system

Abstract

We provide the system. [Solution] Means of registering user information, A means of reading electronic gift tickets, A means of presenting a survey to users and receiving their responses, A method for suggesting products based on user preferences and the value information of electronic gift certificates, A means for the user to select and approve the suggested products, A means of saving the user's purchase history and using it for future recommendations, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, when a user who has received an electronic gift ticket selects an optimal product, there is a problem that it is difficult to make a selection that suits the amount of money and taste. In particular, even when the user tries to select a product to drink, the amount of money may not be sufficient, or a high - priced product that the user does not want may be selected. As a result, the user's satisfaction decreases, and the gift cannot be effectively utilized. In addition, since no proposal based on the user's taste is made, the provided experience lacks consistency, which is also a problem. To solve these problems, a mechanism for proposing an optimal product based on the user's taste and the amount information of the electronic gift ticket is necessary.

Means for Solving the Problems

[0005] This invention provides a system that includes means for registering user information, means for reading electronic gift tickets, means for presenting questionnaires to users and receiving responses, means for suggesting products based on user preferences and the amount of the electronic gift ticket, means for users to select and approve suggested products, and means for saving the user's purchase history and using it for future suggestions. This makes it possible to suggest the most suitable products that match the user's preferences, while taking into account the amount and expiration date of the electronic gift ticket received by the user. Furthermore, by generating personalized questionnaires based on the user's past purchase history and suggesting products according to their preferences, user satisfaction can be increased. In addition, by selecting the most suitable products using an algorithm, it is possible to always suggest appropriate products to the user.

[0006] "User information" refers to data used to identify individual users and understand their preferences, such as their name, email address, interests, and purchase history.

[0007] An "electronic gift ticket" is a gift card or coupon provided in digital format, and is recognized by a QR code (registered trademark) or serial number.

[0008] A "survey" is a set of questions presented to understand a user's preferences and tastes, and the necessary data is obtained when the user answers them.

[0009] "Preferences" refer to a user's tastes and preferences, and in particular, to patterns of preferences regarding food and beverages.

[0010] "Amount information" refers to data representing the valid amount of an electronic gift ticket, specifying the range of amounts that the user can use.

[0011] "Product recommendation" refers to the act of selecting and recommending the most suitable product to a user based on their preferences and the value information of the electronic gift certificate.

[0012] "Purchase history" refers to data that records products a user has purchased in the past and their details (price, date, options, etc.).

[0013] "Personalization" is a method of providing optimal suggestions and services based on each user's individual preferences and purchase history.

[0014] An "algorithm" is a computational method that processes data based on specific calculation procedures or rules to derive the optimal result. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The system has the function of registering user information and reading electronic gift tickets. It also has the function of presenting the user with a questionnaire, receiving responses, suggesting the most suitable products based on the responses, and approving the products selected by the user. Furthermore, it has the function of saving the user's purchase history and using it for future suggestions.

[0037] System Configuration

[0038] 1. User Information Registration Module

[0039] The server receives information such as the user's name, email address, preferences, and purchase history, and registers it in the database.

[0040] 2. Electronic gift ticket reading module

[0041] The device has the function of allowing users to read electronic gift tickets such as LINE Gifts. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[0042] The server receives the read ticket data, associates it with user information, and stores it in the database.

[0043] 3. Questionnaire Presentation Module

[0044] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0045] Users answer a survey and send their answers to the server via their device.

[0046] 4. Product Proposal Module

[0047] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[0048] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0049] The device displays detailed information about the products suggested to the user.

[0050] Specific example

[0051] 1. User Information Registration

[0052] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name and email address.

[0053] The server saves the entered information to the database and generates a user ID.

[0054] 2. Electronic gift ticket reading

[0055] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[0056] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[0057] The server stores ticket data, associating it with user information.

[0058] 3. Presenting the questionnaire

[0059] The device displays a survey for "Taro Tanaka".

[0060] Type of beverage (e.g., coffee, tea, frappuccino)

[0061] Sweetness level (e.g., not sweet, normal, sweet)

[0062] Size (e.g., Short, Tall, Grande)

[0063] The user selects "Frappuccino," "Sweet," and "Grande," and then submits their response.

[0064] 4. Product proposal

[0065] The server considers the survey results and past purchase history to select "Caramel Frappuccino (Grande)" as the most suitable product.

[0066] The server generates detailed information about the product and sends it to the terminal.

[0067] The terminal displays an image and price information for "Caramel Frappuccino (Grande)" for "Taro Tanaka".

[0068] 5. User Approval

[0069] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0070] The terminal sends the user's selection to the server.

[0071] The server generates a barcode and sends it to the terminal in a format usable by the store.

[0072] The terminal displays the barcode as "Taro Tanaka".

[0073] 6. Save purchase history

[0074] The server updates "Taro Tanaka's" purchase history and saves it to the database. From then on, personalized product suggestions will be provided based on this purchase history.

[0075] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their preferences.

[0076] The following describes the processing flow.

[0077] Step 1:

[0078] Users enter necessary information such as their name and email address into a new registration form via the app or website.

[0079] Step 2:

[0080] The terminal sends the entered information to the server.

[0081] Step 3:

[0082] The server stores the received user information in a database, generates a user ID, and notifies the user.

[0083] Step 4:

[0084] The user scans the Starbucks ticket received via LINE Gift using the QR code scanning function within the app.

[0085] Step 5:

[0086] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[0087] Step 6:

[0088] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[0089] Step 7:

[0090] The server generates personalized survey questions based on the user's past purchase history.

[0091] Step 8:

[0092] The device displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[0093] Step 9:

[0094] Users answer a survey and send their answers to the server via their device.

[0095] Step 10:

[0096] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[0097] Step 11:

[0098] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0099] Step 12:

[0100] The device displays detailed information about the products suggested to the user. For example, it might show an image and price information for a "Caramel Frappuccino (Grande)".

[0101] Step 13:

[0102] The user selects one product from the suggested options and presses the approve button.

[0103] Step 14:

[0104] The terminal sends the user's selection to the server.

[0105] Step 15:

[0106] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[0107] Step 16:

[0108] The server sends the generated barcode to the terminal.

[0109] Step 17:

[0110] The terminal displays a barcode to the user.

[0111] Step 18:

[0112] The server stores users' purchase history and preference data in a database, which is then used to make future recommendations.

[0113] (Example 1)

[0114] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0115] Conventional systems have problems such as cumbersome product selection and insufficient product suggestions tailored to user preferences when users purchase products using electronic gift tickets. Furthermore, there is a problem that users' purchase history is not reflected in subsequent suggestions, resulting in a lack of personalized recommendations. The present invention aims to solve these problems and provide a system in which users can use electronic gift tickets efficiently and effectively.

[0116] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0117] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for displaying the generated barcode, and means for saving the user's purchase history and using it for future suggestions. This makes it possible for users to easily and efficiently purchase products that suit their preferences using electronic gift tickets.

[0118] "Means of registering user information" refers to the function of registering information such as the user's name, email address, preferences, and purchase history in a database.

[0119] "Methods for reading electronic gift tickets" refers to functions that analyze QR codes or serial numbers to extract the amount and expiration date of electronic gift tickets.

[0120] "A means of presenting a survey to a user and receiving their response" refers to a function that displays questions about the user's preferences and purchase intentions and obtains their response.

[0121] "A method for suggesting products based on user preferences and electronic gift ticket value information" refers to a function that selects the most suitable product based on user responses and existing data, and then suggests it to the user.

[0122] "A means for users to select and approve suggested products" refers to a function that allows users to select from the presented products and perform actions to confirm their purchase.

[0123] "Means for displaying generated barcodes" refers to a function that generates barcodes for use by the user in stores and displays them on the user's device.

[0124] "A means of saving a user's purchase history and using it for future recommendations" refers to a function that saves data on products purchased by the user in a database and uses that data to make future recommendations.

[0125] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The following describes a specific system configuration and operating procedure for carrying out the invention.

[0126] System Configuration

[0127] The system mainly consists of the following hardware and software.

[0128] server

[0129] Database servers: MySQL (registered trademark) and PostgreSQL, etc.

[0130] Application server: Apache (registered trademark), Tomcat, Node.js, etc.

[0131] Algorithmic processing: Python scripts and machine learning models

[0132] terminal

[0133] Smartphones and tablets: iOS, ANDROID® devices

[0134] QR code reader: Uses a smartphone camera and a dedicated app.

[0135] User

[0136] General user: A user of the system

[0137] User Information Registration

[0138] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name, email address, and preferences (e.g., likes coffee, dislikes tea). The device sends this information to the server, which stores it in a database. At this time, the server generates a new user ID.

[0139] Electronic gift ticket reading

[0140] Users scan electronic gift tickets received from LINE Gift or other platforms using the app. The device uses the smartphone's camera to read the QR code or serial number and sends the data to the server. The server analyzes the received ticket data, extracts monetary information, and associates it with user information.

[0141] Presenting a questionnaire and obtaining responses.

[0142] The device displays a personalized questionnaire to the user. The questionnaire includes questions such as the type of beverage (coffee, tea, frappuccino), sweetness level (not sweet, normal, sweet), and size (short, tall, grande). The user answers the questionnaire and sends their answers to the server via the device.

[0143] Product proposals

[0144] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value of the electronic gift certificate. For example, if the user selects "Frappuccino," "Sweet," and "Grande," the server will recommend "Caramel Frappuccino (Grande)." The server sends the generated product details to the terminal, which then displays that information to the user.

[0145] User authorization and barcode display

[0146] The user selects items to purchase from the suggested products and presses the approve button. The terminal sends this information to the server. After the server completes the purchase process, it generates a barcode that can be used in the store and sends it to the terminal. The terminal displays the generated barcode to the user.

[0147] Saving purchase history and using it for future proposals.

[0148] The server stores information about the products the user has purchased in a database and updates the purchase history. This history is then used to improve future recommendations. For example, if a user purchases a "Caramel Frappuccino (Grande)," that information will be reflected in future recommendations, allowing for more accurate suggestions tailored to the user's preferences.

[0149] Specific example

[0150] Examples of prompt statements are as follows:

[0151] Registration screen: "Please enter your name."

[0152] Electronic gift ticket scanning screen: "Please scan the QR code on the gift ticket."

[0153] Survey screen:

[0154] Drink options: "Please choose from coffee, tea, or frappuccino."

[0155] Sweetness level: "Please choose from Not Sweet, Normal, or Sweet."

[0156] Size: "Please choose from Short, Tall, or Grande."

[0157] This concludes the detailed description of how the present invention can be implemented. By using this system, users can efficiently and effectively utilize electronic gift tickets and obtain a more personalized purchasing experience.

[0158] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0159] Step 1: User Information Registration

[0160] Users open the new registration screen on the app or website and enter their name, email address, preferences, etc. The entered data is sent to the device in the following format.

[0161] Input: User's name, email address, and preferences

[0162] Specific operation: The user enters the name "Taro Tanaka," the email address "tanaka@example.com," and their preferences as "Likes coffee, dislikes tea."

[0163] The terminal organizes this data and sends it to the server in the following format.

[0164] Output: Registration data (name, email address, preferences)

[0165] Step 2: Saving User Information

[0166] The server stores the received user information in the database server and generates a user ID. This user ID is used in subsequent processing and is linked to the user information.

[0167] Input: Registration data (name, email address, preferences)

[0168] Data processing: Create a new entry in the database and save each item.

[0169] Specific operation: The server saves information about "Taro Tanaka" to the MySQL database and generates user ID "12345".

[0170] Output: User ID

[0171] Step 3: Scan the e-gift ticket

[0172] The user scans the QR code of the electronic gift ticket received via LINE Gift using the app. The device reads the QR code using the smartphone's camera and analyzes the data.

[0173] Input: QR code image data

[0174] Data processing: Extracting price information and expiration date from QR codes.

[0175] Specific operation: When a user scans an electronic gift ticket worth 500 yen, the terminal analyzes the QR code and extracts the amount "500 yen" and the expiration date "December 31, 2023".

[0176] Output: Extracted amount information and expiration date

[0177] Step 4: Save ticket data

[0178] The terminal sends the analyzed ticket data to the server and associates it with the user ID. The server stores the received ticket data in a database.

[0179] Input: Amount information, expiration date, user ID

[0180] Data processing: Ticket data is linked to user information and saved.

[0181] Specific operation: The terminal sends the analysis results, and the server associates the user ID "12345" with a "ticket worth 500 yen" and saves it in the database.

[0182] Output: Database update status

[0183] Step 5: Presenting the questionnaire

[0184] The device displays a personalized survey based on the user's preferences. The survey includes questions about the type of beverage, sweetness level, size, and other factors.

[0185] Input: None (User interaction)

[0186] Specific actions: The device displays a questionnaire to "Taro Tanaka." The questionnaire includes questions such as: "Type of drink (coffee, tea, frappuccino)", "Sweetness level (not sweet, normal, sweet)", and "Size (short, tall, grande)".

[0187] Output: Survey screen

[0188] Step 6: Collecting survey responses

[0189] The user answers the displayed questionnaire and sends their selections to the server via their device.

[0190] Input: User survey responses

[0191] Data processing: Formatting and sending of survey response data.

[0192] Specific operation: The user selects "Frappuccino," "Sweet," and "Grande," and submits their response. The device sends the selection data to the server.

[0193] Output: User response data

[0194] Step 7: Product Selection

[0195] The server uses an algorithm to select the most suitable product based on the received survey responses, past purchase history, and the value information of the electronic gift certificate.

[0196] Input: Survey response data, purchase history data, ticket price information

[0197] Data processing: Input each data point into an algorithm to select the optimal product.

[0198] Specific operation: Based on the survey results "Frappuccino," "Sweet," and "Grande," as well as purchase history, the server recommends "Caramel Frappuccino (Grande)."

[0199] Output: Recommended product data

[0200] Step 8: Display product details

[0201] The device displays detailed information about the products suggested to the user. This information includes the product name, price, calories, and options.

[0202] Input: Recommended product data

[0203] Specific action: The device displays an image and price information for "Caramel Frappuccino (Grande)" to "Taro Tanaka".

[0204] Output: Product Information Screen

[0205] Step 9: User Approval

[0206] The user selects the items they wish to purchase from the displayed products and presses the confirm button. The device then sends this information to the server.

[0207] Input: User's selection information

[0208] Data processing: Send user selection information to the server.

[0209] Specific action: The user selects "Caramel Frappuccino (Grande)" and presses the confirm button. The device sends the selection information to the server.

[0210] Output: User approval data

[0211] Step 10: Generate and display the barcode

[0212] The server completes the user's purchase process, generates a barcode usable in the store, and sends it to the terminal. The terminal displays the generated barcode to the user.

[0213] Input: User approval data

[0214] Data processing: Barcode generation and transmission

[0215] Specific operation: The server completes the purchase process, generates a barcode, and sends it to the terminal. The terminal displays the barcode on "Taro Tanaka".

[0216] Output: Barcode display

[0217] Step 11: Update Purchase History

[0218] The server stores the user's purchase history in a database and uses it to make recommendations for future purchases.

[0219] Input: User approval data, purchased product data

[0220] Data processing: Updating and saving purchase history

[0221] Specific action: The server adds "Caramel Frappuccino (Grande)" to "Taro Tanaka's" purchase history and saves it to the database.

[0222] Output: Updated purchase history

[0223] Through the steps described above, the system of the present invention enables users to efficiently utilize electronic gift tickets and receive personalized product recommendations.

[0224] (Application Example 1)

[0225] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0226] Traditional electronic gift ticket-based product purchase systems have the problem of not being able to fully utilize user preferences and past purchase history, making it difficult to recommend products that are optimal for individual users. Furthermore, there is a lack of mechanisms to allow users to complete purchases directly using electronic payment services and use them quickly at stores. This results in a degraded user experience and a cumbersome process.

[0227] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0228] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for saving the user's purchase history and using it for future suggestions, and means for completing the purchase using an electronic payment service, generating a barcode, and displaying it on the user's terminal. As a result, the user can efficiently select products that suit their preferences and enjoy the convenience of purchasing and paying using electronic gift tickets.

[0229] "User information" refers to information such as the user's name, contact information, preferences, and purchase history.

[0230] An "electronic gift ticket" is a gift certificate issued electronically, provided in a format that includes a QR code or serial number.

[0231] A "survey" is a tool used to ask questions about a user's preferences and collect their responses.

[0232] "Product suggestion" refers to the act of selecting and presenting the most suitable product based on the user's preferences and the value of the electronic gift certificate.

