System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input marital status, number of dependents, and mortgage use status; means for a server to send the information input by the user to the server; means for the server to analyze the user's status using a AI module; means for the server to obtain the most recent tax savings cases from a database of experts; means for the server to suggest optimal tax savings methods to the user; and means for the user to display the suggestions received from the server.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] Many self-employed individuals and high-income company employees today are unable to effectively utilize the wide range of tax-saving information available, making it difficult to find the tax-saving method that best suits them. This results in them paying more tax and reducing their take-home pay. Furthermore, traditional tax-saving advice is provided in a uniform format and does not address individual circumstances, resulting in a lack of personalized tax-saving suggestions. This invention aims to solve these problems and increase users' take-home pay by suggesting effective tax-saving methods. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: a means for a user to input information such as marital status, number of dependents, and mortgage usage status; a means for a terminal to transmit this information to a server; a means for the server to analyze the user's situation using an AI module; a means for the server to obtain the latest tax-saving examples from an expert database; a means for the server to suggest optimal tax-saving methods to the user; and a means for the terminal to display the suggestions received from the server to the user. Furthermore, by adding a means for sending additional questions generated by the AI ​​module to the user and then sending the answers back to the server for detailed analysis, it becomes possible to provide customized tax-saving suggestions based on the user's individual situation. This makes it easier for users to find tax-saving methods that suit them and achieve effective tax savings.

[0006] "Users" refer to self-employed individuals and high-income company employees who use this system to find tax-saving methods that suit their own circumstances.

[0007] "Terminal" refers to a device used by a user to input information and communicate with a server, including smartphones and computers.

[0008] "Server" refers to a central processing unit for receiving and analyzing information sent by a user and returning appropriate tax saving suggestions to the user.

[0009] "AI Module" refers to a software component that uses artificial intelligence technology to analyze the information it receives and generate personalized tax-saving suggestions for the User.

[0010] An "expert database" refers to a source of information that collects and stores the latest information and examples on tax savings, and includes databases built based on the knowledge and experience of experts.

[0011] "Tax saving methods" refer to specific means and procedures for legally reducing taxes.

[0012] "Additional questions" refer to questions generated by the AI ​​module based on the user's initial information to request more detailed information from the user.

[0013] "Analysis" refers to the process by which the AI ​​module processes the information provided by the user and performs calculations and evaluations to identify appropriate tax-saving strategies.

[0014] "Proposal content" refers to the specific tax-saving measures and procedures that the server generates based on the analysis and provides to the user.

[0015] "Display" refers to the act of displaying the proposal content received by the terminal from the server on the screen in a format that is easy for the user to understand. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention is a system that proposes optimal tax-saving methods based on information input by a user, and an embodiment thereof will be described below.

[0038] System Overview

[0039] The system allows users to input their tax information and information related to life events, and the AI ​​module then suggests optimal tax-saving methods. The system is primarily comprised of three main components: the user, the terminal, and the server.

[0040] Collecting user input information

[0041] User

[0042] A user logs in to the system using a device such as a smartphone or computer.

[0043] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0044] Terminal

[0045] The terminal receives the user's input information and sends it to the server.

[0046] Analyzing user information and asking follow-up questions

[0047] server

[0048] The server receives the information sent by the user and activates the AI ​​module.

[0049] The AI ​​module analyzes the initial information and generates follow-up questions to gather more information if necessary.

[0050] Terminal

[0051] The terminal displays the additional question received from the server to the user.

[0052] User

[0053] The user answers the additional questions and sends them to the server via the terminal.

[0054] Detailed analysis and tax saving suggestions

[0055] server

[0056] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0057] The AI ​​module generates a list of optimal tax-saving strategies based on the user's individual circumstances.

[0058] The server accesses a database of experts to retrieve the latest tax saving cases.

[0059] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0060] Viewing Proposals

[0061] Terminal

[0062] The terminal displays the tax saving proposal received from the server to the user.

[0063] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[0064] Specific examples

[0065] 1. Enter your user information

[0066] User A logs into the system for the first time and provides the following information:

[0067] Marital status: Yes

[0068] Number of dependents: 2

[0069] Mortgage status: Currently in use

[0070] Annual income: 9 million yen

[0071] Other deductions (e.g., insurance enrollment status)

[0072] 2. Generate and answer follow-up questions

[0073] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0074] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0075] 3. Detailed analysis and generation of tax saving suggestions

[0076] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0077] Spousal deductions can save you 300,000 yen a year in taxes.

[0078] Dependent deductions allow for a deduction of 380,000 yen per year.

[0079] Home loan deduction of 400,000 yen per year.

[0080] Insurance premium deduction of 100,000 yen per year.

[0081] 4. Display of proposals

[0082] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[0083] In this way, the system provides users with customized tax-saving suggestions and offers them ways to increase their take-home pay, making it easier for them to find tax-saving methods that suit them and enabling them to achieve effective tax savings.

[0084] The processing flow will be explained below.

[0085] Step 1:

[0086] User

[0087] A user logs in to the system using a device such as a smartphone or computer.

[0088] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0089] Step 2:

[0090] Terminal

[0091] The terminal receives the user's input information and sends it to the server.

[0092] The terminal checks the communication status with the server, and if successful, proceeds to the next process.

[0093] Step 3:

[0094] server

[0095] The server prepares the received user information for analysis.

[0096] The server starts the AI ​​module and passes the user information to the AI.

[0097] The AI ​​module analyzes user information and generates follow-up questions as needed.

[0098] Step 4:

[0099] server

[0100] The server sends the generated follow-up question to the terminal.

[0101] Step 5:

[0102] Terminal

[0103] The terminal displays the additional question received from the server to the user.

[0104] Step 6:

[0105] User

[0106] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[0107] The user sends the answer to the server via the terminal.

[0108] Step 7:

[0109] Terminal

[0110] The terminal transmits the additional response received from the user to the server.

[0111] Step 8:

[0112] server

[0113] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0114] The AI ​​module performs detailed analysis and generates a list of tax-saving methods that are best suited to each user's individual situation.

[0115] Step 9:

[0116] server

[0117] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[0118] Step 10:

[0119] server

[0120] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0121] Step 11:

[0122] server

[0123] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[0124] Step 12:

[0125] Terminal

[0126] The terminal displays the received proposal to the user.

[0127] It provides detailed tax-saving methods and procedures in a user-friendly interface.

[0128] Step 13:

[0129] User

[0130] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[0131] Example 1

[0132] 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."

[0133] In today's tax environment, it is difficult for individuals to find the right tax-saving methods. With a wide variety of tax laws and deductions, expertise is required to find the best tax-saving methods for each individual situation. However, hiring a tax professional is costly and time-consuming. To solve this problem, a system is needed that automatically suggests the best tax-saving methods based on information that the user simply enters.

[0134] 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.

[0135] In this invention, the server includes means for analyzing the initial information received from the user, generating additional questions and sending them to the terminal, means for the terminal to receive the user's additional answers and send them to the server, and means for the server to perform detailed analysis using an AI module based on all the information received and propose customized tax saving methods based on the user's individual circumstances. This allows the user to find the optimal tax saving method based on the information they simply input.

[0136] A "user" is an individual who uses the system to provide input information and receive tax-saving suggestions.

[0137] A "terminal" is an electronic device, such as a smartphone or computer, that a user uses to input information and send and receive data to and from a server.

[0138] The "server" is a central processing unit that receives user input information, analyzes it, and uses an AI module to suggest optimal tax-saving methods.

[0139] The "AI module" is an artificial intelligence system that analyzes input data and suggests optimal tax-saving methods tailored to the user's individual circumstances.

[0140] The "database" is a collection of information that stores the latest tax saving cases from experts and user input information, and is accessed by the server as needed.

[0141] "Analysis" is the process in which the AI ​​module analyzes data based on user input and derives the optimal tax-saving method.

[0142] "Additional questions" are questions generated by the AI ​​module to gather additional information needed by the user to suggest the best tax-saving methods.

[0143] "Tax saving methods" are specific techniques and procedures for optimal tax savings that the AI ​​module suggests to users through analysis.

[0144] MODE FOR CARRYING OUT THE INVENTION

[0145] System Overview

[0146] This invention is a system in which users input their tax information and information related to life events, and an AI module then suggests optimal tax-saving methods based on that information. The system is primarily composed of three main components: the user, the terminal, and the server.

[0147] Collecting user input information

[0148] User

[0149] A user logs in to the system using a device such as a smartphone or computer, using an email address and password as login information.

[0150] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0151] Terminal

[0152] The device receives the user's input and sends it to the server, using a protocol (e.g., HTTPS) that transmits the data securely over the Internet.

[0153] Analyzing user information and asking follow-up questions

[0154] server

[0155] The server receives the information sent by the user and launches an AI module, which can use a machine learning framework implemented in Python (e.g., TensorFlow or PyTorch).

[0156] The server uses an AI module to analyze the initial information and generate follow-up questions to gather more detailed information.

[0157] Terminal

[0158] The terminal displays the follow-up questions received from the server to the user, for example, using an interface that displays form input or options.

[0159] User

[0160] The user answers the additional questions and sends them to the server via the terminal.

[0161] Detailed analysis and tax saving suggestions

[0162] server

[0163] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0164] The AI ​​module generates a list of optimal tax-saving methods based on the user's individual circumstances, including spouse deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[0165] The server accesses a database of experts to retrieve the latest tax savings tips, including information on the latest tax laws and deductions.

[0166] The server combines the analysis results of the AI ​​module with expert data to generate specific tax-saving proposals tailored to the user.

[0167] Viewing Proposals

[0168] Terminal

[0169] The terminal displays the tax saving proposal received from the server to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[0170] Specific examples

[0171] 1. Enter your user information

[0172] User A logs into the system for the first time and provides the following information:

[0173] Marital status: Yes

[0174] Number of dependents: 2

[0175] Mortgage status: Currently in use

[0176] Annual income: 9 million yen

[0177] Other deductions (e.g., insurance enrollment status)

[0178] 2. Generate and answer follow-up questions

[0179] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0180] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0181] 3. Detailed analysis and generation of tax saving suggestions

[0182] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0183] Spousal deductions can save you 300,000 yen a year in taxes.

[0184] Dependent deductions allow for a deduction of 380,000 yen per year.

[0185] Home loan deduction of 400,000 yen per year.

[0186] Insurance premium deduction of 100,000 yen per year.

[0187] 4. Display of proposals

[0188] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[0189] Example prompts for generative AI models

[0190] "The app suggests optimal tax-saving strategies based on the tax information and life events you enter. This includes information such as marital status, number of dependents, mortgage status, and annual income."

[0191] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0192] Step 1: User Login

[0193] User

[0194] A user accesses the system using a device such as a smartphone or computer and logs in by entering their email address and password.

[0195] Input: Email address, password

[0196] Output: Login request

[0197] Terminal

[0198] The terminal receives the user's login information and sends it to the server.

[0199] Input: Login request

[0200] Output: Login information (email address, password)

[0201] server

[0202] The server authenticates the received login information and, if authentication is successful, starts the user session.

[0203] Input: Login information (email address, password)

[0204] Output: Authentication result (success / failure), session start

[0205] Step 2: Enter initial information

[0206] User

[0207] After logging in, users enter initial information such as marital status, number of dependents, mortgage status, and annual income.

[0208] Input: Marital status, number of dependents, mortgage status, annual income

[0209] Output: Initial information

[0210] Terminal

[0211] The terminal receives the user's initial information and sends it to the server.

[0212] Input: Initial information

[0213] Output: Initial information (marriage status, number of dependents, mortgage status, annual income)

[0214] Step 3: Processing initial information

[0215] server

[0216] The server stores the received initial information in a database and launches an AI module to analyze the initial information.

[0217] Input: Initial information

[0218] Data processing and calculation: Saving to database, analysis by AI module

[0219] Output: Analysis results, additional questions if necessary

[0220] Step 4: Generate and present follow-up questions

[0221] server

[0222] Based on the initial information, the AI ​​module generates follow-up questions to gather more detailed information.

[0223] Input: Analysis results

[0224] Data processing and calculation: Generation of additional questions

[0225] Output: Additional questions

[0226] Terminal

[0227] The terminal displays the additional question received from the server to the user.

[0228] Input: Additional Question

[0229] Output: Show additional questions

[0230] User

[0231] The user answers the additional questions and sends them to the server via the terminal.

[0232] Input: Answer to additional question

[0233] Output: Additional answers

[0234] Terminal

[0235] The terminal receives the user's additional response and transmits it to the server.

[0236] Input: Additional Answer

[0237] Output: Additional answers

[0238] Step 5: Process additional information

[0239] server

[0240] The server stores the additional information it receives in a database and uses the AI ​​module again for further analysis.

[0241] Input: Additional Answer

[0242] Data processing and calculation: Saving to database, detailed analysis by AI module

[0243] Output: Detailed analysis results

[0244] Step 6: Generate tax savings

[0245] server

[0246] The AI ​​module analyzes each user's individual circumstances and generates a list of optimal tax-saving methods, including spousal deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[0247] The server accesses a database of experts to retrieve the latest tax-saving cases, and combines the analysis results of the AI ​​module with the expert data to generate specific tax-saving proposals tailored to the user.

[0248] Input: Detailed analysis results, expert data

[0249] Data processing and calculation: Creating a list of tax-saving methods, integrating data

[0250] Output: Tax Savings Suggestion

[0251] Step 7: Submit and view your proposal

[0252] server

[0253] The server generates tax saving suggestions and sends them to the terminal.

[0254] Input: Tax Savings Proposal

[0255] Output: Submit tax saving proposal

[0256] Terminal

[0257] The terminal displays the tax saving suggestions received to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[0258] Input: Tax Savings Proposal

[0259] Output: Display tax saving proposals

[0260] User

[0261] The user reviews the proposal and views specific steps and related information.

[0262] Input: Tax Savings Proposal

[0263] Output: User confirmation, viewing of proposals

[0264] (Application example 1)

[0265] 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."

[0266] Conventional tax-saving suggestion systems require users to spend a lot of time and effort to find the tax-saving method that best suits them. Furthermore, they lack the functionality to comprehensively analyze income and consumption history and suggest optimal tax-saving methods in real time, making it difficult for users to quickly obtain the latest tax-saving information. Furthermore, they lack immediate notifications about tax-saving opportunities and deadlines, which can lead to users missing important opportunities. This invention solves the above problems and provides a system that allows users to save on taxes more effectively.

[0267] 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.

[0268] In this invention, the server includes a means for inputting information including income data and consumption history, a means for analyzing the user's situation and proposing optimal tax-saving methods in real time, and a means for immediately notifying the user of tax-saving opportunities and deadlines. This allows the user to quickly obtain the latest tax-saving information that is appropriate for them. Furthermore, the server can collect necessary additional information and provide detailed tax-saving proposals via a user interface, helping the user to effectively achieve tax savings.

[0269] 1. "User" means a person who uses the system to receive tax saving suggestions.

[0270] 2. "Marital status" is information indicating whether the user is married or not.

[0271] 3. "Number of dependents" is information indicating the number of family members the user financially supports.

[0272] 4. "Mortgage usage status" is information indicating whether the user has taken out a loan to purchase a home.

[0273] 5. "Income Data" means information about a User's annual income or other income.

[0274] 6. "Consumption History" means a record of purchases made by a User through electronic payment.

[0275] 7. A "terminal" is a device, such as a smartphone or computer, that a user uses to input information.

[0276] 8. "Server" means a central computer that receives and analyzes information sent by users.

[0277] 9. "AI Module" means a software component that uses artificial intelligence to analyze the user's situation and generate optimal suggestions.

[0278] 10. The "Expert Database" is a data collection device that collects and manages the latest tax saving cases and legal information.

[0279] 11. A "tax saving method" is a specific means of reducing the amount of tax.

[0280] 12. "Real-time" is a term that indicates near-instant processing.

[0281] 13. "Tax Saving Opportunity" means an opportunity for a user to save on tax by taking a specific action or procedure.

[0282] 14. "Deadline" means the last date by which tax-related procedures must be carried out.

[0283] 15. "Notification" means the system notifying the user of new information or important deadlines.

[0284] 16. "Recommendations" refers to information generated by the AI ​​module regarding optimal tax saving methods.

[0285] 17. "User interface" means the system, including the screen and input devices, that allows a user to interact with a system.

[0286] 18. "Additional Information" is data requested from the user to obtain further details when the initial information is insufficient.

[0287] The embodiment of this invention is a system in which a user inputs various information, including income data and consumption history, and an AI module proposes optimal tax-saving methods in real time based on that data. This system consists of three main components: a user, a terminal, and a server.

[0288] Collecting user input information

[0289] Users log in to the system using a device such as a smartphone or computer. As an initial setup, the user enters information such as whether they have a spouse, the number of dependents, their mortgage loan status, their annual income, and their consumption history. This allows the system to obtain the user's basic tax information.

[0290] Data transmission and analysis

[0291] The device sends the information entered by the user to a cloud server. An AI module running on this cloud server analyzes the information entered by the user and prepares to propose optimal tax-saving methods. The AI ​​module used here uses a machine learning library such as TensorFlow. Based on the analyzed data, it generates follow-up questions to gather more detailed information.

[0292] Obtaining additional information and conducting detailed analysis

[0293] The server sends the generated follow-up questions to the terminal and displays them to the user. The user answers these questions, and the answer data is sent back to the server. The server then uses the AI ​​module again to perform a detailed analysis and propose the optimal tax-saving method based on the user's individual circumstances. The database used here is, for example, DynamoDB.

[0294] Stay informed and notified

[0295] The server retrieves the latest tax saving cases from a database of experts and combines them with the analysis results of the AI ​​module. Based on this integration result, the server immediately notifies users of tax saving opportunities and deadlines.

[0296] Displaying suggestions to users

[0297] The terminal displays the tax saving proposals received from the server to the user, providing detailed tax saving methods and procedures in an easy-to-understand format through a user-friendly interface.

[0298] Specific examples

[0299] For example, user A enters the following information: "annual income 9 million yen, married, two dependents, mortgage loan, annual insurance premium payment 100,000 yen." The AI ​​module then analyzes this information and generates a follow-up question: "What is the annual insurance premium payment?" If user A answers "100,000 yen," the AI ​​module analyzes again and generates the following proposal:

[0300] Spouse deduction: 300,000 yen tax savings

[0301] Dependent deduction: 380,000 yen deduction

[0302] Housing loan deduction: 400,000 yen deduction

[0303] Insurance premium deduction: 100,000 yen deduction

[0304] These suggestions are instantly sent to User A's smartphone, showing how to apply each deduction and the specific steps for the application process. In addition, the system also sends alerts about important tax-saving opportunities and deadlines for application.

[0305] Prompt Sentence Examples

[0306] Example prompt: "Please suggest the best tax-saving method based on the user's income and spending history."

[0307] In this way, the system helps users easily and quickly find the best tax saving method, enabling them to achieve effective tax savings.

[0308] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0309] Step 1:

[0310] Users log in to the system using a device such as a smartphone or computer and enter information such as marital status, number of dependents, mortgage status, annual income, consumption history, etc. At this time, the information entered by the user is collected through the device interface.

[0311] Step 2:

[0312] The device sends the information entered by the user to a cloud server. The input data includes marital status, number of dependents, mortgage status, annual income, consumption history, etc. The server stores the received data in a database.

[0313] Step 3:

[0314] The server launches an AI module to analyze the user's input. Specifically, it uses machine learning libraries such as TensorFlow to perform initial data analysis. The input here is the user data, and the output is the analysis results.

[0315] Step 4:

[0316] The server uses the analysis results to generate follow-up questions to gather more information. This process uses the user's initial data and the analysis results as inputs and generates follow-up questions as output.

[0317] Step 5:

[0318] The server generates additional questions and sends them to the terminal, which then displays them to the user. The displayed questions include, for example, "How much do you pay for insurance premiums per year?" The user answers the questions.

[0319] Step 6:

[0320] The user inputs the answers to the follow-up questions into the terminal, and the terminal sends the answer data to the server. The user's answers are stored as input data, and updated user information is stored as output data.

[0321] Step 7:

[0322] The server restarts the AI ​​module and re-analyzes all of the user's information. A detailed analysis is performed to determine the optimal tax-saving method. The input data is the updated user information, and the output data is the optimal tax-saving proposal.

[0323] Step 8:

[0324] The server accesses the expert database to obtain the latest tax saving examples. This ensures that the proposals are based on the latest information, improving reliability. The input data is the expert database, and the output data is the latest tax saving information.

[0325] Step 9:

[0326] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user. Here, an information integration algorithm is used to process the data and output the optimal tax-saving plan.

