system

Abstract

We provide the system. [Solution] A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift, A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift, A means of obtaining information from an external database to propose the most suitable tax deductions and return gifts based on donation amounts and return gift information, A method using an optimization algorithm that proposes suitable municipalities and return gifts to users based on acquired data, Based on the proposed information, a means to automate the donation process, A means of seamlessly completing donations through electronic payment functions, A means of notifying users of donations and processing results, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When using hometown tax payment, many users need to spend time and effort on complex procedures and the selection of optimal return gifts. Therefore, users who have no time or feel the procedures are troublesome tend to hesitate to use it. Furthermore, it is difficult to collect information for obtaining optimal tax deductions, and there is a problem that it is difficult for users to achieve efficient donations. It is an object of the present invention to solve these problems and enable users to effectively utilize hometown tax payment.

Means for Solving the Problems

[0005] This invention includes means for acquiring input information regarding donation amounts and return gift selections from a user terminal, and means for collecting the latest data on hometown tax donations from an external database. Furthermore, it provides means for suggesting suitable municipalities and return gifts to users by using an optimization algorithm to propose the most suitable tax deductions and return gifts based on the acquired data. In addition, by including means for automating the donation procedure and notifying the user of the donation and processing results, it significantly reduces the time and effort required compared to conventional methods, enabling effective use of hometown tax donations.

[0006] A "user terminal" is a device used by a user to input information and communicate with the system.

[0007] "Input information" refers to data that users provide to the system regarding donation amounts and the selection of return gifts.

[0008] An "external database" is an external information resource that holds the latest information on local governments, return gifts, and tax deductions related to the Furusato Nozei (hometown tax donation) system.

[0009] An "optimization algorithm" is a mathematical method that processes collected data in order to suggest the most suitable donation plan and reward to the user.

[0010] A "local government" refers to a local public entity that is eligible to receive donations under the Furusato Nozei (hometown tax) system.

[0011] A "return gift" is an item or service that a donor receives in return for paying taxes.

[0012] "Automating the donation process" refers to a system automatically executing the necessary donation processes based on the user's choices.

[0013] "Notification" refers to a means of communicating information to users regarding donations and processing results. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system for effectively utilizing the Furusato Nozei (hometown tax donation) system. It allows users to easily input information regarding their desired donation amount and return gifts, and based on that information, provides optimal suggestions and procedures, thereby reducing the burden on users.

[0036] The main components of the system include user terminals, a server, and an external database. The user terminal has an interface for users to provide input information and can communicate with the server. When a user enters their desired donation amount and return gift into the terminal, that data is sent to the server.

[0037] The server retrieves municipality information and gift information from an external database based on the donation amount and the selected gift. Then, an optimization algorithm built into the server calculates the donation plan best suited to the user's needs. At this stage, past donation history and user preferences are also considered to generate individually personalized suggestions.

[0038] Once a proposal is generated, the server sends the information to the user's terminal, and the user reviews the proposed plan. If the user selects a proposal, the server automatically initiates and executes the donation process and monitors its progress.

[0039] For example, if a user sets their donation amount to 15,000 yen and expresses a preference for local specialty products, the system will suggest a list of appropriate municipalities and specialty products. For instance, it might offer options such as local rice or a beef set. If the user selects the beef set, the server automates the donation process and manages the entire process until the selected gift is sent.

[0040] In this way, the present invention greatly improves the convenience of the hometown tax donation system while minimizing the time and effort required from the user.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uses their device to enter information such as the donation amount, the type of return gift they want, and their past donation history. Once the user has finished entering the information, it is sent from the device to the server.

[0044] Step 2:

[0045] The server accesses an external database to collect the latest information on local governments and return gifts. This includes a list of local governments that accept donations and details of the return gifts currently offered.

[0046] Step 3:

[0047] The server uses AI-powered optimization algorithms based on collected data and user information. These algorithms calculate the optimal combination of recipient municipalities and return gifts, as well as the expected tax deductions.

[0048] Step 4:

[0049] The server sends the optimized results to the user's terminal and proposes donation plans for the user to choose from. The proposals include detailed information about each option, such as an introduction to the local government and the features of the return gifts.

[0050] Step 5:

[0051] The user reviews the proposal on their device and selects their preferred donation plan. This selection is then sent back to the server via the device.

[0052] Step 6:

[0053] The server automatically initiates the donation process based on the selected donation plan. This includes submitting the donation application to the local government and preparing the relevant documents electronically.

[0054] Step 7:

[0055] The server notifies the user's device that the donation process is complete. At the same time, it also provides the shipping schedule and tracking information for the thank-you gift.

[0056] Through these steps, users can make hometown tax donations efficiently and easily.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] The process of making a donation through the Furusato Nozei (hometown tax) system is a significant burden for users because it requires a lot of information, time, and effort. In particular, selecting the optimal donation destination and return gift, and ensuring a smooth process through automated procedures, is not easy. Therefore, the challenge is to improve user convenience and provide an efficient and personalized donation process.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for receiving input information from a computing device and acquiring user input data including donation amount and return gift selection; means for acquiring information from external sources for proposing the optimal refund and return gift based on the donation amount and return gift information; and means for using the acquired data to perform an optimization process that proposes organizations and return gifts suitable for the user. As a result, users can efficiently select recipient organizations and return gifts, and complete the optimal donation procedure in a short time through individually tailored suggestions.

[0062] A "computational device" refers to a device used to input and transmit information in order to improve convenience.

[0063] "User input data" refers to information provided by users, including donation amounts and selections of return gifts.

[0064] "External information sources" refer to external databases or information provision systems accessed to obtain information about refunds and return gifts related to donations.

[0065] "Optimization process" refers to the algorithms and calculation methods used to determine the most suitable donation plan for each user.

[0066] "Refund" refers to the tax deduction or economic benefit obtained as a result of a donation.

[0067] "Organization" refers to the local government or other organizations to which users can make donations.

[0068] "Return gifts" refer to goods or services provided in response to a donation.

[0069] "Monitoring measures" refer to methods and devices for tracking the progress of donation procedures in real time and detecting and correcting malfunctions.

[0070] This system simplifies the hometown tax donation process by allowing users to input donation information via a computer and receive suggestions for efficient and optimized donation plans. A specific implementation of this system is described below.

[0071] Terminal role

[0072] The terminal provides an interface for users to input donation amounts and desired return gifts. To fulfill this role, the terminal is typically a computing device such as a computer or smartphone connected to the internet. The information entered from the terminal is transmitted to the server as data packets.

[0073] Server Role

[0074] The server receives user input data transmitted from the computing device and uses that data to access external information sources to obtain relevant refund and return gift information. In this process, database queries such as SQL are used to quickly extract the necessary data. Furthermore, the server uses optimization processing to perform calculations to determine the most suitable organizations and return gifts for the user.

[0075] The server also automates the donation process and monitors its progress in real time. In the event of a malfunction, corrective action is taken immediately and users are notified.

[0076] Specific example

[0077] For example, if a user enters a prompt indicating a donation amount of 15,000 yen and a request for a beef set as a local specialty product, the server will use this information to generate a list of the most relevant organizations and specialty products. The user then selects the beef set from the suggested list, and the server automatically proceeds with the donation process based on that selection. Throughout this entire process, the user is notified of the progress in real time.

[0078] Example of a prompt

[0079] "I would like to donate 15,000 yen and receive a beef set as a local specialty. Please suggest the most suitable organization and gift."

[0080] In this way, the system aims to reduce the burden on users and significantly streamline the process of making hometown tax donations.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user enters the donation amount and desired return gift through a calculator. The entered information is received as numerical data (donation amount) and text data (return gift name). The specific action here is for the user to type the information into the form and click the "Submit" button. The input data is formatted in JSON format.

[0084] Step 2:

[0085] The terminal sends data entered by the user to the server. Here, the data is encrypted and securely transmitted to the server using the HTTPS protocol. Specifically, the data is packetized and sent over the network.

[0086] Step 3:

[0087] The server checks the user input data received from the terminal and issues database queries to external information sources. Based on the donation amount and return gift information received as input, it retrieves a list of potential donation recipients and return gifts. The server generates SQL statements, extracts the necessary records from the external database, and obtains a dataset as output.

[0088] Step 4:

[0089] The server uses the acquired dataset to perform optimization processing. Specifically, it uses a generative AI model to calculate the donation value of each candidate and selects the plan that best suits user needs. The input is the dataset, and the output is the calculated optimal donation plan.

[0090] Step 5:

[0091] The server sends an optimized donation plan to the terminal. The output data is text information containing details of the proposed recipient and reward. Specifically, the data is returned to the terminal as an HTTP response.

[0092] Step 6:

[0093] The user reviews and selects a plan from the options presented on their device. The selection is sent to the server as information about the chosen recipient and the return gift. Specifically, the user clicks on an option on the screen to confirm their selection.

[0094] Step 7:

[0095] The server automates the donation process based on the user's selections. It processes online payments based on the submitted selection data and confirms the completion of the donation. Specific actions include calling payment APIs and monitoring the success / failure status of the process.

[0096] Step 8:

[0097] The server monitors the completion of the donation process and the preparation status of the thank-you gift shipment in real time, and notifies the user. Specifically, the server generates status update information and sends it to the user's terminal to inform the user of the progress. The output includes a notification that includes a donation completion message and an estimated delivery date and time.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] The challenges in the Furusato Nozei (hometown tax donation) system include the complexity of the donation process for users, the difficulty in receiving optimal suggestions, and the need to reduce the hassle of payment procedures. Furthermore, these efforts should encourage donations and improve the user experience.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including donation amount and return gift selection; means for acquiring information from an external database for proposing the most suitable tax deduction and return gift based on the donation amount and return gift information; means for using an optimization algorithm that proposes a suitable municipality and return gift to the user using the acquired data; means for automating the donation procedure based on the proposed information; means for seamlessly completing the donation through an electronic payment function; and means for notifying the user of the donation and processing results. This makes it possible for users to easily make hometown tax donations, saving time and effort while obtaining highly satisfying results.

[0103] A "user terminal" is a device used by users to input information and communicate with a server via a network.

[0104] "Donation amount" refers to the total amount of funds contributed by a user for a specific purpose.

[0105] A "return gift" refers to an item or service offered as a token of appreciation for a donation.

[0106] "User input data" refers to information about the donation amount and the selection of return gifts that users provide to the system.

[0107] An "external database" is a collection of data that exists externally and stores information such as local government information and information about return gifts.

[0108] An "optimization algorithm" is a computational method used to calculate the most suitable proposal for the user's requirements.

[0109] "Means of automation" refer to methods that minimize manual intervention and mechanically execute the desired procedure.

[0110] "Electronic payment functionality" refers to the ability to complete payments online via a network.

[0111] "Means of notification" refers to methods for informing users of the results or status of a process.

[0112] The system for implementing this invention is implemented with the following configuration: The user uses a user terminal such as a smartphone or tablet. This terminal is equipped with an interface that allows the user to input the donation amount and desired return gift, and the user input data is sent to the server. The server operates using Node.js and retrieves information on the recipient municipality and return gift from an external database.

[0113] The server uses React Native for its frontend, enabling intuitive user interaction. Within the server, it retrieves necessary information from data managed in MySQL® and uses an optimization algorithm to calculate the most suitable donation plan for the user. Electronic payment functionality is implemented using the Stripe API, and payment is processed according to the donation plan selected by the user.

[0114] Furthermore, by automating the donation process, the server monitors the entire process and performs real-time error detection and resolution through event monitoring. Finally, users are notified of the donation progress and processing results.

[0115] For example, a user might donate 15,000 yen to the Furusato Nozei (hometown tax) program and request a set of local specialty agricultural products. In this case, relevant information is sent from the user's terminal, and the server lists and proposes corresponding municipalities and return gifts. Based on the selected return gift, a smooth electronic payment is completed via Stripe, and the donation and return gift delivery procedures proceed automatically.

[0116] A useful prompt for the generating AI model would be: "Create an application scenario that allows users to make hometown tax donations, presenting them with a specific donation amount and desired return gift, and completing the payment efficiently and seamlessly via electronic payment."

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] Users input their donation amount and desired return gift into the interface using their smartphone. The entered information is immediately sent to the server. Here, the donation amount and desired return gift information are sent as user input data, and this becomes the initial data for the program.