[0233] "Electronic payment services" refer to services that conduct financial transactions via the internet, and include the use of electronic gift tickets.

[0234] A "barcode" is a machine-readable code generated to prove the purchase of a product.

[0235] "Purchase history" refers to data that includes information such as the products a user has purchased in the past and the date and time of those purchases.

[0236] A "server" refers to a computer system that manages user information and electronic gift ticket information, and processes various procedures.

[0237] A "user terminal" refers to a device operated by the user, such as a smartphone or tablet.

[0238] System program

[0239] The system implementing this application includes programs for registering user information, reading electronic gift tickets, presenting questionnaires, suggesting products, completing electronic payments, generating and displaying barcodes, and saving purchase history. The programs are implemented using Python and run as a web application using Flask.

[0240] Program Processing Description

[0241] The system uses the following hardware and software:

[0242] Hardware:

[0243] Server: A computer system that performs data processing and storage.

[0244] User device: A mobile device such as a smartphone or tablet.

[0245] software:

[0246] Python: A programming language used for implementing programs.

[0247] Flask: A web application framework.

[0248] qrcode: A library for generating QR codes.

[0249] 1. User information registration:

[0250] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database.

[0251] 2. Electronic gift ticket reading:

[0252] The user's device uses its camera to scan the QR code on the electronic gift ticket. The scanned data is sent to a server for analysis.

[0253] 3. Presenting the questionnaire:

[0254] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server.

[0255] 4. Product suggestion:

[0256] The server uses an algorithm to select the most suitable product based on the user's survey results and past purchase history, and then sends that information to the user's terminal.

[0257] 5. Electronic payment completion and barcode generation:

[0258] Once the user approves the suggested product, the server completes the electronic payment, generates a barcode, and displays it on the user's device.

[0259] 6. Save purchase history:

[0260] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[0261] Specific example

[0262] As a concrete example, this system can be implemented using the following prompt statement:

[0263] Example of a prompt:

[0264] User information:

[0265] Name: Taro Tanaka

[0266] Email: taro.tanaka@example.com

[0267] Preferences: Frappuccino, sweet, grande

[0268] Electronic gift tickets:

[0269] Amount: 500 yen

[0270] Expiration Date: 2024-12-31

[0271] Based on the following information, this system will suggest the most suitable product to the user and complete the electronic payment. For example, if Taro Tanaka answers "Frappuccino," "Sweet," and "Grande," the system will suggest "Caramel Frappuccino (Grande)." After that, the electronic payment will be completed and a barcode will be displayed on Taro Tanaka's smartphone.

[0272] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0273] Step 1:

[0274] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database. Specifically, it receives information entered by the user through the application screen and writes it to the database in the appropriate format. At this time, a user ID is generated and stored along with other related information.

[0275] Input: User information (name, contact information, preferences, past purchase history)

[0276] Data processing: Converting user information into an appropriate format.

[0277] Output: User information stored in the database

[0278] Step 2:

[0279] The user's device uses its camera to scan the QR code on the electronic gift ticket. The data read from the QR code is sent to the server. The server analyzes this data, extracts information such as the ticket's value and expiration date, and stores it in association with the user's information.

[0280] Input: QR code data

[0281] Data processing: Analyze QR code data to extract ticket information.

[0282] Output: Ticket information saved in association with user information

[0283] Step 3:

[0284] The user terminal displays a questionnaire regarding product selection to the user and sends the response to the server. The questionnaire questions are based on the user's preferences, such as the type of drink, level of sweetness, size, etc. <00009​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Data processing: Conversion to the display format of product information

[0297] Output: Approval information by the user

[0298] Step 6:

[0299] The server receives the approval information from the user and completes the electronic payment. When the payment is completed, the server generates a barcode and transmits it to the user terminal in a format that can be used in the store.

[0300] Input: Approval information of the user

[0301] Data processing: Electronic payment processing, barcode generation

[0302] Output: Barcode transmitted to the user terminal

[0303] Step 7:

[0304] The server stores the user's new purchase information in the database and utilizes it for personalized proposals in subsequent times.

[0305] Input: New purchase information

[0306] Data processing: Storage and structuring of purchase information [[ID=​​​​​​​​​This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present and receive questionnaires, suggest products based on the user's preferences, the value of the electronic gift ticket, and emotion recognition by an emotion engine, and approve the products selected by the user. It also includes a function to save the user's purchase history and utilize it for future suggestions.

[0310] System Configuration

[0311] 1. User Information Registration Module

[0312] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database.

[0313] 2. Electronic gift ticket reading module

[0314] The device has the function of reading electronic gift tickets received by the user. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[0315] The server receives the read ticket data, associates it with user information, and stores it in the database.

[0316] 3. Questionnaire Presentation Module

[0317] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0318] The emotion engine can analyze the user's facial expressions and tone of voice, and adjust the survey content based on the results.

[0319] Users answer a survey and send their answers to the server via their device.

[0320] 4. Product Proposal Module

[0321] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotional data generated by an emotion engine.

[0322] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0323] The device displays detailed information about the products suggested to the user.

[0324] Specific example

[0325] 1. User Information Registration

[0326] Users register through the app or website. For example, they enter their name, email address, and interests.

[0327] The server saves the entered information to the database and generates a user ID.

[0328] 2. Electronic gift ticket reading

[0329] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[0330] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[0331] The server stores ticket data, associating it with user information.

[0332] 3. Presenting the questionnaire

[0333] The device displays personalized surveys to the user.

[0334] The emotion engine uses facial recognition and voice analysis to adjust the displayed survey questions according to the user's emotional state. For example, the questions might change to something like, "You seem a little tired. Would you like to refresh yourself?"

[0335] Users answer a survey and send their answers to the server via their device.

[0336] 4. Product proposal

[0337] Based on survey results, past purchase history, electronic gift ticket value information, and sentiment data obtained from the sentiment engine, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product.

[0338] The server generates detailed information about the product and sends it to the terminal.

[0339] The device displays an image and detailed information about "Caramel Frappuccino (Grande)" to the user.

[0340] 5. User Approval

[0341] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0342] The terminal sends the user's selection to the server.

[0343] The server generates a barcode and sends it to the terminal in a format that can be used in Starbucks stores.

[0344] The terminal displays a barcode to the user.

[0345] 6. Save purchase history

[0346] The server can store the user's purchase history and sentiment data in a database, which can then be used to improve future recommendations. This makes it possible to provide even more personalized product suggestions.

[0347] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[0348] The following describes the processing flow.

[0349] Step 1:

[0350] Users enter their name, email address, and preferences into a new registration form via the app or website.

[0351] Step 2:

[0352] The terminal sends the entered information to the server.

[0353] Step 3:

[0354] The server stores the received user information in a database, generates a user ID, and notifies the user.

[0355] Step 4:

[0356] Users scan the electronic gift ticket they received via LINE Gift using the QR code scanning function within the app.

[0357] Step 5:

[0358] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[0359] Step 6:

[0360] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[0361] Step 7:

[0362] The server generates personalized survey questions based on the user's past purchase history.

[0363] Step 8:

[0364] The terminal displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[0365] Step 9:

[0366] The emotion engine uses facial recognition and voice analysis to evaluate the user's emotions in real time. Based on this evaluation, it adjusts the survey questions. For example, it might change the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[0367] Step 10:

[0368] Users answer a survey and send their answers to the server via their device.

[0369] Step 11:

[0370] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotion engine evaluation data.

[0371] Step 12:

[0372] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0373] Step 13:

[0374] The device displays detailed information about the product suggested to the user. For example, it displays an image and description of a "Caramel Frappuccino (Grande)".

[0375] Step 14:

[0376] The user selects one product from the suggested options and presses the approve button.

[0377] Step 15:

[0378] The terminal sends the user's selection to the server.

[0379] Step 16:

[0380] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[0381] Step 17:

[0382] The server sends the generated barcode to the terminal.

[0383] Step 18:

[0384] The terminal displays a barcode to the user.

[0385] Step 19:

[0386] The server saves the user's purchase history and sentiment data to a database along with a thank-you message, and uses this data to make future suggestions.

[0387] Step 20:

[0388] The emotion engine analyzes emotional data throughout the user's entire experience and provides feedback data for further personalization.

[0389] (Example 2)

[0390] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0391] In conventional systems, when users purchase products using electronic gift tickets, personalized product suggestions that take into account the user's preferences and emotional state are not provided, which often leads to lower user satisfaction. Furthermore, there is no mechanism to dynamically adjust survey content and product suggestions using user emotional data, resulting in a challenge in accurately responding to user needs.

[0392] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving a response, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and emotional data from an emotional engine, means for the user to select and approve the suggested products, and means for saving the user's purchase history and emotional data and utilizing them for future suggestions. This makes it possible to make personalized product suggestions based on the user's preferences and emotional state, thereby improving user satisfaction.

[0393] "User information" refers to individual information about a user, such as their name, email address, preferences, purchase history, and sentiment data.

[0394] An "electronic gift ticket" is a ticket issued in electronic format that can be exchanged for goods or services based on a specific amount or expiration date.

[0395] A "survey" is a series of questions presented to a user, used to understand their preferences and needs.

[0396] An "emotion engine" is a technological system that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[0397] "Product suggestion" is the process of presenting products suitable for the user based on the user's preferences, the value information of the electronic gift certificate, and sentiment data.

[0398] "Purchase history" refers to a record of products a user has purchased in the past, and this information is stored to be used for future recommendations.

[0399] A "personalized survey" is a survey that is individually tailored based on a user's past purchase history and sentiment data.

[0400] The "optimal product" is a product selected by an algorithm that comprehensively considers user preferences, the value information of the electronic gift certificate, and emotional data.

[0401] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present questionnaires, and receive responses. Furthermore, it has a function to suggest products based on the user's preferences, the amount of the electronic gift ticket, and emotion recognition by an emotion engine, and to approve the products selected by the user. It also has a function to save the user's purchase history and utilize it for future suggestions.

[0402] System configuration and details

[0403] 1. User Information Registration Module

[0404] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database. This step uses a database management system such as MySQL or PostgreSQL.

[0405] For example, a user registers through an app or website, entering their name, email address, and preferences. The server stores this information in a database and generates a user ID.

[0406] 2. Electronic gift ticket reading module

[0407] The device has the functionality to read electronic gift tickets received by the user. It analyzes the QR code and serial number to extract the ticket's value and expiration date. This is done using QR code reading libraries such as ZBar and ZXing.

[0408] For example, a user scans a 500 yen Starbucks ticket received via LINE Gift within the app. The device reads the QR code and sends the ticket data to the server.

[0409] 3. Questionnaire Presentation Module

[0410] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0411] The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the survey content based on the results. For example, if it determines that the user is tired, it changes the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[0412] For example, a user answers a survey and sends their answers to a server via their device.

[0413] 4. Product Proposal Module

[0414] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data generated by an emotion engine. This process utilizes machine learning models and recommendation engines such as TENSORFLOW® and Scikit-Learn.

[0415] For example, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product and sends its detailed information to the terminal. The terminal then displays this information to the user.

[0416] 5. User Approval Module

[0417] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0418] The terminal sends the user's selection to the server. The server generates a barcode and sends it to the terminal. The user can use this barcode to purchase products in the store.

[0419] 6. Purchase history storage module

[0420] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations. This will enable even more personalized product suggestions.

[0421] Examples of specific cases and prompt statements

[0422] Specific example:

[0423] For example, the terminal displays the question, "You seem a little tired. Would you like to refresh yourself?" and the user replies that they would like to refresh themselves. Based on this, the server suggests a "Caramel Frappuccino (Grande)," and if the user selects it, a barcode is generated that can be used in the store.

[0424] Example of a prompt:

[0425] Please describe a system that allows users to register new user information, scan electronic gift tickets, answer questionnaires, and receive product recommendations. In particular, please explain in detail how the emotion engine adjusts the displayed questionnaire content.

[0426] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[0427] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0428] Program processing flow

[0429] Step 1: Register User Information

[0430] 1.1 Input: The user enters their name, email address, preferences, purchase history, and sentiment data.

[0431] Specific operation: The user launches the app from their smartphone or PC and enters information into the input form.

[0432] Output: The entered user information is sent to the server.

[0433] 1.2 Data Processing and Calculation: The server applies a data format to the user information it receives in order to register it in the database.

[0434] Specific operation: The server saves the data received in the HTTP request to a database management system (e.g., MySQL, PostgreSQL).

[0435] Output: User information stored in the database.

[0436] Step 2: Read the electronic gift ticket

[0437] 2.1 Input: The user scans the electronic gift ticket (QR code or serial number).

[0438] Specific operation: The user uses the camera on their smartphone app to scan the electronic gift ticket.

[0439] 2.2 Data Processing and Calculation: The terminal analyzes the QR code or serial number and extracts the ticket price and expiration date.

[0440] Specific operation: The device analyzes the data using QR code reading software (e.g., ZBar, ZXing).

[0441] Output: Extracted ticket information.

[0442] 2.3 Input: The extracted ticket information is sent to the server.

[0443] Specific action: The terminal sends the analyzed ticket information to the server.

[0444] Output: Ticket information sent to the server.

[0445] 2.4 Data Processing and Calculation: The server stores the received ticket information in the database, associating it with user information.

[0446] Specific operation: The server links the received ticket information with the user ID and saves it to the database.

[0447] Output: Ticket information stored in the database.

[0448] Step 3: Presenting the questionnaire

[0449] 3.1 Input: The server obtains the data necessary to provide users with personalized surveys (preferences, past purchase history, sentiment data).

[0450] Specific operation: The server retrieves user preferences, purchase history, and sentiment data from the database.

[0451] 3.2 Data Processing and Calculation: The server generates survey questions based on the acquired data.

[0452] Specific operation: The server generates survey questions using an algorithm and adjusts them based on sentiment data.

[0453] Output: Personalized survey.

[0454] 3.3 Input: The generated questionnaire is sent to the device.

[0455] Specific operation: The server sends the survey data to the terminal.

[0456] Output: The survey content displayed on the device.

[0457] 3.4 Input: The user answers the survey.

[0458] Specific action: The user enters their answers into the survey form and presses the submit button.

[0459] 3.5 Data Processing and Calculation: The terminal sends the user's survey responses to the server.

[0460] Specific action: The device sends the response data to the server.

[0461] Output: Survey responses sent to the server.

[0462] Step 4: Product Proposal

[0463] 4.1 Input: The server receives survey responses, purchase history, electronic gift certificate amount information, and sentiment data.

[0464] Specific operation: The server receives the user's survey responses and related data.

[0465] 4.2 Data Processing and Calculation: The server uses an algorithm to select the optimal product.

[0466] Specific operation: The server uses machine learning models and recommendation engines (e.g., TensorFlow, Scikit-Learn) to select the most suitable products.

[0467] Output: Detailed information on the selected products.

[0468] 4.3 Input: Detailed information about the selected product is sent to the terminal.

[0469] Specific operation: The server sends detailed product information to the terminal.

[0470] Output: Product information displayed on the terminal.

[0471] Step 5: User Approval

[0472] 5.1 Input: The user selects and approves the suggested product.

[0473] Specific actions: The user clicks the "Select Product" button and then clicks the "Approve" button.

[0474] 5.2 Data Processing and Calculation: The terminal sends the user's selected data to the server.

[0475] Specific operation: The terminal sends the selected data to the server as an HTTP request.

[0476] Output: Selected data sent to the server.

[0477] 5.3 Data Processing and Calculation: The server generates a barcode and sends it to the terminal.

[0478] Specific operation: The server generates barcodes using a barcode generation library (e.g., Barcode4J, ZXing).

[0479] Output: The generated barcode.

[0480] 5.4 Input: The generated barcode is sent to the terminal.

[0481] Specific operation: The server sends barcode data to the terminal.

[0482] Output: The barcode displayed on the terminal.

[0483] Step 6: Saving Purchase History

[0484] 6.1 Input: The server receives the user's purchase history and sentiment data.

[0485] Specific operation: The server receives purchase history and sentiment data.

[0486] 6.2 Data Processing and Calculation: The server saves the received data to a database and uses it for future proposals.

[0487] Specific operation: The server stores purchase history data and sentiment data in a database.

[0488] Output: Purchase history and sentiment data stored in the database.

[0489] (Application Example 2)

[0490] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0491] In today's world, when users use electronic gift tickets to purchase products that match their preferences and emotions, it is difficult to provide personalized recommendations. This can lead to wasted time and a poor purchasing experience. Furthermore, existing systems do not consider the user's emotional state when making product recommendations, thus failing to increase user satisfaction.

