving customer satisfaction and enabling efficient marketing.

[1423] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1424] Step 1:

[1425] A user installs and launches a smartphone app. The app displays a questionnaire about the user's interests, and the user answers it. The information entered is the user's main interests (e.g., "home appliances," "fashion," "food," etc.). This input data forms the basis for building the user's interest profile.

[1426] Step 2:

[1427] The device (smartphone) sends data about the user's interests to the server, which analyzes the data and creates an interest profile for the user. This profile includes categories that reflect the user's interests.

[1428] Step 3:

[1429] The server searches for matching product information from its database based on the generated interest profile. For example, if the user is interested in "home appliances," the server will list product information such as "smart refrigerators" and "smart washing machines." The searched product information is prioritized based on the user's interests.

[1430] Step 4:

[1431] The server sends the search results to the smartphone device, which receives this information and displays the matching product information to the user. The user can then check the displayed product information and select the products they wish to purchase.

[1432] Step 5:

[1433] When a user selects a product they wish to purchase, the device sends the selection back to the server. The server then starts a simulation of the purchase outcome based on the selected product information. The simulation takes into account past purchase data and market conditions to calculate the predicted social and economic impact of the purchase.

[1434] Step 6:

[1435] The server generates simulation results and sends them to the device. The device visually displays the simulation results to the user. For example, it displays a predicted result such as "If you purchase a smart refrigerator, your electricity consumption will decrease by 10%."

[1436] Step 7:

[1437] The server records the user's purchasing behavior. If the user actually purchases a product and then provides a survey or feedback, points or coupons are issued if certain conditions are met. This incentive is intended to encourage purchases.

[1438] Step 8:

[1439] The server sends the generated points and coupon information to the terminal, which notifies the user and displays a message such as "You can use these points for your next purchase." This notification allows the user to use the incentive for their next purchase.

[1440] These are the specific processing steps of this system. At each step, the roles of the user, device, and server are clearly separated, and the input, processing, and output of information are carried out continuously, enabling smart customer matching and incentive provision in physical stores.

[1441] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1442] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. In addition, by combining it with an emotion engine, it takes into account the user's emotional state, selects more appropriate candidates, and presents simulation results.

[1443] Collection of User Information

[1444] When users install and launch the application, the device displays a survey about their political beliefs, including the question, "What policy area are you most interested in?" Users answer the survey and input their interests, such as "welfare," "environment," and "education."

[1445] Once this information is entered, the device sends it to a server, which analyzes it and generates a political profile of the user, including their political interests.

[1446] Emotion recognition by emotion engine

[1447] The device collects the user's facial expressions, tone of voice, and input patterns when answering the questionnaire, and analyzes them using an emotion engine. For example, if the user expresses high interest or anxiety about a particular question, this emotional information is collected. The server then adds the results from the emotion engine to the user's profile to generate an overall political belief of the user.

[1448] Emotion-based candidate matching

[1449] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it searches for candidates who prioritize "welfare" and lists Candidate A and Candidate B.

[1450] The search results are sent to the device, which displays the candidate information to the user. The user then checks the displayed candidate information and selects the candidate they plan to vote for (e.g., Candidate A). This selection also takes into account the user's emotional information, making it easier for the user to find a candidate they are more comfortable with.

[1451] Simulation of voting results

[1452] When the user selects Candidate A, the device sends that information back to the server, which then uses past voting data and the current political situation to simulate the social and economic impacts of the selected Candidate A being elected.

[1453] For example, the simulation results predict that if Candidate A is elected, "welfare budgets will increase by 10% and support for the elderly will be strengthened." The server sends these simulation results to the device, which then visually displays the results to the user. The device also takes into account the user's emotional information and presents the results in a format that is easier to understand. This allows the user to understand the effects that would be expected if the candidate they selected were elected.

[1454] Incentive distribution

[1455] The server records the user's voting behavior and issues points or coupons when certain conditions are met. For example, if a user actually votes for "Candidate A" at the polling station and the number of votes for that candidate exceeds a certain threshold after the election, points will be awarded.

