System

Abstract

A system is provided.SOLUTION: This system includes a means for unitarily managing points acquired by a user in a plurality of point programs, a means for generating the optimal proposal of point use on the basis of the purchase history and taste information of the user, and a means for notifying the user when the expiration date of the points approaches.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Today's consumers often participate in multiple point programs, and the complicated task of managing these points often results in points expiring or missed opportunities to use them optimally. To solve this problem, it is necessary to provide a system that centrally manages users' acquired points and allows them to use them efficiently and optimally. Furthermore, there is a need to maximize the value of points and improve consumer convenience by suggesting ways to use points based on users' purchase history and preferences, and by including a notification function for points that are about to expire. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. First, it provides a means for centrally managing points earned by a user across multiple point programs. Second, it provides a means for generating optimal point usage suggestions based on the user's purchase history and preference information. Furthermore, it adds a means for notifying the user when points are about to expire, allowing the user to use their points efficiently. This system allows users to make the most of their points and minimize the risk of them expiring. In addition, it also provides a means for making point usage suggestions for products in different categories based on the user's preference information, and a means for analyzing the user's purchase history to identify patterns that optimize point usage, thereby enabling the system to provide even more useful suggestions to the user.

[0006] "Centralized management" refers to the user managing points earned in multiple different point programs in an integrated manner through a single system.

[0007] "Purchase history" means a record of information about all of a user's past purchase transactions, including the date and time of purchase, the products purchased, and the services used.

[0008] "Preference information" refers to information about what products and services a user prefers, and is data that indicates the user's preferences and interests.

[0009] "Optimal suggestions for using points" refers to specific suggestions for how to use or exchange points that are generated based on the user's purchasing history and preference information, so that the user can make the most of the points they hold.

[0010] A "notification" is a message sent to inform the user of important information, and in the case of the present invention, it particularly refers to an alert when the expiration date of points is approaching.

[0011] A "category" is a group of products or services that are classified based on their nature or characteristics, such as "electronics" or "fashion."

[0012] "Patterns" refer to the scale and tendency identified based on a user's purchasing behavior and point usage history, which allows us to suggest the most optimal way to use points.

[0013] "Expiration date" refers to the last day of the period during which points can be used, after which points will expire. [Brief explanation of the drawings]

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

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

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

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

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

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

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

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

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

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

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0035] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on their purchasing history and preferences. This system functions in cooperation with the server, terminals, and users.

[0036] User registration and input of preferences

[0037] First, a user accesses the system using their own terminal and registers. When registering, they enter their user ID and preference information and send it to the server. The server stores the received user ID and preference information in a database, and creates and manages a new user object.

[0038] Integration with points purchase history

[0039] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0040] Generate optimal point usage proposals

[0041] Next, when the user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using the points when purchasing electronic products.

[0042] Points expiration notification

[0043] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0044] Specific examples

[0045] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0046] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0047] The processing flow will be explained below.

[0048] Step 1:

[0049] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID and preference information (e.g., electronic products, fashion, etc.).

[0050] Step 2:

[0051] The device sends the user ID and preference information entered by the user to the server, and the data is sent using a secure protocol.

[0052] Step 3:

[0053] The server stores the received user ID and preference information in a database, creates a user object, and adds it to the user list in the system.

[0054] Step 4:

[0055] When users earn points from multiple services, they enter their purchase data (service ID, number of points earned, purchase date, etc.) into the terminal.

[0056] Step 5:

[0057] The terminal sends the entered purchase data to the server, which receives it and saves and updates the user's purchase history and point balance in the database.

[0058] Step 6:

[0059] The server centralizes all received point information and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0060] Step 7:

[0061] When a user wants to know the best way to use points, the user uses the terminal to request a suggestion for the best use from the server.

[0062] Step 8:

[0063] The server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates optimal point usage suggestions, suggesting point usage for specific categories (e.g., electronic products).

[0064] Step 9:

[0065] The server sends the generated proposals to the user's device, where the user can review the proposals and select the optimal way to use their points.

[0066] Step 10:

[0067] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0068] Step 11:

[0069] The server notifies the user's device that the points are about to expire, and the user receives a notification on the device and is prompted to use the points before the expiration date.

[0070] Step 12:

[0071] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0072] These are the specific processing steps of the system, which allow users to efficiently manage multiple points and utilize them in the most optimal way.

[0073] Example 1

[0074] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0075] There is a need to centrally manage points earned by users across multiple point programs and to present optimal ways to use points by utilizing the user's purchase history and preference information. Another challenge is to efficiently notify users when points are about to expire and prevent them from expiring. There is a need to provide a system that allows users to use points in the most optimal way and avoid missing their expiration dates.

[0076] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0077] In this invention, the server includes a means for centrally managing points earned by a user through multiple point programs, a means for the user to register using their own terminal and input their user ID and preference information, a means for the server to store the received user information in a database and create and manage a new user object, and a means for generating optimal point usage suggestions based on the user's purchase history and preference information. This allows the user to easily centrally manage points earned through multiple point programs and use them in the most optimal way. The server also includes a means for notifying the user when points are about to expire, allowing the user to use them efficiently without missing their expiration dates.

[0078] A "user" is an individual or corporation that uses the system to centrally manage points and receive suggestions based on their purchasing history and preferences.

[0079] A "points program" is an incentive program in which a certain number of points are awarded when using or purchasing a specific service or product.

[0080] "Centralized management" refers to the centralized management of points earned in multiple point programs in one system or database.

[0081] "Terminal" means a device (such as a personal computer, smartphone, or tablet) that a user uses to access the system.

[0082] A "server" is a computing device that processes information received from users, stores it in a database, generates various offers, and sends notifications.

[0083] A "database" is a digital repository for storing and managing user information, preferences, purchase history, point balance, etc.

[0084] A "user object" is a collection of data including user information (ID, preferences, purchase history, etc.), and is an entity managed by the server.

[0085] "Purchase history" is a record of information about products and services a user has purchased in the past and points earned.

[0086] "Preference information" is information about product categories and services in which a user is interested, and is data that indicates the requests and wishes of individual users.

[0087] The "optimal point usage method" is the most effective way to use points, presented based on the user's purchasing history and preference information.

[0088] A "machine learning algorithm" is a computational method for analyzing user data and extracting patterns and trends, which are used to generate optimal recommendations.

[0089] The "expiration date" is information indicating the last day that points can be used, and points will expire after this date.

[0090] A "notification" is a message sent by the server to the terminal to inform the user that the expiration date of points is approaching.

[0091] This invention is a system that centrally manages points earned by a user through multiple point programs and suggests optimal ways to use points based on purchase history and preferences. This system functions in cooperation with the server, terminals, and users.

[0092] User registration and input of preferences

[0093] Users access the system using their own terminals and register as new users. When registering, the user enters their user ID and preference information, which are then sent to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. For example, MySQL is used as the database management system, and Apache is used as the web server software.

[0094] Integration with points purchase history

[0095] Every time a user earns points from a service, the user sends their purchase history and point information from their device to the server. The server receives this information and stores it in a database. The server then updates each user's point balance and centrally manages points for all services. This process uses data analysis tools such as the Python pandas library.

[0096] Generate optimal point usage proposals

[0097] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and a machine learning algorithm (e.g., random forest) is used to suggest the best way to use points for the user. After generating the suggestion, the server returns the best way to use points to the user's device. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0098] Points expiration notification

[0099] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. The server detects points that are about to expire and sends a notification to the user's device. This notification uses a push notification service such as Firebase Cloud Messaging. For example, if "Service 1 points will expire in one week," the server will detect this and notify the user.

[0100] Specific examples

[0101] For example, suppose user "user_123" is interested in electronic products and fashion. "user_123" earns 100 points from service 1 and 150 points from service 2, and enters this information into the system through his terminal. The server receives this information, stores it in the database, and consolidates his points, bringing his total points to 250. The server then suggests using his points to purchase electronic products based on his preferences. Furthermore, if his points from service 1 are about to expire in a week, the server will detect this and send a notification to his terminal.

[0102] Prompt Sentence Examples

[0103] Below are some example prompts to input to a generative AI model:

[0104] "User 'user_123' is interested in electronics and fashion. He has earned 100 points from Service 1 and 150 points from Service 2. Based on his preferences, please suggest the best way to use his points. Also, please explain how to notify him when his points from Service 1 will expire in a week."

[0105] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0107] Step 1:

[0108] A user accesses the system's web page or app using their own device and enters their user ID and preference information in the new registration form. The entered information (user ID and preference information) is sent from the device to the server. The server receives this information and stores it in a database. Specifically, the server uses a MySQL database to store the user ID and preference information as a new user object. The input of this step is the user ID and preference information, and the output is the creation and storage of a new user object.

[0109] Step 2:

[0110] Every time a user earns points from each service, the point information (purchase history and earned points) is sent from the terminal to the server. The server saves the received point information in the database and updates the existing user object. Specifically, the Python pandas library is used to add the purchase history and point information to the database and calculate the point balance for each user. The input to this step is the purchase history and earned point information, and the output is the updated user object and point balance.

[0111] Step 3:

[0112] The user uses their device to request an "optimal point usage suggestion" from the server. The server receives this request and retrieves the user's preference information and purchase history from a database. It then performs data analysis using the retrieved information and applies a machine learning algorithm (e.g., random forest) to generate the optimal point usage method. The generated suggestion is sent back from the server to the user's device. The input to this step is the preference information, purchase history, and suggestion request, and the output is the generated optimal point usage suggestion.

[0113] Step 4:

[0114] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. If the server detects that points are about to expire, it notifies the user's device of that information (e.g., "Service 1 points will expire in one week"). For notifications, a push notification service such as Firebase Cloud Messaging is used. The input of this step is the point expiration data, and the output is a notification of the expiration date sent to the user.

[0115] Specifically, the process proceeds as follows:

[0116] Step 1:

[0117] The user ID and preference information entered by the user on the device is sent to the server.

[0118] The server stores the received information in a MySQL database and creates a new user object.

[0119] Step 2:

[0120] Every time a user earns points, the purchase history and point information are sent from the terminal to the server.

[0121] The server uses the pandas library to store the received information in a database and update the user object.

[0122] Step 3:

[0123] The user requests the server from the terminal for optimal point usage suggestions.

[0124] The server retrieves preference information and purchase history from a database and uses machine learning algorithms such as random forests to generate and return suggestions.

[0125] Step 4:

[0126] The server periodically checks the point information using cron.

[0127] When it detects that a point is about to expire, it uses Firebase Cloud Messaging to notify the user of that information.

[0128] This system allows users to effectively manage their points in one place, receive suggestions on how to best use them, and prevent them from expiring.

[0129] (Application example 1)

[0130] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0131] In conventional point programs, users often had difficulty managing multiple points and often forgot about expiration dates. Furthermore, there were often insufficient suggestions on how to best use points, making it difficult for users to use points efficiently. As a result, points were often wasted, and there were issues with user convenience and satisfaction not improving.

[0132] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0133] In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the points are about to expire, and means for making point usage suggestions for multiple categories based on the user's preference information and purchase history. This allows the user to centrally manage points and receive optimal point usage suggestions based on the purchase history and preference information, enabling effective use of points and resolving conventional problems.

[0134] "Multiple point programs" refers to the entire point system in which a user earns points from different services and stores.

[0135] "Means of centralized management" refers to a method of integrating and managing points earned through different point programs in one place.

[0136] "Purchase history" refers to the complete record of a user's past purchases.

[0137] "Preference information" refers to information based on a user's hobbies and interests.

[0138] The "means for generating optimal proposals" refers to a method for providing the most effective way to use points based on the user's purchase history and preference information.

[0139] "Means for notifying users when the expiration date is approaching" refers to a method for notifying users when the expiration date of points is approaching.

[0140] "Multiple categories" refers to a whole range of different types or genres of goods and services.

[0141] "Means for making suggestions on how to use points" refers to a method or system for making suggestions to users on how to use points.

[0142] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on purchase history and preference information. This system functions in cooperation with the server, terminals, and users.

[0143] User registration and input of preferences

[0144] First, the user accesses the system using their own device and registers. When registering, they enter their user ID and preference information and send it to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. This makes it possible to suggest optimal ways to use points based on the user's preferences.

[0145] Integration with points purchase history

[0146] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0147] Generate optimal point usage proposals

[0148] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0149] Points expiration notification

[0150] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0151] Specific examples

[0152] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0153] This system allows users to centrally manage their points and receive optimal point usage suggestions based on their purchasing history and preference information, allowing them to make effective use of their points.

[0154] Examples of prompt statements

[0155] Example prompts to input to the generative AI model:

[0156] Develop a system that offers optimal point usage suggestions based on the user's purchase history and preferences. Design a system that works in cooperation between the server and the device, taking into account the following information:

[0157] 1. Registration of user ID and preference information.

[0158] 2. Integrated management of points earned through each service.

[0159] 3. Optimal point usage suggestions based on purchase history.

[0160] 4. Points Expiration Notification.

[0161] The system is implemented in Python and uses SQLite as the database.

[0162] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0163] Step 1: Register and enter your preferences

[0164] A user registers using a terminal, entering their user ID and preferences, which are then sent to the server, which stores the information in a database and creates a new user object.

[0165] Input: User ID, preference information

[0166] Data processing: Save user information to the database and create a user object

[0167] Output: User information is added to the database

[0168] Step 2: Merging your points with your purchase history

[0169] Users use their devices to send information about points earned across different services and their purchase history to the server. The server receives this information and stores it in a database. At the same time, it updates each user's point balance and manages it centrally.

[0170] Input: Service name, points information, purchase history

[0171] Data processing: Save information to database, update point balance

[0172] Output: Updated points balance reflected in database

[0173] Step 3: Generate optimal point usage proposals

[0174] When a user requests a point usage suggestion from the server, the server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates the optimal point usage suggestion and presents it to the user.

[0175] Input: User ID, preference information, purchase history

[0176] Data processing: Generate optimal proposals based on preference information and purchase history

[0177] Output: The best point usage suggestion is sent to the user.

[0178] Step 4: Points expiration notification

[0179] The server periodically checks the database for upcoming point expiration dates, and if any points are about to expire, the server sends a notification to the user's device.

[0180] Input: Point information, expiration date

[0181] Data processing: detecting points approaching expiration

[0182] Output: Expiration notification sent to user

[0183] Step 5: Use your points

[0184] If the user accepts the proposed point usage method, the terminal sends a notification to the server, which updates the point balance and subtracts the used points from the database.

[0185] Input: Point usage instructions

[0186] Data processing: Update point balance, subtract used points

[0187] Output: The updated points balance is reflected in the database and the user is notified of the result.

[0188] This trend will allow users to easily manage their points centrally and use them efficiently by being suggested the most optimal way to use them.