[0492] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0493] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and the emotion recognition results, means for the user to select and approve the suggested products, means for saving the user's purchase history and emotion data and using them for future suggestions, and means for suggesting products using a generation AI model based on the generated prompt text. As a result, the user can efficiently select and purchase products that match their preferences and emotions, thereby realizing a highly satisfying shopping experience.

[0494] "Means for registering user information" refers to a function for registering information such as the user's name, email address, preferences, purchase history, and sentiment data on the server.

[0495] "Methods for reading electronic gift tickets" refer to functions that analyze QR codes or serial numbers to extract the ticket's value and expiration date.

[0496] "A means of presenting a survey to a user and receiving their response" refers to a function that displays a personalized survey to a user and receives their response.

[0497] "A means of suggesting products based on user preferences, electronic gift ticket value information, and emotion recognition results" refers to a function that uses user survey results, past purchase history, electronic gift ticket value information, and emotion data from an emotion engine to algorithmically select and suggest the most suitable products.

[0498] "A means for users to select and approve suggested products" refers to a function that allows users to review detailed information about suggested products, select them, and approve their purchase.

[0499] "Means for saving users' purchase history and sentiment data and using them for future recommendations" refers to a function that saves users' purchase history and sentiment data in a database and uses it to make personalized product recommendations for future purchases.

[0500] "A means of suggesting products using a generative AI model based on generated prompt sentences" refers to a function that generates prompt sentences according to the user's situation and suggests the most suitable product using a generative AI model (e.g., GPT-3® or GPT-4®).

[0501] The system implementing the present invention is designed to perform a series of steps, from user information registration and reading of electronic gift tickets to presenting and receiving responses to questionnaires, product suggestions, user product approval, saving of purchase history, and product suggestions using a generative AI model. The specific operation method is described below.

[0502] The system consists of the following elements:

[0503] 1. User Information Registration Module

[0504] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in the database. This module is responsible for saving information entered by the user through the app or website when they start using the application to the database.

[0505] 2. Electronic gift ticket reading module

[0506] The terminal has the function of reading electronic gift tickets received by the user. When the user scans a QR code or serial number, the terminal analyzes the information and sends it to the server. The server stores the received ticket data in a database, associating it with the user's information.

[0507] 3. Questionnaire Presentation Module

[0508] The device displays personalized surveys to the user. The survey questions are generated based on the user's preferences and past purchase history. An emotion engine performs facial recognition and voice analysis of the user, adjusting the survey content based on the results. For example, it could display a question such as, "You seem a little tired. Would you like to refresh yourself?"

[0509] 4. Product Proposal Module

[0510] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data from the sentiment engine. This process uses a generative AI model to suggest products based on prompt messages. The generated prompt messages are in the following format:

[0511] You have received an electronic gift certificate worth 500 yen. The user says they want coffee. Facial analysis suggests they are a little tired. Please suggest a refreshing drink.

[0512] Based on the results of this AI model, the server selects the most suitable product, generates detailed information about that product, and sends it to the terminal.

[0513] 5. User Approval Module

[0514] The terminal displays detailed information about the products suggested to the user. The user reviews the information, selects a product, and presses the approve button, at which point the information is sent to the server. The server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays the barcode to the user, enabling its use in physical stores.

[0515] 6. Purchase history storage module

[0516] The server stores the user's purchase history and sentiment data in a database. This data is used to personalize product recommendations for future purchases.

[0517] By combining these elements, the present invention realizes a system that allows users to easily purchase products that match their preferences and emotions using electronic gift tickets. This system enables users to enjoy a more satisfying and personalized purchasing experience.

[0518] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0519] Step 1:

[0520] Users register through the app or website.

[0521] Input: Information such as the user's name, email address, and preferences entered in the app or website.

[0522] Data processing and calculation: The terminal sends input information to the server, which receives the information and stores it in the database. It also generates a user ID.

[0523] Output: Registration success notification and generation of a unique user ID.

[0524] Specific operation: The server stores the registered information in a database, generates a user ID, and notifies the terminal.

[0525] Step 2:

[0526] The user scans the electronic gift ticket received within the app.

[0527] Input: Scanned image of a QR code or serial number.

[0528] Data processing and calculation: The terminal analyzes QR codes and serial numbers to extract ticket price information and expiration dates. The results are sent to the server.

[0529] Output: Analyzed ticket data.

[0530] Specific operation: The terminal reads the code using a barcode reader or OpenCV, the server stores that information in a database, and associates it with user information.

[0531] Step 3:

[0532] The device displays personalized surveys to the user.

[0533] Input: Past purchase history, user preference data, sentiment recognition data.

[0534] Data processing and calculation: The server generates survey content based on this data and sends it to the terminal. The terminal uses an emotion engine to perform facial recognition and voice analysis of the user and adaptively adjust the survey.

[0535] Output: Personalized survey.

[0536] Specific operation: The terminal displays the survey content to the user, and the user answers it. The answers are then sent back to the server.

[0537] Step 4:

[0538] The server suggests the most suitable product based on survey results, past purchase history, electronic gift certificate value information, and emotion recognition results.

[0539] Inputs: Survey results, past purchase history, electronic gift certificate amount information, sentiment data.

[0540] Data processing and calculation: The server processes this data using algorithms to select the optimal product. It also generates product suggestions based on prompt text using a generative AI model.

[0541] Output: Suggestions for the most suitable products.

[0542] Specific operation: The server uses the generated prompt message (e.g., "You have received an electronic gift ticket worth 500 yen. The user says they want coffee. Facial analysis results indicate they are a little tired. Please suggest a refreshing drink.") to make product suggestions and send the results to the terminal.

[0543] Step 5:

[0544] The user reviews the details of the suggested products, selects a product, and approves it.

[0545] Input: Product information displayed on the terminal.

[0546] Data processing and calculation: User selection information is sent from the terminal to the server, which then records it.

[0547] Output: User selection and approval of products.

[0548] Specific operation: When the user selects an item and presses the approval button, the server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays this barcode to the user, enabling its use in physical stores.

[0549] Step 6:

[0550] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations.

[0551] Input: User purchase information and sentiment data.

[0552] Data processing and calculations: The server stores this data in a database and uses it for personalized suggestions in the future.

[0553] Output: Saved purchase history and sentiment data.

[0554] Specific operation: The server stores purchase history and sentiment data, and retains it in a database in a format that can be used for future product recommendations.

[0555] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0556] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0557] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0558] [Second Embodiment]

[0559] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0560] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0561] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0562] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0563] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0564] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0565] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0566] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0567] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0568] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0569] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0570] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0571] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The system has the function of registering user information and reading electronic gift tickets. It also has the function of presenting the user with a questionnaire, receiving responses, suggesting the most suitable products based on the responses, and approving the products selected by the user. Furthermore, it has the function of saving the user's purchase history and using it for future suggestions.

[0572] System Configuration

[0573] 1. User Information Registration Module

[0574] The server receives information such as the user's name, email address, preferences, and purchase history, and registers it in the database.

[0575] 2. Electronic gift ticket reading module

[0576] The device has the function of allowing users to read electronic gift tickets such as LINE Gifts. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[0577] The server receives the read ticket data, associates it with user information, and stores it in the database.

[0578] 3. Questionnaire Presentation Module

[0579] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0580] Users answer a survey and send their answers to the server via their device.

[0581] 4. Product Proposal Module

[0582] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[0583] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0584] The device displays detailed information about the products suggested to the user.

[0585] Specific example

[0586] 1. User Information Registration

[0587] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name and email address.

[0588] The server saves the entered information to the database and generates a user ID.

[0589] 2. Electronic gift ticket reading

[0590] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[0591] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[0592] The server stores ticket data, associating it with user information.

[0593] 3. Presenting the questionnaire

[0594] The device displays a survey for "Taro Tanaka".

[0595] Type of beverage (e.g., coffee, tea, frappuccino)

[0596] Sweetness level (e.g., not sweet, normal, sweet)

[0597] Size (e.g., Short, Tall, Grande)

[0598] The user selects "Frappuccino," "Sweet," and "Grande," and then submits their response.

[0599] 4. Product proposal

[0600] The server considers the survey results and past purchase history to select "Caramel Frappuccino (Grande)" as the most suitable product.

[0601] The server generates detailed information about the product and sends it to the terminal.

[0602] The terminal displays an image and price information for "Caramel Frappuccino (Grande)" for "Taro Tanaka".

[0603] 5. User Approval

[0604] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0605] The terminal sends the user's selection to the server.

[0606] The server generates a barcode and sends it to the terminal in a format usable by the store.

[0607] The terminal displays the barcode as "Taro Tanaka".

[0608] 6. Save purchase history

[0609] The server updates "Taro Tanaka's" purchase history and saves it to the database. From then on, personalized product suggestions will be provided based on this purchase history.

[0610] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their preferences.

[0611] The following describes the processing flow.

[0612] Step 1:

[0613] Users enter necessary information such as their name and email address into a new registration form via the app or website.

[0614] Step 2:

[0615] The terminal sends the entered information to the server.

[0616] Step 3:

[0617] The server stores the received user information in a database, generates a user ID, and notifies the user.

[0618] Step 4:

[0619] The user scans the Starbucks ticket received via LINE Gift using the QR code scanning function within the app.

[0620] Step 5:

[0621] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[0622] Step 6:

[0623] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[0624] Step 7:

[0625] The server generates personalized survey questions based on the user's past purchase history.

[0626] Step 8:

[0627] The device displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[0628] Step 9:

[0629] Users answer a survey and send their answers to the server via their device.

[0630] Step 10:

[0631] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[0632] Step 11:

[0633] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0634] Step 12:

[0635] The device displays detailed information about the products suggested to the user. For example, it might show an image and price information for a "Caramel Frappuccino (Grande)".

[0636] Step 13:

[0637] The user selects one product from the suggested options and presses the approve button.

[0638] Step 14:

[0639] The terminal sends the user's selection to the server.

[0640] Step 15:

[0641] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[0642] Step 16:

[0643] The server sends the generated barcode to the terminal.

[0644] Step 17:

[0645] The terminal displays a barcode to the user.

[0646] Step 18:

[0647] The server stores users' purchase history and preference data in a database, which is then used to make future recommendations.

[0648] (Example 1)

[0649] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0650] Conventional systems have problems such as cumbersome product selection and insufficient product suggestions tailored to user preferences when users purchase products using electronic gift tickets. Furthermore, there is a problem that users' purchase history is not reflected in subsequent suggestions, resulting in a lack of personalized recommendations. The present invention aims to solve these problems and provide a system in which users can use electronic gift tickets efficiently and effectively.

[0651] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0652] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for displaying the generated barcode, and means for saving the user's purchase history and using it for future suggestions. This makes it possible for users to easily and efficiently purchase products that suit their preferences using electronic gift tickets.

[0653] "Means of registering user information" refers to the function of registering information such as the user's name, email address, preferences, and purchase history in a database.

[0654] "Methods for reading electronic gift tickets" refers to functions that analyze QR codes or serial numbers to extract the amount and expiration date of electronic gift tickets.

[0655] "A means of presenting a survey to a user and receiving their response" refers to a function that displays questions about the user's preferences and purchase intentions and obtains their response.

[0656] "A method for suggesting products based on user preferences and electronic gift ticket value information" refers to a function that selects the most suitable product based on user responses and existing data, and then suggests it to the user.

[0657] "A means for users to select and approve suggested products" refers to a function that allows users to select from the presented products and perform actions to confirm their purchase.

[0658] "Means for displaying generated barcodes" refers to a function that generates barcodes for use by the user in stores and displays them on the user's device.

[0659] "A means of saving a user's purchase history and using it for future recommendations" refers to a function that saves data on products purchased by the user in a database and uses that data to make future recommendations.

[0660] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The following describes a specific system configuration and operating procedure for carrying out the invention.

[0661] System Configuration

[0662] The system mainly consists of the following hardware and software.

[0663] server

[0664] Database server: MySQL, PostgreSQL, etc.

[0665] Application server: Apache Tomcat, Node.js, etc.

[0666] Algorithmic processing: Python scripts and machine learning models

[0667] terminal

[0668] Smartphones and tablets: iOS, Android devices

[0669] QR code reader: Uses a smartphone camera and a dedicated app.

[0670] User

[0671] General user: A user of the system

[0672] User Information Registration

[0673] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name, email address, and preferences (e.g., likes coffee, dislikes tea). The device sends this information to the server, which stores it in a database. At this time, the server generates a new user ID.

[0674] Electronic gift ticket reading

[0675] Users scan electronic gift tickets received from LINE Gift or other platforms using the app. The device uses the smartphone's camera to read the QR code or serial number and sends the data to the server. The server analyzes the received ticket data, extracts monetary information, and associates it with user information.

[0676] Presenting a questionnaire and obtaining responses.

[0677] The device displays a personalized questionnaire to the user. The questionnaire includes questions such as the type of beverage (coffee, tea, frappuccino), sweetness level (not sweet, normal, sweet), and size (short, tall, grande). The user answers the questionnaire and sends their answers to the server via the device.

[0678] Product proposals

[0679] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value of the electronic gift certificate. For example, if the user selects "Frappuccino," "Sweet," and "Grande," the server will recommend "Caramel Frappuccino (Grande)." The server sends the generated product details to the terminal, which then displays that information to the user.

[0680] User authorization and barcode display

[0681] The user selects items to purchase from the suggested products and presses the approve button. The terminal sends this information to the server. After the server completes the purchase process, it generates a barcode that can be used in the store and sends it to the terminal. The terminal displays the generated barcode to the user.

[0682] Saving purchase history and using it for future proposals.

[0683] The server stores information about the products the user has purchased in a database and updates the purchase history. This history is then used to improve future recommendations. For example, if a user purchases a "Caramel Frappuccino (Grande)," that information will be reflected in future recommendations, allowing for more accurate suggestions tailored to the user's preferences.

[0684] Specific example

[0685] Examples of prompt statements are as follows:

[0686] Registration screen: "Please enter your name."

[0687] Electronic gift ticket scanning screen: "Please scan the QR code on the gift ticket."

[0688] Survey screen:

[0689] Drink options: "Please choose from coffee, tea, or frappuccino."

[0690] Sweetness level: "Please choose from Not Sweet, Normal, or Sweet."

[0691] Size: "Please choose from Short, Tall, or Grande."

[0692] This concludes the detailed description of how the present invention can be implemented. By using this system, users can efficiently and effectively utilize electronic gift tickets and obtain a more personalized purchasing experience.

[0693] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0694] Step 1: User Information Registration

[0695] Users open the new registration screen on the app or website and enter their name, email address, preferences, etc. The entered data is sent to the device in the following format.

[0696] Input: User's name, email address, and preferences

[0697] Specific operation: The user enters the name "Taro Tanaka," the email address "tanaka@example.com," and their preferences as "Likes coffee, dislikes tea."

[0698] The terminal organizes this data and sends it to the server in the following format.

[0699] Output: Registration data (name, email address, preferences)

[0700] Step 2: Saving User Information

[0701] The server stores the received user information in the database server and generates a user ID. This user ID is used in subsequent processing and is linked to the user information.

[0702] Input: Registration data (name, email address, preferences)

[0703] Data processing: Create a new entry in the database and save each item.

[0704] Specific operation: The server saves information about "Taro Tanaka" to the MySQL database and generates user ID "12345".

[0705] Output: User ID

[0706] Step 3: Scan the e-gift ticket

[0707] The user scans the QR code of the electronic gift ticket received via LINE Gift using the app. The device reads the QR code using the smartphone's camera and analyzes the data.

[0708] Input: QR code image data

[0709] Data processing: Extracting price information and expiration date from QR codes.

[0710] Specific operation: When a user scans an electronic gift ticket worth 500 yen, the terminal analyzes the QR code and extracts the amount "500 yen" and the expiration date "December 31, 2023".

[0711] Output: Extracted amount information and expiration date

[0712] Step 4: Save ticket data

[0713] The terminal sends the analyzed ticket data to the server and associates it with the user ID. The server stores the received ticket data in a database.

[0714] Input: Amount information, expiration date, user ID

[0715] Data processing: Ticket data is linked to user information and saved.

[0716] Specific operation: The terminal sends the analysis results, and the server associates the user ID "12345" with a "ticket worth 500 yen" and saves it in the database.

[0717] Output: Database update status

[0718] Step 5: Presenting the questionnaire

[0719] The device displays a personalized survey based on the user's preferences. The survey includes questions about the type of beverage, sweetness level, size, and other factors.