[0120] Step 2:

[0121] The server runs on Node.js and processes the received user input data. Based on this data, the server retrieves municipality information and return gift information from an external database to formulate the most suitable donation plan. In this process, it uses SQL queries to retrieve data from MySQL and generates candidate donation destinations.

[0122] Step 3:

[0123] The server processes the acquired data using an optimization algorithm. Here, it calculates the optimal combination of municipality and return gift based on the user's donation amount and desired return gift. Past donation history and user preferences are also incorporated into the algorithm to generate individually customized suggestions.

[0124] Step 4:

[0125] The server sends the suggestions generated by the optimization algorithm to the user's terminal. Here, the user is provided with a list of candidate municipalities and return gifts. Based on this information, the user can select the most suitable donation plan.

[0126] Step 5:

[0127] The user reviews and selects a proposed donation plan through their device. Once the selection is complete, the information is sent back to the server, and the process proceeds to the next step.

[0128] Step 6:

[0129] The server initiates the electronic payment process based on the selected donation plan. It uses the Stripe API to process the user's payment information and execute the online payment. During this process, the payment information is encrypted and handled securely.

[0130] Step 7:

[0131] The server confirms the completion of the electronic payment and automates the donation process. At this point, the entire donation process is complete, and the delivery of the selected reward item also begins.

[0132] Step 8:

[0133] The server notifies the user of the final status of the donation completion and the delivery of the thank-you gift. This information can be viewed on the user's device, confirming that the hometown tax donation has been successfully completed.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention aims to enhance user satisfaction and willingness to donate by combining an emotion engine with the hometown tax donation system. In this system, the emotion engine operates based on user input information and behavioral data, recognizing the user's emotional state in real time. As a result, the donation suggestion optimization algorithm generates personalized suggestions according to the user's emotions.

[0136] The system includes a user terminal, a server, and an emotion engine. The user terminal provides an interface for users to input information about donation amounts and reward selections. In addition to this information, the emotion engine also analyzes user behavior on the terminal, such as click frequency and scroll speed. Once the user inputs information, the terminal sends it to the server.

[0137] The server retrieves donation amounts and reward information, and collects the latest data from an external database. Based on this information, the emotion engine evaluates the user's emotional state, and the AI ​​optimization algorithm makes adjustments that take the emotional data into account. For example, if the user is feeling stressed, it prioritizes suggesting simple and straightforward configurations.

[0138] Based on the analysis results from the emotion engine, the server generates optimized suggestions for recipient municipalities and return gifts, and sends them to the user's terminal. These suggestions may include detailed explanations that take into account the user's emotional state, as well as messages designed to promote relaxation.

[0139] As a concrete example, if a user sets their donation amount to 20,000 yen and expresses interest in seafood, the system uses an emotion engine to detect the user's excitement and proposes a special seafood set. Furthermore, by analyzing the user's emotions, it can also send product introductions that include videos designed to capture their interest. In this way, the system significantly enhances the user experience and provides an effective hometown tax donation process.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user uses the device to enter information such as the desired donation amount and the categories of return gifts they are interested in. During this process, the device also records input speed and click patterns collected through the interface.

[0143] Step 2:

[0144] The terminal sends the entered information and behavioral data to the server. Encryption is performed as needed to ensure data security.

[0145] Step 3:

[0146] The server retrieves relevant donation program and reward information from an external database based on the received data. It also analyzes the user's emotional state by inputting the collected data into an emotion engine.

[0147] Step 4:

[0148] The emotion engine infers emotions from user input and behavioral data. This inference indicates how relaxed, excited, or stressed the user is.

[0149] Step 5:

[0150] Based on the emotional state obtained from the emotion engine, the server uses an optimization algorithm to generate a plan of municipalities and return gifts that are suitable for the user. For example, if the analysis determines that the user is seeking relaxation, return gifts with a calming effect will be suggested.

[0151] Step 6:

[0152] The server sends optimized suggestions to the device. These suggestions include personalized messages and product descriptions that take sentiment analysis results into account.

[0153] Step 7:

[0154] The user reviews the donation plans presented on their device and selects their preferred plan. The information reflecting the user's selection is then sent back to the server via the device.

[0155] Step 8:

[0156] Based on your final selection, the server will automatically initiate the donation process and the delivery of the thank-you gift. Notifications, including progress and results, will be sent to your device at any time.

[0157] This process allows users to utilize the hometown tax donation system in a way that best suits their own emotional state.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0160] The Furusato Nozei (hometown tax donation) system lacks appropriate donation suggestions based on user emotions, and fails to provide a personalized experience that increases user motivation. Furthermore, it lacks real-time error detection and automation of the optimal donation process that takes user emotional states into account.

[0161] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0162] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data, means for acquiring information from external data storage based on donation amount and return gift information, and means for using optimization technology to generate suggestions suitable for the user based on sentiment analysis. This enables personalized donation suggestions based on the user's emotions, providing an optimal donation process and real-time error detection.

[0163] A "user terminal" is an electronic device used by users to input donation information and confirm the details of their proposals.

[0164] "Input information" refers to information provided by the user, such as the donation amount, the selection of return gifts, and other related data.

[0165] "Emotion analysis" is a technology that determines a user's emotional state based on their operational data and behavior.

[0166] "Optimization technology" refers to computational techniques for generating optimal suggestions based on user input information and emotional state.

[0167] "External data storage" refers to a data retention system that is referenced to collect the latest information for donations.

[0168] "Suggestions" refer to information about the best return gifts and local governments to help users make informed decisions when making donations.

[0169] Error detection is the process of identifying and correcting potential errors in the donation process in real time.

[0170] This invention relates to a system for generating personalized donation suggestions based on the user's emotional state within a hometown tax donation system. The system includes a user terminal, a server, an emotion analysis engine, and an external database.

[0171] The user terminal provides an interface for users to input information such as donation amounts and desired return gifts. The terminal records the user's input information and operation data (such as click frequency and scrolling speed) and sends this data to the server.

[0172] The server processes user data and operation data received from the terminal. The sentiment analysis engine uses this data to analyze the user's emotional state and perform a real-time sentiment evaluation. Next, the server connects to an external database to retrieve the latest information on donation amounts and reward items.

[0173] This information is processed using an AI-generated model and emotion-based optimization technology. As a result, suggestions for donation destinations and return gifts tailored to each user's emotions are generated. For example, if a user is feeling excited, special gift sets or visually appealing suggestions will be presented.

[0174] For example, if a user is considering a donation of 20,000 yen and is interested in seafood, the system can detect the user's emotional arousal and suggest a special seafood set. This would also include product descriptions that emphasize visual appeal.

[0175] An example of a prompt message might be, "I'm considering a donation of 20,000 yen and I'm interested in seafood. Please suggest some recommended return gifts."

[0176] In this way, it becomes possible to provide personalized suggestions based on emotions and increase users' willingness to donate.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The user enters the donation amount and desired return gift using a device. The device collects this information as input data and also acquires user operation data (e.g., click frequency, scroll speed). This data is then sent to the server.

[0180] Step 2:

[0181] The server receives user input and operation data from the terminal and passes it to the emotion analysis engine. This engine uses the acquired operation data to perform calculations and identify the user's emotional state in order to analyze it. As output, it generates user emotion evaluation data.

[0182] Step 3:

[0183] The server retrieves the latest information related to donation amounts and return gifts from an external database. The server then executes queries based on the input data to gather the necessary information, thereby forming an up-to-date donation-related dataset.

[0184] Step 4:

[0185] A generative AI model is used to integrate sentiment evaluation data with the latest donation dataset. Based on this, the server performs data calculations to generate personalized donation suggestions that respond to emotions. As a result, optimized donation suggestion data is generated.

[0186] Step 5:

[0187] The server sends the generated donation proposal data to the user's terminal. This proposal includes explanations and visual information that take into account the user's emotional state. The terminal displays this information to the user.

[0188] Step 6:

[0189] Users can review the suggestions presented on their device and select a donation recipient and a return gift. The user's selection information is stored in the system as data to improve the accuracy of future donation suggestions.

[0190] (Application Example 2)

[0191] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0192] Current commercial transaction systems do not take into account the emotional state of users, making it difficult to provide personalized suggestions and thus hindering improvements in the quality of the user experience. Furthermore, the standardization of transaction procedures makes it difficult to flexibly adjust them to meet user interests and preferences.

[0193] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0194] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including the transaction amount and selected items; means for acquiring information from an external information set for proposing optimal tax deductions and selected items based on the transaction amount and selected item information; and emotion recognition means for evaluating the user's perception state in real time and providing selection guidance that takes emotion data into consideration. This makes it possible to provide personalized suggestions according to the user's emotional state and improve the quality of the business transaction experience.

[0195] A "user terminal" is a device that provides a digital interface for users to input information and conduct commercial transactions.

[0196] "Commercial transaction amount" refers to numerical information indicating the amount of money a user pays when making a purchase or donation.

[0197] "Product selection" refers to the action of deciding which products or services a user is interested in or considering purchasing.

[0198] An "external information collection" is a source of information that stores the latest data and information related to commercial transactions and is accessible to the server as needed.

[0199] "Emotion recognition means" refers to technology that analyzes a user's emotional state and adjusts the content of business transaction proposals based on that analysis.

[0200] An "optimization method" is an algorithm used to calculate the most suitable product selection and transaction conditions for the user.

[0201] "Automated commercial transaction procedures" refers to a function designed to streamline the commercial transaction process and minimize user interaction.

[0202] "Monitoring measures" refer to technologies that detect anomalies that may occur during commercial transactions in real time and take appropriate action.

[0203] The system for implementing this invention takes the form of a combination of a user terminal, a server, and emotion recognition technology. When a user conducts a commercial transaction, the user terminal first receives input information and obtains the transaction amount and selected items. This clarifies the user's preferences.

[0204] The server collects necessary data from external information sources based on acquired transaction amounts and product selection information. This data is used to calculate the most suitable product selection and transaction conditions for the user using an optimization method. The optimization method utilizes AI technology and operates based on the user's past transaction data and real-time emotional state.

[0205] The emotion recognition system evaluates the user's real-time emotional state and adjusts suggestions based on the results. This technology specifically utilizes AI-based recognition models to analyze user input information (such as click frequency and scrolling speed). Based on this analysis, it can provide personalized messages and benefits tailored to the user's level of happiness and stress.

[0206] For example, if a user is considering purchasing an expensive electronic product, and the emotion recognition system detects the user's state of well-being, it can offer a discount on that specific product. Furthermore, sending the user a product introduction video designed to induce relaxation, tailored to their emotional state, can increase their willingness to make a purchase. In this way, flexible suggestions that respond to the user's emotions can significantly improve the quality of the purchasing experience.

[0207] An example of a prompt to input into a generative AI model is: "Please input data on the emotions a user feels while online shopping and create prompts to design recommended discounts based on that data."

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The user operates the terminal to input transaction-related information. Specifically, they enter the transaction amount and selected items into the input fields. The entered information is collected by the terminal and sent to the server. The input includes the transaction amount and selected items, and this data is used to perform the next processing step.

[0211] Step 2:

[0212] The server retrieves relevant data from an external data set based on the transaction amount and product selection information received from the terminal. This retrieved data includes past sales data and the latest discount information for similar products. As part of the data processing, the server filters the relevant data based on the transaction amount and product selection.

[0213] Step 3:

[0214] The server uses emotion recognition to analyze behavioral data (such as click frequency and scroll speed) sent by the user. Using this data as input, a generative AI model evaluates the user's emotional state and outputs the result. The output represents the user's emotional state (e.g., happiness, stress), which influences the next proposed step.

[0215] Step 4:

[0216] The server integrates the user's emotional state and acquired transaction information to generate optimal recommendations. This process utilizes AI-powered optimization techniques to create product recommendations that resonate most with the user. The output is personalized product recommendations and discount suggestions.

[0217] Step 5:

[0218] The server sends the suggestions generated in step 4 to the terminal. The user can then view personalized product recommendations and discount suggestions on the terminal and proceed with the transaction. The output is a transaction offer displayed to the user, which is adjusted according to the user's emotional state.

[0219] In this way, the system provides optimal business transaction proposals that take into account the user's emotional state at each step.