[0189] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0190] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0191] User registration and input of preferences

[0192] First, a user accesses the system using their own device and registers. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and data for recognizing the user's emotions (e.g., facial expressions, tone of voice, etc.) and send them to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database, and creates and manages a new user object.

[0193] Integration with points purchase history

[0194] For each service for which a user has earned points, the user enters information about their purchase history and earned points into the terminal. The terminal then sends this information to the server. The server stores the received purchase data in a database and updates the user's point balance. It also centrally manages points earned across all services.

[0195] Generate optimal point usage proposals

[0196] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. The server then retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. The server combines and analyzes this data to suggest the best way to use points based on the user's current emotional state. For example, if the user is feeling stressed, it will suggest using points for relaxation-related products and services.

[0197] Points expiration notification

[0198] The server periodically checks the expiration date of the user's points and notifies them if any points are about to expire. The timing and format of these notifications are adjusted based on real-time emotional data, and an approach tailored to the user's state is used. For example, notifications can be sent at times when the user is relaxed, providing information without causing stress.

[0199] Specific examples

[0200] For example, user "user_123" is interested in electronics and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this and consolidates the points. The server sets his balance at 250 points and suggests "using points for relaxation-related products" based on his preference information and emotion data. Also, if his points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0201] This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to use their points efficiently and without missing their points' expiration dates.

[0202] The processing flow will be explained below.

[0203] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0204] Step 1:

[0205] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.).

[0206] Step 2:

[0207] The device sends the user ID, preference information, and emotion recognition data entered by the user to the server using a secure protocol.

[0208] Step 3:

[0209] The server stores the received user ID, preference information, and emotion recognition data in a database, and also creates a new user object and adds it to the user list in the system.

[0210] Step 4:

[0211] The user enters purchase data (service ID, points earned, purchase date, etc.) for each service for which they earned points into the terminal.

[0212] Step 5:

[0213] The terminal sends the entered purchase data to the server, which receives it, stores it in a database, and updates the user's point balance.

[0214] Step 6:

[0215] The server centralizes point information from all services and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0216] Step 7:

[0217] The user sends a request from the device to the server asking how best to use their points, and the request also includes real-time emotional data recognized by the emotion engine.

[0218] Step 8:

[0219] The server retrieves user preference information and purchasing history from the database and analyzes it in combination with real-time emotional data from the emotion engine.

[0220] Step 9:

[0221] The server then uses the analysis results to generate optimal point usage methods based on the user's emotional state. For example, if the user is feeling stressed, the server will suggest using points for relaxation-related products and services.

[0222] Step 10:

[0223] The server sends the generated proposals to the user's device, where the user can review the proposals and select the best way to use their points.

[0224] Step 11:

[0225] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0226] Step 12:

[0227] The server notifies the user's device when their points are about to expire. The timing and format of this notification are adjusted based on the emotion data from the emotion engine. For example, the server can choose to send the notification during a time when the user is relaxed.

[0228] Step 13:

[0229] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0230] The above are the specific processing steps of the system. This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to efficiently manage and use their points.

[0231] Example 2

[0232] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0233] Nowadays, many users earn points from multiple services, but there are few ways to efficiently manage them centrally. Furthermore, there is often a lack of optimal suggestions for how to effectively use earned points. Furthermore, there is no system that can notify users in a timely manner when points are about to expire. To solve these problems, a system is needed that takes into account users' preferences and emotional state and makes optimal point usage suggestions.

[0234] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0235] In this invention, the server includes a means for centrally managing points earned by a user from multiple services, a means for inputting and saving user preference information and emotional data, a means for generating optimal point usage suggestions based on the user's purchase history, preference information, and emotional data, a means for notifying the user when the points are about to expire, and a means for adjusting the timing and format of the notification depending on the user's emotional state. This allows the user to efficiently manage points earned from multiple services and receive optimal point usage suggestions based on the user's emotional state. Furthermore, the user can receive timely notifications when the points are about to expire.

[0236] "User" means an individual or organization that uses the System to acquire points and manages and uses those points.

[0237] "Service" means a business or platform that offers transactions or activities through which users can earn points.

[0238] "Points" are numerical rewards that users earn by using specific services, and can be used for various benefits and exchangeable products.

[0239] "Centralized management" means comprehensively managing points earned from multiple services within a single system.

[0240] "Preference information" refers to information about a user's interests and preferences for specific products or services.

[0241] "Emotional data" is data that indicates the user's current emotional state and is collected from facial expressions, tone of voice, etc.

[0242] "Purchase history" is a record of past purchases made by a user, including the type of product and the date and time of purchase.

[0243] The "optimal suggestion" is a suggestion of how to use points that is considered to be most effective for the user, calculated based on the user's preference information, purchase history, and emotional state.

[0244] "Expiration date" refers to the date and time at which the points you have earned can be used.

[0245] "Notifications" are messages or alerts sent by the system to users to inform them of points expiration dates and other important matters.

[0246] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state in real time.

[0247] This invention relates to a system that centrally manages points earned by a user in multiple point programs and makes optimal point usage suggestions based on the user's purchase history, preference information, and emotional state. This system functions mainly through a server, terminals, and users, and provides suggestions based on the user's emotional state through an emotional engine.

[0248] User registration and input of preferences

[0249] Users access the system using their own devices and register. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.), and send this information to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database (e.g., MySQL or MongoDB) and creates a new user object. This object contains the user's basic information, preference information, and emotion data.

[0250] Integration with points purchase history

[0251] When a user earns points from each service, they enter their purchase history and earned point information into their device. The device converts this information into a structured data format (e.g., CSV or JSON) and sends it to the server. The server stores the received purchase data in a database and updates the user's point balance. The server centrally manages points earned from all services and maintains a consolidated point balance for each user.

[0252] Generate optimal point usage proposals

[0253] When a user wants to know how best to use their points, they use their device to send a request to the server. The server retrieves the user's preference information, purchase history, and real-time emotional data from an emotion engine (e.g., Affectiva or Microsoft Azure Emotion API) from a database. This data is combined and analyzed using a generative AI model. The server then sends the generated suggestions to the user's device, suggesting appropriate ways to use their points. For example, if the user is feeling stressed, it might suggest using their points for relaxation-related products and services.

[0254] Points expiration notification

[0255] The server periodically checks the point information in the database and notifies the user if any points are about to expire. This notification is timed optimally based on the user's real-time emotional data. For example, by selecting a time when the user is relaxed and sending a notification to the device, the information is conveyed to the user without causing stress.

[0256] For example, user "user_123" registers in the system that he is interested in electronic products and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, which he enters into the system. The server receives this and combines the points to make it 250 points. Based on the preference information and emotion data, the server suggests "using points for relaxation-related products." Also, if the points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0257] An example of a prompt sentence is, "For a customer who is interested in electronic products and fashion and is currently relaxing, please suggest using points for relaxation-related products." This system allows users to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also makes it possible to use points without missing their expiration date.

[0258] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0259] Step 1: User Registration

[0260] Users: Access the system using their own device and enter their user ID, password and basic contact information into the new registration form.

[0261] The terminal: collects the user's input data and sends it to the server using the HTTPS protocol.

[0262] The server: stores the received user registration information in a database and creates a new user object, which contains the user's ID and contact information.

[0263] Input: User ID, Password, Contact Information

[0264] Output: Creating a new user object and saving it to the database

[0265] Step 2: Input preference information and emotion data

[0266] Users input their preferences (e.g., electronic products, fashion), and use the camera and microphone to capture emotional data (e.g., facial expressions, voice tone).

[0267] The device: converts preference information into JSON format, analyzes emotion data, and sends it to the server.

[0268] The server: stores the received preference information and emotion data in a database and associates it with the user object.

[0269] Input: preference information, emotional data (facial expressions, tone of voice, etc.)

[0270] Output: Save preference information and emotion data to a database

[0271] Step 3: Input and merge points

[0272] Users: Enter their earned points and purchase history information into the terminal.

[0273] The terminal: converts the entered purchase history and point information into CSV format and sends it to the server.

[0274] The server: stores the received point data in a database, updates the user's point balance, and manages it centrally.

[0275] Input: Purchase history, point information (service name, number of points earned, purchase date, etc.)

[0276] Output: Updated points balance, centralized points data

[0277] Step 4: Generate optimal point usage proposals

[0278] When a user wants to know how to best use their points, they send a request from their device to the server.

[0279] The server retrieves user preference information, purchase history, and emotional data from the database and analyzes them using a generative AI model.

[0280] The server: Based on the analysis results, it generates a point usage suggestion that is optimal for the user's current emotional state and sends it to the terminal.

[0281] Input: User preference information, purchase history, emotional data

[0282] Output: Optimal point usage suggestions

[0283] Step 5: Points Expiration Notification

[0284] The server: periodically checks the expiration dates of points to see if any points are about to expire.

[0285] The server: When there is a point nearing its deadline, it selects the optimal notification timing and format based on the user's emotional data and sends the notification to the device.

[0286] The device: displays received notifications to the user and, if appropriate, alerts them with an audible alert or vibration.

[0287] Input: Points expiration date information, user sentiment data

[0288] Output: Expiration notification, alert to user

[0289] The above are the specific processing steps in which the system cooperates between the user, terminal, and server to send, receive, and process data, thereby suggesting optimal ways to use points to the user and notifying them of expiration dates.

[0290] (Application example 2)

[0291] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0292] Conventional point management systems were unable to centrally manage the points a user had earned, making it cumbersome to use points across multiple point programs. Furthermore, optimal point usage suggestions based on the user's preferences and purchase history were rarely made, and because the user's emotional state was not taken into consideration, point usage suggestions were often inappropriate for the user's current psychological state. As a result, users were unable to make effective use of their points, and points sometimes expired.

[0293] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the point expiration date is approaching, and means for recognizing the user's emotional state in real time and adjusting the suggestion content and notification timing based on the user's emotion. This allows the user to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also enables them to use their points without missing their expiration date.

[0294] "Centralized management" refers to the collection and management of points earned by users across multiple point programs in one place.

[0295] "Optimal proposal" means proposing the most advantageous way to use points to the user based on the user's purchasing history and preference information.

[0296] "Notification" refers to the act of informing a user of the approaching expiration date of points.

[0297] "Real-time recognition" means detecting and analyzing the user's emotional state instantly on the spot.

[0298] "Adjusting" means optimizing the content of suggestions and the timing of notifications according to the user's emotional state.

[0299] "Preference information" is information about the categories and characteristics of products and services that users prefer.

[0300] "Purchase history" is a record of products and services a user has purchased in the past.

[0301] "Emotional state" refers to a user's current emotional or psychological state.

[0302] A "points program" is a system in which points are awarded by using specific services or products, and those points can be exchanged for something.

[0303] "Analyzing" refers to the act of integrating and analyzing data such as a user's purchasing history, preferences, and emotional state to derive the most appropriate suggestions and notification methods.

[0304] "Suggestion content" refers to advice presented to users on how to use points and on product selection.

[0305] A "server" is a computer system that stores and manages user data and performs various processes.

[0306] "Timing" refers to the optimal time and situation for suggesting or notifying the use of points.

[0307] This invention provides a system that centrally manages points earned by a user from multiple point programs and uses emotion recognition to suggest optimal ways to use the points. First, the user accesses the system from their own device and registers. When registering, the user enters their user ID, preference information, and data for emotion recognition (e.g., facial expression data, voice tone data, etc.), and sends them to the server. The server stores the received data in a database and creates a new user object.

[0308] Next, the user enters the points information and purchase history they have earned from each service into the terminal and sends it to the server, which then integrates the received data and updates the point balance for centralized management.

[0309] When a user wants to know how to best use their points, they use their device to request optimal use suggestions. The server retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. Based on this data, a generative AI model is used to make optimal point use suggestions based on the user's current emotional state.

[0310] As an example of suggestions based on real-time emotional data, if a user is feeling stressed, the server will suggest using points to purchase relaxation-related products and services. When points are about to expire, the server will send a notification to the user. This notification will be delivered at the most effective time and in the most effective format, taking into account the user's emotional state.

[0311] The hardware used is a device (e.g., a smartphone or tablet) for emotion recognition, and a server for storing, managing, and processing data. The software includes an EmotionEngine for real-time recognition of user emotions, a database management system (e.g., UserDatabase, PointDatabase), and a module that provides notification functions.

[0312] For example, user "user_123" is recognized as being interested in electronic products and in a relaxed state. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this, consolidates the points, and suggests "using points for relaxation-related products" based on the generative AI model. Furthermore, if the points from service 1 are due to expire in a week, the server detects this and chooses a time when he is relaxing to send a notification.

[0313] Example prompt sentence:

[0314] user_id: 'user_123',

[0315] preferences: ['Electronics'],

[0316] emotion_data: ['Relax']

[0317] In this way, users can receive optimal point usage suggestions based on their emotional state, making efficient use of their points, and avoid missing their points' expiration dates.

[0318] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0319] Step 1:

[0320] A user accesses the system using their own device and registers. As input, they send their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.) to the server. The server receives this data, stores it in a database, and creates a new user object. This allows user information to be centrally managed within the system.

[0321] Step 2:

[0322] For each service for which a user has earned points, the user enters point information and purchase history into the terminal. The input, which includes the points earned, the service name, and purchase details, is sent to the server. The server receives this information, stores it in a database, updates the user's point balance, and centrally manages the points earned across all services.

[0323] Step 3:

[0324] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. As input, they send the user ID and the type of request to the server. The server retrieves the user's preference information, purchase history, and emotion recognition data from the database and recognizes their current emotional state in real time. As output, it makes optimal point use suggestions based on the generative AI model according to the user's emotional state.

[0325] Step 4:

[0326] The server generates suggestions based on real-time emotional data. For example, if a user is feeling stressed, it will suggest using points to purchase relaxation-related products and services. The inputs to the AI ​​model are emotion recognition data, preference information, and purchase history, and the output is a specific suggestion for using points.

[0327] Step 5:

[0328] When the points are about to expire, the server notifies the user. As input, it references the points expiration date and the user's current emotional state. The server sends the notification at the optimal timing, taking into account the emotional state. As output, the user is notified at the appropriate time.

[0329] Step 6:

[0330] Users receive suggestions and notifications through their devices and use points accordingly. As input, notifications and suggestions are received from the server. When users use points based on the suggestions presented, the optimal point usage intended by the system is realized. As output, the user's point usage history is recorded in the system.

[0331] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0332] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0333] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0334] [Second embodiment]

[0335] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0336] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0337] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0338] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0339] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0340] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0341] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0342] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0343] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0344] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0345] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0346] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0347] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on their purchasing history and preferences. This system functions in cooperation with the server, terminals, and users.