[0720] Input: None (User interaction)

[0721] Specific actions: The device displays a questionnaire to "Taro Tanaka." The questionnaire includes questions such as: "Type of drink (coffee, tea, frappuccino)", "Sweetness level (not sweet, normal, sweet)", and "Size (short, tall, grande)".

[0722] Output: Survey screen

[0723] Step 6: Collecting survey responses

[0724] The user answers the displayed questionnaire and sends their selections to the server via their device.

[0725] Input: User survey responses

[0726] Data processing: Formatting and sending of survey response data.

[0727] Specific operation: The user selects "Frappuccino," "Sweet," and "Grande," and submits their response. The device sends the selection data to the server.

[0728] Output: User response data

[0729] Step 7: Product Selection

[0730] The server uses an algorithm to select the most suitable product based on the received survey responses, past purchase history, and the value information of the electronic gift certificate.

[0731] Input: Survey response data, purchase history data, ticket price information

[0732] Data processing: Input each data point into an algorithm to select the optimal product.

[0733] Specific operation: Based on the survey results "Frappuccino," "Sweet," and "Grande," as well as purchase history, the server recommends "Caramel Frappuccino (Grande)."

[0734] Output: Recommended product data

[0735] Step 8: Display product details

[0736] The device displays detailed information about the products suggested to the user. This information includes the product name, price, calories, and options.

[0737] Input: Recommended product data

[0738] Specific action: The device displays an image and price information for "Caramel Frappuccino (Grande)" to "Taro Tanaka".

[0739] Output: Product Information Screen

[0740] Step 9: User Approval

[0741] The user selects the items they wish to purchase from the displayed products and presses the confirm button. The device then sends this information to the server.

[0742] Input: User's selection information

[0743] Data processing: Send user selection information to the server.

[0744] Specific action: The user selects "Caramel Frappuccino (Grande)" and presses the confirm button. The device sends the selection information to the server.

[0745] Output: User approval data

[0746] Step 10: Generate and display the barcode

[0747] The server completes the user's purchase process, generates a barcode usable in the store, and sends it to the terminal. The terminal displays the generated barcode to the user.

[0748] Input: User approval data

[0749] Data processing: Barcode generation and transmission

[0750] Specific operation: The server completes the purchase process, generates a barcode, and sends it to the terminal. The terminal displays the barcode on "Taro Tanaka".

[0751] Output: Barcode display

[0752] Step 11: Update Purchase History

[0753] The server stores the user's purchase history in a database and uses it to make recommendations for future purchases.

[0754] Input: User approval data, purchased product data

[0755] Data processing: Updating and saving purchase history

[0756] Specific action: The server adds "Caramel Frappuccino (Grande)" to "Taro Tanaka's" purchase history and saves it to the database.

[0757] Output: Updated purchase history

[0758] Through the steps described above, the system of the present invention enables users to efficiently utilize electronic gift tickets and receive personalized product recommendations.

[0759] (Application Example 1)

[0760] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0761] Traditional electronic gift ticket-based product purchase systems have the problem of not being able to fully utilize user preferences and past purchase history, making it difficult to recommend products that are optimal for individual users. Furthermore, there is a lack of mechanisms to allow users to complete purchases directly using electronic payment services and use them quickly at stores. This results in a degraded user experience and a cumbersome process.

[0762] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0763] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for saving the user's purchase history and using it for future suggestions, and means for completing the purchase using an electronic payment service, generating a barcode, and displaying it on the user's terminal. As a result, the user can efficiently select products that suit their preferences and enjoy the convenience of purchasing and paying using electronic gift tickets.

[0764] "User information" refers to information such as the user's name, contact information, preferences, and purchase history.

[0765] An "electronic gift ticket" is a gift certificate issued electronically, provided in a format that includes a QR code or serial number.

[0766] A "survey" is a tool used to ask questions about a user's preferences and collect their responses.

[0767] "Product suggestion" refers to the act of selecting and presenting the most suitable product based on the user's preferences and the value of the electronic gift certificate.

[0768] "Electronic payment services" refer to services that conduct financial transactions via the internet, and include the use of electronic gift tickets.

[0769] A "barcode" is a machine-readable code generated to prove the purchase of a product.

[0770] "Purchase history" refers to data that includes information such as the products a user has purchased in the past and the date and time of those purchases.

[0771] A "server" refers to a computer system that manages user information and electronic gift ticket information, and processes various procedures.

[0772] A "user terminal" refers to a device operated by the user, such as a smartphone or tablet.

[0773] System program

[0774] The system implementing this application includes programs for registering user information, reading electronic gift tickets, presenting questionnaires, suggesting products, completing electronic payments, generating and displaying barcodes, and saving purchase history. The programs are implemented using Python and run as a web application using Flask.

[0775] Program Processing Description

[0776] The system uses the following hardware and software:

[0777] Hardware:

[0778] Server: A computer system that performs data processing and storage.

[0779] User device: A mobile device such as a smartphone or tablet.

[0780] software:

[0781] Python: A programming language used for implementing programs.

[0782] Flask: A web application framework.

[0783] qrcode: A library for generating QR codes.

[0784] 1. User information registration:

[0785] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database.

[0786] 2. Electronic gift ticket reading:

[0787] The user's device uses its camera to scan the QR code on the electronic gift ticket. The scanned data is sent to a server for analysis.

[0788] 3. Presenting the questionnaire:

[0789] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server.

[0790] 4. Product suggestion:

[0791] The server uses an algorithm to select the most suitable product based on the user's survey results and past purchase history, and then sends that information to the user's terminal.

[0792] 5. Electronic payment completion and barcode generation:

[0793] Once the user approves the suggested product, the server completes the electronic payment, generates a barcode, and displays it on the user's device.

[0794] 6. Save purchase history:

[0795] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[0796] Specific example

[0797] As a concrete example, this system can be implemented using the following prompt statement:

[0798] Example of a prompt:

[0799] User information:

[0800] Name: Taro Tanaka

[0801] Email: taro.tanaka@example.com

[0802] Preferences: Frappuccino, sweet, grande

[0803] Electronic gift tickets:

[0804] Amount: 500 yen

[0805] Expiration Date: 2024-12-31

[0806] Based on the following information, this system will suggest the most suitable product to the user and complete the electronic payment. For example, if Taro Tanaka answers "Frappuccino," "Sweet," and "Grande," the system will suggest "Caramel Frappuccino (Grande)." After that, the electronic payment will be completed and a barcode will be displayed on Taro Tanaka's smartphone.

[0807] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0808] Step 1:

[0809] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database. Specifically, it receives information entered by the user through the application screen and writes it to the database in the appropriate format. At this time, a user ID is generated and stored along with other related information.

[0810] Input: User information (name, contact information, preferences, past purchase history)

[0811] Data processing: Converting user information into an appropriate format.

[0812] Output: User information stored in the database

[0813] Step 2:

[0814] The user's device uses its camera to scan the QR code on the electronic gift ticket. The data read from the QR code is sent to the server. The server analyzes this data, extracts information such as the ticket's value and expiration date, and stores it in association with the user's information.

[0815] Input: QR code data

[0816] Data processing: Analyze QR code data to extract ticket information.

[0817] Output: Ticket information saved in association with user information

[0818] Step 3:

[0819] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server. The questionnaire questions are based on the user's preferences, such as the type of beverage, sweetness level, and size.

[0820] Input: User survey responses

[0821] Data processing: Converting user responses into structured data.

[0822] Output: Survey response data sent to the server

[0823] Step 4:

[0824] The server uses an algorithm to select the most suitable product based on user survey results and past purchase history. This algorithm considers user preferences, electronic gift certificate value information, and past purchase history to suggest the optimal product.

[0825] Input: Survey response data, past purchase history, electronic gift ticket information

[0826] Data processing: Algorithmic product selection process

[0827] Output: Optimal product suggestion information

[0828] Step 5:

[0829] The user terminal displays product suggestion information received from the server. The user reviews and approves the suggested products. The approval information is sent to the server.

[0830] Input: Product proposal information

[0831] Data processing: Converting product information to a display format.

[0832] Output: User approval information

[0833] Step 6:

[0834] The server receives authorization information from the user and completes the electronic payment. Once the payment is complete, the server generates a barcode and sends it to the user's terminal in a format usable at the store.

[0835] Input: User authorization information

[0836] Data processing: Electronic payment processing, barcode generation

[0837] Output: Barcode sent to the user terminal

[0838] Step 7:

[0839] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[0840] Input: New purchase information

[0841] Data processing: Storage and structuring of purchase information

[0842] Output: Purchase history stored in the database

[0843] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0844] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present and receive questionnaires, suggest products based on the user's preferences, the value of the electronic gift ticket, and emotion recognition by an emotion engine, and approve the products selected by the user. It also includes a function to save the user's purchase history and utilize it for future suggestions.

[0845] System Configuration

[0846] 1. User Information Registration Module

[0847] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database.

[0848] 2. Electronic gift ticket reading module

[0849] The device has the function of reading electronic gift tickets received by the user. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[0850] The server receives the read ticket data, associates it with user information, and stores it in the database.

[0851] 3. Questionnaire Presentation Module

[0852] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0853] The emotion engine can analyze the user's facial expressions and tone of voice, and adjust the survey content based on the results.

[0854] Users answer a survey and send their answers to the server via their device.

[0855] 4. Product Proposal Module

[0856] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotional data generated by an emotion engine.

[0857] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0858] The device displays detailed information about the products suggested to the user.

[0859] Specific example

[0860] 1. User Information Registration

[0861] Users register through the app or website. For example, they enter their name, email address, and interests.

[0862] The server saves the entered information to the database and generates a user ID.

[0863] 2. Electronic gift ticket reading

[0864] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[0865] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[0866] The server stores ticket data, associating it with user information.

[0867] 3. Presenting the questionnaire

[0868] The device displays personalized surveys to the user.

[0869] The emotion engine uses facial recognition and voice analysis to adjust the displayed survey questions according to the user's emotional state. For example, the questions might change to something like, "You seem a little tired. Would you like to refresh yourself?"

[0870] Users answer a survey and send their answers to the server via their device.

[0871] 4. Product proposal

[0872] Based on survey results, past purchase history, electronic gift ticket value information, and sentiment data obtained from the sentiment engine, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product.

[0873] The server generates detailed information about the product and sends it to the terminal.

[0874] The device displays an image and detailed information about "Caramel Frappuccino (Grande)" to the user.

[0875] 5. User Approval

[0876] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0877] The terminal sends the user's selection to the server.

[0878] The server generates a barcode and sends it to the terminal in a format that can be used in Starbucks stores.

[0879] The terminal displays a barcode to the user.

[0880] 6. Save purchase history

[0881] The server can store the user's purchase history and sentiment data in a database, which can then be used to improve future recommendations. This makes it possible to provide even more personalized product suggestions.

[0882] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[0883] The following describes the processing flow.

[0884] Step 1:

[0885] Users enter their name, email address, and preferences into a new registration form via the app or website.

[0886] Step 2:

[0887] The terminal sends the entered information to the server.

[0888] Step 3:

[0889] The server stores the received user information in a database, generates a user ID, and notifies the user.

[0890] Step 4:

[0891] Users scan the electronic gift ticket they received via LINE Gift using the QR code scanning function within the app.

[0892] Step 5:

[0893] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[0894] Step 6:

[0895] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[0896] Step 7:

[0897] The server generates personalized survey questions based on the user's past purchase history.

[0898] Step 8:

[0899] The terminal displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[0900] Step 9:

[0901] The emotion engine uses facial recognition and voice analysis to evaluate the user's emotions in real time. Based on this evaluation, it adjusts the survey questions. For example, it might change the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[0902] Step 10:

[0903] Users answer a survey and send their answers to the server via their device.

[0904] Step 11:

[0905] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotion engine evaluation data.

[0906] Step 12:

[0907] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[0908] Step 13:

[0909] The device displays detailed information about the product suggested to the user. For example, it displays an image and description of a "Caramel Frappuccino (Grande)".

[0910] Step 14:

[0911] The user selects one product from the suggested options and presses the approve button.

[0912] Step 15:

[0913] The terminal sends the user's selection to the server.

[0914] Step 16:

[0915] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[0916] Step 17:

[0917] The server sends the generated barcode to the terminal.

[0918] Step 18:

[0919] The terminal displays a barcode to the user.

[0920] Step 19:

[0921] The server saves the user's purchase history and sentiment data to a database along with a thank-you message, and uses this data to make future suggestions.

[0922] Step 20:

[0923] The emotion engine analyzes emotional data throughout the user's entire experience and provides feedback data for further personalization.

[0924] (Example 2)

[0925] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0926] In conventional systems, when users purchase products using electronic gift tickets, personalized product suggestions that take into account the user's preferences and emotional state are not provided, which often leads to lower user satisfaction. Furthermore, there is no mechanism to dynamically adjust survey content and product suggestions using user emotional data, resulting in a challenge in accurately responding to user needs.

[0927] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving a response, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and emotional data from an emotional engine, means for the user to select and approve the suggested products, and means for saving the user's purchase history and emotional data and utilizing them for future suggestions. This makes it possible to make personalized product suggestions based on the user's preferences and emotional state, thereby improving user satisfaction.

[0928] "User information" refers to individual information about a user, such as their name, email address, preferences, purchase history, and sentiment data.

[0929] An "electronic gift ticket" is a ticket issued in electronic format that can be exchanged for goods or services based on a specific amount or expiration date.

[0930] A "survey" is a series of questions presented to a user, used to understand their preferences and needs.

[0931] An "emotion engine" is a technological system that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[0932] "Product suggestion" is the process of presenting products suitable for the user based on the user's preferences, the value information of the electronic gift certificate, and sentiment data.

[0933] "Purchase history" refers to a record of products a user has purchased in the past, and this information is stored to be used for future recommendations.

[0934] A "personalized survey" is a survey that is individually tailored based on a user's past purchase history and sentiment data.

[0935] The "optimal product" is a product selected by an algorithm that comprehensively considers user preferences, the value information of the electronic gift certificate, and emotional data.

[0936] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present questionnaires, and receive responses. Furthermore, it has a function to suggest products based on the user's preferences, the amount of the electronic gift ticket, and emotion recognition by an emotion engine, and to approve the products selected by the user. It also has a function to save the user's purchase history and utilize it for future suggestions.

[0937] System configuration and details

[0938] 1. User Information Registration Module

[0939] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database. This step uses a database management system such as MySQL or PostgreSQL.

[0940] For example, a user registers through an app or website, entering their name, email address, and preferences. The server stores this information in a database and generates a user ID.

[0941] 2. Electronic gift ticket reading module

[0942] The device has the functionality to read electronic gift tickets received by the user. It analyzes the QR code and serial number to extract the ticket's value and expiration date. This is done using QR code reading libraries such as ZBar and ZXing.

[0943] For example, a user scans a 500 yen Starbucks ticket received via LINE Gift within the app. The device reads the QR code and sends the ticket data to the server.

[0944] 3. Questionnaire Presentation Module

[0945] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[0946] The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the survey content based on the results. For example, if it determines that the user is tired, it changes the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[0947] For example, a user answers a survey and sends their answers to a server via their device.

[0948] 4. Product Proposal Module

[0949] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data generated by an emotion engine. This process utilizes machine learning models and recommendation engines such as TensorFlow and Scikit-Learn.

[0950] For example, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product and sends its detailed information to the terminal. The terminal then displays this information to the user.

[0951] 5. User Approval Module

[0952] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[0953] The terminal sends the user's selection to the server. The server generates a barcode and sends it to the terminal. The user can use this barcode to purchase products in the store.

[0954] 6. Purchase history storage module

[0955] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations. This will enable even more personalized product suggestions.

[0956] Examples of specific cases and prompt statements

[0957] Specific example:

[0958] For example, the terminal displays the question, "You seem a little tired. Would you like to refresh yourself?" and the user replies that they would like to refresh themselves. Based on this, the server suggests a "Caramel Frappuccino (Grande)," and if the user selects it, a barcode is generated that can be used in the store.

[0959] Example of a prompt:

[0960] Please describe a system that allows users to register new user information, scan electronic gift tickets, answer questionnaires, and receive product recommendations. In particular, please explain in detail how the emotion engine adjusts the displayed questionnaire content.

[0961] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[0962] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0963] Program processing flow

[0964] Step 1: Register User Information

[0965] 1.1 Input: The user enters their name, email address, preferences, purchase history, and sentiment data.

[0966] Specific operation: The user launches the app from their smartphone or PC and enters information into the input form.

[0967] Output: The entered user information is sent to the server.

[0968] 1.2 Data Processing and Calculation: The server applies a data format to the user information it receives in order to register it in the database.