[0220] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0221] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0222] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0223] [Second Embodiment]

[0224] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0225] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0226] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0227] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0228] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0229] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0230] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0231] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0232] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0233] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0234] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0235] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0236] This invention is a system for effectively utilizing the Furusato Nozei (hometown tax donation) system. It allows users to easily input information regarding their desired donation amount and return gifts, and based on that information, provides optimal suggestions and procedures, thereby reducing the burden on users.

[0237] The main components of the system include user terminals, a server, and an external database. The user terminal has an interface for users to provide input information and can communicate with the server. When a user enters their desired donation amount and return gift into the terminal, that data is sent to the server.

[0238] The server retrieves municipality information and gift information from an external database based on the donation amount and the selected gift. Then, an optimization algorithm built into the server calculates the donation plan best suited to the user's needs. At this stage, past donation history and user preferences are also considered to generate individually personalized suggestions.

[0239] Once a proposal is generated, the server sends the information to the user's terminal, and the user reviews the proposed plan. If the user selects a proposal, the server automatically initiates and executes the donation process and monitors its progress.

[0240] For example, if a user sets their donation amount to 15,000 yen and expresses a preference for local specialty products, the system will suggest a list of appropriate municipalities and specialty products. For instance, it might offer options such as local rice or a beef set. If the user selects the beef set, the server automates the donation process and manages the entire process until the selected gift is sent.

[0241] In this way, the present invention greatly improves the convenience of the hometown tax donation system while minimizing the time and effort required from the user.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] The user uses their device to enter information such as the donation amount, the type of return gift they want, and their past donation history. Once the user has finished entering the information, it is sent from the device to the server.

[0245] Step 2:

[0246] The server accesses an external database to collect the latest information on local governments and return gifts. This includes a list of local governments that accept donations and details of the return gifts currently offered.

[0247] Step 3:

[0248] The server uses AI-powered optimization algorithms based on collected data and user information. These algorithms calculate the optimal combination of recipient municipalities and return gifts, as well as the expected tax deductions.

[0249] Step 4:

[0250] The server sends the optimized results to the user's terminal and proposes donation plans for the user to choose from. The proposals include detailed information about each option, such as an introduction to the local government and the features of the return gifts.

[0251] Step 5:

[0252] The user reviews the proposal on their device and selects their preferred donation plan. This selection is then sent back to the server via the device.

[0253] Step 6:

[0254] The server automatically initiates the donation process based on the selected donation plan. This includes submitting the donation application to the local government and preparing the relevant documents electronically.

[0255] Step 7:

[0256] The server notifies the user's device that the donation process is complete. At the same time, it also provides the shipping schedule and tracking information for the thank-you gift.

[0257] Through these steps, users can make hometown tax donations efficiently and easily.

[0258] (Example 1)

[0259] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0260] The process of making a donation through the Furusato Nozei (hometown tax) system is a significant burden for users because it requires a lot of information, time, and effort. In particular, selecting the optimal donation destination and return gift, and ensuring a smooth process through automated procedures, is not easy. Therefore, the challenge is to improve user convenience and provide an efficient and personalized donation process.

[0261] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0262] In this invention, the server includes means for receiving input information from a computing device and acquiring user input data including donation amount and return gift selection; means for acquiring information from external sources for proposing the optimal refund and return gift based on the donation amount and return gift information; and means for using the acquired data to perform an optimization process that proposes organizations and return gifts suitable for the user. As a result, users can efficiently select recipient organizations and return gifts, and complete the optimal donation procedure in a short time through individually tailored suggestions.

[0263] A "computational device" refers to a device used to input and transmit information in order to improve convenience.

[0264] "User input data" refers to information provided by users, including donation amounts and selections of return gifts.

[0265] "External information sources" refer to external databases or information provision systems accessed to obtain information about refunds and return gifts related to donations.

[0266] "Optimization process" refers to the algorithms and calculation methods used to determine the most suitable donation plan for each user.

[0267] "Refund" refers to the tax deduction or economic benefit obtained as a result of a donation.

[0268] "Organization" refers to the local government or other organizations to which users can make donations.

[0269] "Return gifts" refer to goods or services provided in response to a donation.

[0270] "Monitoring measures" refer to methods and devices for tracking the progress of donation procedures in real time and detecting and correcting malfunctions.

[0271] This system simplifies the hometown tax donation process by allowing users to input donation information via a computer and receive suggestions for efficient and optimized donation plans. A specific implementation of this system is described below.

[0272] Terminal role

[0273] The terminal provides an interface for users to input donation amounts and desired return gifts. To fulfill this role, the terminal is typically a computing device such as a computer or smartphone connected to the internet. The information entered from the terminal is transmitted to the server as data packets.

[0274] Server Role

[0275] The server receives user input data transmitted from the computing device and uses that data to access external information sources to obtain relevant refund and return gift information. In this process, database queries such as SQL are used to quickly extract the necessary data. Furthermore, the server uses optimization processing to perform calculations to determine the most suitable organizations and return gifts for the user.

[0276] The server also automates the donation process and monitors its progress in real time. In the event of a malfunction, corrective action is taken immediately and users are notified.

[0277] Specific example

[0278] For example, when the user enters a donation amount of 15,000 yen and a prompt requesting a beef set as a local specialty product, the server generates the most relevant list of organizations and specialty products based on this information. Then, the user selects the beef set from the proposed list, and the server automatically proceeds with the donation procedure based on that selection. Throughout this process, the user is notified of the progress in real time.

[0279] Example of a prompt sentence

[0280] "I would like to donate 15,000 yen and request a beef set as a local specialty product. Please propose the most suitable organization and gift for the return."

[0281] In this way, this system aims to reduce the burden on users and significantly improve the efficiency of the hometown tax payment procedure.

[0282] The flow of specific processing in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The user enters the donation amount and the desired gift for return through the computing device. The input information is received as numerical data (donation amount) and text data (name of the gift for return). The specific operation here is that the user types the information into the form and clicks the "Send" button. The input data is formatted in JSON.

[0285] Step 2:

[0286] The terminal sends the data input by the user to the server. Here, the data is encrypted and securely transmitted to the server using the HTTPS protocol. As a specific operation, the data is packetized and sent via the network.

[0287] Step 3:

[0288] The server checks the user input data received from the terminal and issues database queries to external information sources. Based on the donation amount and return gift information received as input, it retrieves a list of potential donation recipients and return gifts. The server generates SQL statements, extracts the necessary records from the external database, and obtains a dataset as output.

[0289] Step 4:

[0290] The server uses the acquired dataset to perform optimization processing. Specifically, it uses a generative AI model to calculate the donation value of each candidate and selects the plan that best suits user needs. The input is the dataset, and the output is the calculated optimal donation plan.

[0291] Step 5:

[0292] The server sends an optimized donation plan to the terminal. The output data is text information containing details of the proposed recipient and reward. Specifically, the data is returned to the terminal as an HTTP response.

[0293] Step 6:

[0294] The user reviews and selects a plan from the options presented on their device. The selection is sent to the server as information about the chosen recipient and the return gift. Specifically, the user clicks on an option on the screen to confirm their selection.

[0295] Step 7:

[0296] The server automates the donation process based on the user's selections. It processes online payments based on the submitted selection data and confirms the completion of the donation. Specific actions include calling payment APIs and monitoring the success / failure status of the process.

[0297] Step 8:

[0298] The server monitors the completion of the donation process and the preparation status of the thank-you gift shipment in real time, and notifies the user. Specifically, the server generates status update information and sends it to the user's terminal to inform the user of the progress. The output includes a notification that includes a donation completion message and an estimated delivery date and time.

[0299] (Application Example 1)

[0300] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0301] The challenges in the Furusato Nozei (hometown tax donation) system include the complexity of the donation process for users, the difficulty in receiving optimal suggestions, and the need to reduce the hassle of payment procedures. Furthermore, these efforts should encourage donations and improve the user experience.

[0302] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0303] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including donation amount and return gift selection; means for acquiring information from an external database for proposing the most suitable tax deduction and return gift based on the donation amount and return gift information; means for using an optimization algorithm that proposes a suitable municipality and return gift to the user using the acquired data; means for automating the donation procedure based on the proposed information; means for seamlessly completing the donation through an electronic payment function; and means for notifying the user of the donation and processing results. This makes it possible for users to easily make hometown tax donations, saving time and effort while obtaining highly satisfying results.

[0304] A "user terminal" is a device used by users to input information and communicate with a server via a network.

[0305] The "donation amount" refers to the total amount of funds contributed by the user for a specific purpose.

[0306] The "return gift" refers to the goods or services provided as a token of gratitude for the donation.

[0307] The "user input data" refers to the information regarding the donation amount and the selection of return gifts provided by the user to the system.

[0308] The "external database" refers to the aggregation of data that exists externally and stores local government information, return gift information, etc.

[0309] The "optimization algorithm" is a calculation method for calculating the proposal that best suits the user's requirements.

[0310] The "means for automation" is a method of mechanically performing the target procedure with minimal manual intervention.

[0311] The "electronic payment function" is a function for completing payments online via a network.

[0312] The "means for notification" is a method for notifying the user of the result or status of the process.

[0313] The system for implementing this invention is realized with the following configuration. The user uses a user terminal such as a smartphone or a tablet. This terminal is equipped with an interface through which the user can input the donation amount and the desired return gift, and the user input data is transmitted to the server. The server operates using Node.js and acquires local government information of the recipient and return gift information from the external database.

[0314] The server uses React Native for its frontend, allowing for intuitive user interaction. Within the server, it retrieves necessary information from data managed in MySQL and uses an optimization algorithm to calculate the most suitable donation plan for the user. Electronic payment functionality is implemented using the Stripe API, and payment is processed according to the donation plan selected by the user.

[0315] Furthermore, by automating the donation process, the server monitors the entire process and performs real-time error detection and resolution through event monitoring. Finally, users are notified of the donation progress and processing results.

[0316] For example, a user might donate 15,000 yen to the Furusato Nozei (hometown tax) program and request a set of local specialty agricultural products. In this case, relevant information is sent from the user's terminal, and the server lists and proposes corresponding municipalities and return gifts. Based on the selected return gift, a smooth electronic payment is completed via Stripe, and the donation and return gift delivery procedures proceed automatically.

[0317] A useful prompt for the generating AI model would be: "Create an application scenario that allows users to make hometown tax donations, presenting them with a specific donation amount and desired return gift, and completing the payment efficiently and seamlessly via electronic payment."

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] Users input their donation amount and desired return gift into the interface using their smartphone. The entered information is immediately sent to the server. Here, the donation amount and desired return gift information are sent as user input data, and this becomes the initial data for the program.

[0321] Step 2:

[0322] The server runs on Node.js and processes the received user input data. Based on this data, the server retrieves municipality information and return gift information from an external database to formulate the most suitable donation plan. In this process, it uses SQL queries to retrieve data from MySQL and generates candidate donation destinations.

[0323] Step 3:

[0324] The server processes the acquired data using an optimization algorithm. Here, it calculates the optimal combination of municipality and return gift based on the user's donation amount and desired return gift. Past donation history and user preferences are also incorporated into the algorithm to generate individually customized suggestions.

[0325] Step 4:

[0326] The server sends the suggestions generated by the optimization algorithm to the user's terminal. Here, the user is provided with a list of candidate municipalities and return gifts. Based on this information, the user can select the most suitable donation plan.

[0327] Step 5:

[0328] The user reviews and selects a proposed donation plan through their device. Once the selection is complete, the information is sent back to the server, and the process proceeds to the next step.

[0329] Step 6:

[0330] The server initiates the electronic payment process based on the selected donation plan. It uses the Stripe API to process the user's payment information and execute the online payment. During this process, the payment information is encrypted and handled securely.

[0331] Step 7:

[0332] The server confirms the completion of the electronic payment and automates the donation process. At this point, the entire donation process is complete, and the delivery of the selected reward item also begins.

[0333] Step 8:

[0334] The server notifies the user of the final status of the donation completion and the delivery of the thank-you gift. This information can be viewed on the user's device, confirming that the hometown tax donation has been successfully completed.

[0335] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0336] This invention aims to enhance user satisfaction and willingness to donate by combining an emotion engine with the hometown tax donation system. In this system, the emotion engine operates based on user input information and behavioral data, recognizing the user's emotional state in real time. As a result, the donation suggestion optimization algorithm generates personalized suggestions according to the user's emotions.