[1456] The server sends the generated points and coupon information to the terminal, and the terminal notifies the user, saying, "You can exchange these points for coupons before the next election."

[1457] Specific examples

[1458] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list Candidates D and E, who are focusing on environmental policies. User B selects Candidate E and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress."

[1459] On election day, if User B actually votes for Candidate E, and Candidate E meets certain criteria and wins, the server will award points to User B, and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[1460] The above is a specific embodiment of the present invention. It is expected that this system will increase voter engagement in politics and encourage active participation in elections. Furthermore, the introduction of an emotion engine will enable optimal candidate selection and information presentation that takes into account the user's emotions, improving the accuracy and satisfaction of voting behavior.

[1461] The processing flow will be explained below.

[1462] Step 1:

[1463] Device: Upon installation and launch of the application, the user is presented with a survey about their political beliefs, including the question, "What policy area do you care most about?"

[1464] Step 2:

[1465] User: Answers a questionnaire and enters his / her interests, such as "welfare," "environment," and "education."

[1466] Step 3:

[1467] Terminal: Sends the user's answer information to the server.

[1468] Step 4:

[1469] Server: Analyzes the received user information and generates a political profile of the user, including the user's political interests.

[1470] Step 5:

[1471] Device: Collects emotional data such as facial expressions, tone of voice, and input patterns when users answer surveys.

[1472] Step 6:

[1473] Terminal: Sends collected emotion data to the emotion engine and receives the analysis results.

[1474] Step 7:

[1475] Server: Adds emotional information to the user's political belief profile based on the analysis results from the emotion engine.

[1476] Step 8:

[1477] Server: Searches for candidate information in the database based on the generated political belief profile and emotional information. Searches for candidates who prioritize "welfare" and creates a list of candidates A and B.

[1478] Step 9:

[1479] Server: Sends candidate information listed as search results to the terminal.

[1480] Step 10:

[1481] Terminal: Displays candidate information to the user.

[1482] Step 11:

[1483] User: Check the displayed candidate information and select the candidate they plan to vote for (e.g., Candidate A) based on emotional information.

[1484] Step 12:

[1485] Terminal: Sends the user's selection information to the server.

[1486] Step 13:

[1487] Server: Based on past voting data and the current political situation, simulate the social and economic impact if the selected candidate A is elected.

[1488] Step 14:

[1489] Server: Generates simulation results and sends them to the terminal. For example, the result may be "The welfare budget will be increased by 10% and support for the elderly will be strengthened."

[1490] Step 15:

[1491] Terminal: Visually displays the simulation results to the user, taking into account the user's emotional state and presenting them in an easy-to-understand format.

[1492] Step 16:

[1493] Server: Records users' voting behavior.

[1494] Step 17:

[1495] User: On election day, go to the polling station and vote for the candidate of your choice.

[1496] Step 18:

[1497] Server: After voting, if certain conditions are met, points or coupons are issued. For example, if a user votes for "Candidate A" and the number of votes exceeds a certain threshold.

[1498] Step 19:

[1499] Server: Sends generated points and coupon information to the terminal.

[1500] Step 20:

[1501] Terminal: Notify the user that points or coupons have been issued and display the message, "You can exchange these points for coupons before the next election."

[1502] Example 2

[1503] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1504] Conventional election systems have the problem that it is difficult for users to select the appropriate candidate based on their own political beliefs, and the selection process does not take emotions into consideration. Furthermore, there is a lack of mechanisms to predict the social and economic impact if the candidate selected by the user is elected, and the lack of effective incentives to encourage users to vote is also an issue.

[1505] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1506] In this invention, the server includes: means for collecting information on a user's political beliefs; means for generating a user profile based on the collected information; means for adding emotional information to the profile, which includes an emotion engine for detecting the user's emotional state; means for matching candidates based on the profile and emotional information; means for selecting a candidate to vote for based on the matched candidates; means for simulating the social and economic impact if the selected candidate is elected; and means for recording the voting behavior and issuing points or coupons under certain conditions. This makes it possible to select the optimal candidate taking into account the user's political beliefs and emotional information, and also makes it possible to effectively provide incentives to encourage voting behavior.