[0327] Step 10:

[0328] The server immediately notifies users of tax-saving opportunities and deadlines, and the terminal displays this information to them. Detailed tax-saving methods and procedures are provided to users through a user-friendly interface. Input data is the proposals from the server, and output data is the notification and display to the user.

[0329] Prompt Sentence Examples

[0330] "Please suggest the best tax saving method based on the user's income and consumption history."

[0331] These steps allow users to receive optimal tax saving suggestions in real time and achieve effective tax savings.

[0332] 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.

[0333] The present invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state, and an embodiment thereof will be described below.

[0334] System Overview

[0335] This system proposes optimal tax-saving methods based on the user's situation. Its main components are the user, device, server, emotion engine, and AI module. Information related to the user's life events is collected, and the AI ​​performs analysis based on that information. The emotion engine recognizes the user's emotions and adaptively changes the content of the proposals and the way they are displayed.

[0336] User input information collection and emotion recognition

[0337] User

[0338] A user logs in to the system using a device such as a smartphone or computer.

[0339] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0340] Terminal

[0341] The terminal receives the user's input information and activates an emotion engine to analyze the user's emotional state.

[0342] The terminal transmits the user's input information and emotional state to the server.

[0343] Analyzing user information and asking follow-up questions

[0344] server

[0345] The server prepares the received user information for analysis.

[0346] The server activates the AI ​​module and passes user information and emotional state to the AI.

[0347] The AI ​​module analyzes user information and generates follow-up questions as needed.

[0348] Terminal

[0349] The terminal displays the additional question received from the server to the user.

[0350] User

[0351] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[0352] The user sends the answer to the server via the terminal.

[0353] Detailed analysis and tax saving suggestions

[0354] server

[0355] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0356] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[0357] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[0358] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0359] The server formats the proposal and sends it to the device.

[0360] Adjusting recommendations with an emotion engine

[0361] Terminal

[0362] The device integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adaptively changes the way the suggestions are displayed (e.g., pop-up messages, color changes, etc.).

[0363] Viewing Proposals

[0364] Terminal

[0365] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[0366] Specific examples

[0367] 1. Inputting user information and emotions

[0368] User A logs into the system for the first time and provides the following information and emotional state:

[0369] Marital status: Yes

[0370] Number of dependents: 2

[0371] Mortgage status: Currently in use

[0372] Annual income: 9 million yen

[0373] Emotional state: Excitement

[0374] 2. Generate and answer follow-up questions

[0375] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0376] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0377] 3. Detailed analysis and generation of tax saving suggestions

[0378] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0379] Spousal deductions can save you 300,000 yen a year in taxes.

[0380] Dependent deductions allow for a deduction of 380,000 yen per year.

[0381] Home loan deduction of 400,000 yen per year.

[0382] Insurance premium deduction of 100,000 yen per year.

[0383] 4. Display of proposals

[0384] Based on the analysis results of the emotion engine, the device adjusts the way the suggestions are displayed and presents them in a way that is more familiar to user A (e.g., if the emotion is joy, an encouraging message is added).

[0385] As a result, this system provides personalized tax-saving suggestions that take into account the user's emotional state, enabling users to obtain tax-saving information in a more effective and easy-to-understand manner.

[0386] The processing flow will be explained below.

[0387] Step 1:

[0388] User

[0389] A user logs in to the system using a device such as a smartphone or computer.

[0390] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0391] Step 2:

[0392] Terminal

[0393] The device receives the user's input information and activates the emotion engine.

[0394] The device uses a camera and microphone to analyze the user's facial expressions and tone of voice to recognize their emotional state.

[0395] Step 3:

[0396] Terminal

[0397] The terminal transmits the user's input information and the recognized emotional state to the server.

[0398] Step 4:

[0399] server

[0400] The server prepares the received user information and emotional state for analysis.

[0401] The server activates the AI ​​module and passes user information and emotional state to the AI.

[0402] Step 5:

[0403] AI Module

[0404] The AI ​​module analyzes user information and generates follow-up questions as needed.

[0405] The server sends the generated follow-up question to the terminal.

[0406] Step 6:

[0407] Terminal

[0408] The terminal displays the additional question received from the server to the user.

[0409] Step 7:

[0410] User

[0411] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[0412] The user sends the answer to the server via the terminal.

[0413] Step 8:

[0414] Terminal

[0415] The terminal transmits the additional response received from the user to the server.

[0416] Step 9:

[0417] server

[0418] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0419] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[0420] Step 10:

[0421] server

[0422] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[0423] Step 11:

[0424] server

[0425] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0426] Step 12:

[0427] server

[0428] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[0429] Step 13:

[0430] Terminal

[0431] The device passes the tax saving suggestions received from the server to the emotion engine, which customizes how the tax saving suggestions are displayed based on the user's emotional state (e.g., adding an encouraging message if the user is feeling stressed).

[0432] Step 14:

[0433] Terminal

[0434] The terminal displays detailed tax saving methods and procedures in a user-friendly interface.

[0435] Step 15:

[0436] User

[0437] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[0438] Example 2

[0439] 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."

[0440] In today's world, many users find it difficult to obtain appropriate information on financial management and tax-saving methods and make optimal decisions. Providing uniform information without considering the user's emotional state can lead to stress and prevent appropriate decision-making. Furthermore, there is a need for timely, customized tax-saving proposals tailored to the user's specific circumstances.

[0441] 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.

[0442] In this invention, the server includes: means for a user to input information such as marital status, number of dependents, mortgage usage status, and annual income using a terminal; means for the terminal to transmit the information and emotional state input by the user to the server; means for the server to store the received user information and emotional state for analysis; means for the server to activate an AI module and use it to analyze the user information and emotional state; means for the server to generate necessary follow-up questions based on the analysis results and transmit them to the terminal; means for the terminal to display the received follow-up questions to the user; means for the terminal to transmit the user's follow-up answers to the server; means for the server to perform detailed analysis using the AI ​​module and obtain the latest tax saving examples and tax system information from an expert database; means for the server to generate specific tax saving suggestions optimal for the user and transmit them to the terminal; and means for the terminal to adjust the display method of the suggestions using an emotion engine and display them to the user. This makes it possible to provide personalized tax saving suggestions tailored to the user's specific situation and support the user in making appropriate decisions.

[0443] "User" refers to an individual who inputs and receives information into the system.

[0444] "Terminal" refers to a device that allows a user to input information and send and receive data to and from a server.

[0445] "Server" refers to the central system that processes information received from users and works with AI modules and databases to analyze and make recommendations.

[0446] "Emotional state" refers to information that indicates the user's current state of mind or mood.

[0447] "AI Module" refers to an artificial intelligence program used to analyze user information and emotional state and suggest tax-saving methods.

[0448] "Analysis" refers to the process of analyzing information collected from users using an AI module and obtaining the results.

[0449] "Tax saving methods" refer to specific means and measures to reduce the tax burden.

[0450] "Expert database" refers to an external database that collects and stores the latest tax saving cases and tax system information.

[0451] "Additional questions" refer to questions that the AI ​​module asks the user to gather new information during the analysis process.

[0452] "Format" refers to the format or style used to organize and present information or proposals in an easy-to-read manner.

[0453] An "emotion engine" refers to a program that recognizes a user's tone of voice and facial expressions to analyze their emotional state.

[0454] MODE FOR CARRYING OUT THE INVENTION

[0455] The present invention is a system for proposing optimal tax-saving methods based on information and emotional state input by a user. An embodiment of the system will be described in detail below.

[0456] System configuration

[0457] The main components of this system are a user, a terminal, a server, an emotion engine, and an AI module.

[0458] Collecting user input information

[0459] User

[0460] Users log in to the system using a device such as a smartphone or computer, and enter information such as marital status, number of dependents, mortgage status, and annual income as part of the initial setup.

[0461] The user's input information is sent to the terminal.

[0462] Terminal

[0463] The device activates an emotion engine that analyzes the user's tone of voice and facial expressions to determine their emotional state.

[0464] Data transmission and analysis

[0465] Terminal

[0466] The terminal transmits the information and emotional state received from the user to the server.

[0467] server

[0468] The server stores the received information in a temporary database and prepares it for analysis.

[0469] Activate the AI ​​module to analyze user information and emotional state.

[0470] Generate new questions for the user regarding the additional information needed.

[0471] Collecting additional information

[0472] Terminal

[0473] The terminal displays the follow-up questions received from the server to the user.

[0474] User

[0475] The user answers the additional questions and transmits the answers to the server via the terminal.

[0476] server

[0477] The server stores the additional information it receives in a database and then uses the AI ​​module again for further analysis.

[0478] Proposal of optimal tax saving methods

[0479] server

[0480] The server uses an AI module to generate a list of optimal tax saving methods for the user.

[0481] Access our expert database for the latest tax savings and tax information.

[0482] The AI ​​analysis results are combined with expert data to generate specific tax-saving suggestions for users.

[0483] The proposal is formatted appropriately and sent to the device.

[0484] Viewing Proposals

[0485] Terminal

[0486] It uses an emotion engine to tailor how suggestions are displayed, for example, if the user is "excited," it will display a pop-up with an encouraging message.

[0487] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[0488] Specific examples

[0489] 1. Inputting user information and emotions

[0490] User A logs into the system for the first time and provides the following information and emotional state:

[0491] Marital status: Yes

[0492] Number of dependents: 2

[0493] Mortgage status: Currently in use

[0494] Annual income: 9 million yen

[0495] Emotional state: Excitement

[0496] 2. Generate and answer follow-up questions

[0497] The server inputs this information into an AI module, which then generates follow-up questions such as, "How much do you pay in insurance premiums per year?"

[0498] User A responds, "Annual insurance premium payment: 100,000 yen," and the terminal sends this to the server.

[0499] 3. Detailed analysis and generation of tax saving suggestions

[0500] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0501] Spousal deductions can save you 300,000 yen a year in taxes.

[0502] Dependent deductions allow for a deduction of 380,000 yen per year.

[0503] Home loan deduction of 400,000 yen per year.

[0504] Insurance premium deduction of 100,000 yen per year.

[0505] 4. Display of proposals

[0506] Based on the analysis results of the emotion engine, the device adjusts how the suggestions are displayed. For example, if the emotion is joy, an encouraging message will be added.

[0507] An example prompt is:

[0508] "Describe the natural language processing process for a system that suggests optimal tax-saving strategies based on user information and emotional state."

[0509] "Please explain the process of the system that generates follow-up questions based on the user's situation and emotional state and performs detailed analysis."

[0510] As a result, this system makes personalized tax-saving suggestions that take into account the user's emotional state, allowing the user to obtain tax-saving information that is easy to understand and optimal for them.

[0511] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0512] Step 1:

[0513] A user logs in to the system using a smartphone or computer terminal. By entering their username and password as login information, authentication is performed and the user is able to access the system. Input: Username, password. Output: Authentication result.

[0514] Step 2:

[0515] The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. This records the user's basic financial situation in the system. Input: Marital status, number of dependents, mortgage status, annual income. Output: Saves the initial information.

[0516] Step 3:

[0517] The device passes the initial setting information received from the user to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to determine the user's emotional state. Input: Initial setting information. Output: Emotional state.

[0518] Step 4:

[0519] The device sends the initial setting information and emotional state to the server. The server stores the received information in a temporary database. Input: Initial setting information, emotional state. Output: Stored in the database.

[0520] Step 5:

[0521] The server passes the received information to the AI ​​module, which analyzes the user's information and emotional state. The AI ​​module determines whether additional information is needed based on the user's financial situation and emotional state. Input: Initial setting information, emotional state. Output: Generation of additional questions.

[0522] Step 6:

[0523] The terminal displays the follow-up question received from the server to the user. For example, a question such as "How much is the annual insurance premium payment?" is displayed to the user. Input: Follow-up question. Output: Display of follow-up question.

[0524] Step 7:

[0525] The user answers the additional questions displayed and sends the answers to the server via the terminal. For example, the user answers "Annual insurance premium payment: 100,000 yen." Input: Answer to additional question. Output: Send to server.

[0526] Step 8:

[0527] The server stores the received additional information in a database and uses the AI ​​module again for further analysis. The AI ​​module analyzes all the data and lists the optimal tax saving methods. Input: Additional information. Output: List of tax saving suggestions.

[0528] Step 9:

[0529] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information. The obtained information is integrated with the results of AI analysis to generate specific tax saving proposals. Input: Information from the expert database, AI analysis results. Output: Specific tax saving proposals.

[0530] Step 10:

[0531] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal. Input: Tax saving proposals. Output: Proposal content after formatting.

[0532] Step 11:

[0533] The device uses the emotion engine to adjust how the suggestion is displayed. For example, if the user is "excited," it will add an encouraging message and display a pop-up. Input: Formatted suggestion, emotional state. Output: Display of the adjusted suggestion.

[0534] Step 12:

[0535] The terminal provides the user with detailed tax-saving methods and procedures through a user-friendly interface. The user can take specific actions based on the suggestions presented. Input: Adjusted suggestions. Output: Presentation to the user.

[0536] (Application example 2)

[0537] 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."

[0538] It is generally difficult for users to properly understand their own tax situation and find the optimal tax-saving method. Furthermore, it has not been taken into consideration that users' emotional state can affect how they accept the proposed method. Furthermore, there has been no attempt to predict the tax-saving effect using user purchase data, making it a challenge to quickly and appropriately provide users with advantageous tax-saving methods.

[0539] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the terminal to recognize the emotional state of the user, a means for the terminal to adjust the display method of the proposal content received from the server according to the emotional state of the user and display it, and a means for the terminal to collect the user's purchase data and predict the tax saving effect. This makes it possible to provide the optimal tax saving method in a timely manner while taking the user's emotional state into consideration, and further to make specific tax saving proposals based on the user's purchase history.

[0540] A "user" is a person who uses the system and is the entity that inputs information about tax status and emotional state.

[0541] A "terminal" is an electronic device, such as a smartphone or computer, that allows users to input information and collect emotional and purchasing data.

[0542] "Emotional state" refers to the user's current psychological state, and analyzing this information is used to adjust how the user accepts the proposed content.

[0543] The "server" is a central management system that receives input information and emotional state from users, analyzes it using an AI module, and calculates and provides the optimal tax-saving method.

[0544] The "AI module" is a program with artificial intelligence functions that analyzes the user's input information and emotional state, and generates necessary follow-up questions and tax-saving suggestions.

[0545] The "expert database" is a database that stores the latest tax information and tax saving examples, from which the server can retrieve information.

[0546] "Tax saving methods" refer to specific means and methods for reducing the user's tax burden, including spousal deductions, dependent deductions, and mortgage deductions.

[0547] "Purchase data" is information about the products and services purchased by users, and analyzing this information can predict the tax savings effect.

[0548] "Tax Savings" refers to the tax reduction or other benefit that a user may obtain as a result of a proposed tax saving method.

[0549] This invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state. A specific embodiment of this system is described below. The main components are a user, a terminal, a server, an emotion engine, and an AI module.

[0550] User input information collection and emotion recognition

[0551] User

[0552] Users log in to the system using devices such as smartphones or computers.

[0553] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0554] When the user inputs this information through the terminal, the terminal activates an emotion engine to analyze the user's emotional state.

[0555] Terminal

[0556] The terminal transmits the user's input information and emotional state to the server.

[0557] The terminal also collects the user's purchasing data and transmits it to the server.

[0558] Analyzing user information and asking follow-up questions

[0559] server

[0560] The server prepares for analysis the information received from the user.

[0561] The AI ​​module performs further analysis based on user information and emotional state.

[0562] If necessary, the server generates and sends additional questions to the terminal.

[0563] Terminal

[0564] The terminal displays the follow-up questions received from the server to the user.

[0565] User

[0566] The user answers the additional questions and sends them to the server via the terminal.

[0567] Detailed analysis and tax saving suggestions

[0568] server

[0569] The server uses an AI module to perform detailed analysis and generate a list of tax-saving methods that are best suited to the user's situation.

[0570] The server also retrieves the latest tax savings tips and tax information from a database of experts.

[0571] The AI ​​analysis results are integrated with expert data to generate specific tax-saving proposals tailored to the user.

[0572] Adjusting recommendations with an emotion engine

[0573] Terminal

[0574] The terminal integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adjusts the way the suggestions are displayed according to the user's emotional state.

[0575] Displaying proposals and utilizing purchasing data

[0576] Terminal

[0577] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[0578] The terminal also displays predicted tax savings based on the user's purchasing data.

[0579] Specific examples

[0580] For example, suppose User A logs into the system for the first time and provides the following information and emotional state:

[0581] Marital status: Yes

[0582] Number of dependents: 2

[0583] Mortgage status: Currently in use

[0584] Annual income: 9 million yen

[0585] Emotional state: Excitement

[0586] The server inputs this information into the AI ​​module and generates a more detailed question (e.g., "Annual insurance premium payment amount"). When User A answers this additional question (e.g., "Annual insurance premium payment amount: 100,000 yen") and sends the information to the server, the server performs a detailed analysis and generates a tax saving proposal like the following:

[0587] Spousal deductions can save you 300,000 yen a year in taxes.

[0588] Dependent deductions allow for a deduction of 380,000 yen per year.

[0589] Home loan deduction of 400,000 yen per year.

[0590] Insurance premium deduction of 100,000 yen per year.

[0591] The suggestions are tailored based on the user's emotional state and presented to the user in a friendly way: for example, if the emotion is joyful, an encouraging message can be added.

[0592] Prompt Sentence Examples

[0593] "User ID: 12345 Marital status: Yes Number of dependents: 2 Annual income: 8 million yen Planned purchase: Home appliances (TV) Emotional state: Happy Analyze the optimal tax-saving method for this user and create a proposal."

[0594] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0595] Step 1:

[0596] The user logs into the system using a smartphone or computer. The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. The entered information is received by the terminal.

[0597] Input: User's initial information (married status, number of dependents, mortgage status, annual income)

[0598] Output: Initial information saved on the device

[0599] Specific operation: The user logs in and provides information using an interface for entering initial information.

[0600] Step 2:

[0601] The device sends the user's input information to the server. At the same time, the device's emotion engine is activated and analyzes the user's emotional state. The emotion engine uses the smartphone's camera and sensors to analyze the user's facial expressions and voice.

[0602] Input: User's initial information and camera video or audio data

[0603] Output: Initial information and emotion data sent to the server

[0604] Specific operation: The user's input information and video / audio data are sent from the terminal to the server.

[0605] Step 3:

[0606] The server prepares the received user information and emotional data for analysis. The server launches the AI ​​module and passes the user information and emotional state to the AI. The AI ​​module analyzes the user information and generates follow-up questions as needed.

[0607] Input: User's initial information and emotional data

[0608] Output: Additional Question List

[0609] Specific operation: The server uses an AI module to analyze user information and emotional data and generate additional questions.

[0610] Step 4:

[0611] The terminal displays the additional questions received from the server to the user, and the user answers the additional questions and transmits the answers to the server via the terminal.

[0612] Input: Additional Question List

[0613] Output: User response information

[0614] Specific operation: The terminal displays additional questions to the user, and the user enters additional information and sends it to the server.

[0615] Step 5:

[0616] Based on the additional information received, the server uses the AI ​​module again to perform a detailed analysis. The server retrieves the latest tax saving examples and tax system information from a database of experts and generates a list of tax saving methods that are optimal for the user.

[0617] Input: Additional information for the user

[0618] Output: A list of the best ways to save tax

[0619] Specific operation: The server accesses an expert database to obtain the latest tax saving information, and then analyzes the information using an AI module.

[0620] Step 6:

[0621] The device integrates the tax-saving proposals received from the server with the analysis results of the emotion engine, adjusts the way the proposals are displayed, and presents them to the user. The proposals are displayed in a friendly manner according to the user's emotional state.

[0622] Input: Tax saving proposal content and sentiment analysis results

[0623] Output: Tax saving suggestions with adjusted presentation

[0624] Specific operation: Based on the results of emotion analysis, the device appropriately adjusts the suggestions and displays them to the user.

[0625] Step 7:

[0626] The device collects the user's purchasing data and displays a predicted tax savings effect. The purchasing data is information about the products and services purchased by the user. The device sends this data to the server, and the AI ​​module predicts the tax savings effect.

[0627] Input: User's purchasing data

[0628] Output: Predicted tax savings

[0629] Specific operation: The terminal collects the user's purchasing history, and the server uses this information to predict tax savings and presents them to the user.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] [Second embodiment]

[0634] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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).

[0640] 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. 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] In the smart glasses 214, 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.

[0645] 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."

[0646] The present invention is a system that proposes optimal tax-saving methods based on information input by a user, and an embodiment thereof will be described below.