[0969] Specific operation: The server saves the data received in the HTTP request to a database management system (e.g., MySQL, PostgreSQL).

[0970] Output: User information stored in the database.

[0971] Step 2: Read the electronic gift ticket

[0972] 2.1 Input: The user scans the electronic gift ticket (QR code or serial number).

[0973] Specific operation: The user uses the camera on their smartphone app to scan the electronic gift ticket.

[0974] 2.2 Data Processing and Calculation: The terminal analyzes the QR code or serial number and extracts the ticket price and expiration date.

[0975] Specific operation: The device analyzes the data using QR code reading software (e.g., ZBar, ZXing).

[0976] Output: Extracted ticket information.

[0977] 2.3 Input: The extracted ticket information is sent to the server.

[0978] Specific action: The terminal sends the analyzed ticket information to the server.

[0979] Output: Ticket information sent to the server.

[0980] 2.4 Data Processing and Calculation: The server stores the received ticket information in the database, associating it with user information.

[0981] Specific operation: The server links the received ticket information with the user ID and saves it to the database.

[0982] Output: Ticket information stored in the database.

[0983] Step 3: Presenting the questionnaire

[0984] 3.1 Input: The server obtains the data necessary to provide users with personalized surveys (preferences, past purchase history, sentiment data).

[0985] Specific operation: The server retrieves user preferences, purchase history, and sentiment data from the database.

[0986] 3.2 Data Processing and Calculation: The server generates survey questions based on the acquired data.

[0987] Specific operation: The server generates survey questions using an algorithm and adjusts them based on sentiment data.

[0988] Output: Personalized survey.

[0989] 3.3 Input: The generated questionnaire is sent to the device.

[0990] Specific operation: The server sends the survey data to the terminal.

[0991] Output: The survey content displayed on the device.

[0992] 3.4 Input: The user answers the survey.

[0993] Specific action: The user enters their answers into the survey form and presses the submit button.

[0994] 3.5 Data Processing and Calculation: The terminal sends the user's survey responses to the server.

[0995] Specific action: The device sends the response data to the server.

[0996] Output: Survey responses sent to the server.

[0997] Step 4: Product Proposal

[0998] 4.1 Input: The server receives survey responses, purchase history, electronic gift certificate amount information, and sentiment data.

[0999] Specific operation: The server receives the user's survey responses and related data.

[1000] 4.2 Data Processing and Calculation: The server uses an algorithm to select the optimal product.

[1001] Specific operation: The server uses machine learning models and recommendation engines (e.g., TensorFlow, Scikit-Learn) to select the most suitable products.

[1002] Output: Detailed information on the selected products.

[1003] 4.3 Input: Detailed information about the selected product is sent to the terminal.

[1004] Specific operation: The server sends detailed product information to the terminal.

[1005] Output: Product information displayed on the terminal.

[1006] Step 5: User Approval

[1007] 5.1 Input: The user selects and approves the suggested product.

[1008] Specific actions: The user clicks the "Select Product" button and then clicks the "Approve" button.

[1009] 5.2 Data Processing and Calculation: The terminal sends the user's selected data to the server.

[1010] Specific operation: The terminal sends the selected data to the server as an HTTP request.

[1011] Output: Selected data sent to the server.

[1012] 5.3 Data Processing and Calculation: The server generates a barcode and sends it to the terminal.

[1013] Specific operation: The server generates barcodes using a barcode generation library (e.g., Barcode4J, ZXing).

[1014] Output: The generated barcode.

[1015] 5.4 Input: The generated barcode is sent to the terminal.

[1016] Specific operation: The server sends barcode data to the terminal.

[1017] Output: The barcode displayed on the terminal.

[1018] Step 6: Saving Purchase History

[1019] 6.1 Input: The server receives the user's purchase history and sentiment data.

[1020] Specific operation: The server receives purchase history and sentiment data.

[1021] 6.2 Data Processing and Calculation: The server saves the received data to a database and uses it for future proposals.

[1022] Specific operation: The server stores purchase history data and sentiment data in a database.

[1023] Output: Purchase history and sentiment data stored in the database.

[1024] (Application Example 2)

[1025] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1026] In today's world, when users use electronic gift tickets to purchase products that match their preferences and emotions, it is difficult to provide personalized recommendations. This can lead to wasted time and a poor purchasing experience. Furthermore, existing systems do not consider the user's emotional state when making product recommendations, thus failing to increase user satisfaction.

[1027] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1028] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and the emotion recognition results, means for the user to select and approve the suggested products, means for saving the user's purchase history and emotion data and using them for future suggestions, and means for suggesting products using a generation AI model based on the generated prompt text. As a result, the user can efficiently select and purchase products that match their preferences and emotions, thereby realizing a highly satisfying shopping experience.

[1029] "Means for registering user information" refers to a function for registering information such as the user's name, email address, preferences, purchase history, and sentiment data on the server.

[1030] "Methods for reading electronic gift tickets" refer to functions that analyze QR codes or serial numbers to extract the ticket's value and expiration date.

[1031] "A means of presenting a survey to a user and receiving their response" refers to a function that displays a personalized survey to a user and receives their response.

[1032] "A means of suggesting products based on user preferences, electronic gift ticket value information, and emotion recognition results" refers to a function that uses user survey results, past purchase history, electronic gift ticket value information, and emotion data from an emotion engine to algorithmically select and suggest the most suitable products.

[1033] "A means for users to select and approve suggested products" refers to a function that allows users to review detailed information about suggested products, select them, and approve their purchase.

[1034] "Means for saving users' purchase history and sentiment data and using them for future recommendations" refers to a function that saves users' purchase history and sentiment data in a database and uses it to make personalized product recommendations for future purchases.

[1035] "A means of suggesting products using a generative AI model based on generated prompt sentences" refers to a function that generates prompt sentences according to the user's situation and suggests the most suitable product using a generative AI model (e.g., GPT-3 or GPT-4).

[1036] The system implementing the present invention is designed to perform a series of steps, from user information registration and reading of electronic gift tickets to presenting and receiving responses to questionnaires, product suggestions, user product approval, saving of purchase history, and product suggestions using a generative AI model. The specific operation method is described below.

[1037] The system consists of the following elements:

[1038] 1. User Information Registration Module

[1039] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in the database. This module is responsible for saving information entered by the user through the app or website when they start using the application to the database.

[1040] 2. Electronic gift ticket reading module

[1041] The terminal has the function of reading electronic gift tickets received by the user. When the user scans a QR code or serial number, the terminal analyzes the information and sends it to the server. The server stores the received ticket data in a database, associating it with the user's information.

[1042] 3. Questionnaire Presentation Module

[1043] The device displays personalized surveys to the user. The survey questions are generated based on the user's preferences and past purchase history. An emotion engine performs facial recognition and voice analysis of the user, adjusting the survey content based on the results. For example, it could display a question such as, "You seem a little tired. Would you like to refresh yourself?"

[1044] 4. Product Proposal Module

[1045] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data from the sentiment engine. This process uses a generative AI model to suggest products based on prompt messages. The generated prompt messages are in the following format:

[1046] You have received an electronic gift certificate worth 500 yen. The user says they want coffee. Facial analysis suggests they are a little tired. Please suggest a refreshing drink.

[1047] Based on the results of this AI model, the server selects the most suitable product, generates detailed information about that product, and sends it to the terminal.

[1048] 5. User Approval Module

[1049] The terminal displays detailed information about the products suggested to the user. The user reviews the information, selects a product, and presses the approve button, at which point the information is sent to the server. The server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays the barcode to the user, enabling its use in physical stores.

[1050] 6. Purchase history storage module

[1051] The server stores the user's purchase history and sentiment data in a database. This data is used to personalize product recommendations for future purchases.

[1052] By combining these elements, the present invention realizes a system that allows users to easily purchase products that match their preferences and emotions using electronic gift tickets. This system enables users to enjoy a more satisfying and personalized purchasing experience.

[1053] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1054] Step 1:

[1055] Users register through the app or website.

[1056] Input: Information such as the user's name, email address, and preferences entered in the app or website.

[1057] Data processing and calculation: The terminal sends input information to the server, which receives the information and stores it in the database. It also generates a user ID.

[1058] Output: Registration success notification and generation of a unique user ID.

[1059] Specific operation: The server stores the registered information in a database, generates a user ID, and notifies the terminal.

[1060] Step 2:

[1061] The user scans the electronic gift ticket received within the app.

[1062] Input: Scanned image of a QR code or serial number.

[1063] Data processing and calculation: The terminal analyzes QR codes and serial numbers to extract ticket price information and expiration dates. The results are sent to the server.

[1064] Output: Analyzed ticket data.

[1065] Specific operation: The terminal reads the code using a barcode reader or OpenCV, the server stores that information in a database, and associates it with user information.

[1066] Step 3:

[1067] The device displays personalized surveys to the user.

[1068] Input: Past purchase history, user preference data, sentiment recognition data.

[1069] Data processing and calculation: The server generates survey content based on this data and sends it to the terminal. The terminal uses an emotion engine to perform facial recognition and voice analysis of the user and adaptively adjust the survey.

[1070] Output: Personalized survey.

[1071] Specific operation: The terminal displays the survey content to the user, and the user answers it. The answers are then sent back to the server.

[1072] Step 4:

[1073] The server suggests the most suitable product based on survey results, past purchase history, electronic gift certificate value information, and emotion recognition results.

[1074] Inputs: Survey results, past purchase history, electronic gift certificate amount information, sentiment data.

[1075] Data processing and calculation: The server processes this data using algorithms to select the optimal product. It also generates product suggestions based on prompt text using a generative AI model.

[1076] Output: Suggestions for the most suitable products.

[1077] Specific operation: The server uses the generated prompt message (e.g., "You have received an electronic gift ticket worth 500 yen. The user says they want coffee. Facial analysis results indicate they are a little tired. Please suggest a refreshing drink.") to make product suggestions and send the results to the terminal.

[1078] Step 5:

[1079] The user reviews the details of the suggested products, selects a product, and approves it.

[1080] Input: Product information displayed on the terminal.

[1081] Data processing and calculation: User selection information is sent from the terminal to the server, which then records it.

[1082] Output: User selection and approval of products.

[1083] Specific operation: When the user selects an item and presses the approval button, the server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays this barcode to the user, enabling its use in physical stores.

[1084] Step 6:

[1085] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations.

[1086] Input: User purchase information and sentiment data.

[1087] Data processing and calculations: The server stores this data in a database and uses it for personalized suggestions in the future.

[1088] Output: Saved purchase history and sentiment data.

[1089] Specific operation: The server stores purchase history and sentiment data, and retains it in a database in a format that can be used for future product recommendations.

[1090] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1091] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1092] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1093] [Third Embodiment]

[1094] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1095] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1096] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1097] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1098] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1099] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1100] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1101] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1102] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1103] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1104] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1105] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1106] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The system has the function of registering user information and reading electronic gift tickets. It also has the function of presenting the user with a questionnaire, receiving responses, suggesting the most suitable products based on the responses, and approving the products selected by the user. Furthermore, it has the function of saving the user's purchase history and using it for future suggestions.

[1107] System Configuration

[1108] 1. User Information Registration Module

[1109] The server receives information such as the user's name, email address, preferences, and purchase history, and registers it in the database.

[1110] 2. Electronic gift ticket reading module

[1111] The device has the function of allowing users to read electronic gift tickets such as LINE Gifts. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[1112] The server receives the read ticket data, associates it with user information, and stores it in the database.

[1113] 3. Questionnaire Presentation Module

[1114] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[1115] Users answer a survey and send their answers to the server via their device.

[1116] 4. Product Proposal Module

[1117] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[1118] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1119] The device displays detailed information about the products suggested to the user.

[1120] Specific example

[1121] 1. User Information Registration

[1122] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name and email address.

[1123] The server saves the entered information to the database and generates a user ID.

[1124] 2. Electronic gift ticket reading

[1125] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[1126] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[1127] The server stores ticket data, associating it with user information.

[1128] 3. Presenting the questionnaire

[1129] The device displays a survey for "Taro Tanaka".

[1130] Type of beverage (e.g., coffee, tea, frappuccino)

[1131] Sweetness level (e.g., not sweet, normal, sweet)

[1132] Size (e.g., Short, Tall, Grande)

[1133] The user selects "Frappuccino," "Sweet," and "Grande," and then submits their response.

[1134] 4. Product proposal

[1135] The server considers the survey results and past purchase history to select "Caramel Frappuccino (Grande)" as the most suitable product.

[1136] The server generates detailed information about the product and sends it to the terminal.

[1137] The terminal displays an image and price information for "Caramel Frappuccino (Grande)" for "Taro Tanaka".

[1138] 5. User Approval

[1139] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[1140] The terminal sends the user's selection to the server.

[1141] The server generates a barcode and sends it to the terminal in a format usable by the store.

[1142] The terminal displays the barcode as "Taro Tanaka".

[1143] 6. Save purchase history

[1144] The server updates "Taro Tanaka's" purchase history and saves it to the database. From then on, personalized product suggestions will be provided based on this purchase history.

[1145] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their preferences.

[1146] The following describes the processing flow.

[1147] Step 1:

[1148] Users enter necessary information such as their name and email address into a new registration form via the app or website.

[1149] Step 2:

[1150] The terminal sends the entered information to the server.

[1151] Step 3:

[1152] The server stores the received user information in a database, generates a user ID, and notifies the user.

[1153] Step 4:

[1154] The user scans the Starbucks ticket received via LINE Gift using the QR code scanning function within the app.

[1155] Step 5:

[1156] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[1157] Step 6:

[1158] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[1159] Step 7:

[1160] The server generates personalized survey questions based on the user's past purchase history.

[1161] Step 8:

[1162] The device displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[1163] Step 9:

[1164] Users answer a survey and send their answers to the server via their device.

[1165] Step 10:

[1166] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[1167] Step 11:

[1168] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1169] Step 12:

[1170] The device displays detailed information about the products suggested to the user. For example, it might show an image and price information for a "Caramel Frappuccino (Grande)".

[1171] Step 13:

[1172] The user selects one product from the suggested options and presses the approve button.

[1173] Step 14:

[1174] The terminal sends the user's selection to the server.

[1175] Step 15:

[1176] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[1177] Step 16:

[1178] The server sends the generated barcode to the terminal.

[1179] Step 17:

[1180] The terminal displays a barcode to the user.

[1181] Step 18:

[1182] The server stores users' purchase history and preference data in a database, which is then used to make future recommendations.

[1183] (Example 1)

[1184] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1185] Conventional systems have problems such as cumbersome product selection and insufficient product suggestions tailored to user preferences when users purchase products using electronic gift tickets. Furthermore, there is a problem that users' purchase history is not reflected in subsequent suggestions, resulting in a lack of personalized recommendations. The present invention aims to solve these problems and provide a system in which users can use electronic gift tickets efficiently and effectively.

[1186] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1187] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for displaying the generated barcode, and means for saving the user's purchase history and using it for future suggestions. This makes it possible for users to easily and efficiently purchase products that suit their preferences using electronic gift tickets.

[1188] "Means of registering user information" refers to the function of registering information such as the user's name, email address, preferences, and purchase history in a database.

[1189] "Methods for reading electronic gift tickets" refers to functions that analyze QR codes or serial numbers to extract the amount and expiration date of electronic gift tickets.

[1190] "A means of presenting a survey to a user and receiving their response" refers to a function that displays questions about the user's preferences and purchase intentions and obtains their response.

[1191] "A method for suggesting products based on user preferences and electronic gift ticket value information" refers to a function that selects the most suitable product based on user responses and existing data, and then suggests it to the user.

[1192] "A means for users to select and approve suggested products" refers to a function that allows users to select from the presented products and perform actions to confirm their purchase.

[1193] "Means for displaying generated barcodes" refers to a function that generates barcodes for use by the user in stores and displays them on the user's device.

[1194] "A means of saving a user's purchase history and using it for future recommendations" refers to a function that saves data on products purchased by the user in a database and uses that data to make future recommendations.

[1195] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The following describes a specific system configuration and operating procedure for carrying out the invention.

[1196] System Configuration

[1197] The system mainly consists of the following hardware and software.

[1198] server

[1199] Database server: MySQL, PostgreSQL, etc.

[1200] Application server: Apache Tomcat, Node.js, etc.

[1201] Algorithmic processing: Python scripts and machine learning models

[1202] terminal

[1203] Smartphones and tablets: iOS, Android devices

[1204] QR code reader: Uses a smartphone camera and a dedicated app.