[1507] "User information" is data about a user's political beliefs or emotional state.

[1508] A "profile" is a data set generated from collected user information that indicates a user's political interests and attributes.

[1509] An "emotion engine" is an algorithm and system for detecting and analyzing a user's emotional state based on their facial expressions, tone of voice, input patterns, etc.

[1510] "Candidate matching" is the process of identifying suitable candidates among election candidates based on the user's profile and sentiment information.

[1511] "Selecting a candidate to vote for" is the process by which a user ultimately decides which candidate to vote for from among the matched candidates.

[1512] A "simulation" is a computational and modeling tool used to predict the social and economic impacts of a selected candidate being elected.

[1513] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[1514] This invention relates to a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also combines an emotion engine to consider the user's emotional state, allowing for more appropriate candidate selection and simulation results. A specific embodiment of this system is described below.

[1515] Collection of User Information

[1516] 1. The device displays a survey about political beliefs to users who have the application installed. The survey includes the question, "What policy area do you care most about?"

[1517] Specific operation: The user enters a policy area of ​​interest, such as "environment" or "welfare."

[1518] 2. The device sends the entered information to the server using the REST API.

[1519] 3. The server analyzes the received information and generates a profile of the user's political beliefs, using an analysis algorithm to categorize responses into profiles such as "environmental" or "welfare."

[1520] Emotion recognition by emotion engine

[1521] 1. The device collects the user's facial expressions, tone of voice, input patterns, etc. when answering the survey. Data is collected using a camera and microphone.

[1522] 2. The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the "environment" question, it adds that emotional information to their profile.

[1523] 3. The server updates the user's overall political beliefs based on the analysis results from the emotion engine.

[1524] Candidate Matching

[1525] 1. The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[1526] 2. The search results are sent to the device, which then displays candidate information to the user, including their profile and policy details.

[1527] 3. The user reviews the displayed candidate information and selects the candidate they plan to vote for. This selection process also takes into account emotional information.

[1528] Simulation of voting results

[1529] 1. When the user selects a candidate, the information is sent to the server, which then uses the REST API to send it again.

[1530] 2. The server uses past voting data and the current political situation to simulate the social and economic impact of the selected candidate's election. The simulation is carried out using big data analysis tools.

[1531] 3. The simulation results are sent to the device, which then displays the results visually to the user, using graphs and charts.

[1532] Incentive distribution

[1533] 1. The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[1534] 2. The server sends the generated points and coupon information to the terminal, and the terminal notifies the user. A notification is displayed saying, "You can exchange these points for coupons before the next election."

[1535] Specific examples

[1536] For example, if User B uses the system and responds that he or she is interested in the "environment," and the emotion engine determines that this interest is high, the server will list candidates who are focusing on environmental policies. User B selects a candidate and confirms the simulation result that "the environmental budget will increase by 15% and the introduction of renewable energy will progress." On election day, if User B actually votes for that candidate and that candidate is elected, the server will award User B points and the device will notify User B of this. User B can exchange those points for coupons before the next election.

[1537] Example prompts to input to the generative AI model

[1538] "We want to design a system that suggests the best candidates based on the user's political beliefs and emotional information. If the user expresses a high interest in environmental policy, please explain which candidate would be best to recommend and why."

[1539] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1540] Step 1: Collect user information

[1541] The device will display a survey about political beliefs to users who have the app installed, including the question, "What policy area do you care most about?"

[1542] - Input: User-entered answers regarding political beliefs (e.g., environment, welfare, education)

[1543] - Output: Collected user political belief data

[1544] - Specific behavior: A survey-style interface is displayed, the user enters their answers, and clicks the submit button.

[1545] Step 2: Submit user information

[1546] The device sends the collected user information to the server, which uses a REST API to send the data.

[1547] - Input: User's political beliefs data

[1548] - Output: User information stored on the server

[1549] - Specific operation: The entered data is sent to the server via API and saved in the database.