[0348] User registration and input of preferences

[0349] First, a user accesses the system using their own terminal and registers. When registering, they enter their user ID and preference information and send it to the server. The server stores the received user ID and preference information in a database, and creates and manages a new user object.

[0350] Integration with points purchase history

[0351] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0352] Generate optimal point usage proposals

[0353] Next, when the user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using the points when purchasing electronic products.

[0354] Points expiration notification

[0355] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0356] Specific examples

[0357] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0358] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0359] The processing flow will be explained below.

[0360] Step 1:

[0361] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID and preference information (e.g., electronic products, fashion, etc.).

[0362] Step 2:

[0363] The device sends the user ID and preference information entered by the user to the server, and the data is sent using a secure protocol.

[0364] Step 3:

[0365] The server stores the received user ID and preference information in a database, creates a user object, and adds it to the user list in the system.

[0366] Step 4:

[0367] When users earn points from multiple services, they enter their purchase data (service ID, number of points earned, purchase date, etc.) into the terminal.

[0368] Step 5:

[0369] The terminal sends the entered purchase data to the server, which receives it and saves and updates the user's purchase history and point balance in the database.

[0370] Step 6:

[0371] The server centralizes all received point information and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0372] Step 7:

[0373] When a user wants to know the best way to use points, the user uses the terminal to request a suggestion for the best use from the server.

[0374] Step 8:

[0375] The server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates optimal point usage suggestions, suggesting point usage for specific categories (e.g., electronic products).

[0376] Step 9:

[0377] The server sends the generated proposals to the user's device, where the user can review the proposals and select the optimal way to use their points.

[0378] Step 10:

[0379] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0380] Step 11:

[0381] The server notifies the user's device that the points are about to expire, and the user receives a notification on the device and is prompted to use the points before the expiration date.

[0382] Step 12:

[0383] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0384] These are the specific processing steps of the system, which allow users to efficiently manage multiple points and utilize them in the most optimal way.

[0385] Example 1

[0386] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0387] There is a need to centrally manage points earned by users across multiple point programs and to present optimal ways to use points by utilizing the user's purchase history and preference information. Another challenge is to efficiently notify users when points are about to expire and prevent them from expiring. There is a need to provide a system that allows users to use points in the most optimal way and avoid missing their expiration dates.

[0388] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0389] In this invention, the server includes a means for centrally managing points earned by a user through multiple point programs, a means for the user to register using their own terminal and input their user ID and preference information, a means for the server to store the received user information in a database and create and manage a new user object, and a means for generating optimal point usage suggestions based on the user's purchase history and preference information. This allows the user to easily centrally manage points earned through multiple point programs and use them in the most optimal way. The server also includes a means for notifying the user when points are about to expire, allowing the user to use them efficiently without missing their expiration dates.

[0390] A "user" is an individual or corporation that uses the system to centrally manage points and receive suggestions based on their purchasing history and preferences.

[0391] A "points program" is an incentive program in which a certain number of points are awarded when using or purchasing a specific service or product.

[0392] "Centralized management" refers to the centralized management of points earned in multiple point programs in one system or database.

[0393] "Terminal" means a device (such as a personal computer, smartphone, or tablet) that a user uses to access the system.

[0394] A "server" is a computing device that processes information received from users, stores it in a database, generates various offers, and sends notifications.

[0395] A "database" is a digital repository for storing and managing user information, preferences, purchase history, point balance, etc.

[0396] A "user object" is a collection of data including user information (ID, preferences, purchase history, etc.), and is an entity managed by the server.

[0397] "Purchase history" is a record of information about products and services a user has purchased in the past and points earned.

[0398] "Preference information" is information about product categories and services in which a user is interested, and is data that indicates the requests and wishes of individual users.

[0399] The "optimal point usage method" is the most effective way to use points, presented based on the user's purchasing history and preference information.

[0400] A "machine learning algorithm" is a computational method for analyzing user data and extracting patterns and trends, which are used to generate optimal recommendations.

[0401] The "expiration date" is information indicating the last day that points can be used, and points will expire after this date.

[0402] A "notification" is a message sent by the server to the terminal to inform the user that the expiration date of points is approaching.

[0403] This invention is a system that centrally manages points earned by a user through multiple point programs and suggests optimal ways to use points based on purchase history and preferences. This system functions in cooperation with the server, terminals, and users.

[0404] User registration and input of preferences

[0405] Users access the system using their own terminals and register as new users. When registering, the user enters their user ID and preference information, which are then sent to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. For example, MySQL is used as the database management system, and Apache is used as the web server software.

[0406] Integration with points purchase history

[0407] Every time a user earns points from a service, the user sends their purchase history and point information from their device to the server. The server receives this information and stores it in a database. The server then updates each user's point balance and centrally manages points for all services. This process uses data analysis tools such as the Python pandas library.

[0408] Generate optimal point usage proposals

[0409] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and a machine learning algorithm (e.g., random forest) is used to suggest the best way to use points for the user. After generating the suggestion, the server returns the best way to use points to the user's device. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0410] Points expiration notification

[0411] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. The server detects points that are about to expire and sends a notification to the user's device. This notification uses a push notification service such as Firebase Cloud Messaging. For example, if "Service 1 points will expire in one week," the server will detect this and notify the user.

[0412] Specific examples

[0413] For example, suppose user "user_123" is interested in electronic products and fashion. "user_123" earns 100 points from service 1 and 150 points from service 2, and enters this information into the system through his terminal. The server receives this information, stores it in the database, and consolidates his points, bringing his total points to 250. The server then suggests using his points to purchase electronic products based on his preferences. Furthermore, if his points from service 1 are about to expire in a week, the server will detect this and send a notification to his terminal.

[0414] Prompt Sentence Examples

[0415] Below are some example prompts to input to a generative AI model:

[0416] "User 'user_123' is interested in electronics and fashion. He has earned 100 points from Service 1 and 150 points from Service 2. Based on his preferences, please suggest the best way to use his points. Also, please explain how to notify him when his points from Service 1 will expire in a week."

[0417] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0418] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0419] Step 1:

[0420] A user accesses the system's web page or app using their own device and enters their user ID and preference information in the new registration form. The entered information (user ID and preference information) is sent from the device to the server. The server receives this information and stores it in a database. Specifically, the server uses a MySQL database to store the user ID and preference information as a new user object. The input of this step is the user ID and preference information, and the output is the creation and storage of a new user object.

[0421] Step 2:

[0422] Every time a user earns points from each service, the point information (purchase history and earned points) is sent from the terminal to the server. The server saves the received point information in the database and updates the existing user object. Specifically, the Python pandas library is used to add the purchase history and point information to the database and calculate the point balance for each user. The input to this step is the purchase history and earned point information, and the output is the updated user object and point balance.

[0423] Step 3:

[0424] The user uses their device to request an "optimal point usage suggestion" from the server. The server receives this request and retrieves the user's preference information and purchase history from a database. It then performs data analysis using the retrieved information and applies a machine learning algorithm (e.g., random forest) to generate the optimal point usage method. The generated suggestion is sent back from the server to the user's device. The input to this step is the preference information, purchase history, and suggestion request, and the output is the generated optimal point usage suggestion.

[0425] Step 4:

[0426] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. If the server detects that points are about to expire, it notifies the user's device of that information (e.g., "Service 1 points will expire in one week"). For notifications, a push notification service such as Firebase Cloud Messaging is used. The input of this step is the point expiration data, and the output is a notification of the expiration date sent to the user.

[0427] Specifically, the process proceeds as follows:

[0428] Step 1:

[0429] The user ID and preference information entered by the user on the device is sent to the server.

[0430] The server stores the received information in a MySQL database and creates a new user object.

[0431] Step 2:

[0432] Every time a user earns points, the purchase history and point information are sent from the terminal to the server.

[0433] The server uses the pandas library to store the received information in a database and update the user object.

[0434] Step 3:

[0435] The user requests the server from the terminal for optimal point usage suggestions.

[0436] The server retrieves preference information and purchase history from a database and uses machine learning algorithms such as random forests to generate and return suggestions.

[0437] Step 4:

[0438] The server periodically checks the point information using cron.

[0439] When it detects that a point is about to expire, it uses Firebase Cloud Messaging to notify the user of that information.

[0440] This system allows users to effectively manage their points in one place, receive suggestions on how to best use them, and prevent them from expiring.

[0441] (Application example 1)

[0442] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0443] In conventional point programs, users often had difficulty managing multiple points and often forgot about expiration dates. Furthermore, there were often insufficient suggestions on how to best use points, making it difficult for users to use points efficiently. As a result, points were often wasted, and there were issues with user convenience and satisfaction not improving.

[0444] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0445] In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the points are about to expire, and means for making point usage suggestions for multiple categories based on the user's preference information and purchase history. This allows the user to centrally manage points and receive optimal point usage suggestions based on the purchase history and preference information, enabling effective use of points and resolving conventional problems.

[0446] "Multiple point programs" refers to the entire point system in which a user earns points from different services and stores.

[0447] "Means of centralized management" refers to a method of integrating and managing points earned through different point programs in one place.

[0448] "Purchase history" refers to the complete record of a user's past purchases.

[0449] "Preference information" refers to information based on a user's hobbies and interests.

[0450] The "means for generating optimal proposals" refers to a method for providing the most effective way to use points based on the user's purchase history and preference information.

[0451] "Means for notifying users when the expiration date is approaching" refers to a method for notifying users when the expiration date of points is approaching.

[0452] "Multiple categories" refers to a whole range of different types or genres of goods and services.

[0453] "Means for making suggestions on how to use points" refers to a method or system for making suggestions to users on how to use points.

[0454] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on purchase history and preference information. This system functions in cooperation with the server, terminals, and users.

[0455] User registration and input of preferences

[0456] First, the user accesses the system using their own device and registers. When registering, they enter their user ID and preference information and send it to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. This makes it possible to suggest optimal ways to use points based on the user's preferences.

[0457] Integration with points purchase history

[0458] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0459] Generate optimal point usage proposals

[0460] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0461] Points expiration notification

[0462] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0463] Specific examples

[0464] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0465] This system allows users to centrally manage their points and receive optimal point usage suggestions based on their purchasing history and preference information, allowing them to make effective use of their points.

[0466] Examples of prompt statements

[0467] Example prompts to input to the generative AI model:

[0468] Develop a system that offers optimal point usage suggestions based on the user's purchase history and preferences. Design a system that works in cooperation between the server and the device, taking into account the following information:

[0469] 1. Registration of user ID and preference information.

[0470] 2. Integrated management of points earned through each service.

[0471] 3. Optimal point usage suggestions based on purchase history.

[0472] 4. Points Expiration Notification.

[0473] The system is implemented in Python and uses SQLite as the database.

[0474] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0475] Step 1: Register and enter your preferences

[0476] A user registers using a terminal, entering their user ID and preferences, which are then sent to the server, which stores the information in a database and creates a new user object.

[0477] Input: User ID, preference information

[0478] Data processing: Save user information to the database and create a user object

[0479] Output: User information is added to the database

[0480] Step 2: Merging your points with your purchase history

[0481] Users use their devices to send information about points earned across different services and their purchase history to the server. The server receives this information and stores it in a database. At the same time, it updates each user's point balance and manages it centrally.

[0482] Input: Service name, points information, purchase history

[0483] Data processing: Save information to database, update point balance

[0484] Output: Updated points balance reflected in database

[0485] Step 3: Generate optimal point usage proposals

[0486] When a user requests a point usage suggestion from the server, the server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates the optimal point usage suggestion and presents it to the user.

[0487] Input: User ID, preference information, purchase history

[0488] Data processing: Generate optimal proposals based on preference information and purchase history

[0489] Output: The best point usage suggestion is sent to the user.

[0490] Step 4: Points expiration notification

[0491] The server periodically checks the database for upcoming point expiration dates, and if any points are about to expire, the server sends a notification to the user's device.

[0492] Input: Point information, expiration date

[0493] Data processing: detecting points approaching expiration

[0494] Output: Expiration notification sent to user

[0495] Step 5: Use your points

[0496] If the user accepts the proposed point usage method, the terminal sends a notification to the server, which updates the point balance and subtracts the used points from the database.

[0497] Input: Point usage instructions

[0498] Data processing: Update point balance, subtract used points

[0499] Output: The updated points balance is reflected in the database and the user is notified of the result.

[0500] This trend will allow users to easily manage their points centrally and use them efficiently by being suggested the most optimal way to use them.

[0501] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0502] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0503] User registration and input of preferences

[0504] First, a user accesses the system using their own device and registers. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and data for recognizing the user's emotions (e.g., facial expressions, tone of voice, etc.) and send them to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database, and creates and manages a new user object.

[0505] Integration with points purchase history

[0506] For each service for which a user has earned points, the user enters information about their purchase history and earned points into the terminal. The terminal then sends this information to the server. The server stores the received purchase data in a database and updates the user's point balance. It also centrally manages points earned across all services.

[0507] Generate optimal point usage proposals

[0508] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. The server then retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. The server combines and analyzes this data to suggest the best way to use points based on the user's current emotional state. For example, if the user is feeling stressed, it will suggest using points for relaxation-related products and services.

[0509] Points expiration notification

[0510] The server periodically checks the expiration date of the user's points and notifies them if any points are about to expire. The timing and format of these notifications are adjusted based on real-time emotional data, and an approach tailored to the user's state is used. For example, notifications can be sent at times when the user is relaxed, providing information without causing stress.

[0511] Specific examples

[0512] For example, user "user_123" is interested in electronics and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this and consolidates the points. The server sets his balance at 250 points and suggests "using points for relaxation-related products" based on his preference information and emotion data. Also, if his points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0513] This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to use their points efficiently and without missing their points' expiration dates.

[0514] The processing flow will be explained below.

[0515] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0516] Step 1:

[0517] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.).

[0518] Step 2:

[0519] The device sends the user ID, preference information, and emotion recognition data entered by the user to the server using a secure protocol.

[0520] Step 3:

[0521] The server stores the received user ID, preference information, and emotion recognition data in a database, and also creates a new user object and adds it to the user list in the system.

[0522] Step 4:

[0523] The user enters purchase data (service ID, points earned, purchase date, etc.) for each service for which they earned points into the terminal.

[0524] Step 5:

[0525] The terminal sends the entered purchase data to the server, which receives it, stores it in a database, and updates the user's point balance.

[0526] Step 6:

[0527] The server centralizes point information from all services and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0528] Step 7:

[0529] The user sends a request from the device to the server asking how best to use their points, and the request also includes real-time emotional data recognized by the emotion engine.

[0530] Step 8:

[0531] The server retrieves user preference information and purchasing history from the database and analyzes it in combination with real-time emotional data from the emotion engine.