[1205] User

[1206] General user: A user of the system

[1207] User Information Registration

[1208] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name, email address, and preferences (e.g., likes coffee, dislikes tea). The device sends this information to the server, which stores it in a database. At this time, the server generates a new user ID.

[1209] Electronic gift ticket reading

[1210] Users scan electronic gift tickets received from LINE Gift or other platforms using the app. The device uses the smartphone's camera to read the QR code or serial number and sends the data to the server. The server analyzes the received ticket data, extracts monetary information, and associates it with user information.

[1211] Presenting a questionnaire and obtaining responses.

[1212] The device displays a personalized questionnaire to the user. The questionnaire includes questions such as the type of beverage (coffee, tea, frappuccino), sweetness level (not sweet, normal, sweet), and size (short, tall, grande). The user answers the questionnaire and sends their answers to the server via the device.

[1213] Product proposals

[1214] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value of the electronic gift certificate. For example, if the user selects "Frappuccino," "Sweet," and "Grande," the server will recommend "Caramel Frappuccino (Grande)." The server sends the generated product details to the terminal, which then displays that information to the user.

[1215] User authorization and barcode display

[1216] The user selects items to purchase from the suggested products and presses the approve button. The terminal sends this information to the server. After the server completes the purchase process, it generates a barcode that can be used in the store and sends it to the terminal. The terminal displays the generated barcode to the user.

[1217] Saving purchase history and using it for future proposals.

[1218] The server stores information about the products the user has purchased in a database and updates the purchase history. This history is then used to improve future recommendations. For example, if a user purchases a "Caramel Frappuccino (Grande)," that information will be reflected in future recommendations, allowing for more accurate suggestions tailored to the user's preferences.

[1219] Specific example

[1220] Examples of prompt statements are as follows:

[1221] Registration screen: "Please enter your name."

[1222] Electronic gift ticket scanning screen: "Please scan the QR code on the gift ticket."

[1223] Survey screen:

[1224] Drink options: "Please choose from coffee, tea, or frappuccino."

[1225] Sweetness level: "Please choose from Not Sweet, Normal, or Sweet."

[1226] Size: "Please choose from Short, Tall, or Grande."

[1227] This concludes the detailed description of how the present invention can be implemented. By using this system, users can efficiently and effectively utilize electronic gift tickets and obtain a more personalized purchasing experience.

[1228] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1229] Step 1: User Information Registration

[1230] Users open the new registration screen on the app or website and enter their name, email address, preferences, etc. The entered data is sent to the device in the following format.

[1231] Input: User's name, email address, and preferences

[1232] Specific operation: The user enters the name "Taro Tanaka," the email address "tanaka@example.com," and their preferences as "Likes coffee, dislikes tea."

[1233] The terminal organizes this data and sends it to the server in the following format.

[1234] Output: Registration data (name, email address, preferences)

[1235] Step 2: Saving User Information

[1236] The server stores the received user information in the database server and generates a user ID. This user ID is used in subsequent processing and is linked to the user information.

[1237] Input: Registration data (name, email address, preferences)

[1238] Data processing: Create a new entry in the database and save each item.

[1239] Specific operation: The server saves information about "Taro Tanaka" to the MySQL database and generates user ID "12345".

[1240] Output: User ID

[1241] Step 3: Scan the e-gift ticket

[1242] The user scans the QR code of the electronic gift ticket received via LINE Gift using the app. The device reads the QR code using the smartphone's camera and analyzes the data.

[1243] Input: QR code image data

[1244] Data processing: Extracting price information and expiration date from QR codes.

[1245] Specific operation: When a user scans an electronic gift ticket worth 500 yen, the terminal analyzes the QR code and extracts the amount "500 yen" and the expiration date "December 31, 2023".

[1246] Output: Extracted amount information and expiration date

[1247] Step 4: Save ticket data

[1248] The terminal sends the analyzed ticket data to the server and associates it with the user ID. The server stores the received ticket data in a database.

[1249] Input: Amount information, expiration date, user ID

[1250] Data processing: Ticket data is linked to user information and saved.

[1251] Specific operation: The terminal sends the analysis results, and the server associates the user ID "12345" with a "ticket worth 500 yen" and saves it in the database.

[1252] Output: Database update status

[1253] Step 5: Presenting the questionnaire

[1254] The device displays a personalized survey based on the user's preferences. The survey includes questions about the type of beverage, sweetness level, size, and other factors.

[1255] Input: None (User interaction)

[1256] Specific actions: The device displays a questionnaire to "Taro Tanaka." The questionnaire includes questions such as: "Type of drink (coffee, tea, frappuccino)", "Sweetness level (not sweet, normal, sweet)", and "Size (short, tall, grande)".

[1257] Output: Survey screen

[1258] Step 6: Collecting survey responses

[1259] The user answers the displayed questionnaire and sends their selections to the server via their device.

[1260] Input: User survey responses

[1261] Data processing: Formatting and sending of survey response data.

[1262] Specific operation: The user selects "Frappuccino," "Sweet," and "Grande," and submits their response. The device sends the selection data to the server.

[1263] Output: User response data

[1264] Step 7: Product Selection

[1265] The server uses an algorithm to select the most suitable product based on the received survey responses, past purchase history, and the value information of the electronic gift certificate.

[1266] Input: Survey response data, purchase history data, ticket price information

[1267] Data processing: Input each data point into an algorithm to select the optimal product.

[1268] Specific operation: Based on the survey results "Frappuccino," "Sweet," and "Grande," as well as purchase history, the server recommends "Caramel Frappuccino (Grande)."

[1269] Output: Recommended product data

[1270] Step 8: Display product details

[1271] The device displays detailed information about the products suggested to the user. This information includes the product name, price, calories, and options.

[1272] Input: Recommended product data

[1273] Specific action: The device displays an image and price information for "Caramel Frappuccino (Grande)" to "Taro Tanaka".

[1274] Output: Product Information Screen

[1275] Step 9: User Approval

[1276] The user selects the items they wish to purchase from the displayed products and presses the confirm button. The device then sends this information to the server.

[1277] Input: User's selection information

[1278] Data processing: Send user selection information to the server.

[1279] Specific action: The user selects "Caramel Frappuccino (Grande)" and presses the confirm button. The device sends the selection information to the server.

[1280] Output: User approval data

[1281] Step 10: Generate and display the barcode

[1282] The server completes the user's purchase process, generates a barcode usable in the store, and sends it to the terminal. The terminal displays the generated barcode to the user.

[1283] Input: User approval data

[1284] Data processing: Barcode generation and transmission

[1285] Specific operation: The server completes the purchase process, generates a barcode, and sends it to the terminal. The terminal displays the barcode on "Taro Tanaka".

[1286] Output: Barcode display

[1287] Step 11: Update Purchase History

[1288] The server stores the user's purchase history in a database and uses it to make recommendations for future purchases.

[1289] Input: User approval data, purchased product data

[1290] Data processing: Updating and saving purchase history

[1291] Specific action: The server adds "Caramel Frappuccino (Grande)" to "Taro Tanaka's" purchase history and saves it to the database.

[1292] Output: Updated purchase history

[1293] Through the steps described above, the system of the present invention enables users to efficiently utilize electronic gift tickets and receive personalized product recommendations.

[1294] (Application Example 1)

[1295] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1296] Traditional electronic gift ticket-based product purchase systems have the problem of not being able to fully utilize user preferences and past purchase history, making it difficult to recommend products that are optimal for individual users. Furthermore, there is a lack of mechanisms to allow users to complete purchases directly using electronic payment services and use them quickly at stores. This results in a degraded user experience and a cumbersome process.

[1297] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1298] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for saving the user's purchase history and using it for future suggestions, and means for completing the purchase using an electronic payment service, generating a barcode, and displaying it on the user's terminal. As a result, the user can efficiently select products that suit their preferences and enjoy the convenience of purchasing and paying using electronic gift tickets.

[1299] "User information" refers to information such as the user's name, contact information, preferences, and purchase history.

[1300] An "electronic gift ticket" is a gift certificate issued electronically, provided in a format that includes a QR code or serial number.

[1301] A "survey" is a tool used to ask questions about a user's preferences and collect their responses.

[1302] "Product suggestion" refers to the act of selecting and presenting the most suitable product based on the user's preferences and the value of the electronic gift certificate.

[1303] "Electronic payment services" refer to services that conduct financial transactions via the internet, and include the use of electronic gift tickets.

[1304] A "barcode" is a machine-readable code generated to prove the purchase of a product.

[1305] "Purchase history" refers to data that includes information such as the products a user has purchased in the past and the date and time of those purchases.

[1306] A "server" refers to a computer system that manages user information and electronic gift ticket information, and processes various procedures.

[1307] A "user terminal" refers to a device operated by the user, such as a smartphone or tablet.

[1308] System program

[1309] The system implementing this application includes programs for registering user information, reading electronic gift tickets, presenting questionnaires, suggesting products, completing electronic payments, generating and displaying barcodes, and saving purchase history. The programs are implemented using Python and run as a web application using Flask.

[1310] Program Processing Description

[1311] The system uses the following hardware and software:

[1312] Hardware:

[1313] Server: A computer system that performs data processing and storage.

[1314] User device: A mobile device such as a smartphone or tablet.

[1315] software:

[1316] Python: A programming language used for implementing programs.

[1317] Flask: A web application framework.

[1318] qrcode: A library for generating QR codes.

[1319] 1. User information registration:

[1320] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database.

[1321] 2. Electronic gift ticket reading:

[1322] The user's device uses its camera to scan the QR code on the electronic gift ticket. The scanned data is sent to a server for analysis.

[1323] 3. Presenting the questionnaire:

[1324] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server.

[1325] 4. Product suggestion:

[1326] The server uses an algorithm to select the most suitable product based on the user's survey results and past purchase history, and then sends that information to the user's terminal.

[1327] 5. Electronic payment completion and barcode generation:

[1328] Once the user approves the suggested product, the server completes the electronic payment, generates a barcode, and displays it on the user's device.

[1329] 6. Save purchase history:

[1330] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[1331] Specific example

[1332] As a concrete example, this system can be implemented using the following prompt statement:

[1333] Example of a prompt:

[1334] User information:

[1335] Name: Taro Tanaka

[1336] Email: taro.tanaka@example.com

[1337] Preferences: Frappuccino, sweet, grande

[1338] Electronic gift tickets:

[1339] Amount: 500 yen

[1340] Expiration Date: 2024-12-31

[1341] Based on the following information, this system will suggest the most suitable product to the user and complete the electronic payment. For example, if Taro Tanaka answers "Frappuccino," "Sweet," and "Grande," the system will suggest "Caramel Frappuccino (Grande)." After that, the electronic payment will be completed and a barcode will be displayed on Taro Tanaka's smartphone.

[1342] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1343] Step 1:

[1344] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database. Specifically, it receives information entered by the user through the application screen and writes it to the database in the appropriate format. At this time, a user ID is generated and stored along with other related information.

[1345] Input: User information (name, contact information, preferences, past purchase history)

[1346] Data processing: Converting user information into an appropriate format.

[1347] Output: User information stored in the database

[1348] Step 2:

[1349] The user's device uses its camera to scan the QR code on the electronic gift ticket. The data read from the QR code is sent to the server. The server analyzes this data, extracts information such as the ticket's value and expiration date, and stores it in association with the user's information.

[1350] Input: QR code data

[1351] Data processing: Analyze QR code data to extract ticket information.

[1352] Output: Ticket information saved in association with user information

[1353] Step 3:

[1354] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server. The questionnaire questions are based on the user's preferences, such as the type of beverage, sweetness level, and size.

[1355] Input: User survey responses

[1356] Data processing: Converting user responses into structured data.

[1357] Output: Survey response data sent to the server

[1358] Step 4:

[1359] The server uses an algorithm to select the most suitable product based on user survey results and past purchase history. This algorithm considers user preferences, electronic gift certificate value information, and past purchase history to suggest the optimal product.

[1360] Input: Survey response data, past purchase history, electronic gift ticket information

[1361] Data processing: Algorithmic product selection process

[1362] Output: Optimal product suggestion information

[1363] Step 5:

[1364] The user terminal displays product suggestion information received from the server. The user reviews and approves the suggested products. The approval information is sent to the server.

[1365] Input: Product proposal information

[1366] Data processing: Converting product information to a display format.

[1367] Output: User approval information

[1368] Step 6:

[1369] The server receives authorization information from the user and completes the electronic payment. Once the payment is complete, the server generates a barcode and sends it to the user's terminal in a format usable at the store.

[1370] Input: User authorization information

[1371] Data processing: Electronic payment processing, barcode generation

[1372] Output: Barcode sent to the user terminal

[1373] Step 7:

[1374] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[1375] Input: New purchase information

[1376] Data processing: Storage and structuring of purchase information

[1377] Output: Purchase history stored in the database

[1378] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1379] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present and receive questionnaires, suggest products based on the user's preferences, the value of the electronic gift ticket, and emotion recognition by an emotion engine, and approve the products selected by the user. It also includes a function to save the user's purchase history and utilize it for future suggestions.

[1380] System Configuration

[1381] 1. User Information Registration Module

[1382] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database.

[1383] 2. Electronic gift ticket reading module

[1384] The device has the function of reading electronic gift tickets received by the user. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[1385] The server receives the read ticket data, associates it with user information, and stores it in the database.

[1386] 3. Questionnaire Presentation Module

[1387] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[1388] The emotion engine can analyze the user's facial expressions and tone of voice, and adjust the survey content based on the results.

[1389] Users answer a survey and send their answers to the server via their device.

[1390] 4. Product Proposal Module

[1391] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotional data generated by an emotion engine.

[1392] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1393] The device displays detailed information about the products suggested to the user.

[1394] Specific example

[1395] 1. User Information Registration

[1396] Users register through the app or website. For example, they enter their name, email address, and interests.

[1397] The server saves the entered information to the database and generates a user ID.

[1398] 2. Electronic gift ticket reading

[1399] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[1400] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[1401] The server stores ticket data, associating it with user information.

[1402] 3. Presenting the questionnaire

[1403] The device displays personalized surveys to the user.

[1404] The emotion engine uses facial recognition and voice analysis to adjust the displayed survey questions according to the user's emotional state. For example, the questions might change to something like, "You seem a little tired. Would you like to refresh yourself?"

[1405] Users answer a survey and send their answers to the server via their device.

[1406] 4. Product proposal

[1407] Based on survey results, past purchase history, electronic gift ticket value information, and sentiment data obtained from the sentiment engine, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product.

[1408] The server generates detailed information about the product and sends it to the terminal.

[1409] The device displays an image and detailed information about "Caramel Frappuccino (Grande)" to the user.

[1410] 5. User Approval

[1411] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[1412] The terminal sends the user's selection to the server.

[1413] The server generates a barcode and sends it to the terminal in a format that can be used in Starbucks stores.

[1414] The terminal displays a barcode to the user.

[1415] 6. Save purchase history

[1416] The server can store the user's purchase history and sentiment data in a database, which can then be used to improve future recommendations. This makes it possible to provide even more personalized product suggestions.

[1417] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[1418] The following describes the processing flow.

[1419] Step 1:

[1420] Users enter their name, email address, and preferences into a new registration form via the app or website.

[1421] Step 2:

[1422] The terminal sends the entered information to the server.

[1423] Step 3:

[1424] The server stores the received user information in a database, generates a user ID, and notifies the user.

[1425] Step 4:

[1426] Users scan the electronic gift ticket they received via LINE Gift using the QR code scanning function within the app.

[1427] Step 5:

[1428] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[1429] Step 6:

[1430] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[1431] Step 7:

[1432] The server generates personalized survey questions based on the user's past purchase history.

[1433] Step 8:

[1434] The terminal displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[1435] Step 9:

[1436] The emotion engine uses facial recognition and voice analysis to evaluate the user's emotions in real time. Based on this evaluation, it adjusts the survey questions. For example, it might change the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[1437] Step 10:

[1438] Users answer a survey and send their answers to the server via their device.

[1439] Step 11:

[1440] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotion engine evaluation data.

[1441] Step 12:

[1442] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1443] Step 13:

[1444] The device displays detailed information about the product suggested to the user. For example, it displays an image and description of a "Caramel Frappuccino (Grande)".

[1445] Step 14:

[1446] The user selects one product from the suggested options and presses the approve button.

[1447] Step 15:

[1448] The terminal sends the user's selection to the server.

[1449] Step 16:

[1450] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[1451] Step 17:

[1452] The server sends the generated barcode to the terminal.

[1453] Step 18:

[1454] The terminal displays a barcode to the user.