[0647] System Overview

[0648] The system allows users to input their tax information and information related to life events, and the AI ​​module then suggests optimal tax-saving methods. The system is primarily comprised of three main components: the user, the terminal, and the server.

[0649] Collecting user input information

[0650] User

[0651] A user logs in to the system using a device such as a smartphone or computer.

[0652] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0653] Terminal

[0654] The terminal receives the user's input information and sends it to the server.

[0655] Analyzing user information and asking follow-up questions

[0656] server

[0657] The server receives the information sent by the user and activates the AI ​​module.

[0658] The AI ​​module analyzes the initial information and generates follow-up questions to gather more information if necessary.

[0659] Terminal

[0660] The terminal displays the additional question received from the server to the user.

[0661] User

[0662] The user answers the additional questions and sends them to the server via the terminal.

[0663] Detailed analysis and tax saving suggestions

[0664] server

[0665] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0666] The AI ​​module generates a list of optimal tax-saving strategies based on the user's individual circumstances.

[0667] The server accesses a database of experts to retrieve the latest tax saving cases.

[0668] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0669] Viewing Proposals

[0670] Terminal

[0671] The terminal displays the tax saving proposal received from the server to the user.

[0672] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[0673] Specific examples

[0674] 1. Enter your user information

[0675] User A logs into the system for the first time and provides the following information:

[0676] Marital status: Yes

[0677] Number of dependents: 2

[0678] Mortgage status: Currently in use

[0679] Annual income: 9 million yen

[0680] Other deductions (e.g., insurance enrollment status)

[0681] 2. Generate and answer follow-up questions

[0682] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0683] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0684] 3. Detailed analysis and generation of tax saving suggestions

[0685] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0686] Spousal deductions can save you 300,000 yen a year in taxes.

[0687] Dependent deductions allow for a deduction of 380,000 yen per year.

[0688] Home loan deduction of 400,000 yen per year.

[0689] Insurance premium deduction of 100,000 yen per year.

[0690] 4. Display of proposals

[0691] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[0692] In this way, the system provides users with customized tax-saving suggestions and offers them ways to increase their take-home pay, making it easier for them to find tax-saving methods that suit them and enabling them to achieve effective tax savings.

[0693] The processing flow will be explained below.

[0694] Step 1:

[0695] User

[0696] A user logs in to the system using a device such as a smartphone or computer.

[0697] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0698] Step 2:

[0699] Terminal

[0700] The terminal receives the user's input information and sends it to the server.

[0701] The terminal checks the communication status with the server, and if successful, proceeds to the next process.

[0702] Step 3:

[0703] server

[0704] The server prepares the received user information for analysis.

[0705] The server starts the AI ​​module and passes the user information to the AI.

[0706] The AI ​​module analyzes user information and generates follow-up questions as needed.

[0707] Step 4:

[0708] server

[0709] The server sends the generated follow-up question to the terminal.

[0710] Step 5:

[0711] Terminal

[0712] The terminal displays the additional question received from the server to the user.

[0713] Step 6:

[0714] User

[0715] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[0716] The user sends the answer to the server via the terminal.

[0717] Step 7:

[0718] Terminal

[0719] The terminal transmits the additional response received from the user to the server.

[0720] Step 8:

[0721] server

[0722] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0723] The AI ​​module performs detailed analysis and generates a list of tax-saving methods that are best suited to each user's individual situation.

[0724] Step 9:

[0725] server

[0726] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[0727] Step 10:

[0728] server

[0729] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0730] Step 11:

[0731] server

[0732] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[0733] Step 12:

[0734] Terminal

[0735] The terminal displays the received proposal to the user.

[0736] It provides detailed tax-saving methods and procedures in a user-friendly interface.

[0737] Step 13:

[0738] User

[0739] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[0740] Example 1

[0741] 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."

[0742] In today's tax environment, it is difficult for individuals to find the right tax-saving methods. With a wide variety of tax laws and deductions, expertise is required to find the best tax-saving methods for each individual situation. However, hiring a tax professional is costly and time-consuming. To solve this problem, a system is needed that automatically suggests the best tax-saving methods based on information that the user simply enters.

[0743] 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.

[0744] In this invention, the server includes means for analyzing the initial information received from the user, generating additional questions and sending them to the terminal, means for the terminal to receive the user's additional answers and send them to the server, and means for the server to perform detailed analysis using an AI module based on all the information received and propose customized tax saving methods based on the user's individual circumstances. This allows the user to find the optimal tax saving method based on the information they simply input.

[0745] A "user" is an individual who uses the system to provide input information and receive tax-saving suggestions.

[0746] A "terminal" is an electronic device, such as a smartphone or computer, that a user uses to input information and send and receive data to and from a server.

[0747] The "server" is a central processing unit that receives user input information, analyzes it, and uses an AI module to suggest optimal tax-saving methods.

[0748] The "AI module" is an artificial intelligence system that analyzes input data and suggests optimal tax-saving methods tailored to the user's individual circumstances.

[0749] The "database" is a collection of information that stores the latest tax saving cases from experts and user input information, and is accessed by the server as needed.

[0750] "Analysis" is the process in which the AI ​​module analyzes data based on user input and derives the optimal tax-saving method.

[0751] "Additional questions" are questions generated by the AI ​​module to gather additional information needed by the user to suggest the best tax-saving methods.

[0752] "Tax saving methods" are specific techniques and procedures for optimal tax savings that the AI ​​module suggests to users through analysis.

[0753] MODE FOR CARRYING OUT THE INVENTION

[0754] System Overview

[0755] This invention is a system in which users input their tax information and information related to life events, and an AI module then suggests optimal tax-saving methods based on that information. The system is primarily composed of three main components: the user, the terminal, and the server.

[0756] Collecting user input information

[0757] User

[0758] A user logs in to the system using a device such as a smartphone or computer, using an email address and password as login information.

[0759] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0760] Terminal

[0761] The device receives the user's input and sends it to the server, using a protocol (e.g., HTTPS) that transmits the data securely over the Internet.

[0762] Analyzing user information and asking follow-up questions

[0763] server

[0764] The server receives the information sent by the user and launches an AI module, which can use a machine learning framework implemented in Python (e.g., TensorFlow or PyTorch).

[0765] The server uses an AI module to analyze the initial information and generate follow-up questions to gather more detailed information.

[0766] Terminal

[0767] The terminal displays the follow-up questions received from the server to the user, for example, using an interface that displays form input or options.

[0768] User

[0769] The user answers the additional questions and sends them to the server via the terminal.

[0770] Detailed analysis and tax saving suggestions

[0771] server

[0772] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0773] The AI ​​module generates a list of optimal tax-saving methods based on the user's individual circumstances, including spouse deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[0774] The server accesses a database of experts to retrieve the latest tax savings tips, including information on the latest tax laws and deductions.

[0775] The server combines the analysis results of the AI ​​module with expert data to generate specific tax-saving proposals tailored to the user.

[0776] Viewing Proposals

[0777] Terminal

[0778] The terminal displays the tax saving proposal received from the server to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[0779] Specific examples

[0780] 1. Enter your user information

[0781] User A logs into the system for the first time and provides the following information:

[0782] Marital status: Yes

[0783] Number of dependents: 2

[0784] Mortgage status: Currently in use

[0785] Annual income: 9 million yen

[0786] Other deductions (e.g., insurance enrollment status)

[0787] 2. Generate and answer follow-up questions

[0788] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0789] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0790] 3. Detailed analysis and generation of tax saving suggestions

[0791] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0792] Spousal deductions can save you 300,000 yen a year in taxes.

[0793] Dependent deductions allow for a deduction of 380,000 yen per year.

[0794] Home loan deduction of 400,000 yen per year.

[0795] Insurance premium deduction of 100,000 yen per year.

[0796] 4. Display of proposals

[0797] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[0798] Example prompts for generative AI models

[0799] "The app suggests optimal tax-saving strategies based on the tax information and life events you enter. This includes information such as marital status, number of dependents, mortgage status, and annual income."

[0800] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0801] Step 1: User Login

[0802] User

[0803] A user accesses the system using a device such as a smartphone or computer and logs in by entering their email address and password.

[0804] Input: Email address, password

[0805] Output: Login request

[0806] Terminal

[0807] The terminal receives the user's login information and sends it to the server.

[0808] Input: Login request

[0809] Output: Login information (email address, password)

[0810] server

[0811] The server authenticates the received login information and, if authentication is successful, starts the user session.

[0812] Input: Login information (email address, password)

[0813] Output: Authentication result (success / failure), session start

[0814] Step 2: Enter initial information

[0815] User

[0816] After logging in, users enter initial information such as marital status, number of dependents, mortgage status, and annual income.

[0817] Input: Marital status, number of dependents, mortgage status, annual income

[0818] Output: Initial information

[0819] Terminal

[0820] The terminal receives the user's initial information and sends it to the server.

[0821] Input: Initial information

[0822] Output: Initial information (marriage status, number of dependents, mortgage status, annual income)

[0823] Step 3: Processing initial information

[0824] server

[0825] The server stores the received initial information in a database and launches an AI module to analyze the initial information.

[0826] Input: Initial information

[0827] Data processing and calculation: Saving to database, analysis by AI module

[0828] Output: Analysis results, additional questions if necessary

[0829] Step 4: Generate and present follow-up questions

[0830] server

[0831] Based on the initial information, the AI ​​module generates follow-up questions to gather more detailed information.

[0832] Input: Analysis results

[0833] Data processing and calculation: Generation of additional questions

[0834] Output: Additional questions

[0835] Terminal

[0836] The terminal displays the additional question received from the server to the user.

[0837] Input: Additional Question

[0838] Output: Show additional questions

[0839] User

[0840] The user answers the additional questions and sends them to the server via the terminal.

[0841] Input: Answer to additional question

[0842] Output: Additional answers

[0843] Terminal

[0844] The terminal receives the user's additional response and transmits it to the server.

[0845] Input: Additional Answer

[0846] Output: Additional answers

[0847] Step 5: Process additional information

[0848] server

[0849] The server stores the additional information it receives in a database and uses the AI ​​module again for further analysis.

[0850] Input: Additional Answer

[0851] Data processing and calculation: Saving to database, detailed analysis by AI module

[0852] Output: Detailed analysis results

[0853] Step 6: Generate tax savings

[0854] server

[0855] The AI ​​module analyzes each user's individual circumstances and generates a list of optimal tax-saving methods, including spousal deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[0856] The server accesses a database of experts to retrieve the latest tax-saving cases, and combines the analysis results of the AI ​​module with the expert data to generate specific tax-saving proposals tailored to the user.

[0857] Input: Detailed analysis results, expert data

[0858] Data processing and calculation: Creating a list of tax-saving methods, integrating data

[0859] Output: Tax Savings Suggestion

[0860] Step 7: Submit and view your proposal

[0861] server

[0862] The server generates tax saving suggestions and sends them to the terminal.

[0863] Input: Tax Savings Proposal

[0864] Output: Submit tax saving proposal

[0865] Terminal

[0866] The terminal displays the tax saving suggestions received to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[0867] Input: Tax Savings Proposal

[0868] Output: Display tax saving proposals

[0869] User

[0870] The user reviews the proposal and views specific steps and related information.

[0871] Input: Tax Savings Proposal

[0872] Output: User confirmation, viewing of proposals

[0873] (Application example 1)

[0874] 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."

[0875] Conventional tax-saving suggestion systems require users to spend a lot of time and effort to find the tax-saving method that best suits them. Furthermore, they lack the functionality to comprehensively analyze income and consumption history and suggest optimal tax-saving methods in real time, making it difficult for users to quickly obtain the latest tax-saving information. Furthermore, they lack immediate notifications about tax-saving opportunities and deadlines, which can lead to users missing important opportunities. This invention solves the above problems and provides a system that allows users to save on taxes more effectively.

[0876] 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.

[0877] In this invention, the server includes a means for inputting information including income data and consumption history, a means for analyzing the user's situation and proposing optimal tax-saving methods in real time, and a means for immediately notifying the user of tax-saving opportunities and deadlines. This allows the user to quickly obtain the latest tax-saving information that is appropriate for them. Furthermore, the server can collect necessary additional information and provide detailed tax-saving proposals via a user interface, helping the user to effectively achieve tax savings.

[0878] 1. "User" means a person who uses the system to receive tax saving suggestions.

[0879] 2. "Marital status" is information indicating whether the user is married or not.

[0880] 3. "Number of dependents" is information indicating the number of family members the user financially supports.

[0881] 4. "Mortgage usage status" is information indicating whether the user has taken out a loan to purchase a home.

[0882] 5. "Income Data" means information about a User's annual income or other income.

[0883] 6. "Consumption History" means a record of purchases made by a User through electronic payment.

[0884] 7. A "terminal" is a device, such as a smartphone or computer, that a user uses to input information.

[0885] 8. "Server" means a central computer that receives and analyzes information sent by users.

[0886] 9. "AI Module" means a software component that uses artificial intelligence to analyze the user's situation and generate optimal suggestions.

[0887] 10. The "Expert Database" is a data collection device that collects and manages the latest tax saving cases and legal information.

[0888] 11. A "tax saving method" is a specific means of reducing the amount of tax.

[0889] 12. "Real-time" is a term that indicates near-instant processing.

[0890] 13. "Tax Saving Opportunity" means an opportunity for a user to save on tax by taking a specific action or procedure.

[0891] 14. "Deadline" means the last date by which tax-related procedures must be carried out.

[0892] 15. "Notification" means the system notifying the user of new information or important deadlines.

[0893] 16. "Recommendations" refers to information generated by the AI ​​module regarding optimal tax saving methods.

[0894] 17. "User interface" means the system, including the screen and input devices, that allows a user to interact with a system.

[0895] 18. "Additional Information" is data requested from the user to obtain further details when the initial information is insufficient.

[0896] The embodiment of this invention is a system in which a user inputs various information, including income data and consumption history, and an AI module proposes optimal tax-saving methods in real time based on that data. This system consists of three main components: a user, a terminal, and a server.

[0897] Collecting user input information

[0898] Users log in to the system using a device such as a smartphone or computer. As an initial setup, the user enters information such as whether they have a spouse, the number of dependents, their mortgage loan status, their annual income, and their consumption history. This allows the system to obtain the user's basic tax information.

[0899] Data transmission and analysis

[0900] The device sends the information entered by the user to a cloud server. An AI module running on this cloud server analyzes the information entered by the user and prepares to propose optimal tax-saving methods. The AI ​​module used here uses a machine learning library such as TensorFlow. Based on the analyzed data, it generates follow-up questions to gather more detailed information.

[0901] Obtaining additional information and conducting detailed analysis

[0902] The server sends the generated follow-up questions to the terminal and displays them to the user. The user answers these questions, and the answer data is sent back to the server. The server then uses the AI ​​module again to perform a detailed analysis and propose the optimal tax-saving method based on the user's individual circumstances. The database used here is, for example, DynamoDB.

[0903] Stay informed and notified

[0904] The server retrieves the latest tax saving cases from a database of experts and combines them with the analysis results of the AI ​​module. Based on this integration result, the server immediately notifies users of tax saving opportunities and deadlines.

[0905] Displaying suggestions to users

[0906] The terminal displays the tax saving proposals received from the server to the user, providing detailed tax saving methods and procedures in an easy-to-understand format through a user-friendly interface.

[0907] Specific examples

[0908] For example, user A enters the following information: "annual income 9 million yen, married, two dependents, mortgage loan, annual insurance premium payment 100,000 yen." The AI ​​module then analyzes this information and generates a follow-up question: "What is the annual insurance premium payment?" If user A answers "100,000 yen," the AI ​​module analyzes again and generates the following proposal:

[0909] Spouse deduction: 300,000 yen tax savings

[0910] Dependent deduction: 380,000 yen deduction

[0911] Housing loan deduction: 400,000 yen deduction

[0912] Insurance premium deduction: 100,000 yen deduction

[0913] These suggestions are instantly sent to User A's smartphone, showing how to apply each deduction and the specific steps for the application process. In addition, the system also sends alerts about important tax-saving opportunities and deadlines for application.

[0914] Prompt Sentence Examples

[0915] Example prompt: "Please suggest the best tax-saving method based on the user's income and spending history."

[0916] In this way, the system helps users easily and quickly find the best tax saving method, enabling them to achieve effective tax savings.

[0917] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0918] Step 1:

[0919] Users log in to the system using a device such as a smartphone or computer and enter information such as marital status, number of dependents, mortgage status, annual income, consumption history, etc. At this time, the information entered by the user is collected through the device interface.

[0920] Step 2:

[0921] The device sends the information entered by the user to a cloud server. The input data includes marital status, number of dependents, mortgage status, annual income, consumption history, etc. The server stores the received data in a database.

[0922] Step 3:

[0923] The server launches an AI module to analyze the user's input. Specifically, it uses machine learning libraries such as TensorFlow to perform initial data analysis. The input here is the user data, and the output is the analysis results.

[0924] Step 4:

[0925] The server uses the analysis results to generate follow-up questions to gather more information. This process uses the user's initial data and the analysis results as inputs and generates follow-up questions as output.

[0926] Step 5:

[0927] The server generates additional questions and sends them to the terminal, which then displays them to the user. The displayed questions include, for example, "How much do you pay for insurance premiums per year?" The user answers the questions.

[0928] Step 6:

[0929] The user inputs the answers to the follow-up questions into the terminal, and the terminal sends the answer data to the server. The user's answers are stored as input data, and updated user information is stored as output data.

[0930] Step 7:

[0931] The server restarts the AI ​​module and re-analyzes all of the user's information. A detailed analysis is performed to determine the optimal tax-saving method. The input data is the updated user information, and the output data is the optimal tax-saving proposal.

[0932] Step 8:

[0933] The server accesses the expert database to obtain the latest tax saving examples. This ensures that the proposals are based on the latest information, improving reliability. The input data is the expert database, and the output data is the latest tax saving information.

[0934] Step 9:

[0935] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user. Here, an information integration algorithm is used to process the data and output the optimal tax-saving plan.

[0936] Step 10:

[0937] The server immediately notifies users of tax-saving opportunities and deadlines, and the terminal displays this information to them. Detailed tax-saving methods and procedures are provided to users through a user-friendly interface. Input data is the proposals from the server, and output data is the notification and display to the user.

[0938] Prompt Sentence Examples

[0939] "Please suggest the best tax saving method based on the user's income and consumption history."

[0940] These steps allow users to receive optimal tax saving suggestions in real time and achieve effective tax savings.

[0941] 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.

[0942] The present invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state, and an embodiment thereof will be described below.

[0943] System Overview

[0944] This system proposes optimal tax-saving methods based on the user's situation. Its main components are the user, device, server, emotion engine, and AI module. Information related to the user's life events is collected, and the AI ​​performs analysis based on that information. The emotion engine recognizes the user's emotions and adaptively changes the content of the proposals and the way they are displayed.

[0945] User input information collection and emotion recognition

[0946] User

[0947] A user logs in to the system using a device such as a smartphone or computer.

[0948] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[0949] Terminal

[0950] The terminal receives the user's input information and activates an emotion engine to analyze the user's emotional state.

[0951] The terminal transmits the user's input information and emotional state to the server.

[0952] Analyzing user information and asking follow-up questions

[0953] server

[0954] The server prepares the received user information for analysis.

[0955] The server activates the AI ​​module and passes user information and emotional state to the AI.

[0956] The AI ​​module analyzes user information and generates follow-up questions as needed.

[0957] Terminal

[0958] The terminal displays the additional question received from the server to the user.

[0959] User

[0960] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[0961] The user sends the answer to the server via the terminal.

[0962] Detailed analysis and tax saving suggestions

[0963] server

[0964] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[0965] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[0966] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[0967] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[0968] The server formats the proposal and sends it to the device.

[0969] Adjusting recommendations with an emotion engine

[0970] Terminal

[0971] The device integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adaptively changes the way the suggestions are displayed (e.g., pop-up messages, color changes, etc.).

[0972] Viewing Proposals

[0973] Terminal

[0974] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[0975] Specific examples

[0976] 1. Inputting user information and emotions

[0977] User A logs into the system for the first time and provides the following information and emotional state:

[0978] Marital status: Yes

[0979] Number of dependents: 2

[0980] Mortgage status: Currently in use

[0981] Annual income: 9 million yen

[0982] Emotional state: Excitement

[0983] 2. Generate and answer follow-up questions

[0984] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[0985] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[0986] 3. Detailed analysis and generation of tax saving suggestions

[0987] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[0988] Spousal deductions can save you 300,000 yen a year in taxes.

[0989] Dependent deductions allow for a deduction of 380,000 yen per year.

[0990] Home loan deduction of 400,000 yen per year.