[0532] Step 9:

[0533] The server then uses the analysis results to generate optimal point usage methods based on the user's emotional state. For example, if the user is feeling stressed, the server will suggest using points for relaxation-related products and services.

[0534] Step 10:

[0535] The server sends the generated proposals to the user's device, where the user can review the proposals and select the best way to use their points.

[0536] Step 11:

[0537] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0538] Step 12:

[0539] The server notifies the user's device when their points are about to expire. The timing and format of this notification are adjusted based on the emotion data from the emotion engine. For example, the server can choose to send the notification during a time when the user is relaxed.

[0540] Step 13:

[0541] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0542] The above are the specific processing steps of the system. This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to efficiently manage and use their points.

[0543] Example 2

[0544] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0545] Nowadays, many users earn points from multiple services, but there are few ways to efficiently manage them centrally. Furthermore, there is often a lack of optimal suggestions for how to effectively use earned points. Furthermore, there is no system that can notify users in a timely manner when points are about to expire. To solve these problems, a system is needed that takes into account users' preferences and emotional state and makes optimal point usage suggestions.

[0546] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0547] In this invention, the server includes a means for centrally managing points earned by a user from multiple services, a means for inputting and saving user preference information and emotional data, a means for generating optimal point usage suggestions based on the user's purchase history, preference information, and emotional data, a means for notifying the user when the points are about to expire, and a means for adjusting the timing and format of the notification depending on the user's emotional state. This allows the user to efficiently manage points earned from multiple services and receive optimal point usage suggestions based on the user's emotional state. Furthermore, the user can receive timely notifications when the points are about to expire.

[0548] "User" means an individual or organization that uses the System to acquire points and manages and uses those points.

[0549] "Service" means a business or platform that offers transactions or activities through which users can earn points.

[0550] "Points" are numerical rewards that users earn by using specific services, and can be used for various benefits and exchangeable products.

[0551] "Centralized management" means comprehensively managing points earned from multiple services within a single system.

[0552] "Preference information" refers to information about a user's interests and preferences for specific products or services.

[0553] "Emotional data" is data that indicates the user's current emotional state and is collected from facial expressions, tone of voice, etc.

[0554] "Purchase history" is a record of past purchases made by a user, including the type of product and the date and time of purchase.

[0555] The "optimal suggestion" is a suggestion of how to use points that is considered to be most effective for the user, calculated based on the user's preference information, purchase history, and emotional state.

[0556] "Expiration date" refers to the date and time at which the points you have earned can be used.

[0557] "Notifications" are messages or alerts sent by the system to users to inform them of points expiration dates and other important matters.

[0558] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state in real time.

[0559] This invention relates to a system that centrally manages points earned by a user in multiple point programs and makes optimal point usage suggestions based on the user's purchase history, preference information, and emotional state. This system functions mainly through a server, terminals, and users, and provides suggestions based on the user's emotional state through an emotional engine.

[0560] User registration and input of preferences

[0561] Users access the system using their own devices and register. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.), and send this information to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database (e.g., MySQL or MongoDB) and creates a new user object. This object contains the user's basic information, preference information, and emotion data.

[0562] Integration with points purchase history

[0563] When a user earns points from each service, they enter their purchase history and earned point information into their device. The device converts this information into a structured data format (e.g., CSV or JSON) and sends it to the server. The server stores the received purchase data in a database and updates the user's point balance. The server centrally manages points earned from all services and maintains a consolidated point balance for each user.

[0564] Generate optimal point usage proposals

[0565] When a user wants to know how best to use their points, they use their device to send a request to the server. The server retrieves the user's preference information, purchase history, and real-time emotional data from an emotion engine (e.g., Affectiva or Microsoft Azure Emotion API) from a database. This data is combined and analyzed using a generative AI model. The server then sends the generated suggestions to the user's device, suggesting appropriate ways to use their points. For example, if the user is feeling stressed, it might suggest using their points for relaxation-related products and services.

[0566] Points expiration notification

[0567] The server periodically checks the point information in the database and notifies the user if any points are about to expire. This notification is timed optimally based on the user's real-time emotional data. For example, by selecting a time when the user is relaxed and sending a notification to the device, the information is conveyed to the user without causing stress.

[0568] For example, user "user_123" registers in the system that he is interested in electronic products and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, which he enters into the system. The server receives this and combines the points to make it 250 points. Based on the preference information and emotion data, the server suggests "using points for relaxation-related products." Also, if the points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0569] An example of a prompt sentence is, "For a customer who is interested in electronic products and fashion and is currently relaxing, please suggest using points for relaxation-related products." This system allows users to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also makes it possible to use points without missing their expiration date.

[0570] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0571] Step 1: User Registration

[0572] Users: Access the system using their own device and enter their user ID, password and basic contact information into the new registration form.

[0573] The terminal: collects the user's input data and sends it to the server using the HTTPS protocol.

[0574] The server: stores the received user registration information in a database and creates a new user object, which contains the user's ID and contact information.

[0575] Input: User ID, Password, Contact Information

[0576] Output: Creating a new user object and saving it to the database

[0577] Step 2: Input preference information and emotion data

[0578] Users input their preferences (e.g., electronic products, fashion), and use the camera and microphone to capture emotional data (e.g., facial expressions, voice tone).

[0579] The device: converts preference information into JSON format, analyzes emotion data, and sends it to the server.

[0580] The server: stores the received preference information and emotion data in a database and associates it with the user object.

[0581] Input: preference information, emotional data (facial expressions, tone of voice, etc.)

[0582] Output: Save preference information and emotion data to a database

[0583] Step 3: Input and merge points

[0584] Users: Enter their earned points and purchase history information into the terminal.

[0585] The terminal: converts the entered purchase history and point information into CSV format and sends it to the server.

[0586] The server: stores the received point data in a database, updates the user's point balance, and manages it centrally.

[0587] Input: Purchase history, point information (service name, number of points earned, purchase date, etc.)

[0588] Output: Updated points balance, centralized points data

[0589] Step 4: Generate optimal point usage proposals

[0590] When a user wants to know how to best use their points, they send a request from their device to the server.

[0591] The server retrieves user preference information, purchase history, and emotional data from the database and analyzes them using a generative AI model.

[0592] The server: Based on the analysis results, it generates a point usage suggestion that is optimal for the user's current emotional state and sends it to the terminal.

[0593] Input: User preference information, purchase history, emotional data

[0594] Output: Optimal point usage suggestions

[0595] Step 5: Points Expiration Notification

[0596] The server: periodically checks the expiration dates of points to see if any points are about to expire.

[0597] The server: When there is a point nearing its deadline, it selects the optimal notification timing and format based on the user's emotional data and sends the notification to the device.

[0598] The device: displays received notifications to the user and, if appropriate, alerts them with an audible alert or vibration.

[0599] Input: Points expiration date information, user sentiment data

[0600] Output: Expiration notification, alert to user

[0601] The above are the specific processing steps in which the system cooperates between the user, terminal, and server to send, receive, and process data, thereby suggesting optimal ways to use points to the user and notifying them of expiration dates.

[0602] (Application example 2)

[0603] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0604] Conventional point management systems were unable to centrally manage the points a user had earned, making it cumbersome to use points across multiple point programs. Furthermore, optimal point usage suggestions based on the user's preferences and purchase history were rarely made, and because the user's emotional state was not taken into consideration, point usage suggestions were often inappropriate for the user's current psychological state. As a result, users were unable to make effective use of their points, and points sometimes expired.

[0605] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the point expiration date is approaching, and means for recognizing the user's emotional state in real time and adjusting the suggestion content and notification timing based on the user's emotion. This allows the user to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also enables them to use their points without missing their expiration date.

[0606] "Centralized management" refers to the collection and management of points earned by users across multiple point programs in one place.

[0607] "Optimal proposal" means proposing the most advantageous way to use points to the user based on the user's purchasing history and preference information.

[0608] "Notification" refers to the act of informing a user of the approaching expiration date of points.

[0609] "Real-time recognition" means detecting and analyzing the user's emotional state instantly on the spot.

[0610] "Adjusting" means optimizing the content of suggestions and the timing of notifications according to the user's emotional state.

[0611] "Preference information" is information about the categories and characteristics of products and services that users prefer.

[0612] "Purchase history" is a record of products and services a user has purchased in the past.

[0613] "Emotional state" refers to a user's current emotional or psychological state.

[0614] A "points program" is a system in which points are awarded by using specific services or products, and those points can be exchanged for something.

[0615] "Analyzing" refers to the act of integrating and analyzing data such as a user's purchasing history, preferences, and emotional state to derive the most appropriate suggestions and notification methods.

[0616] "Suggestion content" refers to advice presented to users on how to use points and on product selection.

[0617] A "server" is a computer system that stores and manages user data and performs various processes.

[0618] "Timing" refers to the optimal time and situation for suggesting or notifying the use of points.

[0619] This invention provides a system that centrally manages points earned by a user from multiple point programs and uses emotion recognition to suggest optimal ways to use the points. First, the user accesses the system from their own device and registers. When registering, the user enters their user ID, preference information, and data for emotion recognition (e.g., facial expression data, voice tone data, etc.), and sends them to the server. The server stores the received data in a database and creates a new user object.

[0620] Next, the user enters the points information and purchase history they have earned from each service into the terminal and sends it to the server, which then integrates the received data and updates the point balance for centralized management.

[0621] When a user wants to know how to best use their points, they use their device to request optimal use suggestions. The server retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. Based on this data, a generative AI model is used to make optimal point use suggestions based on the user's current emotional state.

[0622] As an example of suggestions based on real-time emotional data, if a user is feeling stressed, the server will suggest using points to purchase relaxation-related products and services. When points are about to expire, the server will send a notification to the user. This notification will be delivered at the most effective time and in the most effective format, taking into account the user's emotional state.

[0623] The hardware used is a device (e.g., a smartphone or tablet) for emotion recognition, and a server for storing, managing, and processing data. The software includes an EmotionEngine for real-time recognition of user emotions, a database management system (e.g., UserDatabase, PointDatabase), and a module that provides notification functions.

[0624] For example, user "user_123" is recognized as being interested in electronic products and in a relaxed state. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this, consolidates the points, and suggests "using points for relaxation-related products" based on the generative AI model. Furthermore, if the points from service 1 are due to expire in a week, the server detects this and chooses a time when he is relaxing to send a notification.

[0625] Example prompt sentence:

[0626] user_id: 'user_123',

[0627] preferences: ['Electronics'],

[0628] emotion_data: ['Relax']

[0629] In this way, users can receive optimal point usage suggestions based on their emotional state, making efficient use of their points, and avoid missing their points' expiration dates.

[0630] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0631] Step 1:

[0632] A user accesses the system using their own device and registers. As input, they send their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.) to the server. The server receives this data, stores it in a database, and creates a new user object. This allows user information to be centrally managed within the system.

[0633] Step 2:

[0634] For each service for which a user has earned points, the user enters point information and purchase history into the terminal. The input, which includes the points earned, the service name, and purchase details, is sent to the server. The server receives this information, stores it in a database, updates the user's point balance, and centrally manages the points earned across all services.

[0635] Step 3:

[0636] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. As input, they send the user ID and the type of request to the server. The server retrieves the user's preference information, purchase history, and emotion recognition data from the database and recognizes their current emotional state in real time. As output, it makes optimal point use suggestions based on the generative AI model according to the user's emotional state.

[0637] Step 4:

[0638] The server generates suggestions based on real-time emotional data. For example, if a user is feeling stressed, it will suggest using points to purchase relaxation-related products and services. The inputs to the AI ​​model are emotion recognition data, preference information, and purchase history, and the output is a specific suggestion for using points.

[0639] Step 5:

[0640] When the points are about to expire, the server notifies the user. As input, it references the points expiration date and the user's current emotional state. The server sends the notification at the optimal timing, taking into account the emotional state. As output, the user is notified at the appropriate time.

[0641] Step 6:

[0642] Users receive suggestions and notifications through their devices and use points accordingly. As input, notifications and suggestions are received from the server. When users use points based on the suggestions presented, the optimal point usage intended by the system is realized. As output, the user's point usage history is recorded in the system.

[0643] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0644] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0645] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0646] [Third embodiment]

[0647] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0648] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0649] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0650] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0651] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0652] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0653] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0654] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0655] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0656] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0657] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0658] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0659] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on their purchasing history and preferences. This system functions in cooperation with the server, terminals, and users.

[0660] User registration and input of preferences

[0661] First, a user accesses the system using their own terminal and registers. When registering, they enter their user ID and preference information and send it to the server. The server stores the received user ID and preference information in a database, and creates and manages a new user object.

[0662] Integration with points purchase history

[0663] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0664] Generate optimal point usage proposals

[0665] Next, when the user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using the points when purchasing electronic products.

[0666] Points expiration notification

[0667] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0668] Specific examples

[0669] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0670] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0671] The processing flow will be explained below.

[0672] Step 1:

[0673] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID and preference information (e.g., electronic products, fashion, etc.).

[0674] Step 2:

[0675] The device sends the user ID and preference information entered by the user to the server, and the data is sent using a secure protocol.

[0676] Step 3:

[0677] The server stores the received user ID and preference information in a database, creates a user object, and adds it to the user list in the system.

[0678] Step 4:

[0679] When users earn points from multiple services, they enter their purchase data (service ID, number of points earned, purchase date, etc.) into the terminal.

[0680] Step 5:

[0681] The terminal sends the entered purchase data to the server, which receives it and saves and updates the user's purchase history and point balance in the database.

[0682] Step 6:

[0683] The server centralizes all received point information and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0684] Step 7:

[0685] When a user wants to know the best way to use points, the user uses the terminal to request a suggestion for the best use from the server.

[0686] Step 8:

[0687] The server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates optimal point usage suggestions, suggesting point usage for specific categories (e.g., electronic products).

[0688] Step 9:

[0689] The server sends the generated proposals to the user's device, where the user can review the proposals and select the optimal way to use their points.

[0690] Step 10:

[0691] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0692] Step 11:

[0693] The server notifies the user's device that the points are about to expire, and the user receives a notification on the device and is prompted to use the points before the expiration date.

[0694] Step 12:

[0695] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0696] These are the specific processing steps of the system, which allow users to efficiently manage multiple points and utilize them in the most optimal way.

[0697] Example 1

[0698] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0699] There is a need to centrally manage points earned by users across multiple point programs and to present optimal ways to use points by utilizing the user's purchase history and preference information. Another challenge is to efficiently notify users when points are about to expire and prevent them from expiring. There is a need to provide a system that allows users to use points in the most optimal way and avoid missing their expiration dates.