[0337] The system includes a user terminal, a server, and an emotion engine. The user terminal provides an interface for users to input information about donation amounts and reward selections. In addition to this information, the emotion engine also analyzes user behavior on the terminal, such as click frequency and scroll speed. Once the user inputs information, the terminal sends it to the server.

[0338] The server retrieves donation amounts and reward information, and collects the latest data from an external database. Based on this information, the emotion engine evaluates the user's emotional state, and the AI ​​optimization algorithm makes adjustments that take the emotional data into account. For example, if the user is feeling stressed, it prioritizes suggesting simple and straightforward configurations.

[0339] Based on the analysis results from the emotion engine, the server generates optimized suggestions for recipient municipalities and return gifts, and sends them to the user's terminal. These suggestions may include detailed explanations that take into account the user's emotional state, as well as messages designed to promote relaxation.

[0340] As a concrete example, if a user sets their donation amount to 20,000 yen and expresses interest in seafood, the system uses an emotion engine to detect the user's excitement and proposes a special seafood set. Furthermore, by analyzing the user's emotions, it can also send product introductions that include videos designed to capture their interest. In this way, the system significantly enhances the user experience and provides an effective hometown tax donation process.

[0341] The following describes the processing flow.

[0342] Step 1:

[0343] The user uses the device to enter information such as the desired donation amount and the categories of return gifts they are interested in. During this process, the device also records input speed and click patterns collected through the interface.

[0344] Step 2:

[0345] The terminal sends the entered information and behavioral data to the server. Encryption is performed as needed to ensure data security.

[0346] Step 3:

[0347] The server retrieves relevant donation program and reward information from an external database based on the received data. It also analyzes the user's emotional state by inputting the collected data into an emotion engine.

[0348] Step 4:

[0349] The emotion engine infers emotions from user input and behavioral data. This inference indicates how relaxed, excited, or stressed the user is.

[0350] Step 5:

[0351] Based on the emotional state obtained from the emotion engine, the server uses an optimization algorithm to generate a plan of municipalities and return gifts that are suitable for the user. For example, if the analysis determines that the user is seeking relaxation, return gifts with a calming effect will be suggested.

[0352] Step 6:

[0353] The server sends optimized suggestions to the device. These suggestions include personalized messages and product descriptions that take sentiment analysis results into account.

[0354] Step 7:

[0355] The user reviews the donation plans presented on their device and selects their preferred plan. The information reflecting the user's selection is then sent back to the server via the device.

[0356] Step 8:

[0357] Based on your final selection, the server will automatically initiate the donation process and the delivery of the thank-you gift. Notifications, including progress and results, will be sent to your device at any time.

[0358] This process allows users to utilize the hometown tax donation system in a way that best suits their own emotional state.

[0359] (Example 2)

[0360] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0361] The Furusato Nozei (hometown tax donation) system lacks appropriate donation suggestions based on user emotions, and fails to provide a personalized experience that increases user motivation. Furthermore, it lacks real-time error detection and automation of the optimal donation process that takes user emotional states into account.

[0362] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0363] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data, means for acquiring information from external data storage based on donation amount and return gift information, and means for using optimization technology to generate suggestions suitable for the user based on sentiment analysis. This enables personalized donation suggestions based on the user's emotions, providing an optimal donation process and real-time error detection.

[0364] A "user terminal" is an electronic device used by users to input donation information and confirm the details of their proposals.

[0365] "Input information" refers to information provided by the user, such as the donation amount, the selection of return gifts, and other related data.

[0366] "Emotion analysis" is a technology that determines a user's emotional state based on their operational data and behavior.

[0367] "Optimization technology" refers to computational techniques for generating optimal suggestions based on user input information and emotional state.

[0368] "External data storage" refers to a data retention system that is referenced to collect the latest information for donations.

[0369] "Suggestions" refer to information about the best return gifts and local governments to help users make informed decisions when making donations.

[0370] Error detection is the process of identifying and correcting potential errors in the donation process in real time.

[0371] This invention relates to a system for generating personalized donation suggestions based on the user's emotional state within a hometown tax donation system. The system includes a user terminal, a server, an emotion analysis engine, and an external database.

[0372] The user terminal provides an interface for users to input information such as donation amounts and desired return gifts. The terminal records the user's input information and operation data (such as click frequency and scrolling speed) and sends this data to the server.

[0373] The server processes user data and operation data received from the terminal. The sentiment analysis engine uses this data to analyze the user's emotional state and perform a real-time sentiment evaluation. Next, the server connects to an external database to retrieve the latest information on donation amounts and reward items.

[0374] This information is processed using an AI-generated model and emotion-based optimization technology. As a result, suggestions for donation destinations and return gifts tailored to each user's emotions are generated. For example, if a user is feeling excited, special gift sets or visually appealing suggestions will be presented.

[0375] For example, if a user is considering a donation of 20,000 yen and is interested in seafood, the system can detect the user's emotional arousal and suggest a special seafood set. This would also include product descriptions that emphasize visual appeal.

[0376] An example of a prompt message might be, "I'm considering a donation of 20,000 yen and I'm interested in seafood. Please suggest some recommended return gifts."

[0377] In this way, it becomes possible to provide personalized suggestions based on emotions and increase users' willingness to donate.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The user enters the donation amount and desired return gift using a device. The device collects this information as input data and also acquires user operation data (e.g., click frequency, scroll speed). This data is then sent to the server.

[0381] Step 2:

[0382] The server receives user input and operation data from the terminal and passes it to the emotion analysis engine. This engine uses the acquired operation data to perform calculations and identify the user's emotional state in order to analyze it. As output, it generates user emotion evaluation data.

[0383] Step 3:

[0384] The server retrieves the latest information related to donation amounts and return gifts from an external database. The server then executes queries based on the input data to gather the necessary information, thereby forming an up-to-date donation-related dataset.

[0385] Step 4:

[0386] A generative AI model is used to integrate sentiment evaluation data with the latest donation dataset. Based on this, the server performs data calculations to generate personalized donation suggestions that respond to emotions. As a result, optimized donation suggestion data is generated.

[0387] Step 5:

[0388] The server sends the generated donation proposal data to the user's terminal. This proposal includes explanations and visual information that take into account the user's emotional state. The terminal displays this information to the user.

[0389] Step 6:

[0390] Users can review the suggestions presented on their device and select a donation recipient and a return gift. The user's selection information is stored in the system as data to improve the accuracy of future donation suggestions.

[0391] (Application Example 2)

[0392] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0393] Current commercial transaction systems do not take into account the emotional state of users, making it difficult to provide personalized suggestions and thus hindering improvements in the quality of the user experience. Furthermore, the standardization of transaction procedures makes it difficult to flexibly adjust them to meet user interests and preferences.

[0394] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0395] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including the transaction amount and selected items; means for acquiring information from an external information set for proposing optimal tax deductions and selected items based on the transaction amount and selected item information; and emotion recognition means for evaluating the user's perception state in real time and providing selection guidance that takes emotion data into consideration. This makes it possible to provide personalized suggestions according to the user's emotional state and improve the quality of the business transaction experience.

[0396] A "user terminal" is a device that provides a digital interface for users to input information and conduct commercial transactions.

[0397] "Commercial transaction amount" refers to numerical information indicating the amount of money a user pays when making a purchase or donation.

[0398] "Product selection" refers to the action of deciding which products or services a user is interested in or considering purchasing.

[0399] An "external information collection" is a source of information that stores the latest data and information related to commercial transactions and is accessible to the server as needed.

[0400] "Emotion recognition means" refers to technology that analyzes a user's emotional state and adjusts the content of business transaction proposals based on that analysis.

[0401] An "optimization method" is an algorithm used to calculate the most suitable product selection and transaction conditions for the user.

[0402] "Automated commercial transaction procedures" refers to a function designed to streamline the commercial transaction process and minimize user interaction.

[0403] "Monitoring measures" refer to technologies that detect anomalies that may occur during commercial transactions in real time and take appropriate action.

[0404] The system for implementing this invention takes the form of a combination of a user terminal, a server, and emotion recognition technology. When a user conducts a commercial transaction, the user terminal first receives input information and obtains the transaction amount and selected items. This clarifies the user's preferences.

[0405] The server collects necessary data from external information sources based on acquired transaction amounts and product selection information. This data is used to calculate the most suitable product selection and transaction conditions for the user using an optimization method. The optimization method utilizes AI technology and operates based on the user's past transaction data and real-time emotional state.

[0406] The emotion recognition system evaluates the user's real-time emotional state and adjusts suggestions based on the results. This technology specifically utilizes AI-based recognition models to analyze user input information (such as click frequency and scrolling speed). Based on this analysis, it can provide personalized messages and benefits tailored to the user's level of happiness and stress.

[0407] For example, if a user is considering purchasing an expensive electronic product, and the emotion recognition system detects the user's state of well-being, it can offer a discount on that specific product. Furthermore, sending the user a product introduction video designed to induce relaxation, tailored to their emotional state, can increase their willingness to make a purchase. In this way, flexible suggestions that respond to the user's emotions can significantly improve the quality of the purchasing experience.

[0408] An example of a prompt to input into a generative AI model is: "Please input data on the emotions a user feels while online shopping and create prompts to design recommended discounts based on that data."

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The user operates the terminal to input transaction-related information. Specifically, they enter the transaction amount and selected items into the input fields. The entered information is collected by the terminal and sent to the server. The input includes the transaction amount and selected items, and this data is used to perform the next processing step.

[0412] Step 2:

[0413] The server retrieves relevant data from an external data set based on the transaction amount and product selection information received from the terminal. This retrieved data includes past sales data and the latest discount information for similar products. As part of the data processing, the server filters the relevant data based on the transaction amount and product selection.

[0414] Step 3:

[0415] The server uses emotion recognition to analyze behavioral data (such as click frequency and scroll speed) sent by the user. Using this data as input, a generative AI model evaluates the user's emotional state and outputs the result. The output represents the user's emotional state (e.g., happiness, stress), which influences the next proposed step.

[0416] Step 4:

[0417] The server integrates the user's emotional state and acquired transaction information to generate optimal recommendations. This process utilizes AI-powered optimization techniques to create product recommendations that resonate most with the user. The output is personalized product recommendations and discount suggestions.

[0418] Step 5:

[0419] The server sends the suggestions generated in step 4 to the terminal. The user can then view personalized product recommendations and discount suggestions on the terminal and proceed with the transaction. The output is a transaction offer displayed to the user, which is adjusted according to the user's emotional state.

[0420] In this way, the system provides optimal business transaction proposals that take into account the user's emotional state at each step.

[0421] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0422] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0423] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0424] [Third Embodiment]

[0425] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0426] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0427] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0428] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0429] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0430] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0431] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0432] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0433] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0434] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0435] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0436] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0437] This invention is a system for effectively utilizing the Furusato Nozei (hometown tax donation) system. It allows users to easily input information regarding their desired donation amount and return gifts, and based on that information, provides optimal suggestions and procedures, thereby reducing the burden on users.

[0438] The main components of the system include user terminals, a server, and an external database. The user terminal has an interface for users to provide input information and can communicate with the server. When a user enters their desired donation amount and return gift into the terminal, that data is sent to the server.

[0439] The server retrieves municipality information and gift information from an external database based on the donation amount and the selected gift. Then, an optimization algorithm built into the server calculates the donation plan best suited to the user's needs. At this stage, past donation history and user preferences are also considered to generate individually personalized suggestions.

[0440] Once a proposal is generated, the server sends the information to the user's terminal, and the user reviews the proposed plan. If the user selects a proposal, the server automatically initiates and executes the donation process and monitors its progress.

[0441] For example, if a user sets their donation amount to 15,000 yen and expresses a preference for local specialty products, the system will suggest a list of appropriate municipalities and specialty products. For instance, it might offer options such as local rice or a beef set. If the user selects the beef set, the server automates the donation process and manages the entire process until the selected gift is sent.

[0442] In this way, the present invention greatly improves the convenience of the hometown tax donation system while minimizing the time and effort required from the user.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The user uses their device to enter information such as the donation amount, the type of return gift they want, and their past donation history. Once the user has finished entering the information, it is sent from the device to the server.

[0446] Step 2:

[0447] The server accesses an external database to collect the latest information on local governments and return gifts. This includes a list of local governments that accept donations and details of the return gifts currently offered.