[1550] Step 3: Generate a profile

[1551] The server analyzes the received user information, generates a profile of the user's political beliefs, and uses an analysis algorithm to categorize the responses.

[1552] - Input: User's political beliefs data

[1553] - Output: User's political belief profile

[1554] - Specific operation: A data analysis algorithm analyzes the responses and classifies them into profiles such as "environment-oriented" or "welfare-oriented."

[1555] Step 4: Collecting emotion data

[1556] The device collects data such as the user's facial expressions, tone of voice, and input patterns when answering the survey. Data is collected using a camera and microphone.

[1557] - Input: User's facial expressions, tone of voice, input patterns

[1558] - Output: Data representing emotional state

[1559] - Specific operation: The camera and microphone will operate and record the user's facial expressions and voice in real time.

[1560] Step 5: Analyze the sentiment data

[1561] The emotion engine analyzes the collected data and evaluates the user's emotional state. For example, if a user expresses high interest in the question "environment," it adds that emotional information to their profile.

[1562] - Input: User's facial expressions, tone of voice, input patterns

[1563] - Output: Political belief profile with sentiment information

[1564] - What happens: The sentiment analysis algorithm processes the data and generates a sentiment rating, which is added to your profile.

[1565] Step 6: Matching candidate information

[1566] The server searches for candidate information in the database based on the generated political belief profile and emotional information. For example, it recommends candidates who prioritize the environment.

[1567] - Input: Political belief profile with emotional information

[1568] - Output: Matched candidate list

[1569] - What it does: The database search algorithm will produce a list of candidates who best fit your profile.

[1570] Step 7: View candidate information

[1571] The server sends the search results to the device, which then displays candidate information to the user, including their profile and policy details.

[1572] - Input: Matched candidate list

[1573] - Output: Candidate information displayed to the user

[1574] - Specific behavior: Candidate information is visually displayed in the interface for user confirmation.

[1575] Step 8: Choose the candidate you plan to vote for

[1576] Users review the displayed candidate information and select the candidate they plan to vote for, a selection process that also takes into account emotional information.

[1577] - Input: Displayed candidate information

[1578] - Output: Candidates selected by the user

[1579] - Specific action: The user selects a candidate and clicks the "Next" button.

[1580] Step 9: Simulate the voting results

[1581] The server then receives information about the candidate selected by the user and, based on past voting data and the current political situation, simulates the social and economic impact of the selected candidate being elected.

[1582] - Input: Candidate selected by the user

[1583] - Output: Simulation results

[1584] - Specific actions: Big data analysis tools run simulations and generate results, such as "welfare budgets will increase by 10% and support for the elderly will be strengthened."

[1585] Step 10: Viewing Simulation Results

[1586] The server sends the simulation results to the device, which then visually displays the results to the user using graphs and charts.

[1587] - Input: Simulation results

[1588] - Output: Simulation results displayed to the user

[1589] - Specific operation: Simulation results are visually displayed in the interface for user confirmation.

[1590] Step 11: Record and issue incentives

[1591] The server records the user's voting behavior and issues points or coupons when certain conditions are met, such as when the user actually votes for the candidate of their choice at the polling station and the number of votes exceeds a certain threshold.

[1592] - Input: User voting behavior, election results

[1593] - Output: Points or coupons

[1594] - Specific behavior: Voting behavior is logged, and if the conditions are met, points are calculated and awarded.

[1595] Step 12: Incentive Notification

[1596] The server transmits the generated points and coupon information to the terminal, which then notifies the user of the same.

[1597] - Input: Points or coupon information

[1598] - Output: Incentive notification distributed to users

[1599] - Specific operation: A notification will appear on the device saying, "You can exchange these points for coupons before the next election."

[1600] (Application example 2)

[1601] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1602] Conventional voting systems did not adequately match candidates based on users' political beliefs or promote voting behavior. Furthermore, it was difficult to select the optimal candidate and present information based on the user's emotional state, and the management and coordination of points and coupons given as incentives was insufficient. This resulted in low voter engagement and a decline in voter motivation to participate in elections.