[1455] Step 19:

[1456] The server saves the user's purchase history and sentiment data to a database along with a thank-you message, and uses this data to make future suggestions.

[1457] Step 20:

[1458] The emotion engine analyzes emotional data throughout the user's entire experience and provides feedback data for further personalization.

[1459] (Example 2)

[1460] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1461] In conventional systems, when users purchase products using electronic gift tickets, personalized product suggestions that take into account the user's preferences and emotional state are not provided, which often leads to lower user satisfaction. Furthermore, there is no mechanism to dynamically adjust survey content and product suggestions using user emotional data, resulting in a challenge in accurately responding to user needs.

[1462] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving a response, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and emotional data from an emotional engine, means for the user to select and approve the suggested products, and means for saving the user's purchase history and emotional data and utilizing them for future suggestions. This makes it possible to make personalized product suggestions based on the user's preferences and emotional state, thereby improving user satisfaction.

[1463] "User information" refers to individual information about a user, such as their name, email address, preferences, purchase history, and sentiment data.

[1464] An "electronic gift ticket" is a ticket issued in electronic format that can be exchanged for goods or services based on a specific amount or expiration date.

[1465] A "survey" is a series of questions presented to a user, used to understand their preferences and needs.

[1466] An "emotion engine" is a technological system that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[1467] "Product suggestion" is the process of presenting products suitable for the user based on the user's preferences, the value information of the electronic gift certificate, and sentiment data.

[1468] "Purchase history" refers to a record of products a user has purchased in the past, and this information is stored to be used for future recommendations.

[1469] A "personalized survey" is a survey that is individually tailored based on a user's past purchase history and sentiment data.

[1470] The "optimal product" is a product selected by an algorithm that comprehensively considers user preferences, the value information of the electronic gift certificate, and emotional data.

[1471] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present questionnaires, and receive responses. Furthermore, it has a function to suggest products based on the user's preferences, the amount of the electronic gift ticket, and emotion recognition by an emotion engine, and to approve the products selected by the user. It also has a function to save the user's purchase history and utilize it for future suggestions.

[1472] System configuration and details

[1473] 1. User Information Registration Module

[1474] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database. This step uses a database management system such as MySQL or PostgreSQL.

[1475] For example, a user registers through an app or website, entering their name, email address, and preferences. The server stores this information in a database and generates a user ID.

[1476] 2. Electronic gift ticket reading module

[1477] The device has the functionality to read electronic gift tickets received by the user. It analyzes the QR code and serial number to extract the ticket's value and expiration date. This is done using QR code reading libraries such as ZBar and ZXing.

[1478] For example, a user scans a 500 yen Starbucks ticket received via LINE Gift within the app. The device reads the QR code and sends the ticket data to the server.

[1479] 3. Questionnaire Presentation Module

[1480] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[1481] The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the survey content based on the results. For example, if it determines that the user is tired, it changes the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[1482] For example, a user answers a survey and sends their answers to a server via their device.

[1483] 4. Product Proposal Module

[1484] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data generated by an emotion engine. This process utilizes machine learning models and recommendation engines such as TensorFlow and Scikit-Learn.

[1485] For example, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product and sends its detailed information to the terminal. The terminal then displays this information to the user.

[1486] 5. User Approval Module

[1487] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[1488] The terminal sends the user's selection to the server. The server generates a barcode and sends it to the terminal. The user can use this barcode to purchase products in the store.

[1489] 6. Purchase history storage module

[1490] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations. This will enable even more personalized product suggestions.

[1491] Examples of specific cases and prompt statements

[1492] Specific example:

[1493] For example, the terminal displays the question, "You seem a little tired. Would you like to refresh yourself?" and the user replies that they would like to refresh themselves. Based on this, the server suggests a "Caramel Frappuccino (Grande)," and if the user selects it, a barcode is generated that can be used in the store.

[1494] Example of a prompt:

[1495] Please describe a system that allows users to register new user information, scan electronic gift tickets, answer questionnaires, and receive product recommendations. In particular, please explain in detail how the emotion engine adjusts the displayed questionnaire content.

[1496] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[1497] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1498] Program processing flow

[1499] Step 1: Register User Information

[1500] 1.1 Input: The user enters their name, email address, preferences, purchase history, and sentiment data.

[1501] Specific operation: The user launches the app from their smartphone or PC and enters information into the input form.

[1502] Output: The entered user information is sent to the server.

[1503] 1.2 Data Processing and Calculation: The server applies a data format to the user information it receives in order to register it in the database.

[1504] Specific operation: The server saves the data received in the HTTP request to a database management system (e.g., MySQL, PostgreSQL).

[1505] Output: User information stored in the database.

[1506] Step 2: Read the electronic gift ticket

[1507] 2.1 Input: The user scans the electronic gift ticket (QR code or serial number).

[1508] Specific operation: The user uses the camera on their smartphone app to scan the electronic gift ticket.

[1509] 2.2 Data Processing and Calculation: The terminal analyzes the QR code or serial number and extracts the ticket price and expiration date.

[1510] Specific operation: The device analyzes the data using QR code reading software (e.g., ZBar, ZXing).

[1511] Output: Extracted ticket information.

[1512] 2.3 Input: The extracted ticket information is sent to the server.

[1513] Specific action: The terminal sends the analyzed ticket information to the server.

[1514] Output: Ticket information sent to the server.

[1515] 2.4 Data Processing and Calculation: The server stores the received ticket information in the database, associating it with user information.

[1516] Specific operation: The server links the received ticket information with the user ID and saves it to the database.

[1517] Output: Ticket information stored in the database.

[1518] Step 3: Presenting the questionnaire

[1519] 3.1 Input: The server obtains the data necessary to provide users with personalized surveys (preferences, past purchase history, sentiment data).

[1520] Specific operation: The server retrieves user preferences, purchase history, and sentiment data from the database.

[1521] 3.2 Data Processing and Calculation: The server generates survey questions based on the acquired data.

[1522] Specific operation: The server generates survey questions using an algorithm and adjusts them based on sentiment data.

[1523] Output: Personalized survey.

[1524] 3.3 Input: The generated questionnaire is sent to the device.

[1525] Specific operation: The server sends the survey data to the terminal.

[1526] Output: The survey content displayed on the device.

[1527] 3.4 Input: The user answers the survey.

[1528] Specific action: The user enters their answers into the survey form and presses the submit button.

[1529] 3.5 Data Processing and Calculation: The terminal sends the user's survey responses to the server.

[1530] Specific action: The device sends the response data to the server.

[1531] Output: Survey responses sent to the server.

[1532] Step 4: Product Proposal

[1533] 4.1 Input: The server receives survey responses, purchase history, electronic gift certificate amount information, and sentiment data.

[1534] Specific operation: The server receives the user's survey responses and related data.

[1535] 4.2 Data Processing and Calculation: The server uses an algorithm to select the optimal product.

[1536] Specific operation: The server uses machine learning models and recommendation engines (e.g., TensorFlow, Scikit-Learn) to select the most suitable products.

[1537] Output: Detailed information on the selected products.

[1538] 4.3 Input: Detailed information about the selected product is sent to the terminal.

[1539] Specific operation: The server sends detailed product information to the terminal.

[1540] Output: Product information displayed on the terminal.

[1541] Step 5: User Approval

[1542] 5.1 Input: The user selects and approves the suggested product.

[1543] Specific actions: The user clicks the "Select Product" button and then clicks the "Approve" button.

[1544] 5.2 Data Processing and Calculation: The terminal sends the user's selected data to the server.

[1545] Specific operation: The terminal sends the selected data to the server as an HTTP request.

[1546] Output: Selected data sent to the server.

[1547] 5.3 Data Processing and Calculation: The server generates a barcode and sends it to the terminal.

[1548] Specific operation: The server generates barcodes using a barcode generation library (e.g., Barcode4J, ZXing).

[1549] Output: The generated barcode.

[1550] 5.4 Input: The generated barcode is sent to the terminal.

[1551] Specific operation: The server sends barcode data to the terminal.

[1552] Output: The barcode displayed on the terminal.

[1553] Step 6: Saving Purchase History

[1554] 6.1 Input: The server receives the user's purchase history and sentiment data.

[1555] Specific operation: The server receives purchase history and sentiment data.

[1556] 6.2 Data Processing and Calculation: The server saves the received data to a database and uses it for future proposals.

[1557] Specific operation: The server stores purchase history data and sentiment data in a database.

[1558] Output: Purchase history and sentiment data stored in the database.

[1559] (Application Example 2)

[1560] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1561] In today's world, when users use electronic gift tickets to purchase products that match their preferences and emotions, it is difficult to provide personalized recommendations. This can lead to wasted time and a poor purchasing experience. Furthermore, existing systems do not consider the user's emotional state when making product recommendations, thus failing to increase user satisfaction.

[1562] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1563] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and the emotion recognition results, means for the user to select and approve the suggested products, means for saving the user's purchase history and emotion data and using them for future suggestions, and means for suggesting products using a generation AI model based on the generated prompt text. As a result, the user can efficiently select and purchase products that match their preferences and emotions, thereby realizing a highly satisfying shopping experience.

[1564] "Means for registering user information" refers to a function for registering information such as the user's name, email address, preferences, purchase history, and sentiment data on the server.

[1565] "Methods for reading electronic gift tickets" refer to functions that analyze QR codes or serial numbers to extract the ticket's value and expiration date.

[1566] "A means of presenting a survey to a user and receiving their response" refers to a function that displays a personalized survey to a user and receives their response.

[1567] "A means of suggesting products based on user preferences, electronic gift ticket value information, and emotion recognition results" refers to a function that uses user survey results, past purchase history, electronic gift ticket value information, and emotion data from an emotion engine to algorithmically select and suggest the most suitable products.

[1568] "A means for users to select and approve suggested products" refers to a function that allows users to review detailed information about suggested products, select them, and approve their purchase.

[1569] "Means for saving users' purchase history and sentiment data and using them for future recommendations" refers to a function that saves users' purchase history and sentiment data in a database and uses it to make personalized product recommendations for future purchases.

[1570] "A means of suggesting products using a generative AI model based on generated prompt sentences" refers to a function that generates prompt sentences according to the user's situation and suggests the most suitable product using a generative AI model (e.g., GPT-3 or GPT-4).

[1571] The system implementing the present invention is designed to perform a series of steps, from user information registration and reading of electronic gift tickets to presenting and receiving responses to questionnaires, product suggestions, user product approval, saving of purchase history, and product suggestions using a generative AI model. The specific operation method is described below.

[1572] The system consists of the following elements:

[1573] 1. User Information Registration Module

[1574] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in the database. This module is responsible for saving information entered by the user through the app or website when they start using the application to the database.

[1575] 2. Electronic gift ticket reading module

[1576] The terminal has the function of reading electronic gift tickets received by the user. When the user scans a QR code or serial number, the terminal analyzes the information and sends it to the server. The server stores the received ticket data in a database, associating it with the user's information.

[1577] 3. Questionnaire Presentation Module

[1578] The device displays personalized surveys to the user. The survey questions are generated based on the user's preferences and past purchase history. An emotion engine performs facial recognition and voice analysis of the user, adjusting the survey content based on the results. For example, it could display a question such as, "You seem a little tired. Would you like to refresh yourself?"

[1579] 4. Product Proposal Module

[1580] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data from the sentiment engine. This process uses a generative AI model to suggest products based on prompt messages. The generated prompt messages are in the following format:

[1581] You have received an electronic gift certificate worth 500 yen. The user says they want coffee. Facial analysis suggests they are a little tired. Please suggest a refreshing drink.

[1582] Based on the results of this AI model, the server selects the most suitable product, generates detailed information about that product, and sends it to the terminal.

[1583] 5. User Approval Module

[1584] The terminal displays detailed information about the products suggested to the user. The user reviews the information, selects a product, and presses the approve button, at which point the information is sent to the server. The server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays the barcode to the user, enabling its use in physical stores.

[1585] 6. Purchase history storage module

[1586] The server stores the user's purchase history and sentiment data in a database. This data is used to personalize product recommendations for future purchases.

[1587] By combining these elements, the present invention realizes a system that allows users to easily purchase products that match their preferences and emotions using electronic gift tickets. This system enables users to enjoy a more satisfying and personalized purchasing experience.

[1588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1589] Step 1:

[1590] Users register through the app or website.

[1591] Input: Information such as the user's name, email address, and preferences entered in the app or website.

[1592] Data processing and calculation: The terminal sends input information to the server, which receives the information and stores it in the database. It also generates a user ID.

[1593] Output: Registration success notification and generation of a unique user ID.

[1594] Specific operation: The server stores the registered information in a database, generates a user ID, and notifies the terminal.

[1595] Step 2:

[1596] The user scans the electronic gift ticket received within the app.

[1597] Input: Scanned image of a QR code or serial number.

[1598] Data processing and calculation: The terminal analyzes QR codes and serial numbers to extract ticket price information and expiration dates. The results are sent to the server.

[1599] Output: Analyzed ticket data.

[1600] Specific operation: The terminal reads the code using a barcode reader or OpenCV, the server stores that information in a database, and associates it with user information.

[1601] Step 3:

[1602] The device displays personalized surveys to the user.

[1603] Input: Past purchase history, user preference data, sentiment recognition data.

[1604] Data processing and calculation: The server generates survey content based on this data and sends it to the terminal. The terminal uses an emotion engine to perform facial recognition and voice analysis of the user and adaptively adjust the survey.

[1605] Output: Personalized survey.

[1606] Specific operation: The terminal displays the survey content to the user, and the user answers it. The answers are then sent back to the server.

[1607] Step 4:

[1608] The server suggests the most suitable product based on survey results, past purchase history, electronic gift certificate value information, and emotion recognition results.

[1609] Inputs: Survey results, past purchase history, electronic gift certificate amount information, sentiment data.

[1610] Data processing and calculation: The server processes this data using algorithms to select the optimal product. It also generates product suggestions based on prompt text using a generative AI model.

[1611] Output: Suggestions for the most suitable products.

[1612] Specific operation: The server uses the generated prompt message (e.g., "You have received an electronic gift ticket worth 500 yen. The user says they want coffee. Facial analysis results indicate they are a little tired. Please suggest a refreshing drink.") to make product suggestions and send the results to the terminal.

[1613] Step 5:

[1614] The user reviews the details of the suggested products, selects a product, and approves it.

[1615] Input: Product information displayed on the terminal.

[1616] Data processing and calculation: User selection information is sent from the terminal to the server, which then records it.

[1617] Output: User selection and approval of products.

[1618] Specific operation: When the user selects an item and presses the approval button, the server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays this barcode to the user, enabling its use in physical stores.

[1619] Step 6:

[1620] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations.

[1621] Input: User purchase information and sentiment data.

[1622] Data processing and calculations: The server stores this data in a database and uses it for personalized suggestions in the future.

[1623] Output: Saved purchase history and sentiment data.

[1624] Specific operation: The server stores purchase history and sentiment data, and retains it in a database in a format that can be used for future product recommendations.

[1625] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1626] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1627] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1628] [Fourth Embodiment]

[1629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1630] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1631] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1632] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1633] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1634] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1635] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1636] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1637] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1638] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1639] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1640] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1641] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1642] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The system has the function of registering user information and reading electronic gift tickets. It also has the function of presenting the user with a questionnaire, receiving responses, suggesting the most suitable products based on the responses, and approving the products selected by the user. Furthermore, it has the function of saving the user's purchase history and using it for future suggestions.

[1643] System Configuration

[1644] 1. User Information Registration Module

[1645] The server receives information such as the user's name, email address, preferences, and purchase history, and registers it in the database.

[1646] 2. Electronic gift ticket reading module

[1647] The device has the function of allowing users to read electronic gift tickets such as LINE Gifts. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[1648] The server receives the read ticket data, associates it with user information, and stores it in the database.

[1649] 3. Questionnaire Presentation Module

[1650] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[1651] Users answer a survey and send their answers to the server via their device.

[1652] 4. Product Proposal Module

[1653] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[1654] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1655] The device displays detailed information about the products suggested to the user.

[1656] Specific example

[1657] 1. User Information Registration

[1658] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name and email address.

[1659] The server saves the entered information to the database and generates a user ID.

[1660] 2. Electronic gift ticket reading

[1661] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[1662] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[1663] The server stores ticket data, associating it with user information.

[1664] 3. Presenting the questionnaire

[1665] The device displays a survey for "Taro Tanaka".

[1666] Type of beverage (e.g., coffee, tea, frappuccino)

[1667] Sweetness level (e.g., not sweet, normal, sweet)

[1668] Size (e.g., Short, Tall, Grande)

[1669] The user selects "Frappuccino," "Sweet," and "Grande," and then submits their response.