[0448] Step 3:

[0449] The server uses AI-powered optimization algorithms based on collected data and user information. These algorithms calculate the optimal combination of recipient municipalities and return gifts, as well as the expected tax deductions.

[0450] Step 4:

[0451] The server sends the optimized results to the user's terminal and proposes donation plans for the user to choose from. The proposals include detailed information about each option, such as an introduction to the local government and the features of the return gifts.

[0452] Step 5:

[0453] The user reviews the proposal on their device and selects their preferred donation plan. This selection is then sent back to the server via the device.

[0454] Step 6:

[0455] The server automatically initiates the donation process based on the selected donation plan. This includes submitting the donation application to the local government and preparing the relevant documents electronically.

[0456] Step 7:

[0457] The server notifies the user's device that the donation process is complete. At the same time, it also provides the shipping schedule and tracking information for the thank-you gift.

[0458] Through these steps, users can make hometown tax donations efficiently and easily.

[0459] (Example 1)

[0460] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0461] The process of making a donation through the Furusato Nozei (hometown tax) system is a significant burden for users because it requires a lot of information, time, and effort. In particular, selecting the optimal donation destination and return gift, and ensuring a smooth process through automated procedures, is not easy. Therefore, the challenge is to improve user convenience and provide an efficient and personalized donation process.

[0462] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0463] In this invention, the server includes means for receiving input information from a computing device and acquiring user input data including donation amount and return gift selection; means for acquiring information from external sources for proposing the optimal refund and return gift based on the donation amount and return gift information; and means for using the acquired data to perform an optimization process that proposes organizations and return gifts suitable for the user. As a result, users can efficiently select recipient organizations and return gifts, and complete the optimal donation procedure in a short time through individually tailored suggestions.

[0464] A "computational device" refers to a device used to input and transmit information in order to improve convenience.

[0465] "User input data" refers to information provided by users, including donation amounts and selections of return gifts.

[0466] "External information sources" refer to external databases or information provision systems accessed to obtain information about refunds and return gifts related to donations.

[0467] "Optimization process" refers to the algorithms and calculation methods used to determine the most suitable donation plan for each user.

[0468] "Refund" refers to the tax deduction or economic benefit obtained as a result of a donation.

[0469] "Organization" refers to the local government or other organizations to which users can make donations.

[0470] "Return gifts" refer to goods or services provided in response to a donation.

[0471] "Monitoring measures" refer to methods and devices for tracking the progress of donation procedures in real time and detecting and correcting malfunctions.

[0472] This system simplifies the hometown tax donation process by allowing users to input donation information via a computer and receive suggestions for efficient and optimized donation plans. A specific implementation of this system is described below.

[0473] Terminal role

[0474] The terminal provides an interface for users to input donation amounts and desired return gifts. To fulfill this role, the terminal is typically a computing device such as a computer or smartphone connected to the internet. The information entered from the terminal is transmitted to the server as data packets.

[0475] Server Role

[0476] The server receives user input data transmitted from the computing device and uses that data to access external information sources to obtain relevant refund and return gift information. In this process, database queries such as SQL are used to quickly extract the necessary data. Furthermore, the server uses optimization processing to perform calculations to determine the most suitable organizations and return gifts for the user.

[0477] The server also automates the donation process and monitors its progress in real time. In the event of a malfunction, corrective action is taken immediately and users are notified.

[0478] Specific example

[0479] For example, if a user enters a prompt indicating a donation amount of 15,000 yen and a request for a beef set as a local specialty product, the server will use this information to generate a list of the most relevant organizations and specialty products. The user then selects the beef set from the suggested list, and the server automatically proceeds with the donation process based on that selection. Throughout this entire process, the user is notified of the progress in real time.

[0480] Example of a prompt

[0481] "I would like to donate 15,000 yen and receive a beef set as a local specialty. Please suggest the most suitable organization and gift."

[0482] In this way, the system aims to reduce the burden on users and significantly streamline the process of making hometown tax donations.

[0483] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0484] Step 1:

[0485] The user enters the donation amount and desired return gift through a calculator. The entered information is received as numerical data (donation amount) and text data (return gift name). The specific action here is for the user to type the information into the form and click the "Submit" button. The input data is formatted in JSON format.

[0486] Step 2:

[0487] The terminal sends data entered by the user to the server. Here, the data is encrypted and securely transmitted to the server using the HTTPS protocol. Specifically, the data is packetized and sent over the network.

[0488] Step 3:

[0489] The server checks the user input data received from the terminal and issues database queries to external information sources. Based on the donation amount and return gift information received as input, it retrieves a list of potential donation recipients and return gifts. The server generates SQL statements, extracts the necessary records from the external database, and obtains a dataset as output.

[0490] Step 4:

[0491] The server uses the acquired dataset to perform optimization processing. Specifically, it uses a generative AI model to calculate the donation value of each candidate and selects the plan that best suits user needs. The input is the dataset, and the output is the calculated optimal donation plan.

[0492] Step 5:

[0493] The server sends an optimized donation plan to the terminal. The output data is text information containing details of the proposed recipient and reward. Specifically, the data is returned to the terminal as an HTTP response.

[0494] Step 6:

[0495] The user reviews and selects a plan from the options presented on their device. The selection is sent to the server as information about the chosen recipient and the return gift. Specifically, the user clicks on an option on the screen to confirm their selection.

[0496] Step 7:

[0497] The server automates the donation process based on the user's selections. It processes online payments based on the submitted selection data and confirms the completion of the donation. Specific actions include calling payment APIs and monitoring the success / failure status of the process.

[0498] Step 8:

[0499] The server monitors the completion of the donation process and the preparation status of the thank-you gift shipment in real time, and notifies the user. Specifically, the server generates status update information and sends it to the user's terminal to inform the user of the progress. The output includes a notification that includes a donation completion message and an estimated delivery date and time.

[0500] (Application Example 1)

[0501] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0502] The challenges in the Furusato Nozei (hometown tax donation) system include the complexity of the donation process for users, the difficulty in receiving optimal suggestions, and the need to reduce the hassle of payment procedures. Furthermore, these efforts should encourage donations and improve the user experience.

[0503] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0504] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including donation amount and return gift selection; means for acquiring information from an external database for proposing the most suitable tax deduction and return gift based on the donation amount and return gift information; means for using an optimization algorithm that proposes a suitable municipality and return gift to the user using the acquired data; means for automating the donation procedure based on the proposed information; means for seamlessly completing the donation through an electronic payment function; and means for notifying the user of the donation and processing results. This makes it possible for users to easily make hometown tax donations, saving time and effort while obtaining highly satisfying results.

[0505] A "user terminal" is a device used by users to input information and communicate with a server via a network.

[0506] "Donation amount" refers to the total amount of funds contributed by a user for a specific purpose.

[0507] A "return gift" refers to an item or service offered as a token of appreciation for a donation.

[0508] "User input data" refers to information about the donation amount and the selection of return gifts that users provide to the system.

[0509] An "external database" is a collection of data that exists externally and stores information such as local government information and information about return gifts.

[0510] An "optimization algorithm" is a computational method used to calculate the most suitable proposal for the user's requirements.

[0511] "Means of automation" refer to methods that minimize manual intervention and mechanically execute the desired procedure.

[0512] "Electronic payment functionality" refers to the ability to complete payments online via a network.

[0513] "Means of notification" refers to methods for informing users of the results or status of a process.

[0514] The system for implementing this invention is implemented with the following configuration: The user uses a user terminal such as a smartphone or tablet. This terminal is equipped with an interface that allows the user to input the donation amount and desired return gift, and the user input data is sent to the server. The server operates using Node.js and retrieves information on the recipient municipality and return gift from an external database.

[0515] The server uses React Native for its frontend, allowing for intuitive user interaction. Within the server, it retrieves necessary information from data managed in MySQL and uses an optimization algorithm to calculate the most suitable donation plan for the user. Electronic payment functionality is implemented using the Stripe API, and payment is processed according to the donation plan selected by the user.

[0516] Furthermore, by automating the donation process, the server monitors the entire process and performs real-time error detection and resolution through event monitoring. Finally, users are notified of the donation progress and processing results.

[0517] For example, a user might donate 15,000 yen to the Furusato Nozei (hometown tax) program and request a set of local specialty agricultural products. In this case, relevant information is sent from the user's terminal, and the server lists and proposes corresponding municipalities and return gifts. Based on the selected return gift, a smooth electronic payment is completed via Stripe, and the donation and return gift delivery procedures proceed automatically.

[0518] A useful prompt for the generating AI model would be: "Create an application scenario that allows users to make hometown tax donations, presenting them with a specific donation amount and desired return gift, and completing the payment efficiently and seamlessly via electronic payment."

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] Users input their donation amount and desired return gift into the interface using their smartphone. The entered information is immediately sent to the server. Here, the donation amount and desired return gift information are sent as user input data, and this becomes the initial data for the program.

[0522] Step 2:

[0523] The server runs on Node.js and processes the received user input data. Based on this data, the server retrieves municipality information and return gift information from an external database to formulate the most suitable donation plan. In this process, it uses SQL queries to retrieve data from MySQL and generates candidate donation destinations.

[0524] Step 3:

[0525] The server processes the acquired data using an optimization algorithm. Here, it calculates the optimal combination of municipality and return gift based on the user's donation amount and desired return gift. Past donation history and user preferences are also incorporated into the algorithm to generate individually customized suggestions.

[0526] Step 4:

[0527] The server sends the suggestions generated by the optimization algorithm to the user's terminal. Here, the user is provided with a list of candidate municipalities and return gifts. Based on this information, the user can select the most suitable donation plan.

[0528] Step 5:

[0529] The user reviews and selects a proposed donation plan through their device. Once the selection is complete, the information is sent back to the server, and the process proceeds to the next step.

[0530] Step 6:

[0531] The server initiates the electronic payment process based on the selected donation plan. It uses the Stripe API to process the user's payment information and execute the online payment. During this process, the payment information is encrypted and handled securely.

[0532] Step 7:

[0533] The server confirms the completion of the electronic payment and automates the donation process. At this point, the entire donation process is complete, and the delivery of the selected reward item also begins.

[0534] Step 8:

[0535] The server notifies the user of the final status of the donation completion and the delivery of the thank-you gift. This information can be viewed on the user's device, confirming that the hometown tax donation has been successfully completed.

[0536] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0537] This invention aims to enhance user satisfaction and willingness to donate by combining an emotion engine with the hometown tax donation system. In this system, the emotion engine operates based on user input information and behavioral data, recognizing the user's emotional state in real time. As a result, the donation suggestion optimization algorithm generates personalized suggestions according to the user's emotions.

[0538] The system includes a user terminal, a server, and an emotion engine. The user terminal provides an interface for users to input information about donation amounts and reward selections. In addition to this information, the emotion engine also analyzes user behavior on the terminal, such as click frequency and scroll speed. Once the user inputs information, the terminal sends it to the server.

[0539] The server retrieves donation amounts and reward information, and collects the latest data from an external database. Based on this information, the emotion engine evaluates the user's emotional state, and the AI ​​optimization algorithm makes adjustments that take the emotional data into account. For example, if the user is feeling stressed, it prioritizes suggesting simple and straightforward configurations.

[0540] Based on the analysis results from the emotion engine, the server generates optimized suggestions for recipient municipalities and return gifts, and sends them to the user's terminal. These suggestions may include detailed explanations that take into account the user's emotional state, as well as messages designed to promote relaxation.

[0541] As a concrete example, if a user sets their donation amount to 20,000 yen and expresses interest in seafood, the system uses an emotion engine to detect the user's excitement and proposes a special seafood set. Furthermore, by analyzing the user's emotions, it can also send product introductions that include videos designed to capture their interest. In this way, the system significantly enhances the user experience and provides an effective hometown tax donation process.

[0542] The following describes the processing flow.

[0543] Step 1:

[0544] The user uses the device to enter information such as the desired donation amount and the categories of return gifts they are interested in. During this process, the device also records input speed and click patterns collected through the interface.

[0545] Step 2:

[0546] The terminal sends the entered information and behavioral data to the server. Encryption is performed as needed to ensure data security.

[0547] Step 3:

[0548] The server retrieves relevant donation program and reward information from an external database based on the received data. It also analyzes the user's emotional state by inputting the collected data into an emotion engine.

[0549] Step 4:

[0550] The emotion engine infers emotions from user input and behavioral data. This inference indicates how relaxed, excited, or stressed the user is.