[1603] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1604] In this invention, the server includes means for collecting information on the user's political beliefs, means for matching candidates based on the collected information and the user's emotional state, means for selecting a candidate to vote for based on the matched candidates, means for simulating the social and economic impact if the selected candidate is elected, and means for recording the voting behavior, issuing points or coupons under certain conditions, and linking with an electronic payment service. This enables the selection of the optimal candidate taking the user's emotional state into consideration, promotes voting behavior, and enables incentive management linked with an electronic payment service.

[1605] A "user" is someone who uses the system to provide information about their political beliefs, select candidates, and vote.

[1606] "Political beliefs" refers to information that refers to a user's political opinions, values, and interests.

[1607] "Emotional state" refers to the emotional response state recognized from the facial expressions, tone of voice, input patterns, etc. shown by the user when answering a questionnaire or using the system.

[1608] "Candidates" refers to people or organizations running for office, who are matched based on users' political beliefs.

[1609] "Matching" is the process of comparing the user's political beliefs and emotional state with the candidates' policies and positions to select the most suitable candidate.

[1610] "Selection" refers to the act of a user deciding which candidate they intend to vote for from among the matched candidates.

[1611] "Simulation" is the process of calculation and analysis that predicts the social and economic impacts if the selected candidate is elected.

[1612] "Voting behavior" refers to the entire act of a user actually voting for the selected candidate at a polling station.

[1613] "Incentives" are rewards such as points or coupons that are offered to encourage users to vote.

[1614] An "electronic payment service" is a payment system that uses the Internet and electronic devices, and supports the management and use of points and coupons.

[1615] This invention is a system that matches candidates based on the user's political beliefs and encourages voting behavior. It also uses emotion recognition technology to consider the user's emotional state, selecting more appropriate candidates and presenting simulation results. Furthermore, by linking with electronic payment services, it is possible to smoothly manage incentives according to voting behavior.

[1616] Specifically, users answer a questionnaire about their political beliefs through an application installed on their smartphone. Emotional data, such as the user's facial expressions, tone of voice, and input patterns, is collected while answering the questionnaire and analyzed by an emotion engine. The server generates a political belief profile for the user based on the collected information and emotional data, and compares it with candidate information in a database to match the most suitable candidate.

[1617] When a user checks the candidate information provided and selects the candidate they plan to vote for, the server simulates the social and economic impact if the selected candidate is elected. The simulation results are presented to the user in a visually easy-to-understand format. For example, if a user interested in the environment selects a candidate who is focusing on environmental policies, the server will display a forecast showing the increased adoption of renewable energy.

[1618] Furthermore, if a user actually votes and their actions meet certain conditions, points or coupons are issued in cooperation with an electronic payment service. This allows users to exchange their points for coupons before the next election. Incentive conditions can be set, for example, if the voter turnout for the election is above a certain level, or if the number of votes received by the candidate selected in the application is within a certain range.

[1619] Hardware: Smartphone

[1620] Software: Python, emotion recognition library (emotion_recognition), candidate matching algorithm (match_candidates)

[1621] An example prompt is:

[1622] "The system analyzes the emotions expressed when users answer surveys and matches them with the most suitable candidates based on their political beliefs. It visually displays the simulation results of what would happen if the candidate were elected, and awards incentives (points or coupons) based on voting behavior."

[1623] This system makes it possible to select the most appropriate candidate taking into account the user's emotional state, encouraging voting behavior and facilitating incentive management in conjunction with electronic payment services.

[1624] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1625] Step 1:

[1626] The user launches an application installed on their smartphone and answers a questionnaire about their political beliefs.

[1627] Input: Survey response about user's political beliefs

[1628] Output: Response data

[1629] Specific operation: The user launches the application and enters their interests, such as "welfare" or "environment," in response to the questions that appear.

[1630] Step 2:

[1631] Emotional data such as facial expressions, tone of voice, and input patterns of users when answering surveys are collected.

[1632] Input: User facial expressions, tone of voice, and input patterns while answering the survey

[1633] Output: Emotion data

[1634] Specific operation: Using the device's camera and microphone, the user's facial expressions and tone of voice are captured and analyzed using an emotion engine.