[0700] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0701] In this invention, the server includes a means for centrally managing points earned by a user through multiple point programs, a means for the user to register using their own terminal and input their user ID and preference information, a means for the server to store the received user information in a database and create and manage a new user object, and a means for generating optimal point usage suggestions based on the user's purchase history and preference information. This allows the user to easily centrally manage points earned through multiple point programs and use them in the most optimal way. The server also includes a means for notifying the user when points are about to expire, allowing the user to use them efficiently without missing their expiration dates.

[0702] A "user" is an individual or corporation that uses the system to centrally manage points and receive suggestions based on their purchasing history and preferences.

[0703] A "points program" is an incentive program in which a certain number of points are awarded when using or purchasing a specific service or product.

[0704] "Centralized management" refers to the centralized management of points earned in multiple point programs in one system or database.

[0705] "Terminal" means a device (such as a personal computer, smartphone, or tablet) that a user uses to access the system.

[0706] A "server" is a computing device that processes information received from users, stores it in a database, generates various offers, and sends notifications.

[0707] A "database" is a digital repository for storing and managing user information, preferences, purchase history, point balance, etc.

[0708] A "user object" is a collection of data including user information (ID, preferences, purchase history, etc.), and is an entity managed by the server.

[0709] "Purchase history" is a record of information about products and services a user has purchased in the past and points earned.

[0710] "Preference information" is information about product categories and services in which a user is interested, and is data that indicates the requests and wishes of individual users.

[0711] The "optimal point usage method" is the most effective way to use points, presented based on the user's purchasing history and preference information.

[0712] A "machine learning algorithm" is a computational method for analyzing user data and extracting patterns and trends, which are used to generate optimal recommendations.

[0713] The "expiration date" is information indicating the last day that points can be used, and points will expire after this date.

[0714] A "notification" is a message sent by the server to the terminal to inform the user that the expiration date of points is approaching.

[0715] This invention is a system that centrally manages points earned by a user through multiple point programs and suggests optimal ways to use points based on purchase history and preferences. This system functions in cooperation with the server, terminals, and users.

[0716] User registration and input of preferences

[0717] Users access the system using their own terminals and register as new users. When registering, the user enters their user ID and preference information, which are then sent to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. For example, MySQL is used as the database management system, and Apache is used as the web server software.

[0718] Integration with points purchase history

[0719] Every time a user earns points from a service, the user sends their purchase history and point information from their device to the server. The server receives this information and stores it in a database. The server then updates each user's point balance and centrally manages points for all services. This process uses data analysis tools such as the Python pandas library.

[0720] Generate optimal point usage proposals

[0721] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and a machine learning algorithm (e.g., random forest) is used to suggest the best way to use points for the user. After generating the suggestion, the server returns the best way to use points to the user's device. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0722] Points expiration notification

[0723] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. The server detects points that are about to expire and sends a notification to the user's device. This notification uses a push notification service such as Firebase Cloud Messaging. For example, if "Service 1 points will expire in one week," the server will detect this and notify the user.

[0724] Specific examples

[0725] For example, suppose user "user_123" is interested in electronic products and fashion. "user_123" earns 100 points from service 1 and 150 points from service 2, and enters this information into the system through his terminal. The server receives this information, stores it in the database, and consolidates his points, bringing his total points to 250. The server then suggests using his points to purchase electronic products based on his preferences. Furthermore, if his points from service 1 are about to expire in a week, the server will detect this and send a notification to his terminal.

[0726] Prompt Sentence Examples

[0727] Below are some example prompts to input to a generative AI model:

[0728] "User 'user_123' is interested in electronics and fashion. He has earned 100 points from Service 1 and 150 points from Service 2. Based on his preferences, please suggest the best way to use his points. Also, please explain how to notify him when his points from Service 1 will expire in a week."

[0729] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0730] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0731] Step 1:

[0732] A user accesses the system's web page or app using their own device and enters their user ID and preference information in the new registration form. The entered information (user ID and preference information) is sent from the device to the server. The server receives this information and stores it in a database. Specifically, the server uses a MySQL database to store the user ID and preference information as a new user object. The input of this step is the user ID and preference information, and the output is the creation and storage of a new user object.

[0733] Step 2:

[0734] Every time a user earns points from each service, the point information (purchase history and earned points) is sent from the terminal to the server. The server saves the received point information in the database and updates the existing user object. Specifically, the Python pandas library is used to add the purchase history and point information to the database and calculate the point balance for each user. The input to this step is the purchase history and earned point information, and the output is the updated user object and point balance.

[0735] Step 3:

[0736] The user uses their device to request an "optimal point usage suggestion" from the server. The server receives this request and retrieves the user's preference information and purchase history from a database. It then performs data analysis using the retrieved information and applies a machine learning algorithm (e.g., random forest) to generate the optimal point usage method. The generated suggestion is sent back from the server to the user's device. The input to this step is the preference information, purchase history, and suggestion request, and the output is the generated optimal point usage suggestion.

[0737] Step 4:

[0738] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. If the server detects that points are about to expire, it notifies the user's device of that information (e.g., "Service 1 points will expire in one week"). For notifications, a push notification service such as Firebase Cloud Messaging is used. The input of this step is the point expiration data, and the output is a notification of the expiration date sent to the user.

[0739] Specifically, the process proceeds as follows:

[0740] Step 1:

[0741] The user ID and preference information entered by the user on the device is sent to the server.

[0742] The server stores the received information in a MySQL database and creates a new user object.

[0743] Step 2:

[0744] Every time a user earns points, the purchase history and point information are sent from the terminal to the server.

[0745] The server uses the pandas library to store the received information in a database and update the user object.

[0746] Step 3:

[0747] The user requests the server from the terminal for optimal point usage suggestions.

[0748] The server retrieves preference information and purchase history from a database and uses machine learning algorithms such as random forests to generate and return suggestions.

[0749] Step 4:

[0750] The server periodically checks the point information using cron.

[0751] When it detects that a point is about to expire, it uses Firebase Cloud Messaging to notify the user of that information.

[0752] This system allows users to effectively manage their points in one place, receive suggestions on how to best use them, and prevent them from expiring.

[0753] (Application example 1)

[0754] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0755] In conventional point programs, users often had difficulty managing multiple points and often forgot about expiration dates. Furthermore, there were often insufficient suggestions on how to best use points, making it difficult for users to use points efficiently. As a result, points were often wasted, and there were issues with user convenience and satisfaction not improving.

[0756] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0757] In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the points are about to expire, and means for making point usage suggestions for multiple categories based on the user's preference information and purchase history. This allows the user to centrally manage points and receive optimal point usage suggestions based on the purchase history and preference information, enabling effective use of points and resolving conventional problems.

[0758] "Multiple point programs" refers to the entire point system in which a user earns points from different services and stores.

[0759] "Means of centralized management" refers to a method of integrating and managing points earned through different point programs in one place.

[0760] "Purchase history" refers to the complete record of a user's past purchases.

[0761] "Preference information" refers to information based on a user's hobbies and interests.

[0762] The "means for generating optimal proposals" refers to a method for providing the most effective way to use points based on the user's purchase history and preference information.

[0763] "Means for notifying users when the expiration date is approaching" refers to a method for notifying users when the expiration date of points is approaching.

[0764] "Multiple categories" refers to a whole range of different types or genres of goods and services.

[0765] "Means for making suggestions on how to use points" refers to a method or system for making suggestions to users on how to use points.

[0766] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on purchase history and preference information. This system functions in cooperation with the server, terminals, and users.

[0767] User registration and input of preferences

[0768] First, the user accesses the system using their own device and registers. When registering, they enter their user ID and preference information and send it to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. This makes it possible to suggest optimal ways to use points based on the user's preferences.

[0769] Integration with points purchase history

[0770] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0771] Generate optimal point usage proposals

[0772] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[0773] Points expiration notification

[0774] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0775] Specific examples

[0776] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0777] This system allows users to centrally manage their points and receive optimal point usage suggestions based on their purchasing history and preference information, allowing them to make effective use of their points.

[0778] Examples of prompt statements

[0779] Example prompts to input to the generative AI model:

[0780] Develop a system that offers optimal point usage suggestions based on the user's purchase history and preferences. Design a system that works in cooperation between the server and the device, taking into account the following information:

[0781] 1. Registration of user ID and preference information.

[0782] 2. Integrated management of points earned through each service.

[0783] 3. Optimal point usage suggestions based on purchase history.

[0784] 4. Points Expiration Notification.

[0785] The system is implemented in Python and uses SQLite as the database.

[0786] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0787] Step 1: Register and enter your preferences

[0788] A user registers using a terminal, entering their user ID and preferences, which are then sent to the server, which stores the information in a database and creates a new user object.

[0789] Input: User ID, preference information

[0790] Data processing: Save user information to the database and create a user object

[0791] Output: User information is added to the database

[0792] Step 2: Merging your points with your purchase history

[0793] Users use their devices to send information about points earned across different services and their purchase history to the server. The server receives this information and stores it in a database. At the same time, it updates each user's point balance and manages it centrally.

[0794] Input: Service name, points information, purchase history

[0795] Data processing: Save information to database, update point balance

[0796] Output: Updated points balance reflected in database

[0797] Step 3: Generate optimal point usage proposals

[0798] When a user requests a point usage suggestion from the server, the server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates the optimal point usage suggestion and presents it to the user.

[0799] Input: User ID, preference information, purchase history

[0800] Data processing: Generate optimal proposals based on preference information and purchase history

[0801] Output: The best point usage suggestion is sent to the user.

[0802] Step 4: Points expiration notification

[0803] The server periodically checks the database for upcoming point expiration dates, and if any points are about to expire, the server sends a notification to the user's device.

[0804] Input: Point information, expiration date

[0805] Data processing: detecting points approaching expiration

[0806] Output: Expiration notification sent to user

[0807] Step 5: Use your points

[0808] If the user accepts the proposed point usage method, the terminal sends a notification to the server, which updates the point balance and subtracts the used points from the database.

[0809] Input: Point usage instructions

[0810] Data processing: Update point balance, subtract used points

[0811] Output: The updated points balance is reflected in the database and the user is notified of the result.

[0812] This trend will allow users to easily manage their points centrally and use them efficiently by being suggested the most optimal way to use them.

[0813] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0814] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0815] User registration and input of preferences

[0816] First, a user accesses the system using their own device and registers. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and data for recognizing the user's emotions (e.g., facial expressions, tone of voice, etc.) and send them to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database, and creates and manages a new user object.

[0817] Integration with points purchase history

[0818] For each service for which a user has earned points, the user enters information about their purchase history and earned points into the terminal. The terminal then sends this information to the server. The server stores the received purchase data in a database and updates the user's point balance. It also centrally manages points earned across all services.

[0819] Generate optimal point usage proposals

[0820] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. The server then retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. The server combines and analyzes this data to suggest the best way to use points based on the user's current emotional state. For example, if the user is feeling stressed, it will suggest using points for relaxation-related products and services.

[0821] Points expiration notification

[0822] The server periodically checks the expiration date of the user's points and notifies them if any points are about to expire. The timing and format of these notifications are adjusted based on real-time emotional data, and an approach tailored to the user's state is used. For example, notifications can be sent at times when the user is relaxed, providing information without causing stress.

[0823] Specific examples

[0824] For example, user "user_123" is interested in electronics and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this and consolidates the points. The server sets his balance at 250 points and suggests "using points for relaxation-related products" based on his preference information and emotion data. Also, if his points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0825] This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to use their points efficiently and without missing their points' expiration dates.

[0826] The processing flow will be explained below.

[0827] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[0828] Step 1:

[0829] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.).

[0830] Step 2:

[0831] The device sends the user ID, preference information, and emotion recognition data entered by the user to the server using a secure protocol.

[0832] Step 3:

[0833] The server stores the received user ID, preference information, and emotion recognition data in a database, and also creates a new user object and adds it to the user list in the system.

[0834] Step 4:

[0835] The user enters purchase data (service ID, points earned, purchase date, etc.) for each service for which they earned points into the terminal.

[0836] Step 5:

[0837] The terminal sends the entered purchase data to the server, which receives it, stores it in a database, and updates the user's point balance.

[0838] Step 6:

[0839] The server centralizes point information from all services and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0840] Step 7:

[0841] The user sends a request from the device to the server asking how best to use their points, and the request also includes real-time emotional data recognized by the emotion engine.

[0842] Step 8:

[0843] The server retrieves user preference information and purchasing history from the database and analyzes it in combination with real-time emotional data from the emotion engine.

[0844] Step 9:

[0845] The server then uses the analysis results to generate optimal point usage methods based on the user's emotional state. For example, if the user is feeling stressed, the server will suggest using points for relaxation-related products and services.

[0846] Step 10:

[0847] The server sends the generated proposals to the user's device, where the user can review the proposals and select the best way to use their points.

[0848] Step 11:

[0849] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[0850] Step 12:

[0851] The server notifies the user's device when their points are about to expire. The timing and format of this notification are adjusted based on the emotion data from the emotion engine. For example, the server can choose to send the notification during a time when the user is relaxed.

[0852] Step 13:

[0853] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[0854] The above are the specific processing steps of the system. This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to efficiently manage and use their points.

[0855] Example 2

[0856] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0857] Nowadays, many users earn points from multiple services, but there are few ways to efficiently manage them centrally. Furthermore, there is often a lack of optimal suggestions for how to effectively use earned points. Furthermore, there is no system that can notify users in a timely manner when points are about to expire. To solve these problems, a system is needed that takes into account users' preferences and emotional state and makes optimal point usage suggestions.

[0858] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0859] In this invention, the server includes a means for centrally managing points earned by a user from multiple services, a means for inputting and saving user preference information and emotional data, a means for generating optimal point usage suggestions based on the user's purchase history, preference information, and emotional data, a means for notifying the user when the points are about to expire, and a means for adjusting the timing and format of the notification depending on the user's emotional state. This allows the user to efficiently manage points earned from multiple services and receive optimal point usage suggestions based on the user's emotional state. Furthermore, the user can receive timely notifications when the points are about to expire.

[0860] "User" means an individual or organization that uses the System to acquire points and manages and uses those points.

[0861] "Service" means a business or platform that offers transactions or activities through which users can earn points.

[0862] "Points" are numerical rewards that users earn by using specific services, and can be used for various benefits and exchangeable products.

[0863] "Centralized management" means comprehensively managing points earned from multiple services within a single system.

[0864] "Preference information" refers to information about a user's interests and preferences for specific products or services.

[0865] "Emotional data" is data that indicates the user's current emotional state and is collected from facial expressions, tone of voice, etc.

[0866] "Purchase history" is a record of past purchases made by a user, including the type of product and the date and time of purchase.