[0991] Insurance premium deduction of 100,000 yen per year.

[0992] 4. Display of proposals

[0993] Based on the analysis results of the emotion engine, the device adjusts the way the suggestions are displayed and presents them in a way that is more familiar to user A (e.g., if the emotion is joy, an encouraging message is added).

[0994] As a result, this system provides personalized tax-saving suggestions that take into account the user's emotional state, enabling users to obtain tax-saving information in a more effective and easy-to-understand manner.

[0995] The processing flow will be explained below.

[0996] Step 1:

[0997] User

[0998] A user logs in to the system using a device such as a smartphone or computer.

[0999] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1000] Step 2:

[1001] Terminal

[1002] The device receives the user's input information and activates the emotion engine.

[1003] The device uses a camera and microphone to analyze the user's facial expressions and tone of voice to recognize their emotional state.

[1004] Step 3:

[1005] Terminal

[1006] The terminal transmits the user's input information and the recognized emotional state to the server.

[1007] Step 4:

[1008] server

[1009] The server prepares the received user information and emotional state for analysis.

[1010] The server activates the AI ​​module and passes user information and emotional state to the AI.

[1011] Step 5:

[1012] AI Module

[1013] The AI ​​module analyzes user information and generates follow-up questions as needed.

[1014] The server sends the generated follow-up question to the terminal.

[1015] Step 6:

[1016] Terminal

[1017] The terminal displays the additional question received from the server to the user.

[1018] Step 7:

[1019] User

[1020] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[1021] The user sends the answer to the server via the terminal.

[1022] Step 8:

[1023] Terminal

[1024] The terminal transmits the additional response received from the user to the server.

[1025] Step 9:

[1026] server

[1027] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1028] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[1029] Step 10:

[1030] server

[1031] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[1032] Step 11:

[1033] server

[1034] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1035] Step 12:

[1036] server

[1037] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[1038] Step 13:

[1039] Terminal

[1040] The device passes the tax saving suggestions received from the server to the emotion engine, which customizes how the tax saving suggestions are displayed based on the user's emotional state (e.g., adding an encouraging message if the user is feeling stressed).

[1041] Step 14:

[1042] Terminal

[1043] The terminal displays detailed tax saving methods and procedures in a user-friendly interface.

[1044] Step 15:

[1045] User

[1046] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[1047] Example 2

[1048] 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."

[1049] In today's world, many users find it difficult to obtain appropriate information on financial management and tax-saving methods and make optimal decisions. Providing uniform information without considering the user's emotional state can lead to stress and prevent appropriate decision-making. Furthermore, there is a need for timely, customized tax-saving proposals tailored to the user's specific circumstances.

[1050] 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.

[1051] In this invention, the server includes: means for a user to input information such as marital status, number of dependents, mortgage usage status, and annual income using a terminal; means for the terminal to transmit the information and emotional state input by the user to the server; means for the server to store the received user information and emotional state for analysis; means for the server to activate an AI module and use it to analyze the user information and emotional state; means for the server to generate necessary follow-up questions based on the analysis results and transmit them to the terminal; means for the terminal to display the received follow-up questions to the user; means for the terminal to transmit the user's follow-up answers to the server; means for the server to perform detailed analysis using the AI ​​module and obtain the latest tax saving examples and tax system information from an expert database; means for the server to generate specific tax saving suggestions optimal for the user and transmit them to the terminal; and means for the terminal to adjust the display method of the suggestions using an emotion engine and display them to the user. This makes it possible to provide personalized tax saving suggestions tailored to the user's specific situation and support the user in making appropriate decisions.

[1052] "User" refers to an individual who inputs and receives information into the system.

[1053] "Terminal" refers to a device that allows a user to input information and send and receive data to and from a server.

[1054] "Server" refers to the central system that processes information received from users and works with AI modules and databases to analyze and make recommendations.

[1055] "Emotional state" refers to information that indicates the user's current state of mind or mood.

[1056] "AI Module" refers to an artificial intelligence program used to analyze user information and emotional state and suggest tax-saving methods.

[1057] "Analysis" refers to the process of analyzing information collected from users using an AI module and obtaining the results.

[1058] "Tax saving methods" refer to specific means and measures to reduce the tax burden.

[1059] "Expert database" refers to an external database that collects and stores the latest tax saving cases and tax system information.

[1060] "Additional questions" refer to questions that the AI ​​module asks the user to gather new information during the analysis process.

[1061] "Format" refers to the format or style used to organize and present information or proposals in an easy-to-read manner.

[1062] An "emotion engine" refers to a program that recognizes a user's tone of voice and facial expressions to analyze their emotional state.

[1063] MODE FOR CARRYING OUT THE INVENTION

[1064] The present invention is a system for proposing optimal tax-saving methods based on information and emotional state input by a user. An embodiment of the system will be described in detail below.

[1065] System configuration

[1066] The main components of this system are a user, a terminal, a server, an emotion engine, and an AI module.

[1067] Collecting user input information

[1068] User

[1069] Users log in to the system using a device such as a smartphone or computer, and enter information such as marital status, number of dependents, mortgage status, and annual income as part of the initial setup.

[1070] The user's input information is sent to the terminal.

[1071] Terminal

[1072] The device activates an emotion engine that analyzes the user's tone of voice and facial expressions to determine their emotional state.

[1073] Data transmission and analysis

[1074] Terminal

[1075] The terminal transmits the information and emotional state received from the user to the server.

[1076] server

[1077] The server stores the received information in a temporary database and prepares it for analysis.

[1078] Activate the AI ​​module to analyze user information and emotional state.

[1079] Generate new questions for the user regarding the additional information needed.

[1080] Collecting additional information

[1081] Terminal

[1082] The terminal displays the follow-up questions received from the server to the user.

[1083] User

[1084] The user answers the additional questions and transmits the answers to the server via the terminal.

[1085] server

[1086] The server stores the additional information it receives in a database and then uses the AI ​​module again for further analysis.

[1087] Proposal of optimal tax saving methods

[1088] server

[1089] The server uses an AI module to generate a list of optimal tax saving methods for the user.

[1090] Access our expert database for the latest tax savings and tax information.

[1091] The AI ​​analysis results are combined with expert data to generate specific tax-saving suggestions for users.

[1092] The proposal is formatted appropriately and sent to the device.

[1093] Viewing Proposals

[1094] Terminal

[1095] It uses an emotion engine to tailor how suggestions are displayed, for example, if the user is "excited," it will display a pop-up with an encouraging message.

[1096] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[1097] Specific examples

[1098] 1. Inputting user information and emotions

[1099] User A logs into the system for the first time and provides the following information and emotional state:

[1100] Marital status: Yes

[1101] Number of dependents: 2

[1102] Mortgage status: Currently in use

[1103] Annual income: 9 million yen

[1104] Emotional state: Excitement

[1105] 2. Generate and answer follow-up questions

[1106] The server inputs this information into an AI module, which then generates follow-up questions such as, "How much do you pay in insurance premiums per year?"

[1107] User A responds, "Annual insurance premium payment: 100,000 yen," and the terminal sends this to the server.

[1108] 3. Detailed analysis and generation of tax saving suggestions

[1109] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1110] Spousal deductions can save you 300,000 yen a year in taxes.

[1111] Dependent deductions allow for a deduction of 380,000 yen per year.

[1112] Home loan deduction of 400,000 yen per year.

[1113] Insurance premium deduction of 100,000 yen per year.

[1114] 4. Display of proposals

[1115] Based on the analysis results of the emotion engine, the device adjusts how the suggestions are displayed. For example, if the emotion is joy, an encouraging message will be added.

[1116] An example prompt is:

[1117] "Describe the natural language processing process for a system that suggests optimal tax-saving strategies based on user information and emotional state."

[1118] "Please explain the process of the system that generates follow-up questions based on the user's situation and emotional state and performs detailed analysis."

[1119] As a result, this system makes personalized tax-saving suggestions that take into account the user's emotional state, allowing the user to obtain tax-saving information that is easy to understand and optimal for them.

[1120] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1121] Step 1:

[1122] A user logs in to the system using a smartphone or computer terminal. By entering their username and password as login information, authentication is performed and the user is able to access the system. Input: Username, password. Output: Authentication result.

[1123] Step 2:

[1124] The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. This records the user's basic financial situation in the system. Input: Marital status, number of dependents, mortgage status, annual income. Output: Saves the initial information.

[1125] Step 3:

[1126] The device passes the initial setting information received from the user to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to determine the user's emotional state. Input: Initial setting information. Output: Emotional state.

[1127] Step 4:

[1128] The device sends the initial setting information and emotional state to the server. The server stores the received information in a temporary database. Input: Initial setting information, emotional state. Output: Stored in the database.

[1129] Step 5:

[1130] The server passes the received information to the AI ​​module, which analyzes the user's information and emotional state. The AI ​​module determines whether additional information is needed based on the user's financial situation and emotional state. Input: Initial setting information, emotional state. Output: Generation of additional questions.

[1131] Step 6:

[1132] The terminal displays the follow-up question received from the server to the user. For example, a question such as "How much is the annual insurance premium payment?" is displayed to the user. Input: Follow-up question. Output: Display of follow-up question.

[1133] Step 7:

[1134] The user answers the additional questions displayed and sends the answers to the server via the terminal. For example, the user answers "Annual insurance premium payment: 100,000 yen." Input: Answer to additional question. Output: Send to server.

[1135] Step 8:

[1136] The server stores the received additional information in a database and uses the AI ​​module again for further analysis. The AI ​​module analyzes all the data and lists the optimal tax saving methods. Input: Additional information. Output: List of tax saving suggestions.

[1137] Step 9:

[1138] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information. The obtained information is integrated with the results of AI analysis to generate specific tax saving proposals. Input: Information from the expert database, AI analysis results. Output: Specific tax saving proposals.

[1139] Step 10:

[1140] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal. Input: Tax saving proposals. Output: Proposal content after formatting.

[1141] Step 11:

[1142] The device uses the emotion engine to adjust how the suggestion is displayed. For example, if the user is "excited," it will add an encouraging message and display a pop-up. Input: Formatted suggestion, emotional state. Output: Display of the adjusted suggestion.

[1143] Step 12:

[1144] The terminal provides the user with detailed tax-saving methods and procedures through a user-friendly interface. The user can take specific actions based on the suggestions presented. Input: Adjusted suggestions. Output: Presentation to the user.

[1145] (Application example 2)

[1146] 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."

[1147] It is generally difficult for users to properly understand their own tax situation and find the optimal tax-saving method. Furthermore, it has not been taken into consideration that users' emotional state can affect how they accept the proposed method. Furthermore, there has been no attempt to predict the tax-saving effect using user purchase data, making it a challenge to quickly and appropriately provide users with advantageous tax-saving methods.

[1148] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the terminal to recognize the emotional state of the user, a means for the terminal to adjust the display method of the proposal content received from the server according to the emotional state of the user and display it, and a means for the terminal to collect the user's purchase data and predict the tax saving effect. This makes it possible to provide the optimal tax saving method in a timely manner while taking the user's emotional state into consideration, and further to make specific tax saving proposals based on the user's purchase history.

[1149] A "user" is a person who uses the system and is the entity that inputs information about tax status and emotional state.

[1150] A "terminal" is an electronic device, such as a smartphone or computer, that allows users to input information and collect emotional and purchasing data.

[1151] "Emotional state" refers to the user's current psychological state, and analyzing this information is used to adjust how the user accepts the proposed content.

[1152] The "server" is a central management system that receives input information and emotional state from users, analyzes it using an AI module, and calculates and provides the optimal tax-saving method.

[1153] The "AI module" is a program with artificial intelligence functions that analyzes the user's input information and emotional state, and generates necessary follow-up questions and tax-saving suggestions.

[1154] The "expert database" is a database that stores the latest tax information and tax saving examples, from which the server can retrieve information.

[1155] "Tax saving methods" refer to specific means and methods for reducing the user's tax burden, including spousal deductions, dependent deductions, and mortgage deductions.

[1156] "Purchase data" is information about the products and services purchased by users, and analyzing this information can predict the tax savings effect.

[1157] "Tax Savings" refers to the tax reduction or other benefit that a user may obtain as a result of a proposed tax saving method.

[1158] This invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state. A specific embodiment of this system is described below. The main components are a user, a terminal, a server, an emotion engine, and an AI module.

[1159] User input information collection and emotion recognition

[1160] User

[1161] Users log in to the system using devices such as smartphones or computers.

[1162] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1163] When the user inputs this information through the terminal, the terminal activates an emotion engine to analyze the user's emotional state.

[1164] Terminal

[1165] The terminal transmits the user's input information and emotional state to the server.

[1166] The terminal also collects the user's purchasing data and transmits it to the server.

[1167] Analyzing user information and asking follow-up questions

[1168] server

[1169] The server prepares for analysis the information received from the user.

[1170] The AI ​​module performs further analysis based on user information and emotional state.

[1171] If necessary, the server generates and sends additional questions to the terminal.

[1172] Terminal

[1173] The terminal displays the follow-up questions received from the server to the user.

[1174] User

[1175] The user answers the additional questions and sends them to the server via the terminal.

[1176] Detailed analysis and tax saving suggestions

[1177] server

[1178] The server uses an AI module to perform detailed analysis and generate a list of tax-saving methods that are best suited to the user's situation.

[1179] The server also retrieves the latest tax savings tips and tax information from a database of experts.

[1180] The AI ​​analysis results are integrated with expert data to generate specific tax-saving proposals tailored to the user.

[1181] Adjusting recommendations with an emotion engine

[1182] Terminal

[1183] The terminal integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adjusts the way the suggestions are displayed according to the user's emotional state.

[1184] Displaying proposals and utilizing purchasing data

[1185] Terminal

[1186] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[1187] The terminal also displays predicted tax savings based on the user's purchasing data.

[1188] Specific examples

[1189] For example, suppose User A logs into the system for the first time and provides the following information and emotional state:

[1190] Marital status: Yes

[1191] Number of dependents: 2

[1192] Mortgage status: Currently in use

[1193] Annual income: 9 million yen

[1194] Emotional state: Excitement

[1195] The server inputs this information into the AI ​​module and generates a more detailed question (e.g., "Annual insurance premium payment amount"). When User A answers this additional question (e.g., "Annual insurance premium payment amount: 100,000 yen") and sends the information to the server, the server performs a detailed analysis and generates a tax saving proposal like the following:

[1196] Spousal deductions can save you 300,000 yen a year in taxes.

[1197] Dependent deductions allow for a deduction of 380,000 yen per year.

[1198] Home loan deduction of 400,000 yen per year.

[1199] Insurance premium deduction of 100,000 yen per year.

[1200] The suggestions are tailored based on the user's emotional state and presented to the user in a friendly way: for example, if the emotion is joyful, an encouraging message can be added.

[1201] Prompt Sentence Examples

[1202] "User ID: 12345 Marital status: Yes Number of dependents: 2 Annual income: 8 million yen Planned purchase: Home appliances (TV) Emotional state: Happy Analyze the optimal tax-saving method for this user and create a proposal."

[1203] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1204] Step 1:

[1205] The user logs into the system using a smartphone or computer. The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. The entered information is received by the terminal.

[1206] Input: User's initial information (married status, number of dependents, mortgage status, annual income)

[1207] Output: Initial information saved on the device

[1208] Specific operation: The user logs in and provides information using an interface for entering initial information.

[1209] Step 2:

[1210] The device sends the user's input information to the server. At the same time, the device's emotion engine is activated and analyzes the user's emotional state. The emotion engine uses the smartphone's camera and sensors to analyze the user's facial expressions and voice.

[1211] Input: User's initial information and camera video or audio data

[1212] Output: Initial information and emotion data sent to the server

[1213] Specific operation: The user's input information and video / audio data are sent from the terminal to the server.

[1214] Step 3:

[1215] The server prepares the received user information and emotional data for analysis. The server launches the AI ​​module and passes the user information and emotional state to the AI. The AI ​​module analyzes the user information and generates follow-up questions as needed.

[1216] Input: User's initial information and emotional data

[1217] Output: Additional Question List

[1218] Specific operation: The server uses an AI module to analyze user information and emotional data and generate additional questions.

[1219] Step 4:

[1220] The terminal displays the additional questions received from the server to the user, and the user answers the additional questions and transmits the answers to the server via the terminal.

[1221] Input: Additional Question List

[1222] Output: User response information

[1223] Specific operation: The terminal displays additional questions to the user, and the user enters additional information and sends it to the server.

[1224] Step 5:

[1225] Based on the additional information received, the server uses the AI ​​module again to perform a detailed analysis. The server retrieves the latest tax saving examples and tax system information from a database of experts and generates a list of tax saving methods that are optimal for the user.

[1226] Input: Additional information for the user

[1227] Output: A list of the best ways to save tax

[1228] Specific operation: The server accesses an expert database to obtain the latest tax saving information, and then analyzes the information using an AI module.

[1229] Step 6:

[1230] The device integrates the tax-saving proposals received from the server with the analysis results of the emotion engine, adjusts the way the proposals are displayed, and presents them to the user. The proposals are displayed in a friendly manner according to the user's emotional state.

[1231] Input: Tax saving proposal content and sentiment analysis results

[1232] Output: Tax saving suggestions with adjusted presentation

[1233] Specific operation: Based on the results of emotion analysis, the device appropriately adjusts the suggestions and displays them to the user.

[1234] Step 7:

[1235] The device collects the user's purchasing data and displays a predicted tax savings effect. The purchasing data is information about the products and services purchased by the user. The device sends this data to the server, and the AI ​​module predicts the tax savings effect.

[1236] Input: User's purchasing data

[1237] Output: Predicted tax savings

[1238] Specific operation: The terminal collects the user's purchasing history, and the server uses this information to predict tax savings and presents them to the user.

[1239] 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.

[1240] 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.

[1241] 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.

[1242] [Third embodiment]

[1243] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1244] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1245] 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).

[1246] 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.

[1247] 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.

[1248] 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).

[1249] 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. 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.

[1250] 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.

[1251] 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.

[1252] 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.

[1253] 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.

[1254] 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."

[1255] The present invention is a system that proposes optimal tax-saving methods based on information input by a user, and an embodiment thereof will be described below.

[1256] System Overview

[1257] The system allows users to input their tax information and information related to life events, and the AI ​​module then suggests optimal tax-saving methods. The system is primarily comprised of three main components: the user, the terminal, and the server.

[1258] Collecting user input information

[1259] User

[1260] A user logs in to the system using a device such as a smartphone or computer.

[1261] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1262] Terminal

[1263] The terminal receives the user's input information and sends it to the server.

[1264] Analyzing user information and asking follow-up questions

[1265] server

[1266] The server receives the information sent by the user and activates the AI ​​module.

[1267] The AI ​​module analyzes the initial information and generates follow-up questions to gather more information if necessary.

[1268] Terminal

[1269] The terminal displays the additional question received from the server to the user.

[1270] User

[1271] The user answers the additional questions and sends them to the server via the terminal.

[1272] Detailed analysis and tax saving suggestions

[1273] server

[1274] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1275] The AI ​​module generates a list of optimal tax-saving strategies based on the user's individual circumstances.

[1276] The server accesses a database of experts to retrieve the latest tax saving cases.

[1277] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1278] Viewing Proposals

[1279] Terminal

[1280] The terminal displays the tax saving proposal received from the server to the user.

[1281] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[1282] Specific examples

[1283] 1. Enter your user information

[1284] User A logs into the system for the first time and provides the following information:

[1285] Marital status: Yes

[1286] Number of dependents: 2

[1287] Mortgage status: Currently in use

[1288] Annual income: 9 million yen

[1289] Other deductions (e.g., insurance enrollment status)

[1290] 2. Generate and answer follow-up questions

[1291] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[1292] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[1293] 3. Detailed analysis and generation of tax saving suggestions

[1294] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1295] Spousal deductions can save you 300,000 yen a year in taxes.

[1296] Dependent deductions allow for a deduction of 380,000 yen per year.

[1297] Home loan deduction of 400,000 yen per year.

[1298] Insurance premium deduction of 100,000 yen per year.

[1299] 4. Display of proposals

[1300] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[1301] In this way, the system provides users with customized tax-saving suggestions and offers them ways to increase their take-home pay, making it easier for them to find tax-saving methods that suit them and enabling them to achieve effective tax savings.

[1302] The processing flow will be explained below.

[1303] Step 1:

[1304] User

[1305] A user logs in to the system using a device such as a smartphone or computer.

[1306] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1307] Step 2:

[1308] Terminal

[1309] The terminal receives the user's input information and sends it to the server.

[1310] The terminal checks the communication status with the server, and if successful, proceeds to the next process.