[1635] Step 3:

[1636] The server receives the collected political belief information and emotional data and generates a political belief profile for the user.

[1637] Input: Survey response data, emotion data

[1638] Output: Political profile

[1639] What it does: The server analyzes the data it receives and creates a profile of the user that combines their political interests and emotional state.

[1640] Step 4:

[1641] The server matches the most suitable candidate based on the political belief profile with candidate information in the database.

[1642] Input: Political profile, candidate information in database

[1643] Output: A list of matched candidates

[1644] Specific operation: The server matches the user's profile with the policies of each candidate and identifies the most suitable candidate.

[1645] Step 5:

[1646] Information about matched candidates is sent to the terminal and displayed to the user.

[1647] Input: List of matched candidates

[1648] Output: Candidates selected by the user

[1649] Specific operation: Candidate information is displayed on the device, and the user is asked to confirm and select the candidate they plan to vote for.

[1650] Step 6:

[1651] Information about the candidate selected by the user is sent to a server, and the social and economic impact of the selected candidate being elected is simulated.

[1652] Input: Candidate information selected by the user

[1653] Output: Simulation results

[1654] Specific operation: The server calculates the impact of winning based on past data and the current political situation and generates the results.

[1655] Step 7:

[1656] The simulation results are sent to the terminal and displayed visually to the user.

[1657] Input: Simulation results

[1658] Output: Displaying results in a user-friendly format

[1659] Specific operation: The simulation results are displayed on the terminal in a visually easy-to-understand format for the user to confirm.

[1660] Step 8:

[1661] After a user actually votes, their voting behavior is recorded, and if specified conditions are met, points or coupons are generated and distributed via an electronic payment service.

[1662] Input: Voting records, election results, incentive conditions

[1663] Output: Points or coupons

[1664] Specific operation: The server checks the user's voting behavior and determines whether the incentive conditions are met, then generates points or coupons and provides them to the user via an electronic payment service.

[1665] 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.

[1666] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1667] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1668] 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.

[1669] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1670] 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.

[1671] 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).

[1672] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1673] 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."

[1674] 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.

[1675] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1676] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1677] 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.

[1678] 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.

[1679] 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.

[1680] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1681] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1682] 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.

[1683] 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.

[1684] 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.

[1685] 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.

[1686] The following is further disclosed regarding the above embodiment.

[1687] (Claim 1)

[1688] means of collecting information about users' political beliefs;

[1689] means for matching candidates based on the collected information;

[1690] means for selecting a candidate to vote for based on the matched candidates;

[1691] A means for simulating the social and economic impacts of the selected candidate being elected;

[1692] a means for recording the voting behavior and issuing points or coupons under certain conditions;

[1693] A system including:

[1694] (Claim 2)

[1695] Provide a means for users to confirm their political beliefs through dialogue and match them with candidates in their voting districts;

[1696] 10. The system of claim 1.

[1697] (Claim 3)

[1698] The incentive is provided with a means for setting conditions that the voter turnout for the election must be above a certain level and that the deviation from the number of votes received by the candidate selected in the app must be within a certain range.

[1699] 10. The system of claim 1.

[1700] (Claim 4)

[1701] It will provide a means to simulate future policy and economic trends based on users' voting behavior and political beliefs and present them to users.

[1702] 10. The system of claim 1.

[1703] (Claim 5)

[1704] Providing a means to offer points or coupons to users as a voting incentive and allow them to redeem them before the next election;

[1705] 10. The system of claim 1.

[1706] "Example 1"

[1707] (Claim 1)

[1708] means of collecting information about users' political beliefs;

[1709] means for analyzing the collected information to generate a political belief profile of the user;

[1710] means for searching and matching candidates based on the generated profiles;

[1711] means for selecting a candidate to vote for based on the matched candidates;

[1712] A means for simulating the social and economic impacts of the selected candidate being elected;

[1713] means for visually displaying the simulation results to a user;

[1714] a means for recording the voting behavior and issuing points or coupons under certain conditions;

[1715] A system including:

[1716] (Claim 2)

[1717] Provide a means for users to confirm their political beliefs through dialogue and match them with candidates in their voting districts;

[1718] 10. The system of claim 1.