[0867] The "optimal suggestion" is a suggestion of how to use points that is considered to be most effective for the user, calculated based on the user's preference information, purchase history, and emotional state.

[0868] "Expiration date" refers to the date and time at which the points you have earned can be used.

[0869] "Notifications" are messages or alerts sent by the system to users to inform them of points expiration dates and other important matters.

[0870] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state in real time.

[0871] This invention relates to a system that centrally manages points earned by a user in multiple point programs and makes optimal point usage suggestions based on the user's purchase history, preference information, and emotional state. This system functions mainly through a server, terminals, and users, and provides suggestions based on the user's emotional state through an emotional engine.

[0872] User registration and input of preferences

[0873] Users access the system using their own devices and register. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.), and send this information to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database (e.g., MySQL or MongoDB) and creates a new user object. This object contains the user's basic information, preference information, and emotion data.

[0874] Integration with points purchase history

[0875] When a user earns points from each service, they enter their purchase history and earned point information into their device. The device converts this information into a structured data format (e.g., CSV or JSON) and sends it to the server. The server stores the received purchase data in a database and updates the user's point balance. The server centrally manages points earned from all services and maintains a consolidated point balance for each user.

[0876] Generate optimal point usage proposals

[0877] When a user wants to know how best to use their points, they use their device to send a request to the server. The server retrieves the user's preference information, purchase history, and real-time emotional data from an emotion engine (e.g., Affectiva or Microsoft Azure Emotion API) from a database. This data is combined and analyzed using a generative AI model. The server then sends the generated suggestions to the user's device, suggesting appropriate ways to use their points. For example, if the user is feeling stressed, it might suggest using their points for relaxation-related products and services.

[0878] Points expiration notification

[0879] The server periodically checks the point information in the database and notifies the user if any points are about to expire. This notification is timed optimally based on the user's real-time emotional data. For example, by selecting a time when the user is relaxed and sending a notification to the device, the information is conveyed to the user without causing stress.

[0880] For example, user "user_123" registers in the system that he is interested in electronic products and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, which he enters into the system. The server receives this and combines the points to make it 250 points. Based on the preference information and emotion data, the server suggests "using points for relaxation-related products." Also, if the points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[0881] An example of a prompt sentence is, "For a customer who is interested in electronic products and fashion and is currently relaxing, please suggest using points for relaxation-related products." This system allows users to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also makes it possible to use points without missing their expiration date.

[0882] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0883] Step 1: User Registration

[0884] Users: Access the system using their own device and enter their user ID, password and basic contact information into the new registration form.

[0885] The terminal: collects the user's input data and sends it to the server using the HTTPS protocol.

[0886] The server: stores the received user registration information in a database and creates a new user object, which contains the user's ID and contact information.

[0887] Input: User ID, Password, Contact Information

[0888] Output: Creating a new user object and saving it to the database

[0889] Step 2: Input preference information and emotion data

[0890] Users input their preferences (e.g., electronic products, fashion), and use the camera and microphone to capture emotional data (e.g., facial expressions, voice tone).

[0891] The device: converts preference information into JSON format, analyzes emotion data, and sends it to the server.

[0892] The server: stores the received preference information and emotion data in a database and associates it with the user object.

[0893] Input: preference information, emotional data (facial expressions, tone of voice, etc.)

[0894] Output: Save preference information and emotion data to a database

[0895] Step 3: Input and merge points

[0896] Users: Enter their earned points and purchase history information into the terminal.

[0897] The terminal: converts the entered purchase history and point information into CSV format and sends it to the server.

[0898] The server: stores the received point data in a database, updates the user's point balance, and manages it centrally.

[0899] Input: Purchase history, point information (service name, number of points earned, purchase date, etc.)

[0900] Output: Updated points balance, centralized points data

[0901] Step 4: Generate optimal point usage proposals

[0902] When a user wants to know how to best use their points, they send a request from their device to the server.

[0903] The server retrieves user preference information, purchase history, and emotional data from the database and analyzes them using a generative AI model.

[0904] The server: Based on the analysis results, it generates a point usage suggestion that is optimal for the user's current emotional state and sends it to the terminal.

[0905] Input: User preference information, purchase history, emotional data

[0906] Output: Optimal point usage suggestions

[0907] Step 5: Points Expiration Notification

[0908] The server: periodically checks the expiration dates of points to see if any points are about to expire.

[0909] The server: When there is a point nearing its deadline, it selects the optimal notification timing and format based on the user's emotional data and sends the notification to the device.

[0910] The device: displays received notifications to the user and, if appropriate, alerts them with an audible alert or vibration.

[0911] Input: Points expiration date information, user sentiment data

[0912] Output: Expiration notification, alert to user

[0913] The above are the specific processing steps in which the system cooperates between the user, terminal, and server to send, receive, and process data, thereby suggesting optimal ways to use points to the user and notifying them of expiration dates.

[0914] (Application example 2)

[0915] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0916] Conventional point management systems were unable to centrally manage the points a user had earned, making it cumbersome to use points across multiple point programs. Furthermore, optimal point usage suggestions based on the user's preferences and purchase history were rarely made, and because the user's emotional state was not taken into consideration, point usage suggestions were often inappropriate for the user's current psychological state. As a result, users were unable to make effective use of their points, and points sometimes expired.

[0917] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the point expiration date is approaching, and means for recognizing the user's emotional state in real time and adjusting the suggestion content and notification timing based on the user's emotion. This allows the user to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also enables them to use their points without missing their expiration date.

[0918] "Centralized management" refers to the collection and management of points earned by users across multiple point programs in one place.

[0919] "Optimal proposal" means proposing the most advantageous way to use points to the user based on the user's purchasing history and preference information.

[0920] "Notification" refers to the act of informing a user of the approaching expiration date of points.

[0921] "Real-time recognition" means detecting and analyzing the user's emotional state instantly on the spot.

[0922] "Adjusting" means optimizing the content of suggestions and the timing of notifications according to the user's emotional state.

[0923] "Preference information" is information about the categories and characteristics of products and services that users prefer.

[0924] "Purchase history" is a record of products and services a user has purchased in the past.

[0925] "Emotional state" refers to a user's current emotional or psychological state.

[0926] A "points program" is a system in which points are awarded by using specific services or products, and those points can be exchanged for something.

[0927] "Analyzing" refers to the act of integrating and analyzing data such as a user's purchasing history, preferences, and emotional state to derive the most appropriate suggestions and notification methods.

[0928] "Suggestion content" refers to advice presented to users on how to use points and on product selection.

[0929] A "server" is a computer system that stores and manages user data and performs various processes.

[0930] "Timing" refers to the optimal time and situation for suggesting or notifying the use of points.

[0931] This invention provides a system that centrally manages points earned by a user from multiple point programs and uses emotion recognition to suggest optimal ways to use the points. First, the user accesses the system from their own device and registers. When registering, the user enters their user ID, preference information, and data for emotion recognition (e.g., facial expression data, voice tone data, etc.), and sends them to the server. The server stores the received data in a database and creates a new user object.

[0932] Next, the user enters the points information and purchase history they have earned from each service into the terminal and sends it to the server, which then integrates the received data and updates the point balance for centralized management.

[0933] When a user wants to know how to best use their points, they use their device to request optimal use suggestions. The server retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. Based on this data, a generative AI model is used to make optimal point use suggestions based on the user's current emotional state.

[0934] As an example of suggestions based on real-time emotional data, if a user is feeling stressed, the server will suggest using points to purchase relaxation-related products and services. When points are about to expire, the server will send a notification to the user. This notification will be delivered at the most effective time and in the most effective format, taking into account the user's emotional state.

[0935] The hardware used is a device (e.g., a smartphone or tablet) for emotion recognition, and a server for storing, managing, and processing data. The software includes an EmotionEngine for real-time recognition of user emotions, a database management system (e.g., UserDatabase, PointDatabase), and a module that provides notification functions.

[0936] For example, user "user_123" is recognized as being interested in electronic products and in a relaxed state. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this, consolidates the points, and suggests "using points for relaxation-related products" based on the generative AI model. Furthermore, if the points from service 1 are due to expire in a week, the server detects this and chooses a time when he is relaxing to send a notification.

[0937] Example prompt sentence:

[0938] user_id: 'user_123',

[0939] preferences: ['Electronics'],

[0940] emotion_data: ['Relax']

[0941] In this way, users can receive optimal point usage suggestions based on their emotional state, making efficient use of their points, and avoid missing their points' expiration dates.

[0942] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0943] Step 1:

[0944] A user accesses the system using their own device and registers. As input, they send their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.) to the server. The server receives this data, stores it in a database, and creates a new user object. This allows user information to be centrally managed within the system.

[0945] Step 2:

[0946] For each service for which a user has earned points, the user enters point information and purchase history into the terminal. The input, which includes the points earned, the service name, and purchase details, is sent to the server. The server receives this information, stores it in a database, updates the user's point balance, and centrally manages the points earned across all services.

[0947] Step 3:

[0948] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. As input, they send the user ID and the type of request to the server. The server retrieves the user's preference information, purchase history, and emotion recognition data from the database and recognizes their current emotional state in real time. As output, it makes optimal point use suggestions based on the generative AI model according to the user's emotional state.

[0949] Step 4:

[0950] The server generates suggestions based on real-time emotional data. For example, if a user is feeling stressed, it will suggest using points to purchase relaxation-related products and services. The inputs to the AI ​​model are emotion recognition data, preference information, and purchase history, and the output is a specific suggestion for using points.

[0951] Step 5:

[0952] When the points are about to expire, the server notifies the user. As input, it references the points expiration date and the user's current emotional state. The server sends the notification at the optimal timing, taking into account the emotional state. As output, the user is notified at the appropriate time.

[0953] Step 6:

[0954] Users receive suggestions and notifications through their devices and use points accordingly. As input, notifications and suggestions are received from the server. When users use points based on the suggestions presented, the optimal point usage intended by the system is realized. As output, the user's point usage history is recorded in the system.

[0955] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0956] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0957] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0958] [Fourth embodiment]

[0959] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0960] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0961] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0962] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0963] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0964] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0965] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0966] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0967] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0968] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0969] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0970] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0971] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0972] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on their purchasing history and preferences. This system functions in cooperation with the server, terminals, and users.

[0973] User registration and input of preferences

[0974] First, a user accesses the system using their own terminal and registers. When registering, they enter their user ID and preference information and send it to the server. The server stores the received user ID and preference information in a database, and creates and manages a new user object.

[0975] Integration with points purchase history

[0976] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[0977] Generate optimal point usage proposals

[0978] Next, when the user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using the points when purchasing electronic products.

[0979] Points expiration notification

[0980] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[0981] Specific examples

[0982] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[0983] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[0984] The processing flow will be explained below.

[0985] Step 1:

[0986] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID and preference information (e.g., electronic products, fashion, etc.).

[0987] Step 2:

[0988] The device sends the user ID and preference information entered by the user to the server, and the data is sent using a secure protocol.

[0989] Step 3:

[0990] The server stores the received user ID and preference information in a database, creates a user object, and adds it to the user list in the system.

[0991] Step 4:

[0992] When users earn points from multiple services, they enter their purchase data (service ID, number of points earned, purchase date, etc.) into the terminal.

[0993] Step 5:

[0994] The terminal sends the entered purchase data to the server, which receives it and saves and updates the user's purchase history and point balance in the database.

[0995] Step 6:

[0996] The server centralizes all received point information and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[0997] Step 7:

[0998] When a user wants to know the best way to use points, the user uses the terminal to request a suggestion for the best use from the server.

[0999] Step 8:

[1000] The server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates optimal point usage suggestions, suggesting point usage for specific categories (e.g., electronic products).

[1001] Step 9:

[1002] The server sends the generated proposals to the user's device, where the user can review the proposals and select the optimal way to use their points.

[1003] Step 10:

[1004] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[1005] Step 11:

[1006] The server notifies the user's device that the points are about to expire, and the user receives a notification on the device and is prompted to use the points before the expiration date.

[1007] Step 12:

[1008] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[1009] These are the specific processing steps of the system, which allow users to efficiently manage multiple points and utilize them in the most optimal way.

[1010] Example 1

[1011] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1012] There is a need to centrally manage points earned by users across multiple point programs and to present optimal ways to use points by utilizing the user's purchase history and preference information. Another challenge is to efficiently notify users when points are about to expire and prevent them from expiring. There is a need to provide a system that allows users to use points in the most optimal way and avoid missing their expiration dates.

[1013] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1014] In this invention, the server includes a means for centrally managing points earned by a user through multiple point programs, a means for the user to register using their own terminal and input their user ID and preference information, a means for the server to store the received user information in a database and create and manage a new user object, and a means for generating optimal point usage suggestions based on the user's purchase history and preference information. This allows the user to easily centrally manage points earned through multiple point programs and use them in the most optimal way. The server also includes a means for notifying the user when points are about to expire, allowing the user to use them efficiently without missing their expiration dates.

[1015] A "user" is an individual or corporation that uses the system to centrally manage points and receive suggestions based on their purchasing history and preferences.

[1016] A "points program" is an incentive program in which a certain number of points are awarded when using or purchasing a specific service or product.

[1017] "Centralized management" refers to the centralized management of points earned in multiple point programs in one system or database.

[1018] "Terminal" means a device (such as a personal computer, smartphone, or tablet) that a user uses to access the system.

[1019] A "server" is a computing device that processes information received from users, stores it in a database, generates various offers, and sends notifications.

[1020] A "database" is a digital repository for storing and managing user information, preferences, purchase history, point balance, etc.

[1021] A "user object" is a collection of data including user information (ID, preferences, purchase history, etc.), and is an entity managed by the server.

[1022] "Purchase history" is a record of information about products and services a user has purchased in the past and points earned.

[1023] "Preference information" is information about product categories and services in which a user is interested, and is data that indicates the requests and wishes of individual users.

[1024] The "optimal point usage method" is the most effective way to use points, presented based on the user's purchasing history and preference information.

[1025] A "machine learning algorithm" is a computational method for analyzing user data and extracting patterns and trends, which are used to generate optimal recommendations.

[1026] The "expiration date" is information indicating the last day that points can be used, and points will expire after this date.

[1027] A "notification" is a message sent by the server to the terminal to inform the user that the expiration date of points is approaching.

[1028] This invention is a system that centrally manages points earned by a user through multiple point programs and suggests optimal ways to use points based on purchase history and preferences. This system functions in cooperation with the server, terminals, and users.

[1029] User registration and input of preferences

[1030] Users access the system using their own terminals and register as new users. When registering, the user enters their user ID and preference information, which are then sent to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. For example, MySQL is used as the database management system, and Apache is used as the web server software.