[1311] Step 3:

[1312] server

[1313] The server prepares the received user information for analysis.

[1314] The server starts the AI ​​module and passes the user information to the AI.

[1315] The AI ​​module analyzes user information and generates follow-up questions as needed.

[1316] Step 4:

[1317] server

[1318] The server sends the generated follow-up question to the terminal.

[1319] Step 5:

[1320] Terminal

[1321] The terminal displays the additional question received from the server to the user.

[1322] Step 6:

[1323] User

[1324] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[1325] The user sends the answer to the server via the terminal.

[1326] Step 7:

[1327] Terminal

[1328] The terminal transmits the additional response received from the user to the server.

[1329] Step 8:

[1330] server

[1331] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1332] The AI ​​module performs detailed analysis and generates a list of tax-saving methods that are best suited to each user's individual situation.

[1333] Step 9:

[1334] server

[1335] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[1336] Step 10:

[1337] server

[1338] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1339] Step 11:

[1340] server

[1341] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[1342] Step 12:

[1343] Terminal

[1344] The terminal displays the received proposal to the user.

[1345] It provides detailed tax-saving methods and procedures in a user-friendly interface.

[1346] Step 13:

[1347] User

[1348] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[1349] Example 1

[1350] 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."

[1351] In today's tax environment, it is difficult for individuals to find the right tax-saving methods. With a wide variety of tax laws and deductions, expertise is required to find the best tax-saving methods for each individual situation. However, hiring a tax professional is costly and time-consuming. To solve this problem, a system is needed that automatically suggests the best tax-saving methods based on information that the user simply enters.

[1352] 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.

[1353] In this invention, the server includes means for analyzing the initial information received from the user, generating additional questions and sending them to the terminal, means for the terminal to receive the user's additional answers and send them to the server, and means for the server to perform detailed analysis using an AI module based on all the information received and propose customized tax saving methods based on the user's individual circumstances. This allows the user to find the optimal tax saving method based on the information they simply input.

[1354] A "user" is an individual who uses the system to provide input information and receive tax-saving suggestions.

[1355] A "terminal" is an electronic device, such as a smartphone or computer, that a user uses to input information and send and receive data to and from a server.

[1356] The "server" is a central processing unit that receives user input information, analyzes it, and uses an AI module to suggest optimal tax-saving methods.

[1357] The "AI module" is an artificial intelligence system that analyzes input data and suggests optimal tax-saving methods tailored to the user's individual circumstances.

[1358] The "database" is a collection of information that stores the latest tax saving cases from experts and user input information, and is accessed by the server as needed.

[1359] "Analysis" is the process in which the AI ​​module analyzes data based on user input and derives the optimal tax-saving method.

[1360] "Additional questions" are questions generated by the AI ​​module to gather additional information needed by the user to suggest the best tax-saving methods.

[1361] "Tax saving methods" are specific techniques and procedures for optimal tax savings that the AI ​​module suggests to users through analysis.

[1362] MODE FOR CARRYING OUT THE INVENTION

[1363] System Overview

[1364] This invention is a system in which users input their tax information and information related to life events, and an AI module then suggests optimal tax-saving methods based on that information. The system is primarily composed of three main components: the user, the terminal, and the server.

[1365] Collecting user input information

[1366] User

[1367] A user logs in to the system using a device such as a smartphone or computer, using an email address and password as login information.

[1368] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1369] Terminal

[1370] The device receives the user's input and sends it to the server, using a protocol (e.g., HTTPS) that transmits the data securely over the Internet.

[1371] Analyzing user information and asking follow-up questions

[1372] server

[1373] The server receives the information sent by the user and launches an AI module, which can use a machine learning framework implemented in Python (e.g., TensorFlow or PyTorch).

[1374] The server uses an AI module to analyze the initial information and generate follow-up questions to gather more detailed information.

[1375] Terminal

[1376] The terminal displays the follow-up questions received from the server to the user, for example, using an interface that displays form input or options.

[1377] User

[1378] The user answers the additional questions and sends them to the server via the terminal.

[1379] Detailed analysis and tax saving suggestions

[1380] server

[1381] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1382] The AI ​​module generates a list of optimal tax-saving methods based on the user's individual circumstances, including spouse deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[1383] The server accesses a database of experts to retrieve the latest tax savings tips, including information on the latest tax laws and deductions.

[1384] The server combines the analysis results of the AI ​​module with expert data to generate specific tax-saving proposals tailored to the user.

[1385] Viewing Proposals

[1386] Terminal

[1387] The terminal displays the tax saving proposal received from the server to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[1388] Specific examples

[1389] 1. Enter your user information

[1390] User A logs into the system for the first time and provides the following information:

[1391] Marital status: Yes

[1392] Number of dependents: 2

[1393] Mortgage status: Currently in use

[1394] Annual income: 9 million yen

[1395] Other deductions (e.g., insurance enrollment status)

[1396] 2. Generate and answer follow-up questions

[1397] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[1398] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[1399] 3. Detailed analysis and generation of tax saving suggestions

[1400] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1401] Spousal deductions can save you 300,000 yen a year in taxes.

[1402] Dependent deductions allow for a deduction of 380,000 yen per year.

[1403] Home loan deduction of 400,000 yen per year.

[1404] Insurance premium deduction of 100,000 yen per year.

[1405] 4. Display of proposals

[1406] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[1407] Example prompts for generative AI models

[1408] "The app suggests optimal tax-saving strategies based on the tax information and life events you enter. This includes information such as marital status, number of dependents, mortgage status, and annual income."

[1409] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1410] Step 1: User Login

[1411] User

[1412] A user accesses the system using a device such as a smartphone or computer and logs in by entering their email address and password.

[1413] Input: Email address, password

[1414] Output: Login request

[1415] Terminal

[1416] The terminal receives the user's login information and sends it to the server.

[1417] Input: Login request

[1418] Output: Login information (email address, password)

[1419] server

[1420] The server authenticates the received login information and, if authentication is successful, starts the user session.

[1421] Input: Login information (email address, password)

[1422] Output: Authentication result (success / failure), session start

[1423] Step 2: Enter initial information

[1424] User

[1425] After logging in, users enter initial information such as marital status, number of dependents, mortgage status, and annual income.

[1426] Input: Marital status, number of dependents, mortgage status, annual income

[1427] Output: Initial information

[1428] Terminal

[1429] The terminal receives the user's initial information and sends it to the server.

[1430] Input: Initial information

[1431] Output: Initial information (marriage status, number of dependents, mortgage status, annual income)

[1432] Step 3: Processing initial information

[1433] server

[1434] The server stores the received initial information in a database and launches an AI module to analyze the initial information.

[1435] Input: Initial information

[1436] Data processing and calculation: Saving to database, analysis by AI module

[1437] Output: Analysis results, additional questions if necessary

[1438] Step 4: Generate and present follow-up questions

[1439] server

[1440] Based on the initial information, the AI ​​module generates follow-up questions to gather more detailed information.

[1441] Input: Analysis results

[1442] Data processing and calculation: Generation of additional questions

[1443] Output: Additional questions

[1444] Terminal

[1445] The terminal displays the additional question received from the server to the user.

[1446] Input: Additional Question

[1447] Output: Show additional questions

[1448] User

[1449] The user answers the additional questions and sends them to the server via the terminal.

[1450] Input: Answer to additional question

[1451] Output: Additional answers

[1452] Terminal

[1453] The terminal receives the user's additional response and transmits it to the server.

[1454] Input: Additional Answer

[1455] Output: Additional answers

[1456] Step 5: Processing additional information

[1457] server

[1458] The server stores the additional information it receives in a database and uses the AI ​​module again for further analysis.

[1459] Input: Additional Answer

[1460] Data processing and calculation: Saving to database, detailed analysis by AI module

[1461] Output: Detailed analysis results

[1462] Step 6: Generate tax savings

[1463] server

[1464] The AI ​​module analyzes each user's individual circumstances and generates a list of optimal tax-saving methods, including spousal deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[1465] The server accesses a database of experts to retrieve the latest tax saving cases, and then combines the analysis results of the AI ​​module with the expert data to generate specific tax saving suggestions tailored to the user.

[1466] Input: Detailed analysis results, expert data

[1467] Data processing and calculation: Creating a list of tax-saving methods, integrating data

[1468] Output: Tax Savings Suggestion

[1469] Step 7: Submit and view your proposal

[1470] server

[1471] The server generates tax saving suggestions and sends them to the terminal.

[1472] Input: Tax Savings Proposal

[1473] Output: Submit tax saving proposal

[1474] Terminal

[1475] The terminal displays the tax saving suggestions received to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[1476] Input: Tax Savings Proposal

[1477] Output: Display tax saving proposals

[1478] User

[1479] The user reviews the proposal and views specific steps and related information.

[1480] Input: Tax Savings Proposal

[1481] Output: User confirmation, viewing of proposals

[1482] (Application example 1)

[1483] 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."

[1484] Conventional tax-saving suggestion systems require users to spend a lot of time and effort to find the tax-saving method that best suits them. Furthermore, they lack the functionality to comprehensively analyze income and consumption history and suggest optimal tax-saving methods in real time, making it difficult for users to quickly obtain the latest tax-saving information. Furthermore, they lack immediate notifications about tax-saving opportunities and deadlines, which can lead to users missing important opportunities. This invention solves the above problems and provides a system that allows users to save on taxes more effectively.

[1485] 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.

[1486] In this invention, the server includes a means for inputting information including income data and consumption history, a means for analyzing the user's situation and proposing optimal tax-saving methods in real time, and a means for immediately notifying the user of tax-saving opportunities and deadlines. This allows the user to quickly obtain the latest tax-saving information that is appropriate for them. Furthermore, the server can collect necessary additional information and provide detailed tax-saving proposals via a user interface, helping the user to effectively achieve tax savings.

[1487] 1. "User" means a person who uses the system to receive tax saving suggestions.

[1488] 2. "Marital status" is information indicating whether the user is married or not.

[1489] 3. "Number of dependents" is information indicating the number of family members the user financially supports.

[1490] 4. "Mortgage usage status" is information indicating whether the user has taken out a loan to purchase a home.

[1491] 5. "Income Data" means information about a User's annual income or other income.

[1492] 6. "Consumption History" means a record of purchases made by a User through electronic payment.

[1493] 7. A "terminal" is a device, such as a smartphone or computer, that a user uses to input information.

[1494] 8. "Server" means a central computer that receives and analyzes information sent by users.

[1495] 9. "AI Module" means a software component that uses artificial intelligence to analyze the user's situation and generate optimal suggestions.

[1496] 10. The "Expert Database" is a data collection device that collects and manages the latest tax saving cases and legal information.

[1497] 11. A "tax saving method" is a specific means of reducing the amount of tax.

[1498] 12. "Real-time" is a term that indicates near-instant processing.

[1499] 13. "Tax Saving Opportunity" means an opportunity for a user to save on tax by taking a specific action or procedure.

[1500] 14. "Deadline" means the last date by which tax-related procedures must be carried out.

[1501] 15. "Notification" means the system notifying the user of new information or important deadlines.

[1502] 16. "Recommendations" refers to information generated by the AI ​​module regarding optimal tax saving methods.

[1503] 17. "User interface" means the system, including the screen and input devices, that allows a user to interact with a system.

[1504] 18. "Additional Information" is data requested from the user to obtain further details when the initial information is insufficient.

[1505] The embodiment of this invention is a system in which a user inputs various information, including income data and consumption history, and an AI module proposes optimal tax-saving methods in real time based on that data. This system consists of three main components: a user, a terminal, and a server.

[1506] Collecting user input information

[1507] Users log in to the system using a device such as a smartphone or computer. As an initial setup, the user enters information such as whether they have a spouse, the number of dependents, their mortgage loan status, their annual income, and their consumption history. This allows the system to obtain the user's basic tax information.

[1508] Data transmission and analysis

[1509] The device sends the information entered by the user to a cloud server. An AI module running on this cloud server analyzes the information entered by the user and prepares to propose optimal tax-saving methods. The AI ​​module used here uses a machine learning library such as TensorFlow. Based on the analyzed data, it generates follow-up questions to gather more detailed information.

[1510] Obtaining additional information and conducting detailed analysis

[1511] The server sends the generated follow-up questions to the terminal and displays them to the user. The user answers these questions, and the answer data is sent back to the server. The server then uses the AI ​​module again to perform a detailed analysis and propose the optimal tax-saving method based on the user's individual circumstances. The database used here is, for example, DynamoDB.

[1512] Stay informed and notified

[1513] The server retrieves the latest tax saving cases from a database of experts and combines them with the analysis results of the AI ​​module. Based on this integration result, the server immediately notifies users of tax saving opportunities and deadlines.

[1514] Displaying suggestions to users

[1515] The terminal displays the tax saving proposals received from the server to the user, providing detailed tax saving methods and procedures in an easy-to-understand format through a user-friendly interface.

[1516] Specific examples

[1517] For example, user A enters the following information: "annual income 9 million yen, married, two dependents, mortgage loan, annual insurance premium payment 100,000 yen." The AI ​​module then analyzes this information and generates a follow-up question: "What is the annual insurance premium payment?" If user A answers "100,000 yen," the AI ​​module analyzes again and generates the following proposal:

[1518] Spouse deduction: 300,000 yen tax savings

[1519] Dependent deduction: 380,000 yen deduction

[1520] Housing loan deduction: 400,000 yen deduction

[1521] Insurance premium deduction: 100,000 yen deduction

[1522] These suggestions are instantly sent to User A's smartphone, showing how to apply each deduction and the specific steps for the application process. In addition, the system also sends alerts about important tax-saving opportunities and deadlines for application.

[1523] Prompt Sentence Examples

[1524] Example prompt: "Please suggest the best tax-saving method based on the user's income and spending history."

[1525] In this way, the system helps users easily and quickly find the best tax saving method, enabling them to achieve effective tax savings.

[1526] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1527] Step 1:

[1528] Users log in to the system using a device such as a smartphone or computer and enter information such as marital status, number of dependents, mortgage status, annual income, consumption history, etc. At this time, the information entered by the user is collected through the device interface.

[1529] Step 2:

[1530] The device sends the information entered by the user to a cloud server. The input data includes marital status, number of dependents, mortgage status, annual income, consumption history, etc. The server stores the received data in a database.

[1531] Step 3:

[1532] The server launches an AI module to analyze the user's input. Specifically, it uses machine learning libraries such as TensorFlow to perform initial data analysis. The input here is the user data, and the output is the analysis results.

[1533] Step 4:

[1534] The server uses the analysis results to generate follow-up questions to gather more information. This process uses the user's initial data and the analysis results as inputs and generates follow-up questions as output.

[1535] Step 5:

[1536] The server generates additional questions and sends them to the terminal, which then displays them to the user. The displayed questions include, for example, "How much do you pay for insurance premiums per year?" The user answers the questions.

[1537] Step 6:

[1538] The user inputs the answers to the follow-up questions into the terminal, and the terminal sends the answer data to the server. The user's answers are stored as input data, and updated user information is stored as output data.

[1539] Step 7:

[1540] The server restarts the AI ​​module and re-analyzes all of the user's information. A detailed analysis is performed to determine the optimal tax-saving method. The input data is the updated user information, and the output data is the optimal tax-saving proposal.

[1541] Step 8:

[1542] The server accesses the expert database to obtain the latest tax saving examples. This ensures that the proposals are based on the latest information, improving reliability. The input data is the expert database, and the output data is the latest tax saving information.

[1543] Step 9:

[1544] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user. Here, an information integration algorithm is used to process the data and output the optimal tax-saving plan.

[1545] Step 10:

[1546] The server immediately notifies users of tax-saving opportunities and deadlines, and the terminal displays this information to them. Detailed tax-saving methods and procedures are provided to users through a user-friendly interface. Input data is the proposals from the server, and output data is the notification and display to the user.

[1547] Prompt Sentence Examples

[1548] "Please suggest the best tax saving method based on the user's income and consumption history."

[1549] These steps allow users to receive optimal tax saving suggestions in real time and achieve effective tax savings.

[1550] 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.

[1551] The present invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state, and an embodiment thereof will be described below.

[1552] System Overview

[1553] This system proposes optimal tax-saving methods based on the user's situation. Its main components are the user, device, server, emotion engine, and AI module. Information related to the user's life events is collected, and the AI ​​performs analysis based on that information. The emotion engine recognizes the user's emotions and adaptively changes the content of the proposals and the way they are displayed.

[1554] User input information collection and emotion recognition

[1555] User

[1556] A user logs in to the system using a device such as a smartphone or computer.

[1557] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1558] Terminal

[1559] The terminal receives the user's input information and activates an emotion engine to analyze the user's emotional state.

[1560] The terminal transmits the user's input information and emotional state to the server.

[1561] Analyzing user information and asking follow-up questions

[1562] server

[1563] The server prepares the received user information for analysis.

[1564] The server activates the AI ​​module and passes user information and emotional state to the AI.

[1565] The AI ​​module analyzes user information and generates follow-up questions as needed.

[1566] Terminal

[1567] The terminal displays the additional question received from the server to the user.

[1568] User

[1569] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[1570] The user sends the answer to the server via the terminal.

[1571] Detailed analysis and tax saving suggestions

[1572] server

[1573] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1574] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[1575] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[1576] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1577] The server formats the proposal and sends it to the device.

[1578] Adjusting recommendations with an emotion engine

[1579] Terminal

[1580] The device integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adaptively changes the way the suggestions are displayed (e.g., pop-up messages, color changes, etc.).

[1581] Viewing Proposals

[1582] Terminal

[1583] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[1584] Specific examples

[1585] 1. Inputting user information and emotions

[1586] User A logs into the system for the first time and provides the following information and emotional state:

[1587] Marital status: Yes

[1588] Number of dependents: 2

[1589] Mortgage status: Currently in use

[1590] Annual income: 9 million yen

[1591] Emotional state: Excitement

[1592] 2. Generate and answer follow-up questions

[1593] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[1594] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[1595] 3. Detailed analysis and generation of tax saving suggestions

[1596] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1597] Spousal deductions can save you 300,000 yen a year in taxes.

[1598] Dependent deductions allow for a deduction of 380,000 yen per year.

[1599] Home loan deduction of 400,000 yen per year.

[1600] Insurance premium deduction of 100,000 yen per year.

[1601] 4. Display of proposals

[1602] Based on the analysis results of the emotion engine, the device adjusts the way the suggestions are displayed and presents them in a way that is more familiar to user A (e.g., if the emotion is joy, an encouraging message is added).

[1603] As a result, this system provides personalized tax-saving suggestions that take into account the user's emotional state, enabling users to obtain tax-saving information in a more effective and easy-to-understand manner.

[1604] The processing flow will be explained below.

[1605] Step 1:

[1606] User

[1607] A user logs in to the system using a device such as a smartphone or computer.

[1608] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1609] Step 2:

[1610] Terminal

[1611] The device receives the user's input information and activates the emotion engine.

[1612] The device uses a camera and microphone to analyze the user's facial expressions and tone of voice to recognize their emotional state.

[1613] Step 3:

[1614] Terminal

[1615] The terminal transmits the user's input information and the recognized emotional state to the server.

[1616] Step 4:

[1617] server

[1618] The server prepares the received user information and emotional state for analysis.

[1619] The server activates the AI ​​module and passes user information and emotional state to the AI.

[1620] Step 5:

[1621] AI Module

[1622] The AI ​​module analyzes user information and generates follow-up questions as needed.

[1623] The server sends the generated follow-up question to the terminal.

[1624] Step 6:

[1625] Terminal

[1626] The terminal displays the additional question received from the server to the user.

[1627] Step 7:

[1628] User

[1629] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[1630] The user sends the answer to the server via the terminal.

[1631] Step 8:

[1632] Terminal

[1633] The terminal transmits the additional response received from the user to the server.

[1634] Step 9:

[1635] server

[1636] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1637] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[1638] Step 10:

[1639] server

[1640] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[1641] Step 11:

[1642] server

[1643] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1644] Step 12:

[1645] server

[1646] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[1647] Step 13:

[1648] Terminal

[1649] The device passes the tax saving suggestions received from the server to the emotion engine, which customizes how the tax saving suggestions are displayed based on the user's emotional state (e.g., adding an encouraging message if the user is feeling stressed).

[1650] Step 14:

[1651] Terminal

[1652] The terminal displays detailed tax saving methods and procedures in a user-friendly interface.

[1653] Step 15:

[1654] User

[1655] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[1656] Example 2

[1657] 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."