[1719] (Claim 3)

[1720] The system is provided with a means for setting conditions for the incentive, such as a voter turnout for the election being above a certain level and a deviation from the number of votes received by the candidate selected in the application being within a certain range.

[1721] 10. The system of claim 1.

[1722] "Application Example 1"

[1723] (Claim 1)

[1724] means of collecting information about user interests;

[1725] means for matching products based on the collected information;

[1726] means for selecting a product to be purchased based on the matched products;

[1727] A means for simulating the social and economic impacts of the selected product being purchased;

[1728] A means for recording the purchase behavior and issuing points or coupons under certain conditions;

[1729] A system including:

[1730] (Claim 2)

[1731] Provide a means to confirm user interests through dialogue and match products in the user's shopping area;

[1732] 10. The system of claim 1.

[1733] (Claim 3)

[1734] The incentive is provided with a means for setting conditions that the implementation rate of the purchase be above a certain level and that the deviation from the sales number of the product selected in the app be within a certain range.

[1735] 10. The system of claim 1.

[1736] "Example 2: Combining Emotion Engines"

[1737] (Claim 1)

[1738] means of collecting information about users' political beliefs;

[1739] means for generating a user profile based on said collected information;

[1740] means for adding emotional information to said profile, said emotional engine comprising: an emotional engine for detecting an emotional state of a user;

[1741] means for matching candidates based on the profiles and emotional information;

[1742] means for selecting a candidate to vote for based on the matched candidates;

[1743] A means for simulating the social and economic impacts of the selected candidate being elected;

[1744] a means for recording the voting behavior and issuing points or coupons under certain conditions;

[1745] A system including:

[1746] (Claim 2)

[1747] 10. The system of claim 1, further comprising means for interacting with a user to ascertain political beliefs and match with candidates in the user's voting district.

[1748] (Claim 3)

[1749] The system of claim 1, further comprising means for setting conditions for the incentive such that the voter turnout for the election is above a certain level and that the deviation from the number of votes received by the candidate selected in the app is within a certain range.

[1750] "Application example 2 when combining emotion engines"

[1751] (Claim 1)

[1752] means of collecting information about users' political beliefs;

[1753] means for matching candidates based on the collected information and the user's emotional state;

[1754] means for selecting a candidate to vote for based on the matched candidates;

[1755] A means for simulating the social and economic impacts of the selected candidate being elected;

[1756] A means for recording the voting behavior, issuing points or coupons under certain conditions, and linking with an electronic payment service;

[1757] A system including:

[1758] (Claim 2)

[1759] means for recognizing a user's emotional state by analyzing their facial expressions, tone of voice, and input patterns;

[1760] 10. The system of claim 1.

[1761] (Claim 3)

[1762] The system is provided with a means for setting conditions for the incentive, such as a voter turnout for the election being above a certain level and a deviation from the number of votes received by the candidate selected in the application being within a certain range.

[1763] 10. The system of claim 1. [Explanation of symbols]

[1764] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means of collecting information about users' political beliefs; means for matching candidates based on the collected information; means for selecting a candidate to vote for based on the matched candidates; means for simulating the social and economic impacts of the selected candidate being elected; a means for recording the voting behavior and issuing points or coupons under certain conditions; A system including:

2. Provide a means for users to confirm their political beliefs through dialogue and match them with candidates in their voting districts; The system of claim 1 .

3. The incentive is provided with a means for setting conditions that the voter turnout for the election must be above a certain level and that the deviation from the number of votes received by the candidate selected in the app must be within a certain range. The system of claim 1 .

4. It will provide a means to simulate future policy and economic trends based on users' voting behavior and political beliefs and present them to users. The system of claim 1 .

5. Providing a means to offer points or coupons to users as a voting incentive and allow them to redeem them before the next election; The system of claim 1 .

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