[0551] Step 5:

[0552] Based on the emotional state obtained from the emotion engine, the server uses an optimization algorithm to generate a plan of municipalities and return gifts that are suitable for the user. For example, if the analysis determines that the user is seeking relaxation, return gifts with a calming effect will be suggested.

[0553] Step 6:

[0554] The server sends optimized suggestions to the device. These suggestions include personalized messages and product descriptions that take sentiment analysis results into account.

[0555] Step 7:

[0556] The user reviews the donation plans presented on their device and selects their preferred plan. The information reflecting the user's selection is then sent back to the server via the device.

[0557] Step 8:

[0558] Based on your final selection, the server will automatically initiate the donation process and the delivery of the thank-you gift. Notifications, including progress and results, will be sent to your device at any time.

[0559] This process allows users to utilize the hometown tax donation system in a way that best suits their own emotional state.

[0560] (Example 2)

[0561] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0562] The Furusato Nozei (hometown tax donation) system lacks appropriate donation suggestions based on user emotions, and fails to provide a personalized experience that increases user motivation. Furthermore, it lacks real-time error detection and automation of the optimal donation process that takes user emotional states into account.

[0563] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0564] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data, means for acquiring information from external data storage based on donation amount and return gift information, and means for using optimization technology to generate suggestions suitable for the user based on sentiment analysis. This enables personalized donation suggestions based on the user's emotions, providing an optimal donation process and real-time error detection.

[0565] A "user terminal" is an electronic device used by users to input donation information and confirm the details of their proposals.

[0566] "Input information" refers to information provided by the user, such as the donation amount, the selection of return gifts, and other related data.

[0567] "Emotion analysis" is a technology that determines a user's emotional state based on their operational data and behavior.

[0568] "Optimization technology" refers to computational techniques for generating optimal suggestions based on user input information and emotional state.

[0569] "External data storage" refers to a data retention system that is referenced to collect the latest information for donations.

[0570] "Suggestions" refer to information about the best return gifts and local governments to help users make informed decisions when making donations.

[0571] Error detection is the process of identifying and correcting potential errors in the donation process in real time.

[0572] This invention relates to a system for generating personalized donation suggestions based on the user's emotional state within a hometown tax donation system. The system includes a user terminal, a server, an emotion analysis engine, and an external database.

[0573] The user terminal provides an interface for users to input information such as donation amounts and desired return gifts. The terminal records the user's input information and operation data (such as click frequency and scrolling speed) and sends this data to the server.

[0574] The server processes user data and operation data received from the terminal. The sentiment analysis engine uses this data to analyze the user's emotional state and perform a real-time sentiment evaluation. Next, the server connects to an external database to retrieve the latest information on donation amounts and reward items.

[0575] This information is processed using an AI-generated model and emotion-based optimization technology. As a result, suggestions for donation destinations and return gifts tailored to each user's emotions are generated. For example, if a user is feeling excited, special gift sets or visually appealing suggestions will be presented.

[0576] For example, if a user is considering a donation of 20,000 yen and is interested in seafood, the system can detect the user's emotional arousal and suggest a special seafood set. This would also include product descriptions that emphasize visual appeal.

[0577] An example of a prompt message might be, "I'm considering a donation of 20,000 yen and I'm interested in seafood. Please suggest some recommended return gifts."

[0578] In this way, it becomes possible to provide personalized suggestions based on emotions and increase users' willingness to donate.

[0579] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0580] Step 1:

[0581] The user enters the donation amount and desired return gift using a device. The device collects this information as input data and also acquires user operation data (e.g., click frequency, scroll speed). This data is then sent to the server.

[0582] Step 2:

[0583] The server receives user input and operation data from the terminal and passes it to the emotion analysis engine. This engine uses the acquired operation data to perform calculations and identify the user's emotional state in order to analyze it. As output, it generates user emotion evaluation data.

[0584] Step 3:

[0585] The server retrieves the latest information related to donation amounts and return gifts from an external database. The server then executes queries based on the input data to gather the necessary information, thereby forming an up-to-date donation-related dataset.

[0586] Step 4:

[0587] A generative AI model is used to integrate sentiment evaluation data with the latest donation dataset. Based on this, the server performs data calculations to generate personalized donation suggestions that respond to emotions. As a result, optimized donation suggestion data is generated.

[0588] Step 5:

[0589] The server sends the generated donation proposal data to the user's terminal. This proposal includes explanations and visual information that take into account the user's emotional state. The terminal displays this information to the user.

[0590] Step 6:

[0591] Users can review the suggestions presented on their device and select a donation recipient and a return gift. The user's selection information is stored in the system as data to improve the accuracy of future donation suggestions.

[0592] (Application Example 2)

[0593] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0594] Current commercial transaction systems do not take into account the emotional state of users, making it difficult to provide personalized suggestions and thus hindering improvements in the quality of the user experience. Furthermore, the standardization of transaction procedures makes it difficult to flexibly adjust them to meet user interests and preferences.

[0595] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0596] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including the transaction amount and selected items; means for acquiring information from an external information set for proposing optimal tax deductions and selected items based on the transaction amount and selected item information; and emotion recognition means for evaluating the user's perception state in real time and providing selection guidance that takes emotion data into consideration. This makes it possible to provide personalized suggestions according to the user's emotional state and improve the quality of the business transaction experience.

[0597] A "user terminal" is a device that provides a digital interface for users to input information and conduct commercial transactions.

[0598] "Commercial transaction amount" refers to numerical information indicating the amount of money a user pays when making a purchase or donation.

[0599] "Product selection" refers to the action of deciding which products or services a user is interested in or considering purchasing.

[0600] An "external information collection" is a source of information that stores the latest data and information related to commercial transactions and is accessible to the server as needed.

[0601] "Emotion recognition means" refers to technology that analyzes a user's emotional state and adjusts the content of business transaction proposals based on that analysis.

[0602] An "optimization method" is an algorithm used to calculate the most suitable product selection and transaction conditions for the user.

[0603] "Automated commercial transaction procedures" refers to a function designed to streamline the commercial transaction process and minimize user interaction.

[0604] "Monitoring measures" refer to technologies that detect anomalies that may occur during commercial transactions in real time and take appropriate action.

[0605] The system for implementing this invention takes the form of a combination of a user terminal, a server, and emotion recognition technology. When a user conducts a commercial transaction, the user terminal first receives input information and obtains the transaction amount and selected items. This clarifies the user's preferences.

[0606] The server collects necessary data from external information sources based on acquired transaction amounts and product selection information. This data is used to calculate the most suitable product selection and transaction conditions for the user using an optimization method. The optimization method utilizes AI technology and operates based on the user's past transaction data and real-time emotional state.

[0607] The emotion recognition system evaluates the user's real-time emotional state and adjusts suggestions based on the results. This technology specifically utilizes AI-based recognition models to analyze user input information (such as click frequency and scrolling speed). Based on this analysis, it can provide personalized messages and benefits tailored to the user's level of happiness and stress.

[0608] For example, if a user is considering purchasing an expensive electronic product, and the emotion recognition system detects the user's state of well-being, it can offer a discount on that specific product. Furthermore, sending the user a product introduction video designed to induce relaxation, tailored to their emotional state, can increase their willingness to make a purchase. In this way, flexible suggestions that respond to the user's emotions can significantly improve the quality of the purchasing experience.

[0609] An example of a prompt to input into a generative AI model is: "Please input data on the emotions a user feels while online shopping and create prompts to design recommended discounts based on that data."

[0610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0611] Step 1:

[0612] The user operates the terminal to input transaction-related information. Specifically, they enter the transaction amount and selected items into the input fields. The entered information is collected by the terminal and sent to the server. The input includes the transaction amount and selected items, and this data is used to perform the next processing step.

[0613] Step 2:

[0614] The server retrieves relevant data from an external data set based on the transaction amount and product selection information received from the terminal. This retrieved data includes past sales data and the latest discount information for similar products. As part of the data processing, the server filters the relevant data based on the transaction amount and product selection.

[0615] Step 3:

[0616] The server uses emotion recognition to analyze behavioral data (such as click frequency and scroll speed) sent by the user. Using this data as input, a generative AI model evaluates the user's emotional state and outputs the result. The output represents the user's emotional state (e.g., happiness, stress), which influences the next proposed step.

[0617] Step 4:

[0618] The server integrates the user's emotional state and acquired transaction information to generate optimal recommendations. This process utilizes AI-powered optimization techniques to create product recommendations that resonate most with the user. The output is personalized product recommendations and discount suggestions.

[0619] Step 5:

[0620] The server sends the suggestions generated in step 4 to the terminal. The user can then view personalized product recommendations and discount suggestions on the terminal and proceed with the transaction. The output is a transaction offer displayed to the user, which is adjusted according to the user's emotional state.

[0621] In this way, the system provides optimal business transaction proposals that take into account the user's emotional state at each step.

[0622] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0623] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0624] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0625] [Fourth Embodiment]

[0626] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0627] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0628] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0629] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0630] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0631] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0632] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0633] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0634] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0635] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0636] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0637] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0638] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0639] This invention is a system for effectively utilizing the Furusato Nozei (hometown tax donation) system. It allows users to easily input information regarding their desired donation amount and return gifts, and based on that information, provides optimal suggestions and procedures, thereby reducing the burden on users.

[0640] The main components of the system include user terminals, a server, and an external database. The user terminal has an interface for users to provide input information and can communicate with the server. When a user enters their desired donation amount and return gift into the terminal, that data is sent to the server.

[0641] The server retrieves municipality information and gift information from an external database based on the donation amount and the selected gift. Then, an optimization algorithm built into the server calculates the donation plan best suited to the user's needs. At this stage, past donation history and user preferences are also considered to generate individually personalized suggestions.

[0642] Once a proposal is generated, the server sends the information to the user's terminal, and the user reviews the proposed plan. If the user selects a proposal, the server automatically initiates and executes the donation process and monitors its progress.

[0643] For example, if a user sets their donation amount to 15,000 yen and expresses a preference for local specialty products, the system will suggest a list of appropriate municipalities and specialty products. For instance, it might offer options such as local rice or a beef set. If the user selects the beef set, the server automates the donation process and manages the entire process until the selected gift is sent.

[0644] In this way, the present invention greatly improves the convenience of the hometown tax donation system while minimizing the time and effort required from the user.

[0645] The following describes the processing flow.

[0646] Step 1:

[0647] The user uses their device to enter information such as the donation amount, the type of return gift they want, and their past donation history. Once the user has finished entering the information, it is sent from the device to the server.

[0648] Step 2:

[0649] The server accesses an external database to collect the latest information on local governments and return gifts. This includes a list of local governments that accept donations and details of the return gifts currently offered.

[0650] Step 3:

[0651] The server uses AI-powered optimization algorithms based on collected data and user information. These algorithms calculate the optimal combination of recipient municipalities and return gifts, as well as the expected tax deductions.

[0652] Step 4:

[0653] The server sends the optimized results to the user's terminal and proposes donation plans for the user to choose from. The proposals include detailed information about each option, such as an introduction to the local government and the features of the return gifts.

[0654] Step 5:

[0655] The user reviews the proposal on their device and selects their preferred donation plan. This selection is then sent back to the server via the device.

[0656] Step 6:

[0657] The server automatically initiates the donation process based on the selected donation plan. This includes submitting the donation application to the local government and preparing the relevant documents electronically.

[0658] Step 7:

[0659] The server notifies the user's device that the donation process is complete. At the same time, it also provides the shipping schedule and tracking information for the thank-you gift.

[0660] Through these steps, users can make hometown tax donations efficiently and easily.

[0661] (Example 1)

[0662] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] The process of making a donation through the Furusato Nozei (hometown tax) system is a significant burden for users because it requires a lot of information, time, and effort. In particular, selecting the optimal donation destination and return gift, and ensuring a smooth process through automated procedures, is not easy. Therefore, the challenge is to improve user convenience and provide an efficient and personalized donation process.

[0664] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0665] In this invention, the server includes means for receiving input information from a computing device and acquiring user input data including donation amount and return gift selection; means for acquiring information from external sources for proposing the optimal refund and return gift based on the donation amount and return gift information; and means for using the acquired data to perform an optimization process that proposes organizations and return gifts suitable for the user. As a result, users can efficiently select recipient organizations and return gifts, and complete the optimal donation procedure in a short time through individually tailored suggestions.