[1658] In today's world, many users find it difficult to obtain appropriate information on financial management and tax-saving methods and make optimal decisions. Providing uniform information without considering the user's emotional state can lead to stress and prevent appropriate decision-making. Furthermore, there is a need for timely, customized tax-saving proposals tailored to the user's specific circumstances.

[1659] 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.

[1660] In this invention, the server includes: means for a user to input information such as marital status, number of dependents, mortgage usage status, and annual income using a terminal; means for the terminal to transmit the information and emotional state input by the user to the server; means for the server to store the received user information and emotional state for analysis; means for the server to activate an AI module and use it to analyze the user information and emotional state; means for the server to generate necessary follow-up questions based on the analysis results and transmit them to the terminal; means for the terminal to display the received follow-up questions to the user; means for the terminal to transmit the user's follow-up answers to the server; means for the server to perform detailed analysis using the AI ​​module and obtain the latest tax saving examples and tax system information from an expert database; means for the server to generate specific tax saving suggestions optimal for the user and transmit them to the terminal; and means for the terminal to adjust the display method of the suggestions using an emotion engine and display them to the user. This makes it possible to provide personalized tax saving suggestions tailored to the user's specific situation and support the user in making appropriate decisions.

[1661] "User" refers to an individual who inputs and receives information into the system.

[1662] "Terminal" refers to a device that allows a user to input information and send and receive data to and from a server.

[1663] "Server" refers to the central system that processes information received from users and works with AI modules and databases to analyze and make recommendations.

[1664] "Emotional state" refers to information that indicates the user's current state of mind or mood.

[1665] "AI Module" refers to an artificial intelligence program used to analyze user information and emotional state and suggest tax-saving methods.

[1666] "Analysis" refers to the process of analyzing information collected from users using an AI module and obtaining the results.

[1667] "Tax saving methods" refer to specific means and measures to reduce the tax burden.

[1668] "Expert database" refers to an external database that collects and stores the latest tax saving cases and tax system information.

[1669] "Additional questions" refer to questions that the AI ​​module asks the user to gather new information during the analysis process.

[1670] "Format" refers to the format or style used to organize and present information or proposals in an easy-to-read manner.

[1671] An "emotion engine" refers to a program that recognizes a user's tone of voice and facial expressions to analyze their emotional state.

[1672] MODE FOR CARRYING OUT THE INVENTION

[1673] The present invention is a system for proposing optimal tax-saving methods based on information and emotional state input by a user. An embodiment of the system will be described in detail below.

[1674] System configuration

[1675] The main components of this system are a user, a terminal, a server, an emotion engine, and an AI module.

[1676] Collecting user input information

[1677] User

[1678] Users log in to the system using a device such as a smartphone or computer, and enter information such as marital status, number of dependents, mortgage status, and annual income as part of the initial setup.

[1679] The user's input information is sent to the terminal.

[1680] Terminal

[1681] The device activates an emotion engine that analyzes the user's tone of voice and facial expressions to determine their emotional state.

[1682] Data transmission and analysis

[1683] Terminal

[1684] The terminal transmits the information and emotional state received from the user to the server.

[1685] server

[1686] The server stores the received information in a temporary database and prepares it for analysis.

[1687] Activate the AI ​​module to analyze user information and emotional state.

[1688] Generate new questions for the user regarding the additional information needed.

[1689] Collecting additional information

[1690] Terminal

[1691] The terminal displays the follow-up questions received from the server to the user.

[1692] User

[1693] The user answers the additional questions and transmits the answers to the server via the terminal.

[1694] server

[1695] The server stores the additional information it receives in a database and then uses the AI ​​module again for further analysis.

[1696] Proposal of optimal tax saving methods

[1697] server

[1698] The server uses an AI module to generate a list of optimal tax saving methods for the user.

[1699] Access our expert database for the latest tax savings and tax information.

[1700] The AI ​​analysis results are combined with expert data to generate specific tax-saving suggestions for users.

[1701] The proposal is formatted appropriately and sent to the device.

[1702] Viewing Proposals

[1703] Terminal

[1704] It uses an emotion engine to tailor how suggestions are displayed, for example, if the user is "excited," it will display a pop-up with an encouraging message.

[1705] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[1706] Specific examples

[1707] 1. Inputting user information and emotions

[1708] User A logs into the system for the first time and provides the following information and emotional state:

[1709] Marital status: Yes

[1710] Number of dependents: 2

[1711] Mortgage status: Currently in use

[1712] Annual income: 9 million yen

[1713] Emotional state: Excitement

[1714] 2. Generate and answer follow-up questions

[1715] The server inputs this information into an AI module, which then generates follow-up questions such as, "How much do you pay in insurance premiums per year?"

[1716] User A responds, "Annual insurance premium payment: 100,000 yen," and the terminal sends this to the server.

[1717] 3. Detailed analysis and generation of tax saving suggestions

[1718] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1719] Spousal deductions can save you 300,000 yen a year in taxes.

[1720] Dependent deductions allow for a deduction of 380,000 yen per year.

[1721] Home loan deduction of 400,000 yen per year.

[1722] Insurance premium deduction of 100,000 yen per year.

[1723] 4. Display of proposals

[1724] Based on the analysis results of the emotion engine, the device adjusts how the suggestions are displayed. For example, if the emotion is joy, an encouraging message will be added.

[1725] An example prompt is:

[1726] "Describe the natural language processing process for a system that suggests optimal tax-saving strategies based on user information and emotional state."

[1727] "Please explain the process of the system that generates follow-up questions based on the user's situation and emotional state and performs detailed analysis."

[1728] As a result, this system makes personalized tax-saving suggestions that take into account the user's emotional state, allowing the user to obtain tax-saving information that is easy to understand and optimal for them.

[1729] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1730] Step 1:

[1731] A user logs in to the system using a smartphone or computer terminal. By entering their username and password as login information, authentication is performed and the user is able to access the system. Input: Username, password. Output: Authentication result.

[1732] Step 2:

[1733] The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. This records the user's basic financial situation in the system. Input: Marital status, number of dependents, mortgage status, annual income. Output: Saves the initial information.

[1734] Step 3:

[1735] The device passes the initial setting information received from the user to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to determine the user's emotional state. Input: Initial setting information. Output: Emotional state.

[1736] Step 4:

[1737] The device sends the initial setting information and emotional state to the server. The server stores the received information in a temporary database. Input: Initial setting information, emotional state. Output: Stored in the database.

[1738] Step 5:

[1739] The server passes the received information to the AI ​​module, which analyzes the user's information and emotional state. The AI ​​module determines whether additional information is needed based on the user's financial situation and emotional state. Input: Initial setting information, emotional state. Output: Generation of additional questions.

[1740] Step 6:

[1741] The terminal displays the follow-up question received from the server to the user. For example, a question such as "How much is the annual insurance premium payment?" is displayed to the user. Input: Follow-up question. Output: Display of follow-up question.

[1742] Step 7:

[1743] The user answers the additional questions displayed and sends the answers to the server via the terminal. For example, the user answers "Annual insurance premium payment: 100,000 yen." Input: Answer to additional question. Output: Send to server.

[1744] Step 8:

[1745] The server stores the received additional information in a database and uses the AI ​​module again for further analysis. The AI ​​module analyzes all the data and lists the optimal tax saving methods. Input: Additional information. Output: List of tax saving suggestions.

[1746] Step 9:

[1747] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information. The obtained information is integrated with the results of AI analysis to generate specific tax saving proposals. Input: Information from the expert database, AI analysis results. Output: Specific tax saving proposals.

[1748] Step 10:

[1749] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal. Input: Tax saving proposals. Output: Proposal content after formatting.

[1750] Step 11:

[1751] The device uses the emotion engine to adjust how the suggestion is displayed. For example, if the user is "excited," it will add an encouraging message and display a pop-up. Input: Formatted suggestion, emotional state. Output: Display of the adjusted suggestion.

[1752] Step 12:

[1753] The terminal provides the user with detailed tax-saving methods and procedures through a user-friendly interface. The user can take specific actions based on the suggestions presented. Input: Adjusted suggestions. Output: Presentation to the user.

[1754] (Application example 2)

[1755] 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."

[1756] It is generally difficult for users to properly understand their own tax situation and find the optimal tax-saving method. Furthermore, it has not been taken into consideration that users' emotional state can affect how they accept the proposed method. Furthermore, there has been no attempt to predict the tax-saving effect using user purchase data, making it a challenge to quickly and appropriately provide users with advantageous tax-saving methods.

[1757] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the terminal to recognize the emotional state of the user, a means for the terminal to adjust the display method of the proposal content received from the server according to the emotional state of the user and display it, and a means for the terminal to collect the user's purchase data and predict the tax saving effect. This makes it possible to provide the optimal tax saving method in a timely manner while taking the user's emotional state into consideration, and further to make specific tax saving proposals based on the user's purchase history.

[1758] A "user" is a person who uses the system and is the entity that inputs information about tax status and emotional state.

[1759] A "terminal" is an electronic device, such as a smartphone or computer, that allows users to input information and collect emotional and purchasing data.

[1760] "Emotional state" refers to the user's current psychological state, and analyzing this information is used to adjust how the user accepts the proposed content.

[1761] The "server" is a central management system that receives input information and emotional state from users, analyzes it using an AI module, and calculates and provides the optimal tax-saving method.

[1762] The "AI module" is a program with artificial intelligence functions that analyzes the user's input information and emotional state, and generates necessary follow-up questions and tax-saving suggestions.

[1763] The "expert database" is a database that stores the latest tax information and tax saving examples, from which the server can retrieve information.

[1764] "Tax saving methods" refer to specific means and methods for reducing the user's tax burden, including spousal deductions, dependent deductions, and mortgage deductions.

[1765] "Purchase data" is information about the products and services purchased by users, and analyzing this information can predict the tax savings effect.

[1766] "Tax Savings" refers to the tax reduction or other benefit that a user may obtain as a result of a proposed tax saving method.

[1767] This invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state. A specific embodiment of this system is described below. The main components are a user, a terminal, a server, an emotion engine, and an AI module.

[1768] User input information collection and emotion recognition

[1769] User

[1770] Users log in to the system using devices such as smartphones or computers.

[1771] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1772] When the user inputs this information through the terminal, the terminal activates an emotion engine to analyze the user's emotional state.

[1773] Terminal

[1774] The terminal transmits the user's input information and emotional state to the server.

[1775] The terminal also collects the user's purchasing data and transmits it to the server.

[1776] Analyzing user information and asking follow-up questions

[1777] server

[1778] The server prepares for analysis the information received from the user.

[1779] The AI ​​module performs further analysis based on user information and emotional state.

[1780] If necessary, the server generates and sends additional questions to the terminal.

[1781] Terminal

[1782] The terminal displays the follow-up questions received from the server to the user.

[1783] User

[1784] The user answers the additional questions and sends them to the server via the terminal.

[1785] Detailed analysis and tax saving suggestions

[1786] server

[1787] The server uses an AI module to perform detailed analysis and generate a list of tax-saving methods that are best suited to the user's situation.

[1788] The server also retrieves the latest tax savings tips and tax information from a database of experts.

[1789] The AI ​​analysis results are integrated with expert data to generate specific tax-saving proposals tailored to the user.

[1790] Adjusting recommendations with an emotion engine

[1791] Terminal

[1792] The terminal integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adjusts the way the suggestions are displayed according to the user's emotional state.

[1793] Displaying proposals and utilizing purchasing data

[1794] Terminal

[1795] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[1796] The terminal also displays predicted tax savings based on the user's purchasing data.

[1797] Specific examples

[1798] For example, suppose User A logs into the system for the first time and provides the following information and emotional state:

[1799] Marital status: Yes

[1800] Number of dependents: 2

[1801] Mortgage status: Currently in use

[1802] Annual income: 9 million yen

[1803] Emotional state: Excitement

[1804] The server inputs this information into the AI ​​module and generates a more detailed question (e.g., "Annual insurance premium payment amount"). When User A answers this additional question (e.g., "Annual insurance premium payment amount: 100,000 yen") and sends the information to the server, the server performs a detailed analysis and generates a tax saving proposal like the following:

[1805] Spousal deductions can save you 300,000 yen a year in taxes.

[1806] Dependent deductions allow for a deduction of 380,000 yen per year.

[1807] Home loan deduction of 400,000 yen per year.

[1808] Insurance premium deduction of 100,000 yen per year.

[1809] The suggestions are tailored based on the user's emotional state and presented to the user in a friendly way: for example, if the emotion is joyful, an encouraging message can be added.

[1810] Prompt Sentence Examples

[1811] "User ID: 12345 Marital status: Yes Number of dependents: 2 Annual income: 8 million yen Planned purchase: Home appliances (TV) Emotional state: Happy Analyze the optimal tax-saving method for this user and create a proposal."

[1812] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1813] Step 1:

[1814] The user logs into the system using a smartphone or computer. The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. The entered information is received by the terminal.

[1815] Input: User's initial information (married status, number of dependents, mortgage status, annual income)

[1816] Output: Initial information saved on the device

[1817] Specific operation: The user logs in and provides information using an interface for entering initial information.

[1818] Step 2:

[1819] The device sends the user's input information to the server. At the same time, the device's emotion engine is activated and analyzes the user's emotional state. The emotion engine uses the smartphone's camera and sensors to analyze the user's facial expressions and voice.

[1820] Input: User's initial information and camera video or audio data

[1821] Output: Initial information and emotion data sent to the server

[1822] Specific operation: The user's input information and video / audio data are sent from the terminal to the server.

[1823] Step 3:

[1824] The server prepares the received user information and emotional data for analysis. The server launches the AI ​​module and passes the user information and emotional state to the AI. The AI ​​module analyzes the user information and generates follow-up questions as needed.

[1825] Input: User's initial information and emotional data

[1826] Output: Additional Question List

[1827] Specific operation: The server uses an AI module to analyze user information and emotional data and generate additional questions.

[1828] Step 4:

[1829] The terminal displays the additional questions received from the server to the user, and the user answers the additional questions and transmits the answers to the server via the terminal.

[1830] Input: Additional Question List

[1831] Output: User response information

[1832] Specific operation: The terminal displays additional questions to the user, and the user enters additional information and sends it to the server.

[1833] Step 5:

[1834] Based on the additional information received, the server uses the AI ​​module again to perform a detailed analysis. The server retrieves the latest tax saving examples and tax system information from a database of experts and generates a list of tax saving methods that are optimal for the user.

[1835] Input: Additional information for the user

[1836] Output: A list of the best ways to save tax

[1837] Specific operation: The server accesses an expert database to obtain the latest tax saving information, and then analyzes the information using an AI module.

[1838] Step 6:

[1839] The device integrates the tax-saving proposals received from the server with the analysis results of the emotion engine, adjusts the way the proposals are displayed, and presents them to the user. The proposals are displayed in a friendly manner according to the user's emotional state.

[1840] Input: Tax saving proposal content and sentiment analysis results

[1841] Output: Tax saving suggestions with adjusted presentation

[1842] Specific operation: Based on the results of emotion analysis, the device appropriately adjusts the suggestions and displays them to the user.

[1843] Step 7:

[1844] The device collects the user's purchasing data and displays a predicted tax savings effect. The purchasing data is information about the products and services purchased by the user. The device sends this data to the server, and the AI ​​module predicts the tax savings effect.

[1845] Input: User's purchasing data

[1846] Output: Predicted tax savings

[1847] Specific operation: The terminal collects the user's purchasing history, and the server uses this information to predict tax savings and presents them to the user.

[1848] 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.

[1849] 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.

[1850] 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.

[1851] [Fourth embodiment]

[1852] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1853] 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.

[1854] 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).

[1855] 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.

[1856] 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.

[1857] 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).

[1858] 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. 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.

[1859] 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.

[1860] 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.

[1861] 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.

[1862] 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.

[1863] 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.

[1864] 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."

[1865] The present invention is a system that proposes optimal tax-saving methods based on information input by a user, and an embodiment thereof will be described below.

[1866] System Overview

[1867] The system allows users to input their tax information and information related to life events, and the AI ​​module then suggests optimal tax-saving methods. The system is primarily comprised of three main components: the user, the terminal, and the server.

[1868] Collecting user input information

[1869] User

[1870] A user logs in to the system using a device such as a smartphone or computer.

[1871] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1872] Terminal

[1873] The terminal receives the user's input information and sends it to the server.

[1874] Analyzing user information and asking follow-up questions

[1875] server

[1876] The server receives the information sent by the user and activates the AI ​​module.

[1877] The AI ​​module analyzes the initial information and generates follow-up questions to gather more information if necessary.

[1878] Terminal

[1879] The terminal displays the additional question received from the server to the user.

[1880] User

[1881] The user answers the additional questions and sends them to the server via the terminal.

[1882] Detailed analysis and tax saving suggestions

[1883] server

[1884] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1885] The AI ​​module generates a list of optimal tax-saving strategies based on the user's individual circumstances.

[1886] The server accesses a database of experts to retrieve the latest tax saving cases.

[1887] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1888] Viewing Proposals

[1889] Terminal

[1890] The terminal displays the tax saving proposal received from the server to the user.

[1891] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[1892] Specific examples

[1893] 1. Enter your user information

[1894] User A logs into the system for the first time and provides the following information:

[1895] Marital status: Yes

[1896] Number of dependents: 2

[1897] Mortgage status: Currently in use

[1898] Annual income: 9 million yen

[1899] Other deductions (e.g., insurance enrollment status)

[1900] 2. Generate and answer follow-up questions

[1901] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[1902] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[1903] 3. Detailed analysis and generation of tax saving suggestions

[1904] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[1905] Spousal deductions can save you 300,000 yen a year in taxes.

[1906] Dependent deductions allow for a deduction of 380,000 yen per year.

[1907] Home loan deduction of 400,000 yen per year.

[1908] Insurance premium deduction of 100,000 yen per year.

[1909] 4. Display of proposals

[1910] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[1911] In this way, the system provides users with customized tax-saving suggestions and offers them ways to increase their take-home pay, making it easier for them to find tax-saving methods that suit them and enabling them to achieve effective tax savings.

[1912] The processing flow will be explained below.

[1913] Step 1:

[1914] User

[1915] A user logs in to the system using a device such as a smartphone or computer.

[1916] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1917] Step 2:

[1918] Terminal

[1919] The terminal receives the user's input information and sends it to the server.

[1920] The terminal checks the communication status with the server, and if successful, proceeds to the next process.

[1921] Step 3:

[1922] server

[1923] The server prepares the received user information for analysis.

[1924] The server starts the AI ​​module and passes the user information to the AI.

[1925] The AI ​​module analyzes user information and generates follow-up questions as needed.

[1926] Step 4:

[1927] server

[1928] The server sends the generated follow-up question to the terminal.

[1929] Step 5:

[1930] Terminal

[1931] The terminal displays the additional question received from the server to the user.

[1932] Step 6:

[1933] User

[1934] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[1935] The user sends the answer to the server via the terminal.

[1936] Step 7:

[1937] Terminal

[1938] The terminal transmits the additional response received from the user to the server.

[1939] Step 8:

[1940] server

[1941] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1942] The AI ​​module performs detailed analysis and generates a list of tax-saving methods that are best suited to each user's individual situation.

[1943] Step 9:

[1944] server

[1945] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[1946] Step 10:

[1947] server

[1948] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[1949] Step 11:

[1950] server

[1951] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[1952] Step 12:

[1953] Terminal

[1954] The terminal displays the received proposal to the user.

[1955] It provides detailed tax-saving methods and procedures in a user-friendly interface.

[1956] Step 13:

[1957] User

[1958] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[1959] Example 1

[1960] 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."

[1961] In today's tax environment, it is difficult for individuals to find the right tax-saving methods. With a wide variety of tax laws and deductions, expertise is required to find the best tax-saving methods for each individual situation. However, hiring a tax professional is costly and time-consuming. To solve this problem, a system is needed that automatically suggests the best tax-saving methods based on information that the user simply enters.

[1962] 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.

[1963] In this invention, the server includes means for analyzing the initial information received from the user, generating additional questions and sending them to the terminal, means for the terminal to receive the user's additional answers and send them to the server, and means for the server to perform detailed analysis using an AI module based on all the information received and propose customized tax saving methods based on the user's individual circumstances. This allows the user to find the optimal tax saving method based on the information they simply input.

[1964] A "user" is an individual who uses the system to provide input information and receive tax-saving suggestions.

[1965] A "terminal" is an electronic device, such as a smartphone or computer, that a user uses to input information and send and receive data to and from a server.

[1966] The "server" is a central processing unit that receives user input information, analyzes it, and uses an AI module to suggest optimal tax-saving methods.

[1967] The "AI module" is an artificial intelligence system that analyzes input data and suggests optimal tax-saving methods tailored to the user's individual circumstances.