[1031] Integration with points purchase history

[1032] Every time a user earns points from a service, the user sends their purchase history and point information from their device to the server. The server receives this information and stores it in a database. The server then updates each user's point balance and centrally manages points for all services. This process uses data analysis tools such as the Python pandas library.

[1033] Generate optimal point usage proposals

[1034] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and a machine learning algorithm (e.g., random forest) is used to suggest the best way to use points for the user. After generating the suggestion, the server returns the best way to use points to the user's device. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[1035] Points expiration notification

[1036] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. The server detects points that are about to expire and sends a notification to the user's device. This notification uses a push notification service such as Firebase Cloud Messaging. For example, if "Service 1 points will expire in one week," the server will detect this and notify the user.

[1037] Specific examples

[1038] For example, suppose user "user_123" is interested in electronic products and fashion. "user_123" earns 100 points from service 1 and 150 points from service 2, and enters this information into the system through his terminal. The server receives this information, stores it in the database, and consolidates his points, bringing his total points to 250. The server then suggests using his points to purchase electronic products based on his preferences. Furthermore, if his points from service 1 are about to expire in a week, the server will detect this and send a notification to his terminal.

[1039] Prompt Sentence Examples

[1040] Below are some example prompts to input to a generative AI model:

[1041] "User 'user_123' is interested in electronics and fashion. He has earned 100 points from Service 1 and 150 points from Service 2. Based on his preferences, please suggest the best way to use his points. Also, please explain how to notify him when his points from Service 1 will expire in a week."

[1042] This system allows users to easily manage their points in one place and use them in the most optimal way, and also allows them to use their points efficiently without missing their expiration dates.

[1043] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1044] Step 1:

[1045] A user accesses the system's web page or app using their own device and enters their user ID and preference information in the new registration form. The entered information (user ID and preference information) is sent from the device to the server. The server receives this information and stores it in a database. Specifically, the server uses a MySQL database to store the user ID and preference information as a new user object. The input of this step is the user ID and preference information, and the output is the creation and storage of a new user object.

[1046] Step 2:

[1047] Every time a user earns points from each service, the point information (purchase history and earned points) is sent from the terminal to the server. The server saves the received point information in the database and updates the existing user object. Specifically, the Python pandas library is used to add the purchase history and point information to the database and calculate the point balance for each user. The input to this step is the purchase history and earned point information, and the output is the updated user object and point balance.

[1048] Step 3:

[1049] The user uses their device to request an "optimal point usage suggestion" from the server. The server receives this request and retrieves the user's preference information and purchase history from a database. It then performs data analysis using the retrieved information and applies a machine learning algorithm (e.g., random forest) to generate the optimal point usage method. The generated suggestion is sent back from the server to the user's device. The input to this step is the preference information, purchase history, and suggestion request, and the output is the generated optimal point usage suggestion.

[1050] Step 4:

[1051] The server uses a job scheduler (e.g., cron) to periodically check the point information in the database. If the server detects that points are about to expire, it notifies the user's device of that information (e.g., "Service 1 points will expire in one week"). For notifications, a push notification service such as Firebase Cloud Messaging is used. The input of this step is the point expiration data, and the output is a notification of the expiration date sent to the user.

[1052] Specifically, the process proceeds as follows:

[1053] Step 1:

[1054] The user ID and preference information entered by the user on the device is sent to the server.

[1055] The server stores the received information in a MySQL database and creates a new user object.

[1056] Step 2:

[1057] Every time a user earns points, the purchase history and point information are sent from the terminal to the server.

[1058] The server uses the pandas library to store the received information in a database and update the user object.

[1059] Step 3:

[1060] The user requests the server from the terminal for optimal point usage suggestions.

[1061] The server retrieves preference information and purchase history from a database and uses machine learning algorithms such as random forests to generate and return suggestions.

[1062] Step 4:

[1063] The server periodically checks the point information using cron.

[1064] When it detects that a point is about to expire, it uses Firebase Cloud Messaging to notify the user of that information.

[1065] This system allows users to effectively manage their points in one place, receive suggestions on how to best use them, and prevent them from expiring.

[1066] (Application example 1)

[1067] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1068] In conventional point programs, users often had difficulty managing multiple points and often forgot about expiration dates. Furthermore, there were often insufficient suggestions on how to best use points, making it difficult for users to use points efficiently. As a result, points were often wasted, and there were issues with user convenience and satisfaction not improving.

[1069] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1070] In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the points are about to expire, and means for making point usage suggestions for multiple categories based on the user's preference information and purchase history. This allows the user to centrally manage points and receive optimal point usage suggestions based on the purchase history and preference information, enabling effective use of points and resolving conventional problems.

[1071] "Multiple point programs" refers to the entire point system in which a user earns points from different services and stores.

[1072] "Means of centralized management" refers to a method of integrating and managing points earned through different point programs in one place.

[1073] "Purchase history" refers to the complete record of a user's past purchases.

[1074] "Preference information" refers to information based on a user's hobbies and interests.

[1075] The "means for generating optimal proposals" refers to a method for providing the most effective way to use points based on the user's purchase history and preference information.

[1076] "Means for notifying users when the expiration date is approaching" refers to a method for notifying users when the expiration date of points is approaching.

[1077] "Multiple categories" refers to a whole range of different types or genres of goods and services.

[1078] "Means for making suggestions on how to use points" refers to a method or system for making suggestions to users on how to use points.

[1079] This system centralizes the management of points earned by users through multiple point programs and suggests optimal ways to use points based on purchase history and preference information. This system functions in cooperation with the server, terminals, and users.

[1080] User registration and input of preferences

[1081] First, the user accesses the system using their own device and registers. When registering, they enter their user ID and preference information and send it to the server. The server then stores the received user ID and preference information in a database, and creates and manages a new user object. This makes it possible to suggest optimal ways to use points based on the user's preferences.

[1082] Integration with points purchase history

[1083] For each service for which a user has earned points, information on purchase history and earned points is sent to the server via the terminal. The server receives this information and stores it in a database. The server updates each user's point balance and centrally manages points for all services.

[1084] Generate optimal point usage proposals

[1085] When a user requests the server to suggest the best way to use their points, the server obtains the user's preference information and purchase history. This data is analyzed and the server suggests the best way to use the points for the user. For example, if the user's preference information includes electronic products, the server will suggest using points when purchasing electronic products.

[1086] Points expiration notification

[1087] The server periodically checks the expiration date of the user's points and notifies the user if any points are about to expire. This notification is sent to the user's device, urging the user to use the points before the expiration date.

[1088] Specific examples

[1089] For example, suppose user "user_123" is interested in electronic products and fashion. He has earned 100 points from service 1 and 150 points from service 2. The user enters this information into the system through his terminal, and the server receives it and consolidates the points. The server sets his balance to 250 points and suggests using his points to purchase electronic products based on his preferences. Furthermore, if the points from service 1 are due to expire in a week, the server will detect this and send a notification to the user's terminal.

[1090] This system allows users to centrally manage their points and receive optimal point usage suggestions based on their purchasing history and preference information, allowing them to make effective use of their points.

[1091] Examples of prompt statements

[1092] Example prompts to input to the generative AI model:

[1093] Develop a system that offers optimal point usage suggestions based on the user's purchase history and preferences. Design a system that works in cooperation between the server and the device, taking into account the following information:

[1094] 1. Registration of user ID and preference information.

[1095] 2. Integrated management of points earned through each service.

[1096] 3. Optimal point usage suggestions based on purchase history.

[1097] 4. Points Expiration Notification.

[1098] The system is implemented in Python and uses SQLite as the database.

[1099] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1100] Step 1: Register and enter your preferences

[1101] A user registers using a terminal, entering their user ID and preferences, which are then sent to the server, which stores the information in a database and creates a new user object.

[1102] Input: User ID, preference information

[1103] Data processing: Save user information to the database and create a user object

[1104] Output: User information is added to the database

[1105] Step 2: Merging your points with your purchase history

[1106] Users use their devices to send information about points earned across different services and their purchase history to the server. The server receives this information and stores it in a database. At the same time, it updates each user's point balance and manages it centrally.

[1107] Input: Service name, points information, purchase history

[1108] Data processing: Save information to database, update point balance

[1109] Output: Updated points balance reflected in database

[1110] Step 3: Generate optimal point usage proposals

[1111] When a user requests a point usage suggestion from the server, the server retrieves the user's preference information and purchase history from the database, analyzes this data, and generates the optimal point usage suggestion and presents it to the user.

[1112] Input: User ID, preference information, purchase history

[1113] Data processing: Generate optimal proposals based on preference information and purchase history

[1114] Output: The best point usage suggestion is sent to the user.

[1115] Step 4: Points expiration notification

[1116] The server periodically checks the database for upcoming point expiration dates, and if any points are about to expire, the server sends a notification to the user's device.

[1117] Input: Point information, expiration date

[1118] Data processing: detecting points approaching expiration

[1119] Output: Expiration notification sent to user

[1120] Step 5: Use your points

[1121] If the user accepts the proposed point usage method, the terminal sends a notification to the server, which updates the point balance and subtracts the used points from the database.

[1122] Input: Point usage instructions

[1123] Data processing: Update point balance, subtract used points

[1124] Output: The updated points balance is reflected in the database and the user is notified of the result.

[1125] This trend will allow users to easily manage their points centrally and use them efficiently by being suggested the most optimal way to use them.

[1126] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1127] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[1128] User registration and input of preferences

[1129] First, a user accesses the system using their own device and registers. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and data for recognizing the user's emotions (e.g., facial expressions, tone of voice, etc.) and send them to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database, and creates and manages a new user object.

[1130] Integration with points purchase history

[1131] For each service for which a user has earned points, the user enters information about their purchase history and earned points into the terminal. The terminal then sends this information to the server. The server stores the received purchase data in a database and updates the user's point balance. It also centrally manages points earned across all services.

[1132] Generate optimal point usage proposals

[1133] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. The server then retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. The server combines and analyzes this data to suggest the best way to use points based on the user's current emotional state. For example, if the user is feeling stressed, it will suggest using points for relaxation-related products and services.

[1134] Points expiration notification

[1135] The server periodically checks the expiration date of the user's points and notifies them if any points are about to expire. The timing and format of these notifications are adjusted based on real-time emotional data, and an approach tailored to the user's state is used. For example, notifications can be sent at times when the user is relaxed, providing information without causing stress.

[1136] Specific examples

[1137] For example, user "user_123" is interested in electronics and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this and consolidates the points. The server sets his balance at 250 points and suggests "using points for relaxation-related products" based on his preference information and emotion data. Also, if his points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[1138] This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to use their points efficiently and without missing their points' expiration dates.

[1139] The processing flow will be explained below.

[1140] This invention combines a system that centrally manages points earned by a user across multiple point programs and makes optimal point usage suggestions based on the user's purchase history and preference information with an emotion engine that recognizes the user's emotions. This system functions primarily through a server, terminals, and users, and provides suggestions based on the user's emotional state through the emotion engine.

[1141] Step 1:

[1142] A user accesses the system using a terminal and registers as a new user. In the registration form, the user enters their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.).

[1143] Step 2:

[1144] The device sends the user ID, preference information, and emotion recognition data entered by the user to the server using a secure protocol.

[1145] Step 3:

[1146] The server stores the received user ID, preference information, and emotion recognition data in a database, and also creates a new user object and adds it to the user list in the system.

[1147] Step 4:

[1148] The user enters purchase data (service ID, points earned, purchase date, etc.) for each service for which they earned points into the terminal.

[1149] Step 5:

[1150] The terminal sends the entered purchase data to the server, which receives it, stores it in a database, and updates the user's point balance.

[1151] Step 6:

[1152] The server centralizes point information from all services and consolidates all points associated with a specific user ID, allowing users to see the total number of points they have earned across multiple services.

[1153] Step 7:

[1154] The user sends a request from the device to the server asking how best to use their points, and the request also includes real-time emotional data recognized by the emotion engine.

[1155] Step 8:

[1156] The server retrieves user preference information and purchasing history from the database and analyzes it in combination with real-time emotional data from the emotion engine.

[1157] Step 9:

[1158] The server then uses the analysis results to generate optimal point usage methods based on the user's emotional state. For example, if the user is feeling stressed, the server will suggest using points for relaxation-related products and services.

[1159] Step 10:

[1160] The server sends the generated proposals to the user's device, where the user can review the proposals and select the best way to use their points.

[1161] Step 11:

[1162] The server periodically checks the expiration date of the user's points, and if any points are about to expire, calculates the expiration date and creates a list of points that are about to expire.

[1163] Step 12:

[1164] The server notifies the user's device when their points are about to expire. The timing and format of this notification are adjusted based on the emotion data from the emotion engine. For example, the server can choose to send the notification during a time when the user is relaxed.

[1165] Step 13:

[1166] Users can refer to the server's suggested methods for using points and notifications to actually use their points and use them to purchase various services and products.

[1167] The above are the specific processing steps of the system. This system allows users to receive optimal point usage suggestions based on their emotional state, allowing them to efficiently manage and use their points.

[1168] Example 2

[1169] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1170] Nowadays, many users earn points from multiple services, but there are few ways to efficiently manage them centrally. Furthermore, there is often a lack of optimal suggestions for how to effectively use earned points. Furthermore, there is no system that can notify users in a timely manner when points are about to expire. To solve these problems, a system is needed that takes into account users' preferences and emotional state and makes optimal point usage suggestions.

[1171] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1172] In this invention, the server includes a means for centrally managing points earned by a user from multiple services, a means for inputting and saving user preference information and emotional data, a means for generating optimal point usage suggestions based on the user's purchase history, preference information, and emotional data, a means for notifying the user when the points are about to expire, and a means for adjusting the timing and format of the notification depending on the user's emotional state. This allows the user to efficiently manage points earned from multiple services and receive optimal point usage suggestions based on the user's emotional state. Furthermore, the user can receive timely notifications when the points are about to expire.

[1173] "User" means an individual or organization that uses the System to acquire points and manages and uses those points.

[1174] "Service" means a business or platform that offers transactions or activities through which users can earn points.

[1175] "Points" are numerical rewards that users earn by using specific services, and can be used for various benefits and exchangeable products.

[1176] "Centralized management" means comprehensively managing points earned from multiple services within a single system.

[1177] "Preference information" refers to information about a user's interests and preferences for specific products or services.

[1178] "Emotional data" is data that indicates the user's current emotional state and is collected from facial expressions, tone of voice, etc.

[1179] "Purchase history" is a record of past purchases made by a user, including the type of product and the date and time of purchase.

[1180] The "optimal suggestion" is a suggestion of how to use points that is considered to be most effective for the user, calculated based on the user's preference information, purchase history, and emotional state.

[1181] "Expiration date" refers to the date and time at which the points you have earned can be used.