[0666] A "computational device" refers to a device used to input and transmit information in order to improve convenience.

[0667] "User input data" refers to information provided by users, including donation amounts and selections of return gifts.

[0668] "External information sources" refer to external databases or information provision systems accessed to obtain information about refunds and return gifts related to donations.

[0669] "Optimization process" refers to the algorithms and calculation methods used to determine the most suitable donation plan for each user.

[0670] "Refund" refers to the tax deduction or economic benefit obtained as a result of a donation.

[0671] "Organization" refers to the local government or other organizations to which users can make donations.

[0672] "Return gifts" refer to goods or services provided in response to a donation.

[0673] "Monitoring measures" refer to methods and devices for tracking the progress of donation procedures in real time and detecting and correcting malfunctions.

[0674] This system simplifies the hometown tax donation process by allowing users to input donation information via a computer and receive suggestions for efficient and optimized donation plans. A specific implementation of this system is described below.

[0675] Terminal role

[0676] The terminal provides an interface for users to input donation amounts and desired return gifts. To fulfill this role, the terminal is typically a computing device such as a computer or smartphone connected to the internet. The information entered from the terminal is transmitted to the server as data packets.

[0677] Server Role

[0678] The server receives user input data transmitted from the computing device and uses that data to access external information sources to obtain relevant refund and return gift information. In this process, database queries such as SQL are used to quickly extract the necessary data. Furthermore, the server uses optimization processing to perform calculations to determine the most suitable organizations and return gifts for the user.

[0679] The server also automates the donation process and monitors its progress in real time. In the event of a malfunction, corrective action is taken immediately and users are notified.

[0680] Specific example

[0681] For example, if a user enters a prompt indicating a donation amount of 15,000 yen and a request for a beef set as a local specialty product, the server will use this information to generate a list of the most relevant organizations and specialty products. The user then selects the beef set from the suggested list, and the server automatically proceeds with the donation process based on that selection. Throughout this entire process, the user is notified of the progress in real time.

[0682] Example of a prompt

[0683] "I would like to donate 15,000 yen and receive a beef set as a local specialty. Please suggest the most suitable organization and gift."

[0684] In this way, the system aims to reduce the burden on users and significantly streamline the process of making hometown tax donations.

[0685] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0686] Step 1:

[0687] The user enters the donation amount and desired return gift through a calculator. The entered information is received as numerical data (donation amount) and text data (return gift name). The specific action here is for the user to type the information into the form and click the "Submit" button. The input data is formatted in JSON format.

[0688] Step 2:

[0689] The terminal sends data entered by the user to the server. Here, the data is encrypted and securely transmitted to the server using the HTTPS protocol. Specifically, the data is packetized and sent over the network.

[0690] Step 3:

[0691] The server checks the user input data received from the terminal and issues database queries to external information sources. Based on the donation amount and return gift information received as input, it retrieves a list of potential donation recipients and return gifts. The server generates SQL statements, extracts the necessary records from the external database, and obtains a dataset as output.

[0692] Step 4:

[0693] The server uses the acquired dataset to perform optimization processing. Specifically, it uses a generative AI model to calculate the donation value of each candidate and selects the plan that best suits user needs. The input is the dataset, and the output is the calculated optimal donation plan.

[0694] Step 5:

[0695] The server sends an optimized donation plan to the terminal. The output data is text information containing details of the proposed recipient and reward. Specifically, the data is returned to the terminal as an HTTP response.

[0696] Step 6:

[0697] The user reviews and selects a plan from the options presented on their device. The selection is sent to the server as information about the chosen recipient and the return gift. Specifically, the user clicks on an option on the screen to confirm their selection.

[0698] Step 7:

[0699] The server automates the donation process based on the user's selections. It processes online payments based on the submitted selection data and confirms the completion of the donation. Specific actions include calling payment APIs and monitoring the success / failure status of the process.

[0700] Step 8:

[0701] The server monitors the completion of the donation process and the preparation status of the thank-you gift shipment in real time, and notifies the user. Specifically, the server generates status update information and sends it to the user's terminal to inform the user of the progress. The output includes a notification that includes a donation completion message and an estimated delivery date and time.

[0702] (Application Example 1)

[0703] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] The challenges in the Furusato Nozei (hometown tax donation) system include the complexity of the donation process for users, the difficulty in receiving optimal suggestions, and the need to reduce the hassle of payment procedures. Furthermore, these efforts should encourage donations and improve the user experience.

[0705] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0706] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including donation amount and return gift selection; means for acquiring information from an external database for proposing the most suitable tax deduction and return gift based on the donation amount and return gift information; means for using an optimization algorithm that proposes a suitable municipality and return gift to the user using the acquired data; means for automating the donation procedure based on the proposed information; means for seamlessly completing the donation through an electronic payment function; and means for notifying the user of the donation and processing results. This makes it possible for users to easily make hometown tax donations, saving time and effort while obtaining highly satisfying results.

[0707] A "user terminal" is a device used by users to input information and communicate with a server via a network.

[0708] "Donation amount" refers to the total amount of funds contributed by a user for a specific purpose.

[0709] A "return gift" refers to an item or service offered as a token of appreciation for a donation.

[0710] "User input data" refers to information about the donation amount and the selection of return gifts that users provide to the system.

[0711] An "external database" is a collection of data that exists externally and stores information such as local government information and information about return gifts.

[0712] An "optimization algorithm" is a computational method used to calculate the most suitable proposal for the user's requirements.

[0713] "Means of automation" refer to methods that minimize manual intervention and mechanically execute the desired procedure.

[0714] "Electronic payment functionality" refers to the ability to complete payments online via a network.

[0715] "Means of notification" refers to methods for informing users of the results or status of a process.

[0716] The system for implementing this invention is implemented with the following configuration: The user uses a user terminal such as a smartphone or tablet. This terminal is equipped with an interface that allows the user to input the donation amount and desired return gift, and the user input data is sent to the server. The server operates using Node.js and retrieves information on the recipient municipality and return gift from an external database.

[0717] The server uses React Native for its frontend, allowing for intuitive user interaction. Within the server, it retrieves necessary information from data managed in MySQL and uses an optimization algorithm to calculate the most suitable donation plan for the user. Electronic payment functionality is implemented using the Stripe API, and payment is processed according to the donation plan selected by the user.

[0718] Furthermore, by automating the donation process, the server monitors the entire process and performs real-time error detection and resolution through event monitoring. Finally, users are notified of the donation progress and processing results.

[0719] For example, a user might donate 15,000 yen to the Furusato Nozei (hometown tax) program and request a set of local specialty agricultural products. In this case, relevant information is sent from the user's terminal, and the server lists and proposes corresponding municipalities and return gifts. Based on the selected return gift, a smooth electronic payment is completed via Stripe, and the donation and return gift delivery procedures proceed automatically.

[0720] A useful prompt for the generating AI model would be: "Create an application scenario that allows users to make hometown tax donations, presenting them with a specific donation amount and desired return gift, and completing the payment efficiently and seamlessly via electronic payment."

[0721] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0722] Step 1:

[0723] Users input their donation amount and desired return gift into the interface using their smartphone. The entered information is immediately sent to the server. Here, the donation amount and desired return gift information are sent as user input data, and this becomes the initial data for the program.

[0724] Step 2:

[0725] The server runs on Node.js and processes the received user input data. Based on this data, the server retrieves municipality information and return gift information from an external database to formulate the most suitable donation plan. In this process, it uses SQL queries to retrieve data from MySQL and generates candidate donation destinations.

[0726] Step 3:

[0727] The server processes the acquired data using an optimization algorithm. Here, it calculates the optimal combination of municipality and return gift based on the user's donation amount and desired return gift. Past donation history and user preferences are also incorporated into the algorithm to generate individually customized suggestions.

[0728] Step 4:

[0729] The server sends the suggestions generated by the optimization algorithm to the user's terminal. Here, the user is provided with a list of candidate municipalities and return gifts. Based on this information, the user can select the most suitable donation plan.

[0730] Step 5:

[0731] The user reviews and selects a proposed donation plan through their device. Once the selection is complete, the information is sent back to the server, and the process proceeds to the next step.

[0732] Step 6:

[0733] The server initiates the electronic payment process based on the selected donation plan. It uses the Stripe API to process the user's payment information and execute the online payment. During this process, the payment information is encrypted and handled securely.

[0734] Step 7:

[0735] The server confirms the completion of the electronic payment and automates the donation process. At this point, the entire donation process is complete, and the delivery of the selected reward item also begins.

[0736] Step 8:

[0737] The server notifies the user of the final status of the donation completion and the delivery of the thank-you gift. This information can be viewed on the user's device, confirming that the hometown tax donation has been successfully completed.

[0738] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0739] This invention aims to enhance user satisfaction and willingness to donate by combining an emotion engine with the hometown tax donation system. In this system, the emotion engine operates based on user input information and behavioral data, recognizing the user's emotional state in real time. As a result, the donation suggestion optimization algorithm generates personalized suggestions according to the user's emotions.

[0740] The system includes a user terminal, a server, and an emotion engine. The user terminal provides an interface for users to input information about donation amounts and reward selections. In addition to this information, the emotion engine also analyzes user behavior on the terminal, such as click frequency and scroll speed. Once the user inputs information, the terminal sends it to the server.

[0741] The server retrieves donation amounts and reward information, and collects the latest data from an external database. Based on this information, the emotion engine evaluates the user's emotional state, and the AI ​​optimization algorithm makes adjustments that take the emotional data into account. For example, if the user is feeling stressed, it prioritizes suggesting simple and straightforward configurations.

[0742] Based on the analysis results from the emotion engine, the server generates optimized suggestions for recipient municipalities and return gifts, and sends them to the user's terminal. These suggestions may include detailed explanations that take into account the user's emotional state, as well as messages designed to promote relaxation.

[0743] As a concrete example, if a user sets their donation amount to 20,000 yen and expresses interest in seafood, the system uses an emotion engine to detect the user's excitement and proposes a special seafood set. Furthermore, by analyzing the user's emotions, it can also send product introductions that include videos designed to capture their interest. In this way, the system significantly enhances the user experience and provides an effective hometown tax donation process.

[0744] The following describes the processing flow.

[0745] Step 1:

[0746] The user uses the device to enter information such as the desired donation amount and the categories of return gifts they are interested in. During this process, the device also records input speed and click patterns collected through the interface.

[0747] Step 2:

[0748] The terminal sends the entered information and behavioral data to the server. Encryption is performed as needed to ensure data security.

[0749] Step 3:

[0750] The server retrieves relevant donation program and reward information from an external database based on the received data. It also analyzes the user's emotional state by inputting the collected data into an emotion engine.

[0751] Step 4:

[0752] The emotion engine infers emotions from user input and behavioral data. This inference indicates how relaxed, excited, or stressed the user is.

[0753] Step 5:

[0754] Based on the emotional state obtained from the emotion engine, the server uses an optimization algorithm to generate a plan of municipalities and return gifts that are suitable for the user. For example, if the analysis determines that the user is seeking relaxation, return gifts with a calming effect will be suggested.

[0755] Step 6:

[0756] The server sends optimized suggestions to the device. These suggestions include personalized messages and product descriptions that take sentiment analysis results into account.

[0757] Step 7:

[0758] The user reviews the donation plans presented on their device and selects their preferred plan. The information reflecting the user's selection is then sent back to the server via the device.

[0759] Step 8:

[0760] Based on your final selection, the server will automatically initiate the donation process and the delivery of the thank-you gift. Notifications, including progress and results, will be sent to your device at any time.

[0761] This process allows users to utilize the hometown tax donation system in a way that best suits their own emotional state.

[0762] (Example 2)

[0763] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0764] The Furusato Nozei (hometown tax donation) system lacks appropriate donation suggestions based on user emotions, and fails to provide a personalized experience that increases user motivation. Furthermore, it lacks real-time error detection and automation of the optimal donation process that takes user emotional states into account.

[0765] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0766] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data, means for acquiring information from external data storage based on donation amount and return gift information, and means for using optimization technology to generate suggestions suitable for the user based on sentiment analysis. This enables personalized donation suggestions based on the user's emotions, providing an optimal donation process and real-time error detection.

[0767] A "user terminal" is an electronic device used by users to input donation information and confirm the details of their proposals.