[1968] The "database" is a collection of information that stores the latest tax saving cases from experts and user input information, and is accessed by the server as needed.

[1969] "Analysis" is the process in which the AI ​​module analyzes data based on user input and derives the optimal tax-saving method.

[1970] "Additional questions" are questions generated by the AI ​​module to gather additional information needed by the user to suggest the best tax-saving methods.

[1971] "Tax saving methods" are specific techniques and procedures for optimal tax savings that the AI ​​module suggests to users through analysis.

[1972] MODE FOR CARRYING OUT THE INVENTION

[1973] System Overview

[1974] This invention is a system in which users input their tax information and information related to life events, and an AI module then suggests optimal tax-saving methods based on that information. The system is primarily composed of three main components: the user, the terminal, and the server.

[1975] Collecting user input information

[1976] User

[1977] A user logs in to the system using a device such as a smartphone or computer, using an email address and password as login information.

[1978] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[1979] Terminal

[1980] The device receives the user's input and sends it to the server, using a protocol (e.g., HTTPS) that transmits the data securely over the Internet.

[1981] Analyzing user information and asking follow-up questions

[1982] server

[1983] The server receives the information sent by the user and launches an AI module, which can use a machine learning framework implemented in Python (e.g., TensorFlow or PyTorch).

[1984] The server uses an AI module to analyze the initial information and generate follow-up questions to gather more detailed information.

[1985] Terminal

[1986] The terminal displays the follow-up questions received from the server to the user, for example, using an interface that displays form input or options.

[1987] User

[1988] The user answers the additional questions and sends them to the server via the terminal.

[1989] Detailed analysis and tax saving suggestions

[1990] server

[1991] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[1992] The AI ​​module generates a list of optimal tax-saving methods based on the user's individual circumstances, including spouse deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[1993] The server accesses a database of experts to retrieve the latest tax savings tips, including information on the latest tax laws and deductions.

[1994] The server combines the analysis results of the AI ​​module with expert data to generate specific tax-saving proposals tailored to the user.

[1995] Viewing Proposals

[1996] Terminal

[1997] The terminal displays the tax saving proposal received from the server to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[1998] Specific examples

[1999] 1. Enter your user information

[2000] User A logs into the system for the first time and provides the following information:

[2001] Marital status: Yes

[2002] Number of dependents: 2

[2003] Mortgage status: Currently in use

[2004] Annual income: 9 million yen

[2005] Other deductions (e.g., insurance enrollment status)

[2006] 2. Generate and answer follow-up questions

[2007] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[2008] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[2009] 3. Detailed analysis and generation of tax saving suggestions

[2010] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[2011] Spousal deductions can save you 300,000 yen a year in taxes.

[2012] Dependent deductions allow for a deduction of 380,000 yen per year.

[2013] Home loan deduction of 400,000 yen per year.

[2014] Insurance premium deduction of 100,000 yen per year.

[2015] 4. Display of proposals

[2016] The terminal displays these proposals to User A and provides the application methods and procedures for each deduction.

[2017] Example prompts for generative AI models

[2018] "The app suggests optimal tax-saving strategies based on the tax information and life events you enter. This includes information such as marital status, number of dependents, mortgage status, and annual income."

[2019] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2020] Step 1: User Login

[2021] User

[2022] A user accesses the system using a device such as a smartphone or computer and logs in by entering their email address and password.

[2023] Input: Email address, password

[2024] Output: Login request

[2025] Terminal

[2026] The terminal receives the user's login information and sends it to the server.

[2027] Input: Login request

[2028] Output: Login information (email address, password)

[2029] server

[2030] The server authenticates the received login information and, if authentication is successful, starts the user session.

[2031] Input: Login information (email address, password)

[2032] Output: Authentication result (success / failure), session start

[2033] Step 2: Enter initial information

[2034] User

[2035] After logging in, users enter initial information such as marital status, number of dependents, mortgage status, and annual income.

[2036] Input: Marital status, number of dependents, mortgage status, annual income

[2037] Output: Initial information

[2038] Terminal

[2039] The terminal receives the user's initial information and sends it to the server.

[2040] Input: Initial information

[2041] Output: Initial information (marriage status, number of dependents, mortgage status, annual income)

[2042] Step 3: Processing initial information

[2043] server

[2044] The server stores the received initial information in a database and launches an AI module to analyze the initial information.

[2045] Input: Initial information

[2046] Data processing and calculation: Saving to database, analysis by AI module

[2047] Output: Analysis results, additional questions if necessary

[2048] Step 4: Generate and present follow-up questions

[2049] server

[2050] Based on the initial information, the AI ​​module generates follow-up questions to gather more detailed information.

[2051] Input: Analysis results

[2052] Data processing and calculation: Generation of additional questions

[2053] Output: Additional questions

[2054] Terminal

[2055] The terminal displays the additional question received from the server to the user.

[2056] Input: Additional Question

[2057] Output: Show additional questions

[2058] User

[2059] The user answers the additional questions and sends them to the server via the terminal.

[2060] Input: Answer to additional question

[2061] Output: Additional answers

[2062] Terminal

[2063] The terminal receives the user's additional response and transmits it to the server.

[2064] Input: Additional Answer

[2065] Output: Additional answers

[2066] Step 5: Process additional information

[2067] server

[2068] The server stores the additional information it receives in a database and uses the AI ​​module again for further analysis.

[2069] Input: Additional Answer

[2070] Data processing and calculation: Saving to database, detailed analysis by AI module

[2071] Output: Detailed analysis results

[2072] Step 6: Generate tax savings

[2073] server

[2074] The AI ​​module analyzes each user's individual circumstances and generates a list of optimal tax-saving methods, including spousal deductions, dependent deductions, mortgage deductions, and insurance premium deductions.

[2075] The server accesses a database of experts to retrieve the latest tax-saving cases, and combines the analysis results of the AI ​​module with the expert data to generate specific tax-saving proposals tailored to the user.

[2076] Input: Detailed analysis results, expert data

[2077] Data processing and calculation: Creating a list of tax-saving methods, integrating data

[2078] Output: Tax Savings Suggestion

[2079] Step 7: Submit and view your proposal

[2080] server

[2081] The server generates tax saving suggestions and sends them to the terminal.

[2082] Input: Tax Savings Proposal

[2083] Output: Submit tax saving proposal

[2084] Terminal

[2085] The terminal displays the tax saving suggestions received to the user, and provides the user with detailed tax saving methods and procedures through a user-friendly interface.

[2086] Input: Tax Savings Proposal

[2087] Output: Display tax saving proposals

[2088] User

[2089] The user reviews the proposal and views specific steps and related information.

[2090] Input: Tax Savings Proposal

[2091] Output: User confirmation, viewing of proposals

[2092] (Application example 1)

[2093] 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."

[2094] Conventional tax-saving suggestion systems require users to spend a lot of time and effort to find the tax-saving method that best suits them. Furthermore, they lack the functionality to comprehensively analyze income and consumption history and suggest optimal tax-saving methods in real time, making it difficult for users to quickly obtain the latest tax-saving information. Furthermore, they lack immediate notifications about tax-saving opportunities and deadlines, which can lead to users missing important opportunities. This invention solves the above problems and provides a system that allows users to save on taxes more effectively.

[2095] 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.

[2096] In this invention, the server includes a means for inputting information including income data and consumption history, a means for analyzing the user's situation and proposing optimal tax-saving methods in real time, and a means for immediately notifying the user of tax-saving opportunities and deadlines. This allows the user to quickly obtain the latest tax-saving information that is appropriate for them. Furthermore, the server can collect necessary additional information and provide detailed tax-saving proposals via a user interface, helping the user to effectively achieve tax savings.

[2097] 1. "User" means a person who uses the system to receive tax saving suggestions.

[2098] 2. "Marital status" is information indicating whether the user is married or not.

[2099] 3. "Number of dependents" is information indicating the number of family members the user financially supports.

[2100] 4. "Mortgage usage status" is information indicating whether the user has taken out a loan to purchase a home.

[2101] 5. "Income Data" means information about a User's annual income or other income.

[2102] 6. "Consumption History" means a record of purchases made by a User through electronic payment.

[2103] 7. A "terminal" is a device, such as a smartphone or computer, that a user uses to input information.

[2104] 8. "Server" means a central computer that receives and analyzes information sent by users.

[2105] 9. "AI Module" means a software component that uses artificial intelligence to analyze the user's situation and generate optimal suggestions.

[2106] 10. The "Expert Database" is a data collection device that collects and manages the latest tax saving cases and legal information.

[2107] 11. A "tax saving method" is a specific means of reducing the amount of tax.

[2108] 12. "Real-time" is a term that indicates near-instant processing.

[2109] 13. "Tax Saving Opportunity" means an opportunity for a user to save on tax by taking a specific action or procedure.

[2110] 14. "Deadline" means the last date by which tax-related procedures must be carried out.

[2111] 15. "Notification" means the system notifying the user of new information or important deadlines.

[2112] 16. "Recommendations" refers to information generated by the AI ​​module regarding optimal tax saving methods.

[2113] 17. "User interface" means the system, including the screen and input devices, that allows a user to interact with a system.

[2114] 18. "Additional Information" is data requested from the user to obtain further details when the initial information is insufficient.

[2115] The embodiment of this invention is a system in which a user inputs various information, including income data and consumption history, and an AI module proposes optimal tax-saving methods in real time based on that data. This system consists of three main components: a user, a terminal, and a server.

[2116] Collecting user input information

[2117] Users log in to the system using a device such as a smartphone or computer. As an initial setup, the user enters information such as whether they have a spouse, the number of dependents, their mortgage loan status, their annual income, and their consumption history. This allows the system to obtain the user's basic tax information.

[2118] Data transmission and analysis

[2119] The device sends the information entered by the user to a cloud server. An AI module running on this cloud server analyzes the information entered by the user and prepares to propose optimal tax-saving methods. The AI ​​module used here uses a machine learning library such as TensorFlow. Based on the analyzed data, it generates follow-up questions to gather more detailed information.

[2120] Obtaining additional information and conducting detailed analysis

[2121] The server sends the generated follow-up questions to the terminal and displays them to the user. The user answers these questions, and the answer data is sent back to the server. The server then uses the AI ​​module again to perform a detailed analysis and propose the optimal tax-saving method based on the user's individual circumstances. The database used here is, for example, DynamoDB.

[2122] Stay informed and notified

[2123] The server retrieves the latest tax saving cases from a database of experts and combines them with the analysis results of the AI ​​module. Based on this integration result, the server immediately notifies users of tax saving opportunities and deadlines.

[2124] Displaying suggestions to users

[2125] The terminal displays the tax saving proposals received from the server to the user, providing detailed tax saving methods and procedures in an easy-to-understand format through a user-friendly interface.

[2126] Specific examples

[2127] For example, user A enters the following information: "annual income 9 million yen, married, two dependents, mortgage loan, annual insurance premium payment 100,000 yen." The AI ​​module then analyzes this information and generates a follow-up question: "What is the annual insurance premium payment?" If user A answers "100,000 yen," the AI ​​module analyzes again and generates the following proposal:

[2128] Spouse deduction: 300,000 yen tax savings

[2129] Dependent deduction: 380,000 yen deduction

[2130] Housing loan deduction: 400,000 yen deduction

[2131] Insurance premium deduction: 100,000 yen deduction

[2132] These suggestions are instantly sent to User A's smartphone, showing how to apply each deduction and the specific steps for the application process. In addition, the system also sends alerts about important tax-saving opportunities and deadlines for application.

[2133] Prompt Sentence Examples

[2134] Example prompt: "Please suggest the best tax-saving method based on the user's income and spending history."

[2135] In this way, the system helps users easily and quickly find the best tax saving method, enabling them to achieve effective tax savings.

[2136] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2137] Step 1:

[2138] Users log in to the system using a device such as a smartphone or computer and enter information such as marital status, number of dependents, mortgage status, annual income, consumption history, etc. At this time, the information entered by the user is collected through the device interface.

[2139] Step 2:

[2140] The device sends the information entered by the user to a cloud server. The input data includes marital status, number of dependents, mortgage status, annual income, consumption history, etc. The server stores the received data in a database.

[2141] Step 3:

[2142] The server launches an AI module to analyze the user's input. Specifically, it uses machine learning libraries such as TensorFlow to perform initial data analysis. The input here is the user data, and the output is the analysis results.

[2143] Step 4:

[2144] The server uses the analysis results to generate follow-up questions to gather more information. This process uses the user's initial data and the analysis results as inputs and generates follow-up questions as output.

[2145] Step 5:

[2146] The server generates additional questions and sends them to the terminal, which then displays them to the user. The displayed questions include, for example, "How much do you pay for insurance premiums per year?" The user answers the questions.

[2147] Step 6:

[2148] The user inputs the answers to the follow-up questions into the terminal, and the terminal sends the answer data to the server. The user's answers are stored as input data, and updated user information is stored as output data.

[2149] Step 7:

[2150] The server restarts the AI ​​module and re-analyzes all of the user's information. A detailed analysis is performed to determine the optimal tax-saving method. The input data is the updated user information, and the output data is the optimal tax-saving proposal.

[2151] Step 8:

[2152] The server accesses the expert database to obtain the latest tax saving examples. This ensures that the proposals are based on the latest information, improving reliability. The input data is the expert database, and the output data is the latest tax saving information.

[2153] Step 9:

[2154] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user. Here, an information integration algorithm is used to process the data and output the optimal tax-saving plan.

[2155] Step 10:

[2156] The server immediately notifies users of tax-saving opportunities and deadlines, and the terminal displays this information to them. Detailed tax-saving methods and procedures are provided to users through a user-friendly interface. Input data is the proposals from the server, and output data is the notification and display to the user.

[2157] Prompt Sentence Examples

[2158] "Please suggest the best tax saving method based on the user's income and consumption history."

[2159] These steps allow users to receive optimal tax saving suggestions in real time and achieve effective tax savings.

[2160] 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.

[2161] The present invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state, and an embodiment thereof will be described below.

[2162] System Overview

[2163] This system proposes optimal tax-saving methods based on the user's situation. Its main components are the user, device, server, emotion engine, and AI module. Information related to the user's life events is collected, and the AI ​​performs analysis based on that information. The emotion engine recognizes the user's emotions and adaptively changes the content of the proposals and the way they are displayed.

[2164] User input information collection and emotion recognition

[2165] User

[2166] A user logs in to the system using a device such as a smartphone or computer.

[2167] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[2168] Terminal

[2169] The terminal receives the user's input information and activates an emotion engine to analyze the user's emotional state.

[2170] The terminal transmits the user's input information and emotional state to the server.

[2171] Analyzing user information and asking follow-up questions

[2172] server

[2173] The server prepares the received user information for analysis.

[2174] The server activates the AI ​​module and passes user information and emotional state to the AI.

[2175] The AI ​​module analyzes user information and generates follow-up questions as needed.

[2176] Terminal

[2177] The terminal displays the additional question received from the server to the user.

[2178] User

[2179] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[2180] The user sends the answer to the server via the terminal.

[2181] Detailed analysis and tax saving suggestions

[2182] server

[2183] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[2184] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[2185] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[2186] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[2187] The server formats the proposal and sends it to the device.

[2188] Adjusting recommendations with an emotion engine

[2189] Terminal

[2190] The device integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adaptively changes the way the suggestions are displayed (e.g., pop-up messages, color changes, etc.).

[2191] Viewing Proposals

[2192] Terminal

[2193] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[2194] Specific examples

[2195] 1. Inputting user information and emotions

[2196] User A logs into the system for the first time and provides the following information and emotional state:

[2197] Marital status: Yes

[2198] Number of dependents: 2

[2199] Mortgage status: Currently in use

[2200] Annual income: 9 million yen

[2201] Emotional state: Excitement

[2202] 2. Generate and answer follow-up questions

[2203] The server inputs this information into an AI module, which then generates more detailed questions (e.g., "How much do you pay for insurance annually?").

[2204] User A answers additional questions (e.g., "Annual insurance premium payment: 100,000 yen"), and the terminal sends this to the server.

[2205] 3. Detailed analysis and generation of tax saving suggestions

[2206] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[2207] Spousal deductions can save you 300,000 yen a year in taxes.

[2208] Dependent deductions allow for a deduction of 380,000 yen per year.

[2209] Home loan deduction of 400,000 yen per year.

[2210] Insurance premium deduction of 100,000 yen per year.

[2211] 4. Display of proposals

[2212] Based on the analysis results of the emotion engine, the device adjusts the way the suggestions are displayed and presents them in a way that is more familiar to user A (e.g., if the emotion is joy, an encouraging message is added).

[2213] As a result, this system provides personalized tax-saving suggestions that take into account the user's emotional state, enabling users to obtain tax-saving information in a more effective and easy-to-understand manner.

[2214] The processing flow will be explained below.

[2215] Step 1:

[2216] User

[2217] A user logs in to the system using a device such as a smartphone or computer.

[2218] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[2219] Step 2:

[2220] Terminal

[2221] The device receives the user's input information and activates the emotion engine.

[2222] The device uses a camera and microphone to analyze the user's facial expressions and tone of voice to recognize their emotional state.

[2223] Step 3:

[2224] Terminal

[2225] The terminal transmits the user's input information and the recognized emotional state to the server.

[2226] Step 4:

[2227] server

[2228] The server prepares the received user information and emotional state for analysis.

[2229] The server activates the AI ​​module and passes user information and emotional state to the AI.

[2230] Step 5:

[2231] AI Module

[2232] The AI ​​module analyzes user information and generates follow-up questions as needed.

[2233] The server sends the generated follow-up question to the terminal.

[2234] Step 6:

[2235] Terminal

[2236] The terminal displays the additional question received from the server to the user.

[2237] Step 7:

[2238] User

[2239] The user answers additional questions (e.g., more information such as "How much do you pay for insurance annually?").

[2240] The user sends the answer to the server via the terminal.

[2241] Step 8:

[2242] Terminal

[2243] The terminal transmits the additional response received from the user to the server.

[2244] Step 9:

[2245] server

[2246] Based on the additional information received by the server, the AI ​​module is used again to perform a detailed analysis.

[2247] The AI ​​module generates a list of tax-saving methods that are best suited to each user's individual situation.

[2248] Step 10:

[2249] server

[2250] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information.

[2251] Step 11:

[2252] server

[2253] The server combines the AI ​​analysis results with expert data to generate specific tax-saving proposals tailored to the user.

[2254] Step 12:

[2255] server

[2256] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal.

[2257] Step 13:

[2258] Terminal

[2259] The device passes the tax saving suggestions received from the server to the emotion engine, which customizes how the tax saving suggestions are displayed based on the user's emotional state (e.g., adding an encouraging message if the user is feeling stressed).

[2260] Step 14:

[2261] Terminal

[2262] The terminal displays detailed tax saving methods and procedures in a user-friendly interface.

[2263] Step 15:

[2264] User

[2265] The user can check the proposals through their device and take specific actions to increase their take-home pay.

[2266] Example 2

[2267] 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."

[2268] In today's world, many users find it difficult to obtain appropriate information on financial management and tax-saving methods and make optimal decisions. Providing uniform information without considering the user's emotional state can lead to stress and prevent appropriate decision-making. Furthermore, there is a need for timely, customized tax-saving proposals tailored to the user's specific circumstances.

[2269] 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.

[2270] In this invention, the server includes: means for a user to input information such as marital status, number of dependents, mortgage usage status, and annual income using a terminal; means for the terminal to transmit the information and emotional state input by the user to the server; means for the server to store the received user information and emotional state for analysis; means for the server to activate an AI module and use it to analyze the user information and emotional state; means for the server to generate necessary follow-up questions based on the analysis results and transmit them to the terminal; means for the terminal to display the received follow-up questions to the user; means for the terminal to transmit the user's follow-up answers to the server; means for the server to perform detailed analysis using the AI ​​module and obtain the latest tax saving examples and tax system information from an expert database; means for the server to generate specific tax saving suggestions optimal for the user and transmit them to the terminal; and means for the terminal to adjust the display method of the suggestions using an emotion engine and display them to the user. This makes it possible to provide personalized tax saving suggestions tailored to the user's specific situation and support the user in making appropriate decisions.

[2271] "User" refers to an individual who inputs and receives information into the system.

[2272] "Terminal" refers to a device that allows a user to input information and send and receive data to and from a server.

[2273] "Server" refers to the central system that processes information received from users and works with AI modules and databases to analyze and make recommendations.

[2274] "Emotional state" refers to information that indicates the user's current state of mind or mood.

[2275] "AI Module" refers to an artificial intelligence program used to analyze user information and emotional state and suggest tax-saving methods.