[1182] "Notifications" are messages or alerts sent by the system to users to inform them of points expiration dates and other important matters.

[1183] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state in real time.

[1184] This invention relates to a system that centrally manages points earned by a user in multiple point programs and makes optimal point usage suggestions based on the user's purchase history, preference information, and emotional state. This system functions mainly through a server, terminals, and users, and provides suggestions based on the user's emotional state through an emotional engine.

[1185] User registration and input of preferences

[1186] Users access the system using their own devices and register. During registration, they enter their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.), and send this information to the server. The server then stores the received user ID, preference information, and emotion recognition data in a database (e.g., MySQL or MongoDB) and creates a new user object. This object contains the user's basic information, preference information, and emotion data.

[1187] Integration with points purchase history

[1188] When a user earns points from each service, they enter their purchase history and earned point information into their device. The device converts this information into a structured data format (e.g., CSV or JSON) and sends it to the server. The server stores the received purchase data in a database and updates the user's point balance. The server centrally manages points earned from all services and maintains a consolidated point balance for each user.

[1189] Generate optimal point usage proposals

[1190] When a user wants to know how best to use their points, they use their device to send a request to the server. The server retrieves the user's preference information, purchase history, and real-time emotional data from an emotion engine (e.g., Affectiva or Microsoft Azure Emotion API) from a database. This data is combined and analyzed using a generative AI model. The server then sends the generated suggestions to the user's device, suggesting appropriate ways to use their points. For example, if the user is feeling stressed, it might suggest using their points for relaxation-related products and services.

[1191] Points expiration notification

[1192] The server periodically checks the point information in the database and notifies the user if any points are about to expire. This notification is timed optimally based on the user's real-time emotional data. For example, by selecting a time when the user is relaxed and sending a notification to the device, the information is conveyed to the user without causing stress.

[1193] For example, user "user_123" registers in the system that he is interested in electronic products and fashion, and is recognized through the emotion engine as being relaxed. He earns 100 points from service 1 and 150 points from service 2, which he enters into the system. The server receives this and combines the points to make it 250 points. Based on the preference information and emotion data, the server suggests "using points for relaxation-related products." Also, if the points from service 1 are due to expire in a week, the server detects this and sends a notification at a time when he is relaxing.

[1194] An example of a prompt sentence is, "For a customer who is interested in electronic products and fashion and is currently relaxing, please suggest using points for relaxation-related products." This system allows users to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also makes it possible to use points without missing their expiration date.

[1195] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1196] Step 1: User Registration

[1197] Users: Access the system using their own device and enter their user ID, password and basic contact information into the new registration form.

[1198] The terminal: collects the user's input data and sends it to the server using the HTTPS protocol.

[1199] The server: stores the received user registration information in a database and creates a new user object, which contains the user's ID and contact information.

[1200] Input: User ID, Password, Contact Information

[1201] Output: Creating a new user object and saving it to the database

[1202] Step 2: Input preference information and emotion data

[1203] Users input their preferences (e.g., electronic products, fashion), and use the camera and microphone to capture emotional data (e.g., facial expressions, voice tone).

[1204] The device: converts preference information into JSON format, analyzes emotion data, and sends it to the server.

[1205] The server: stores the received preference information and emotion data in a database and associates it with the user object.

[1206] Input: preference information, emotional data (facial expressions, tone of voice, etc.)

[1207] Output: Save preference information and emotion data to a database

[1208] Step 3: Input and merge points

[1209] Users: Enter their earned points and purchase history information into the terminal.

[1210] The terminal: converts the entered purchase history and point information into CSV format and sends it to the server.

[1211] The server: stores the received point data in a database, updates the user's point balance, and manages it centrally.

[1212] Input: Purchase history, point information (service name, number of points earned, purchase date, etc.)

[1213] Output: Updated points balance, centralized points data

[1214] Step 4: Generate optimal point usage proposals

[1215] When a user wants to know how to best use their points, they send a request from their device to the server.

[1216] The server retrieves user preference information, purchase history, and emotional data from the database and analyzes them using a generative AI model.

[1217] The server: Based on the analysis results, it generates a point usage suggestion that is optimal for the user's current emotional state and sends it to the terminal.

[1218] Input: User preference information, purchase history, emotional data

[1219] Output: Optimal point usage suggestions

[1220] Step 5: Points Expiration Notification

[1221] The server: periodically checks the expiration dates of points to see if any points are about to expire.

[1222] The server: When there is a point nearing its deadline, it selects the optimal notification timing and format based on the user's emotional data and sends the notification to the device.

[1223] The device: displays received notifications to the user and, if appropriate, alerts them with an audible alert or vibration.

[1224] Input: Points expiration date information, user sentiment data

[1225] Output: Expiration notification, alert to user

[1226] The above are the specific processing steps in which the system cooperates between the user, terminal, and server to send, receive, and process data, thereby suggesting optimal ways to use points to the user and notifying them of expiration dates.

[1227] (Application example 2)

[1228] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1229] Conventional point management systems were unable to centrally manage the points a user had earned, making it cumbersome to use points across multiple point programs. Furthermore, optimal point usage suggestions based on the user's preferences and purchase history were rarely made, and because the user's emotional state was not taken into consideration, point usage suggestions were often inappropriate for the user's current psychological state. As a result, users were unable to make effective use of their points, and points sometimes expired.

[1230] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for centrally managing points earned by a user in multiple point programs, means for generating optimal point usage suggestions based on the user's purchase history and preference information, means for notifying the user when the point expiration date is approaching, and means for recognizing the user's emotional state in real time and adjusting the suggestion content and notification timing based on the user's emotion. This allows the user to receive optimal point usage suggestions based on their emotional state, enabling them to use their points efficiently. It also enables them to use their points without missing their expiration date.

[1231] "Centralized management" refers to the collection and management of points earned by users across multiple point programs in one place.

[1232] "Optimal proposal" means proposing the most advantageous way to use points to the user based on the user's purchasing history and preference information.

[1233] "Notification" refers to the act of informing a user of the approaching expiration date of points.

[1234] "Real-time recognition" means detecting and analyzing the user's emotional state instantly on the spot.

[1235] "Adjusting" means optimizing the content of suggestions and the timing of notifications according to the user's emotional state.

[1236] "Preference information" is information about the categories and characteristics of products and services that users prefer.

[1237] "Purchase history" is a record of products and services a user has purchased in the past.

[1238] "Emotional state" refers to a user's current emotional or psychological state.

[1239] A "points program" is a system in which points are awarded by using specific services or products, and those points can be exchanged for something.

[1240] "Analyzing" refers to the act of integrating and analyzing data such as a user's purchasing history, preferences, and emotional state to derive the most appropriate suggestions and notification methods.

[1241] "Suggestion content" refers to advice presented to users on how to use points and on product selection.

[1242] A "server" is a computer system that stores and manages user data and performs various processes.

[1243] "Timing" refers to the optimal time and situation for suggesting or notifying the use of points.

[1244] This invention provides a system that centrally manages points earned by a user from multiple point programs and uses emotion recognition to suggest optimal ways to use the points. First, the user accesses the system from their own device and registers. When registering, the user enters their user ID, preference information, and data for emotion recognition (e.g., facial expression data, voice tone data, etc.), and sends them to the server. The server stores the received data in a database and creates a new user object.

[1245] Next, the user enters the points information and purchase history they have earned from each service into the terminal and sends it to the server, which then integrates the received data and updates the point balance for centralized management.

[1246] When a user wants to know how to best use their points, they use their device to request optimal use suggestions. The server retrieves the user's preference information, purchase history, and real-time emotional data from the emotion engine from the database. Based on this data, a generative AI model is used to make optimal point use suggestions based on the user's current emotional state.

[1247] As an example of suggestions based on real-time emotional data, if a user is feeling stressed, the server will suggest using points to purchase relaxation-related products and services. When points are about to expire, the server will send a notification to the user. This notification will be delivered at the most effective time and in the most effective format, taking into account the user's emotional state.

[1248] The hardware used is a device (e.g., a smartphone or tablet) for emotion recognition, and a server for storing, managing, and processing data. The software includes an EmotionEngine for real-time recognition of user emotions, a database management system (e.g., UserDatabase, PointDatabase), and a module that provides notification functions.

[1249] For example, user "user_123" is recognized as being interested in electronic products and in a relaxed state. He earns 100 points from service 1 and 150 points from service 2, and enters this information into the system via his terminal. The server receives this, consolidates the points, and suggests "using points for relaxation-related products" based on the generative AI model. Furthermore, if the points from service 1 are due to expire in a week, the server detects this and chooses a time when he is relaxing to send a notification.

[1250] Example prompt sentence:

[1251] user_id: 'user_123',

[1252] preferences: ['Electronics'],

[1253] emotion_data: ['Relax']

[1254] In this way, users can receive optimal point usage suggestions based on their emotional state, making efficient use of their points, and avoid missing their points' expiration dates.

[1255] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1256] Step 1:

[1257] A user accesses the system using their own device and registers. As input, they send their user ID, preference information (e.g., electronic products, fashion, etc.), and emotion recognition data (e.g., facial expressions, voice tone, etc.) to the server. The server receives this data, stores it in a database, and creates a new user object. This allows user information to be centrally managed within the system.

[1258] Step 2:

[1259] For each service for which a user has earned points, the user enters point information and purchase history into the terminal. The input, which includes the points earned, the service name, and purchase details, is sent to the server. The server receives this information, stores it in a database, updates the user's point balance, and centrally manages the points earned across all services.

[1260] Step 3:

[1261] When a user wants to know the best way to use their points, they use their device to request optimal use suggestions from the server. As input, they send the user ID and the type of request to the server. The server retrieves the user's preference information, purchase history, and emotion recognition data from the database and recognizes their current emotional state in real time. As output, it makes optimal point use suggestions based on the generative AI model according to the user's emotional state.

[1262] Step 4:

[1263] The server generates suggestions based on real-time emotional data. For example, if a user is feeling stressed, it will suggest using points to purchase relaxation-related products and services. The inputs to the AI ​​model are emotion recognition data, preference information, and purchase history, and the output is a specific suggestion for using points.

[1264] Step 5:

[1265] When the points are about to expire, the server notifies the user. As input, it references the points expiration date and the user's current emotional state. The server sends the notification at the optimal timing, taking into account the emotional state. As output, the user is notified at the appropriate time.

[1266] Step 6:

[1267] Users receive suggestions and notifications through their devices and use points accordingly. As input, notifications and suggestions are received from the server. When users use points based on the suggestions presented, the optimal point usage intended by the system is realized. As output, the user's point usage history is recorded in the system.

[1268] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1269] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1270] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1271] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1272] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1273] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1274] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1275] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1276] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1277] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1278] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1279] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1280] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1281] 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.

[1282] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1283] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1284] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1285] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1286] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1287] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1288] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1289] The following is further disclosed regarding the above embodiment.

[1290] (Claim 1)

[1291] A means for centrally managing points earned by users in multiple point programs;

[1292] A means for generating optimal proposals for using points based on the user's purchase history and preference information;

[1293] A means of notifying users when their points are about to expire,

[1294] A system including:

[1295] (Claim 2)

[1296] The system according to claim 1, further comprising means for suggesting the use of points for products in different categories based on the user's preference information.

[1297] (Claim 3)

[1298] 10. The system of claim 1, further comprising means for analyzing a user's purchasing history and identifying patterns for optimizing point usage.

[1299] "Example 1"

[1300] (Claim 1)

[1301] A means for users to centrally manage points earned through multiple point programs,

[1302] A means for users to register using their own devices and enter their user ID and preference information;

[1303] The server stores the received user information in a database and creates and manages new user objects.

[1304] A means for generating optimal point usage suggestions based on the user's purchase history and preference information;

[1305] A means of notifying users when their points are about to expire,

[1306] A system including:

[1307] (Claim 2)

[1308] The system according to claim 1, further comprising means for analyzing a user's preference information and purchase history and using a machine learning algorithm to suggest an optimal way to use points.

[1309] (Claim 3)

[1310] 10. The system of claim 1, further comprising means for periodically checking a user's point information and sending a notification when points are approaching their expiration date.

[1311] "Application Example 1"

[1312] (Claim 1)

[1313] A means for centrally managing points earned by users in multiple point programs;

[1314] A means for generating optimal proposals for using points based on the user's purchase history and preference information;

[1315] A means of notifying users when their points are about to expire,

[1316] A means for suggesting points for use in multiple categories based on the user's preference information and purchase history;

[1317] A system including:

[1318] (Claim 2)

[1319] The system according to claim 1, further comprising means for suggesting the use of points for products in different categories based on the user's preference information.

[1320] (Claim 3)

[1321] 10. The system of claim 1, further comprising means for analyzing a user's purchasing history and identifying patterns for optimizing point usage.

[1322] "Example 2: Combining Emotion Engines"

[1323] (Claim 1)

[1324] A means for users to centrally manage points earned across multiple services,

[1325] means for inputting and storing user preference information and emotional data;

[1326] A means for generating optimal proposals for using points based on the user's purchase history, preference information, and emotional data;

[1327] A means of notifying users when their points are about to expire,

[1328] A means to adjust the timing and format of notifications depending on the user's emotional state;

[1329] A system including:

[1330] (Claim 2)

[1331] 10. The system of claim 1, further comprising means for generating point use suggestions based on user interest categories in the suggestions generated.

[1332] (Claim 3)

[1333] 10. The system of claim 1, further comprising means for analyzing a user's purchasing history and identifying patterns for optimizing point usage.

[1334] "Application example 2 when combining emotion engines"

[1335] (Claim 1)

[1336] A means for centrally managing points earned by users in multiple point programs;

[1337] A means for generating optimal proposals for using points based on the user's purchase history and preference information;

[1338] A means of notifying users when their points are about to expire,

[1339] a means for recognizing a user's emotional state in real time and adjusting the content of suggestions and the timing of notifications based on the user's emotional state;

[1340] A system including:

[1341] (Claim 2)

[1342] 2. The system of claim 1, further comprising means for providing suggestions adapted to the user's current emotional state to provide suggestions for using points for different product categories based on the user's preference information.

[1343] (Claim 3)

[1344] 10. The system of claim 1, further comprising means for analyzing a user's purchasing history and identifying patterns for optimizing point usage, and means for customizing recommendations based on the user's emotional state. [Explanation of symbols]

[1345] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for centrally managing points earned by users in multiple point programs; A means for generating optimal proposals for using points based on the user's purchase history and preference information; A means of notifying users when their points are about to expire, A system including:

2. The system according to claim 1 , further comprising means for suggesting the use of points for products in different categories based on the user's preference information.

3. The system of claim 1 further comprising means for analyzing a user's purchasing history and identifying patterns for optimizing point usage.

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