[0768] "Input information" refers to information provided by the user, such as the donation amount, the selection of return gifts, and other related data.

[0769] "Emotion analysis" is a technology that determines a user's emotional state based on their operational data and behavior.

[0770] "Optimization technology" refers to computational techniques for generating optimal suggestions based on user input information and emotional state.

[0771] "External data storage" refers to a data retention system that is referenced to collect the latest information for donations.

[0772] "Suggestions" refer to information about the best return gifts and local governments to help users make informed decisions when making donations.

[0773] Error detection is the process of identifying and correcting potential errors in the donation process in real time.

[0774] This invention relates to a system for generating personalized donation suggestions based on the user's emotional state within a hometown tax donation system. The system includes a user terminal, a server, an emotion analysis engine, and an external database.

[0775] The user terminal provides an interface for users to input information such as donation amounts and desired return gifts. The terminal records the user's input information and operation data (such as click frequency and scrolling speed) and sends this data to the server.

[0776] The server processes user data and operation data received from the terminal. The sentiment analysis engine uses this data to analyze the user's emotional state and perform a real-time sentiment evaluation. Next, the server connects to an external database to retrieve the latest information on donation amounts and reward items.

[0777] This information is processed using an AI-generated model and emotion-based optimization technology. As a result, suggestions for donation destinations and return gifts tailored to each user's emotions are generated. For example, if a user is feeling excited, special gift sets or visually appealing suggestions will be presented.

[0778] For example, if a user is considering a donation of 20,000 yen and is interested in seafood, the system can detect the user's emotional arousal and suggest a special seafood set. This would also include product descriptions that emphasize visual appeal.

[0779] An example of a prompt message might be, "I'm considering a donation of 20,000 yen and I'm interested in seafood. Please suggest some recommended return gifts."

[0780] In this way, it becomes possible to provide personalized suggestions based on emotions and increase users' willingness to donate.

[0781] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0782] Step 1:

[0783] The user enters the donation amount and desired return gift using a device. The device collects this information as input data and also acquires user operation data (e.g., click frequency, scroll speed). This data is then sent to the server.

[0784] Step 2:

[0785] The server receives user input and operation data from the terminal and passes it to the emotion analysis engine. This engine uses the acquired operation data to perform calculations and identify the user's emotional state in order to analyze it. As output, it generates user emotion evaluation data.

[0786] Step 3:

[0787] The server retrieves the latest information related to donation amounts and return gifts from an external database. The server then executes queries based on the input data to gather the necessary information, thereby forming an up-to-date donation-related dataset.

[0788] Step 4:

[0789] A generative AI model is used to integrate sentiment evaluation data with the latest donation dataset. Based on this, the server performs data calculations to generate personalized donation suggestions that respond to emotions. As a result, optimized donation suggestion data is generated.

[0790] Step 5:

[0791] The server sends the generated donation proposal data to the user's terminal. This proposal includes explanations and visual information that take into account the user's emotional state. The terminal displays this information to the user.

[0792] Step 6:

[0793] Users can review the suggestions presented on their device and select a donation recipient and a return gift. The user's selection information is stored in the system as data to improve the accuracy of future donation suggestions.

[0794] (Application Example 2)

[0795] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0796] Current commercial transaction systems do not take into account the emotional state of users, making it difficult to provide personalized suggestions and thus hindering improvements in the quality of the user experience. Furthermore, the standardization of transaction procedures makes it difficult to flexibly adjust them to meet user interests and preferences.

[0797] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0798] In this invention, the server includes means for receiving input information from a user terminal and acquiring user input data including the transaction amount and selected items; means for acquiring information from an external information set for proposing optimal tax deductions and selected items based on the transaction amount and selected item information; and emotion recognition means for evaluating the user's perception state in real time and providing selection guidance that takes emotion data into consideration. This makes it possible to provide personalized suggestions according to the user's emotional state and improve the quality of the business transaction experience.

[0799] A "user terminal" is a device that provides a digital interface for users to input information and conduct commercial transactions.

[0800] "Commercial transaction amount" refers to numerical information indicating the amount of money a user pays when making a purchase or donation.

[0801] "Product selection" refers to the action of deciding which products or services a user is interested in or considering purchasing.

[0802] An "external information collection" is a source of information that stores the latest data and information related to commercial transactions and is accessible to the server as needed.

[0803] "Emotion recognition means" refers to technology that analyzes a user's emotional state and adjusts the content of business transaction proposals based on that analysis.

[0804] An "optimization method" is an algorithm used to calculate the most suitable product selection and transaction conditions for the user.

[0805] "Automated commercial transaction procedures" refers to a function designed to streamline the commercial transaction process and minimize user interaction.

[0806] "Monitoring measures" refer to technologies that detect anomalies that may occur during commercial transactions in real time and take appropriate action.

[0807] The system for implementing this invention takes the form of a combination of a user terminal, a server, and emotion recognition technology. When a user conducts a commercial transaction, the user terminal first receives input information and obtains the transaction amount and selected items. This clarifies the user's preferences.

[0808] The server collects necessary data from external information sources based on acquired transaction amounts and product selection information. This data is used to calculate the most suitable product selection and transaction conditions for the user using an optimization method. The optimization method utilizes AI technology and operates based on the user's past transaction data and real-time emotional state.

[0809] The emotion recognition system evaluates the user's real-time emotional state and adjusts suggestions based on the results. This technology specifically utilizes AI-based recognition models to analyze user input information (such as click frequency and scrolling speed). Based on this analysis, it can provide personalized messages and benefits tailored to the user's level of happiness and stress.

[0810] For example, if a user is considering purchasing an expensive electronic product, and the emotion recognition system detects the user's state of well-being, it can offer a discount on that specific product. Furthermore, sending the user a product introduction video designed to induce relaxation, tailored to their emotional state, can increase their willingness to make a purchase. In this way, flexible suggestions that respond to the user's emotions can significantly improve the quality of the purchasing experience.

[0811] An example of a prompt to input into a generative AI model is: "Please input data on the emotions a user feels while online shopping and create prompts to design recommended discounts based on that data."

[0812] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0813] Step 1:

[0814] The user operates the terminal to input transaction-related information. Specifically, they enter the transaction amount and selected items into the input fields. The entered information is collected by the terminal and sent to the server. The input includes the transaction amount and selected items, and this data is used to perform the next processing step.

[0815] Step 2:

[0816] The server retrieves relevant data from an external data set based on the transaction amount and product selection information received from the terminal. This retrieved data includes past sales data and the latest discount information for similar products. As part of the data processing, the server filters the relevant data based on the transaction amount and product selection.

[0817] Step 3:

[0818] The server uses emotion recognition to analyze behavioral data (such as click frequency and scroll speed) sent by the user. Using this data as input, a generative AI model evaluates the user's emotional state and outputs the result. The output represents the user's emotional state (e.g., happiness, stress), which influences the next proposed step.

[0819] Step 4:

[0820] The server integrates the user's emotional state and acquired transaction information to generate optimal recommendations. This process utilizes AI-powered optimization techniques to create product recommendations that resonate most with the user. The output is personalized product recommendations and discount suggestions.

[0821] Step 5:

[0822] The server sends the suggestions generated in step 4 to the terminal. The user can then view personalized product recommendations and discount suggestions on the terminal and proceed with the transaction. The output is a transaction offer displayed to the user, which is adjusted according to the user's emotional state.

[0823] In this way, the system provides optimal business transaction proposals that take into account the user's emotional state at each step.

[0824] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0825] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0826] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0827] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0828] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0829] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0830] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0831] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0832] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0833] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0834] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0835] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0836] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0837] 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.

[0838] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0839] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0840] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0841] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0842] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0843] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0844] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0845] The following is further disclosed regarding the embodiments described above.

[0846] (Claim 1)

[0847] A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift,

[0848] A means of obtaining information from an external database to propose the most suitable tax deductions and return gifts based on donation amounts and return gift information,

[0849] A method using an optimization algorithm that proposes suitable municipalities and return gifts to users based on acquired data,

[0850] Based on the proposed information, a means to automate the donation process,

[0851] A means of notifying users of donations and processing results,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, further comprising means for personalizing a donation optimization algorithm, taking into account the user's past donation history and preferences.

[0855] (Claim 3)

[0856] The system according to claim 1, further comprising monitoring means for real-time error detection and resolution during the automated donation process.

[0857] "Example 1"

[0858] (Claim 1)

[0859] A means for receiving input information from a computing device and obtaining user input data including donation amount and selection of return gift,

[0860] A means of obtaining information from external sources to propose the most suitable refunds and return gifts based on donation amounts and return gift information,

[0861] A means of using an optimization process that proposes organizations and return gifts suitable for the user using the acquired data,

[0862] Based on the proposed information, a means to automate the donation process,

[0863] A means of notifying users of donations and processing results,

[0864] A means for sending the generated proposal to the user's terminal,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, further comprising means for personalizing the donation optimization process by taking into account the user's past donation history and preferences.

[0868] (Claim 3)

[0869] The system according to claim 1, further comprising monitoring means for immediate detection and correction of malfunctions during the automation of the donation process.

[0870] "Application Example 1"

[0871] (Claim 1)

[0872] A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift,

[0873] A means of obtaining information from an external database to propose the most suitable tax deductions and return gifts based on donation amounts and return gift information,

[0874] A method using an optimization algorithm that proposes suitable municipalities and return gifts to users based on acquired data,

[0875] Based on the proposed information, a means to automate the donation process,

[0876] A means of seamlessly completing donations through electronic payment functions,

[0877] A means of notifying users of donations and processing results,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, further comprising means for personalizing a donation optimization algorithm, taking into account the user's past donation history and preferences.

[0881] (Claim 3)

[0882] The system according to claim 1, further comprising monitoring means for real-time error detection and resolution during the automated donation process.

[0883] "Example 2 of combining an emotion engine"

[0884] (Claim 1)

[0885] A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift,

[0886] A means of obtaining information from external data storage to propose the most suitable tax deductions and return gifts based on donation amount and return gift information,

[0887] A means of using optimization technology that generates user-appropriate suggestions based on sentiment analysis using acquired data,

[0888] Based on the proposed information, a means to automate the donation process,

[0889] A means of notifying users of donations and processing results,

[0890] A system that includes this.

[0891] (Claim 2)

[0892] The system according to claim 1, further comprising means for personalizing donation optimization technology, taking into account the user's past donation history and preferences, and for analyzing the user's emotional state.

[0893] (Claim 3)

[0894] The system according to claim 1, further comprising monitoring means for real-time error detection and correction during the automated donation process.

[0895] "Application example 2 when combining with an emotional engine"

[0896] (Claim 1)

[0897] A means for receiving input information from a user terminal and obtaining user input data including the transaction amount and selected items,

[0898] A means of obtaining information from an external information set to propose the optimal tax deduction and product selection based on commercial transaction amount and product selection information,

[0899] A means of using an optimization method that proposes local governments and product selections suitable for the user using the acquired information,

[0900] Based on the proposed information, a means to automate commercial transaction procedures,

[0901] An emotion recognition means that evaluates the user's perception state in real time and provides product selection guidance that takes emotion data into consideration,

[0902] A means of adjusting the content of proposals and benefits according to the emotional state when conducting business transactions,

[0903] A means of notifying the user of commercial transactions and processing results,

[0904] A system that includes this.

[0905] (Claim 2)

[0906] The system according to claim 1, further comprising means for personalizing a transaction optimization method by taking into account the user's past transaction history and preferences.

[0907] (Claim 3)

[0908] The system according to claim 1, further comprising monitoring means for real-time anomaly detection and response during the automation of commercial transaction procedures. [Explanation of Symbols]

[0909] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving input information from a user terminal and obtaining user input data including donation amount and selection of return gift, A means of obtaining information from an external database to propose the most suitable tax deductions and return gifts based on donation amounts and return gift information, A method using an optimization algorithm that proposes suitable municipalities and return gifts to users based on acquired data, Based on the proposed information, a means to automate the donation process, A means of seamlessly completing donations through electronic payment functions, A means of notifying users of donations and processing results, A system that includes this.

2. The system according to claim 1, further comprising means for personalizing a donation optimization algorithm, taking into account the user's past donation history and preferences.

3. The system according to claim 1, further comprising monitoring means for real-time error detection and resolution during the automated donation process.

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