[2276] "Analysis" refers to the process of analyzing information collected from users using an AI module and obtaining the results.

[2277] "Tax saving methods" refer to specific means and measures to reduce the tax burden.

[2278] "Expert database" refers to an external database that collects and stores the latest tax saving cases and tax system information.

[2279] "Additional questions" refer to questions that the AI ​​module asks the user to gather new information during the analysis process.

[2280] "Format" refers to the format or style used to organize and present information or proposals in an easy-to-read manner.

[2281] An "emotion engine" refers to a program that recognizes a user's tone of voice and facial expressions to analyze their emotional state.

[2282] MODE FOR CARRYING OUT THE INVENTION

[2283] The present invention is a system for proposing optimal tax-saving methods based on information and emotional state input by a user. An embodiment of the system will be described in detail below.

[2284] System configuration

[2285] The main components of this system are a user, a terminal, a server, an emotion engine, and an AI module.

[2286] Collecting user input information

[2287] User

[2288] Users log in to the system using a device such as a smartphone or computer, and enter information such as marital status, number of dependents, mortgage status, and annual income as part of the initial setup.

[2289] The user's input information is sent to the terminal.

[2290] Terminal

[2291] The device activates an emotion engine that analyzes the user's tone of voice and facial expressions to determine their emotional state.

[2292] Data transmission and analysis

[2293] Terminal

[2294] The terminal transmits the information and emotional state received from the user to the server.

[2295] server

[2296] The server stores the received information in a temporary database and prepares it for analysis.

[2297] Activate the AI ​​module to analyze user information and emotional state.

[2298] Generate new questions for the user regarding the additional information needed.

[2299] Collecting additional information

[2300] Terminal

[2301] The terminal displays the follow-up questions received from the server to the user.

[2302] User

[2303] The user answers the additional questions and transmits the answers to the server via the terminal.

[2304] server

[2305] The server stores the additional information it receives in a database and then uses the AI ​​module again for further analysis.

[2306] Proposal of optimal tax saving methods

[2307] server

[2308] The server uses an AI module to generate a list of optimal tax saving methods for the user.

[2309] Access our expert database for the latest tax savings and tax information.

[2310] The AI ​​analysis results are combined with expert data to generate specific tax-saving suggestions for users.

[2311] The proposal is formatted appropriately and sent to the device.

[2312] Viewing Proposals

[2313] Terminal

[2314] It uses an emotion engine to tailor how suggestions are displayed, for example, if the user is "excited," it will display a pop-up with an encouraging message.

[2315] It provides users with detailed tax saving methods and procedures through a user-friendly interface.

[2316] Specific examples

[2317] 1. Inputting user information and emotions

[2318] User A logs into the system for the first time and provides the following information and emotional state:

[2319] Marital status: Yes

[2320] Number of dependents: 2

[2321] Mortgage status: Currently in use

[2322] Annual income: 9 million yen

[2323] Emotional state: Excitement

[2324] 2. Generate and answer follow-up questions

[2325] The server inputs this information into an AI module, which then generates follow-up questions such as, "How much do you pay in insurance premiums per year?"

[2326] User A responds, "Annual insurance premium payment: 100,000 yen," and the terminal sends this to the server.

[2327] 3. Detailed analysis and generation of tax saving suggestions

[2328] The server uses an AI module to analyze all of User A's information and generate the following tax saving suggestions:

[2329] Spousal deductions can save you 300,000 yen a year in taxes.

[2330] Dependent deductions allow for a deduction of 380,000 yen per year.

[2331] Home loan deduction of 400,000 yen per year.

[2332] Insurance premium deduction of 100,000 yen per year.

[2333] 4. Display of proposals

[2334] Based on the analysis results of the emotion engine, the device adjusts how the suggestions are displayed. For example, if the emotion is joy, an encouraging message will be added.

[2335] An example prompt is:

[2336] "Describe the natural language processing process for a system that suggests optimal tax-saving strategies based on user information and emotional state."

[2337] "Please explain the process of the system that generates follow-up questions based on the user's situation and emotional state and performs detailed analysis."

[2338] As a result, this system makes personalized tax-saving suggestions that take into account the user's emotional state, allowing the user to obtain tax-saving information that is easy to understand and optimal for them.

[2339] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2340] Step 1:

[2341] A user logs in to the system using a smartphone or computer terminal. By entering their username and password as login information, authentication is performed and the user is able to access the system. Input: Username, password. Output: Authentication result.

[2342] Step 2:

[2343] The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. This records the user's basic financial situation in the system. Input: Marital status, number of dependents, mortgage status, annual income. Output: Saves the initial information.

[2344] Step 3:

[2345] The device passes the initial setting information received from the user to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to determine the user's emotional state. Input: Initial setting information. Output: Emotional state.

[2346] Step 4:

[2347] The device sends the initial setting information and emotional state to the server. The server stores the received information in a temporary database. Input: Initial setting information, emotional state. Output: Stored in the database.

[2348] Step 5:

[2349] The server passes the received information to the AI ​​module, which analyzes the user's information and emotional state. The AI ​​module determines whether additional information is needed based on the user's financial situation and emotional state. Input: Initial setting information, emotional state. Output: Generation of additional questions.

[2350] Step 6:

[2351] The terminal displays the follow-up question received from the server to the user. For example, a question such as "How much is the annual insurance premium payment?" is displayed to the user. Input: Follow-up question. Output: Display of follow-up question.

[2352] Step 7:

[2353] The user answers the additional questions displayed and sends the answers to the server via the terminal. For example, the user answers "Annual insurance premium payment: 100,000 yen." Input: Answer to additional question. Output: Send to server.

[2354] Step 8:

[2355] The server stores the received additional information in a database and uses the AI ​​module again for further analysis. The AI ​​module analyzes all the data and lists the optimal tax saving methods. Input: Additional information. Output: List of tax saving suggestions.

[2356] Step 9:

[2357] The server accesses a database of affiliated experts to obtain the latest tax saving examples and tax system information. The obtained information is integrated with the results of AI analysis to generate specific tax saving proposals. Input: Information from the expert database, AI analysis results. Output: Specific tax saving proposals.

[2358] Step 10:

[2359] The server formats the generated tax saving proposals into an appropriate format and sends them to the terminal. Input: Tax saving proposals. Output: Proposal content after formatting.

[2360] Step 11:

[2361] The device uses the emotion engine to adjust how the suggestion is displayed. For example, if the user is "excited," it will add an encouraging message and display a pop-up. Input: Formatted suggestion, emotional state. Output: Display of the adjusted suggestion.

[2362] Step 12:

[2363] The terminal provides the user with detailed tax-saving methods and procedures through a user-friendly interface. The user can take specific actions based on the suggestions presented. Input: Adjusted suggestions. Output: Presentation to the user.

[2364] (Application example 2)

[2365] 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."

[2366] It is generally difficult for users to properly understand their own tax situation and find the optimal tax-saving method. Furthermore, it has not been taken into consideration that users' emotional state can affect how they accept the proposed method. Furthermore, there has been no attempt to predict the tax-saving effect using user purchase data, making it a challenge to quickly and appropriately provide users with advantageous tax-saving methods.

[2367] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the terminal to recognize the emotional state of the user, a means for the terminal to adjust the display method of the proposal content received from the server according to the emotional state of the user and display it, and a means for the terminal to collect the user's purchase data and predict the tax saving effect. This makes it possible to provide the optimal tax saving method in a timely manner while taking the user's emotional state into consideration, and further to make specific tax saving proposals based on the user's purchase history.

[2368] A "user" is a person who uses the system and is the entity that inputs information about tax status and emotional state.

[2369] A "terminal" is an electronic device, such as a smartphone or computer, that allows users to input information and collect emotional and purchasing data.

[2370] "Emotional state" refers to the user's current psychological state, and analyzing this information is used to adjust how the user accepts the proposed content.

[2371] The "server" is a central management system that receives input information and emotional state from users, analyzes it using an AI module, and calculates and provides the optimal tax-saving method.

[2372] The "AI module" is a program with artificial intelligence functions that analyzes the user's input information and emotional state, and generates necessary follow-up questions and tax-saving suggestions.

[2373] The "expert database" is a database that stores the latest tax information and tax saving examples, from which the server can retrieve information.

[2374] "Tax saving methods" refer to specific means and methods for reducing the user's tax burden, including spousal deductions, dependent deductions, and mortgage deductions.

[2375] "Purchase data" is information about the products and services purchased by users, and analyzing this information can predict the tax savings effect.

[2376] "Tax Savings" refers to the tax reduction or other benefit that a user may obtain as a result of a proposed tax saving method.

[2377] This invention is a system that proposes optimal tax-saving methods based on the user's input information and emotional state. A specific embodiment of this system is described below. The main components are a user, a terminal, a server, an emotion engine, and an AI module.

[2378] User input information collection and emotion recognition

[2379] User

[2380] Users log in to the system using devices such as smartphones or computers.

[2381] As an initial setting, the user enters information such as whether they have a spouse, the number of dependents, their mortgage usage status, and their annual income.

[2382] When the user inputs this information through the terminal, the terminal activates an emotion engine to analyze the user's emotional state.

[2383] Terminal

[2384] The terminal transmits the user's input information and emotional state to the server.

[2385] The terminal also collects the user's purchasing data and transmits it to the server.

[2386] Analyzing user information and asking follow-up questions

[2387] server

[2388] The server prepares for analysis the information received from the user.

[2389] The AI ​​module performs further analysis based on user information and emotional state.

[2390] If necessary, the server generates and sends additional questions to the terminal.

[2391] Terminal

[2392] The terminal displays the follow-up questions received from the server to the user.

[2393] User

[2394] The user answers the additional questions and sends them to the server via the terminal.

[2395] Detailed analysis and tax saving suggestions

[2396] server

[2397] The server uses an AI module to perform detailed analysis and generate a list of tax-saving methods that are best suited to the user's situation.

[2398] The server also retrieves the latest tax savings tips and tax information from a database of experts.

[2399] The AI ​​analysis results are integrated with expert data to generate specific tax-saving proposals tailored to the user.

[2400] Adjusting recommendations with an emotion engine

[2401] Terminal

[2402] The terminal integrates the tax saving suggestions received from the server with the analysis results of the emotion engine, and adjusts the way the suggestions are displayed according to the user's emotional state.

[2403] Displaying proposals and utilizing purchasing data

[2404] Terminal

[2405] It provides users with detailed tax-saving methods and procedures through a user-friendly interface.

[2406] The terminal also displays predicted tax savings based on the user's purchasing data.

[2407] Specific examples

[2408] For example, suppose User A logs into the system for the first time and provides the following information and emotional state:

[2409] Marital status: Yes

[2410] Number of dependents: 2

[2411] Mortgage status: Currently in use

[2412] Annual income: 9 million yen

[2413] Emotional state: Excitement

[2414] The server inputs this information into the AI ​​module and generates a more detailed question (e.g., "Annual insurance premium payment amount"). When User A answers this additional question (e.g., "Annual insurance premium payment amount: 100,000 yen") and sends the information to the server, the server performs a detailed analysis and generates a tax saving proposal like the following:

[2415] Spousal deductions can save you 300,000 yen a year in taxes.

[2416] Dependent deductions allow for a deduction of 380,000 yen per year.

[2417] Home loan deduction of 400,000 yen per year.

[2418] Insurance premium deduction of 100,000 yen per year.

[2419] The suggestions are tailored based on the user's emotional state and presented to the user in a friendly way: for example, if the emotion is joyful, an encouraging message can be added.

[2420] Prompt Sentence Examples

[2421] "User ID: 12345 Marital status: Yes Number of dependents: 2 Annual income: 8 million yen Planned purchase: Home appliances (TV) Emotional state: Happy Analyze the optimal tax-saving method for this user and create a proposal."

[2422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2423] Step 1:

[2424] The user logs into the system using a smartphone or computer. The user enters initial information such as marital status, number of dependents, mortgage status, and annual income. The entered information is received by the terminal.

[2425] Input: User's initial information (married status, number of dependents, mortgage status, annual income)

[2426] Output: Initial information saved on the device

[2427] Specific operation: The user logs in and provides information using an interface for entering initial information.

[2428] Step 2:

[2429] The device sends the user's input information to the server. At the same time, the device's emotion engine is activated and analyzes the user's emotional state. The emotion engine uses the smartphone's camera and sensors to analyze the user's facial expressions and voice.

[2430] Input: User's initial information and camera video or audio data

[2431] Output: Initial information and emotion data sent to the server

[2432] Specific operation: The user's input information and video / audio data are sent from the terminal to the server.

[2433] Step 3:

[2434] The server prepares the received user information and emotional data for analysis. The server launches the AI ​​module and passes the user information and emotional state to the AI. The AI ​​module analyzes the user information and generates follow-up questions as needed.

[2435] Input: User's initial information and emotional data

[2436] Output: Additional Question List

[2437] Specific operation: The server uses an AI module to analyze user information and emotional data and generate additional questions.

[2438] Step 4:

[2439] The terminal displays the additional questions received from the server to the user, and the user answers the additional questions and transmits the answers to the server via the terminal.

[2440] Input: Additional Question List

[2441] Output: User response information

[2442] Specific operation: The terminal displays additional questions to the user, and the user enters additional information and sends it to the server.

[2443] Step 5:

[2444] Based on the additional information received, the server uses the AI ​​module again to perform a detailed analysis. The server retrieves the latest tax saving examples and tax system information from a database of experts and generates a list of tax saving methods that are optimal for the user.

[2445] Input: Additional information for the user

[2446] Output: A list of the best ways to save tax

[2447] Specific operation: The server accesses an expert database to obtain the latest tax saving information, and then analyzes the information using an AI module.

[2448] Step 6:

[2449] The device integrates the tax-saving proposals received from the server with the analysis results of the emotion engine, adjusts the way the proposals are displayed, and presents them to the user. The proposals are displayed in a friendly manner according to the user's emotional state.

[2450] Input: Tax saving proposal content and sentiment analysis results

[2451] Output: Tax saving suggestions with adjusted presentation

[2452] Specific operation: Based on the results of emotion analysis, the device appropriately adjusts the suggestions and displays them to the user.

[2453] Step 7:

[2454] The device collects the user's purchasing data and displays a predicted tax savings effect. The purchasing data is information about the products and services purchased by the user. The device sends this data to the server, and the AI ​​module predicts the tax savings effect.

[2455] Input: User's purchasing data

[2456] Output: Predicted tax savings

[2457] Specific operation: The terminal collects the user's purchasing history, and the server uses this information to predict tax savings and presents them to the user.

[2458] 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.

[2459] 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.

[2460] 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.

[2461] 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.

[2462] 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.

[2463] 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.

[2464] 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).

[2465] 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.

[2466] 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."

[2467] 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.

[2468] 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).

[2469] 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.

[2470] 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.

[2471] 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.

[2472] 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.

[2473] 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.

[2474] 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.

[2475] 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.

[2476] 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.

[2477] 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, in order to avoid confusion and to 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.

[2478] 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.

[2479] The following is further disclosed regarding the above embodiment.

[2480] (Claim 1)

[2481] A means for users to input marital status, number of dependents, and mortgage status;

[2482] A means for the terminal to transmit information input by a user to a server;

[2483] The server uses an AI module to analyze the user's situation,

[2484] A means for the server to obtain the latest tax saving cases from a database of experts;

[2485] A means for the server to suggest optimal tax-saving methods to users;

[2486] and means for displaying to the user the proposals received by the terminal from the server.

[2487] (Claim 2)

[2488] means for generating and sending follow-up questions to the user;

[2489] and means for transmitting the user's additional answers to the server.

[2490] (Claim 3)

[2491] 10. The system of claim 1, further comprising means for customizing the results analyzed by the AI ​​module based on a user's individual circumstances.

[2492] "Example 1"

[2493] (Claim 1)

[2494] A means for users to input marital status, number of dependents, and mortgage status;

[2495] A means for the terminal to transmit information input by a user to a server;

[2496] The server uses an AI module to analyze the user's situation,

[2497] A means for the server to obtain the latest tax saving cases from a database of experts;

[2498] A means for the server to suggest optimal tax-saving methods to users;

[2499] and means for displaying to the user the proposals received by the terminal from the server.

[2500] (Claim 2)

[2501] A means for the server to analyze the initial information received from the user, generate a follow-up question, and transmit the question to the terminal;

[2502] 10. The system of claim 1, further comprising: means for the terminal to receive and transmit to the server additional answers from the user.

[2503] (Claim 3)

[2504] The system of claim 1 further comprising means for using an AI module to perform detailed analysis based on all information received by the server and suggest customized tax-saving methods based on the user's individual circumstances.

[2505] "Application Example 1"

[2506] (Claim 1)

[2507] a means for the user to input marital status, number of dependents, mortgage status, income data and consumption history;

[2508] A means for the terminal to transmit information input by a user to a server;

[2509] The server uses an AI module to analyze the user's situation and propose the best tax-saving method in real time.

[2510] A means for the server to obtain the latest tax saving cases from a database of experts;

[2511] The server provides a means for users to instantly notify them of tax-saving opportunities and deadlines.

[2512] a means for displaying the proposal received by the terminal from the server to the user and providing specific methods for each procedure;

[2513] means for the terminal to collect additional information via a user interface and transmit the information to the server;

[2514] A system including:

[2515] (Claim 2)

[2516] means for generating and sending follow-up questions to the user and sending follow-up answers from the user to the server;

[2517] a means of analyzing payment history;

[2518] 10. The system of claim 1, comprising:

[2519] (Claim 3)

[2520] The system according to claim 1, further comprising means for customizing the results analyzed by the AI ​​module based on the individual circumstances of the user and generating a prompt sentence.

[2521] "Example 2: Combining Emotion Engines"

[2522] (Claim 1)

[2523] A means for the user to input information such as marital status, number of dependents, mortgage status, and annual income using a terminal;

[2524] means for the terminal to transmit information and emotional state input by the user to a server;

[2525] means for the server to store the received user information and emotional state for analysis;

[2526] means used by the server to activate the AI ​​module and analyze user information and emotional state;

[2527] a means for the server to generate necessary follow-up questions based on the analysis results and transmit the questions to the terminal;

[2528] means for displaying the received follow-up question to the user in the terminal;

[2529] means for the terminal to transmit the user's additional answers to the server;

[2530] The server uses an AI module to perform detailed analysis and obtain the latest tax saving examples and tax system information from an expert database.

[2531] A means for the server to generate a specific tax saving proposal that is optimal for the user and transmit it to the terminal;

[2532] The system includes a means for the terminal to adjust the display method of the suggestion content using the emotion engine and display it to the user.

[2533] (Claim 2)

[2534] A means for customizing the results analyzed by the AI ​​module based on the user's individual circumstances; and

[2535] 10. The system of claim 1, further comprising means for adaptively modifying the display of suggestions using an emotion engine.

[2536] (Claim 3)

[2537] means for generating and sending follow-up questions to the user; and

[2538] 10. The system of claim 1, further comprising means for transmitting the user's additional responses to the server.

[2539] "Application example 2 when combining emotion engines"

[2540] (Claim 1)

[2541] A means for users to input marital status, number of dependents, and mortgage status;

[2542] A means for the terminal to transmit information input by a user to a server;

[2543] means for the terminal to recognize the emotional state of the user;

[2544] The server uses an AI module to analyze the user's situation,

[2545] A means for the server to obtain the latest tax saving cases from a database of experts;

[2546] A means for the server to suggest optimal tax-saving methods to users;

[2547] a means for adjusting a display method of the proposal content received by the terminal from the server in accordance with the emotional state of the user and displaying the content;

[2548] The terminal collects user purchasing data and predicts tax savings.

[2549] A system including:

[2550] (Claim 2)

[2551] means for generating and sending follow-up questions to the user and collecting responses;

[2552] means for transmitting the user's additional responses to the server;

[2553] 10. The system of claim 1, further comprising: means for the terminal to display the suggestions in a user-friendly manner.

[2554] (Claim 3)

[2555] A means for customizing the results analyzed by the AI ​​module based on the user's individual circumstances;

[2556] 2. The system according to claim 1, further comprising means for predicting tax saving e...

Claims

1. A means for users to input marital status, number of dependents, and mortgage status; A means for the terminal to transmit information input by a user to a server; The server uses an AI module to analyze the user's situation, A means for the server to obtain the latest tax saving cases from a database of experts; A means for the server to suggest optimal tax-saving methods to users; and means for displaying to the user the proposals received by the terminal from the server.

2. means for generating and sending follow-up questions to the user; and means for transmitting the user's additional answers to the server.

3. The system of claim 1 , further comprising means for customizing the results analyzed by the AI ​​module based on a user's individual circumstances.

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