[1670] 4. Product proposal

[1671] The server considers the survey results and past purchase history to select "Caramel Frappuccino (Grande)" as the most suitable product.

[1672] The server generates detailed information about the product and sends it to the terminal.

[1673] The terminal displays an image and price information for "Caramel Frappuccino (Grande)" for "Taro Tanaka".

[1674] 5. User Approval

[1675] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[1676] The terminal sends the user's selection to the server.

[1677] The server generates a barcode and sends it to the terminal in a format usable by the store.

[1678] The terminal displays the barcode as "Taro Tanaka".

[1679] 6. Save purchase history

[1680] The server updates "Taro Tanaka's" purchase history and saves it to the database. From then on, personalized product suggestions will be provided based on this purchase history.

[1681] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their preferences.

[1682] The following describes the processing flow.

[1683] Step 1:

[1684] Users enter necessary information such as their name and email address into a new registration form via the app or website.

[1685] Step 2:

[1686] The terminal sends the entered information to the server.

[1687] Step 3:

[1688] The server stores the received user information in a database, generates a user ID, and notifies the user.

[1689] Step 4:

[1690] The user scans the Starbucks ticket received via LINE Gift using the QR code scanning function within the app.

[1691] Step 5:

[1692] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[1693] Step 6:

[1694] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[1695] Step 7:

[1696] The server generates personalized survey questions based on the user's past purchase history.

[1697] Step 8:

[1698] The device displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[1699] Step 9:

[1700] Users answer a survey and send their answers to the server via their device.

[1701] Step 10:

[1702] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value information of the electronic gift certificate.

[1703] Step 11:

[1704] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1705] Step 12:

[1706] The device displays detailed information about the products suggested to the user. For example, it might show an image and price information for a "Caramel Frappuccino (Grande)".

[1707] Step 13:

[1708] The user selects one product from the suggested options and presses the approve button.

[1709] Step 14:

[1710] The terminal sends the user's selection to the server.

[1711] Step 15:

[1712] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[1713] Step 16:

[1714] The server sends the generated barcode to the terminal.

[1715] Step 17:

[1716] The terminal displays a barcode to the user.

[1717] Step 18:

[1718] The server stores users' purchase history and preference data in a database, which is then used to make future recommendations.

[1719] (Example 1)

[1720] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1721] Conventional systems have problems such as cumbersome product selection and insufficient product suggestions tailored to user preferences when users purchase products using electronic gift tickets. Furthermore, there is a problem that users' purchase history is not reflected in subsequent suggestions, resulting in a lack of personalized recommendations. The present invention aims to solve these problems and provide a system in which users can use electronic gift tickets efficiently and effectively.

[1722] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1723] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for displaying the generated barcode, and means for saving the user's purchase history and using it for future suggestions. This makes it possible for users to easily and efficiently purchase products that suit their preferences using electronic gift tickets.

[1724] "Means of registering user information" refers to the function of registering information such as the user's name, email address, preferences, and purchase history in a database.

[1725] "Methods for reading electronic gift tickets" refers to functions that analyze QR codes or serial numbers to extract the amount and expiration date of electronic gift tickets.

[1726] "A means of presenting a survey to a user and receiving their response" refers to a function that displays questions about the user's preferences and purchase intentions and obtains their response.

[1727] "A method for suggesting products based on user preferences and electronic gift ticket value information" refers to a function that selects the most suitable product based on user responses and existing data, and then suggests it to the user.

[1728] "A means for users to select and approve suggested products" refers to a function that allows users to select from the presented products and perform actions to confirm their purchase.

[1729] "Means for displaying generated barcodes" refers to a function that generates barcodes for use by the user in stores and displays them on the user's device.

[1730] "A means of saving a user's purchase history and using it for future recommendations" refers to a function that saves data on products purchased by the user in a database and uses that data to make future recommendations.

[1731] This invention provides a system for users to purchase products that suit their preferences using electronic gift tickets. The following describes a specific system configuration and operating procedure for carrying out the invention.

[1732] System Configuration

[1733] The system mainly consists of the following hardware and software.

[1734] server

[1735] Database server: MySQL, PostgreSQL, etc.

[1736] Application server: Apache Tomcat, Node.js, etc.

[1737] Algorithmic processing: Python scripts and machine learning models

[1738] terminal

[1739] Smartphones and tablets: iOS, Android devices

[1740] QR code reader: Uses a smartphone camera and a dedicated app.

[1741] User

[1742] General user: A user of the system

[1743] User Information Registration

[1744] Users register through the app or website. For example, a user named "Taro Tanaka" enters their name, email address, and preferences (e.g., likes coffee, dislikes tea). The device sends this information to the server, which stores it in a database. At this time, the server generates a new user ID.

[1745] Electronic gift ticket reading

[1746] Users scan electronic gift tickets received from LINE Gift or other platforms using the app. The device uses the smartphone's camera to read the QR code or serial number and sends the data to the server. The server analyzes the received ticket data, extracts monetary information, and associates it with user information.

[1747] Presenting a questionnaire and obtaining responses.

[1748] The device displays a personalized questionnaire to the user. The questionnaire includes questions such as the type of beverage (coffee, tea, frappuccino), sweetness level (not sweet, normal, sweet), and size (short, tall, grande). The user answers the questionnaire and sends their answers to the server via the device.

[1749] Product proposals

[1750] The server uses an algorithm to select the most suitable product based on the user's survey results, past purchase history, and the value of the electronic gift certificate. For example, if the user selects "Frappuccino," "Sweet," and "Grande," the server will recommend "Caramel Frappuccino (Grande)." The server sends the generated product details to the terminal, which then displays that information to the user.

[1751] User authorization and barcode display

[1752] The user selects items to purchase from the suggested products and presses the approve button. The terminal sends this information to the server. After the server completes the purchase process, it generates a barcode that can be used in the store and sends it to the terminal. The terminal displays the generated barcode to the user.

[1753] Saving purchase history and using it for future proposals.

[1754] The server stores information about the products the user has purchased in a database and updates the purchase history. This history is then used to improve future recommendations. For example, if a user purchases a "Caramel Frappuccino (Grande)," that information will be reflected in future recommendations, allowing for more accurate suggestions tailored to the user's preferences.

[1755] Specific example

[1756] Examples of prompt statements are as follows:

[1757] Registration screen: "Please enter your name."

[1758] Electronic gift ticket scanning screen: "Please scan the QR code on the gift ticket."

[1759] Survey screen:

[1760] Drink options: "Please choose from coffee, tea, or frappuccino."

[1761] Sweetness level: "Please choose from Not Sweet, Normal, or Sweet."

[1762] Size: "Please choose from Short, Tall, or Grande."

[1763] This concludes the detailed description of how the present invention can be implemented. By using this system, users can efficiently and effectively utilize electronic gift tickets and obtain a more personalized purchasing experience.

[1764] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1765] Step 1: User Information Registration

[1766] Users open the new registration screen on the app or website and enter their name, email address, preferences, etc. The entered data is sent to the device in the following format.

[1767] Input: User's name, email address, and preferences

[1768] Specific operation: The user enters the name "Taro Tanaka," the email address "tanaka@example.com," and their preferences as "Likes coffee, dislikes tea."

[1769] The terminal organizes this data and sends it to the server in the following format.

[1770] Output: Registration data (name, email address, preferences)

[1771] Step 2: Saving User Information

[1772] The server stores the received user information in the database server and generates a user ID. This user ID is used in subsequent processing and is linked to the user information.

[1773] Input: Registration data (name, email address, preferences)

[1774] Data processing: Create a new entry in the database and save each item.

[1775] Specific operation: The server saves information about "Taro Tanaka" to the MySQL database and generates user ID "12345".

[1776] Output: User ID

[1777] Step 3: Scan the e-gift ticket

[1778] The user scans the QR code of the electronic gift ticket received via LINE Gift using the app. The device reads the QR code using the smartphone's camera and analyzes the data.

[1779] Input: QR code image data

[1780] Data processing: Extracting price information and expiration date from QR codes.

[1781] Specific operation: When a user scans an electronic gift ticket worth 500 yen, the terminal analyzes the QR code and extracts the amount "500 yen" and the expiration date "December 31, 2023".

[1782] Output: Extracted amount information and expiration date

[1783] Step 4: Save ticket data

[1784] The terminal sends the analyzed ticket data to the server and associates it with the user ID. The server stores the received ticket data in a database.

[1785] Input: Amount information, expiration date, user ID

[1786] Data processing: Ticket data is linked to user information and saved.

[1787] Specific operation: The terminal sends the analysis results, and the server associates the user ID "12345" with a "ticket worth 500 yen" and saves it in the database.

[1788] Output: Database update status

[1789] Step 5: Presenting the questionnaire

[1790] The device displays a personalized survey based on the user's preferences. The survey includes questions about the type of beverage, sweetness level, size, and other factors.

[1791] Input: None (User interaction)

[1792] Specific actions: The device displays a questionnaire to "Taro Tanaka." The questionnaire includes questions such as: "Type of drink (coffee, tea, frappuccino)", "Sweetness level (not sweet, normal, sweet)", and "Size (short, tall, grande)".

[1793] Output: Survey screen

[1794] Step 6: Collecting survey responses

[1795] The user answers the displayed questionnaire and sends their selections to the server via their device.

[1796] Input: User survey responses

[1797] Data processing: Formatting and sending of survey response data.

[1798] Specific operation: The user selects "Frappuccino," "Sweet," and "Grande," and submits their response. The device sends the selection data to the server.

[1799] Output: User response data

[1800] Step 7: Product Selection

[1801] The server uses an algorithm to select the most suitable product based on the received survey responses, past purchase history, and the value information of the electronic gift certificate.

[1802] Input: Survey response data, purchase history data, ticket price information

[1803] Data processing: Input each data point into an algorithm to select the optimal product.

[1804] Specific operation: Based on the survey results "Frappuccino," "Sweet," and "Grande," as well as purchase history, the server recommends "Caramel Frappuccino (Grande)."

[1805] Output: Recommended product data

[1806] Step 8: Display product details

[1807] The device displays detailed information about the products suggested to the user. This information includes the product name, price, calories, and options.

[1808] Input: Recommended product data

[1809] Specific action: The device displays an image and price information for "Caramel Frappuccino (Grande)" to "Taro Tanaka".

[1810] Output: Product Information Screen

[1811] Step 9: User Approval

[1812] The user selects the items they wish to purchase from the displayed products and presses the confirm button. The device then sends this information to the server.

[1813] Input: User's selection information

[1814] Data processing: Send user selection information to the server.

[1815] Specific action: The user selects "Caramel Frappuccino (Grande)" and presses the confirm button. The device sends the selection information to the server.

[1816] Output: User approval data

[1817] Step 10: Generate and display the barcode

[1818] The server completes the user's purchase process, generates a barcode usable in the store, and sends it to the terminal. The terminal displays the generated barcode to the user.

[1819] Input: User approval data

[1820] Data processing: Barcode generation and transmission

[1821] Specific operation: The server completes the purchase process, generates a barcode, and sends it to the terminal. The terminal displays the barcode on "Taro Tanaka".

[1822] Output: Barcode display

[1823] Step 11: Update Purchase History

[1824] The server stores the user's purchase history in a database and uses it to make recommendations for future purchases.

[1825] Input: User approval data, purchased product data

[1826] Data processing: Updating and saving purchase history

[1827] Specific action: The server adds "Caramel Frappuccino (Grande)" to "Taro Tanaka's" purchase history and saves it to the database.

[1828] Output: Updated purchase history

[1829] Through the steps described above, the system of the present invention enables users to efficiently utilize electronic gift tickets and receive personalized product recommendations.

[1830] (Application Example 1)

[1831] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1832] Traditional electronic gift ticket-based product purchase systems have the problem of not being able to fully utilize user preferences and past purchase history, making it difficult to recommend products that are optimal for individual users. Furthermore, there is a lack of mechanisms to allow users to complete purchases directly using electronic payment services and use them quickly at stores. This results in a degraded user experience and a cumbersome process.

[1833] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1834] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences and the amount of the electronic gift ticket, means for the user to select and approve the suggested products, means for saving the user's purchase history and using it for future suggestions, and means for completing the purchase using an electronic payment service, generating a barcode, and displaying it on the user's terminal. As a result, the user can efficiently select products that suit their preferences and enjoy the convenience of purchasing and paying using electronic gift tickets.

[1835] "User information" refers to information such as the user's name, contact information, preferences, and purchase history.

[1836] An "electronic gift ticket" is a gift certificate issued electronically, provided in a format that includes a QR code or serial number.

[1837] A "survey" is a tool used to ask questions about a user's preferences and collect their responses.

[1838] "Product suggestion" refers to the act of selecting and presenting the most suitable product based on the user's preferences and the value of the electronic gift certificate.

[1839] "Electronic payment services" refer to services that conduct financial transactions via the internet, and include the use of electronic gift tickets.

[1840] A "barcode" is a machine-readable code generated to prove the purchase of a product.

[1841] "Purchase history" refers to data that includes information such as the products a user has purchased in the past and the date and time of those purchases.

[1842] A "server" refers to a computer system that manages user information and electronic gift ticket information, and processes various procedures.

[1843] A "user terminal" refers to a device operated by the user, such as a smartphone or tablet.

[1844] System program

[1845] The system implementing this application includes programs for registering user information, reading electronic gift tickets, presenting questionnaires, suggesting products, completing electronic payments, generating and displaying barcodes, and saving purchase history. The programs are implemented using Python and run as a web application using Flask.

[1846] Program Processing Description

[1847] The system uses the following hardware and software:

[1848] Hardware:

[1849] Server: A computer system that performs data processing and storage.

[1850] User device: A mobile device such as a smartphone or tablet.

[1851] software:

[1852] Python: A programming language used for implementing programs.

[1853] Flask: A web application framework.

[1854] qrcode: A library for generating QR codes.

[1855] 1. User information registration:

[1856] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database.

[1857] 2. Electronic gift ticket reading:

[1858] The user's device uses its camera to scan the QR code on the electronic gift ticket. The scanned data is sent to a server for analysis.

[1859] 3. Presenting the questionnaire:

[1860] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server.

[1861] 4. Product suggestion:

[1862] The server uses an algorithm to select the most suitable product based on the user's survey results and past purchase history, and then sends that information to the user's terminal.

[1863] 5. Electronic payment completion and barcode generation:

[1864] Once the user approves the suggested product, the server completes the electronic payment, generates a barcode, and displays it on the user's device.

[1865] 6. Save purchase history:

[1866] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[1867] Specific example

[1868] As a concrete example, this system can be implemented using the following prompt statement:

[1869] Example of a prompt:

[1870] User information:

[1871] Name: Taro Tanaka

[1872] Email: taro.tanaka@example.com

[1873] Preferences: Frappuccino, sweet, grande

[1874] Electronic gift tickets:

[1875] Amount: 500 yen

[1876] Expiration Date: 2024-12-31

[1877] Based on the following information, this system will suggest the most suitable product to the user and complete the electronic payment. For example, if Taro Tanaka answers "Frappuccino," "Sweet," and "Grande," the system will suggest "Caramel Frappuccino (Grande)." After that, the electronic payment will be completed and a barcode will be displayed on Taro Tanaka's smartphone.

[1878] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1879] Step 1:

[1880] The server receives information provided by the user, such as name, contact information, preferences, and past purchase history, and stores it in a database. Specifically, it receives information entered by the user through the application screen and writes it to the database in the appropriate format. At this time, a user ID is generated and stored along with other related information.

[1881] Input: User information (name, contact information, preferences, past purchase history)

[1882] Data processing: Converting user information into an appropriate format.

[1883] Output: User information stored in the database

[1884] Step 2:

[1885] The user's device uses its camera to scan the QR code on the electronic gift ticket. The data read from the QR code is sent to the server. The server analyzes this data, extracts information such as the ticket's value and expiration date, and stores it in association with the user's information.

[1886] Input: QR code data

[1887] Data processing: Analyze QR code data to extract ticket information.

[1888] Output: Ticket information saved in association with user information

[1889] Step 3:

[1890] The user terminal displays a questionnaire to the user regarding product selection and sends the responses to the server. The questionnaire questions are based on the user's preferences, such as the type of beverage, sweetness level, and size.

[1891] Input: User survey responses

[1892] Data processing: Converting user responses into structured data.

[1893] Output: Survey response data sent to the server

[1894] Step 4:

[1895] The server uses an algorithm to select the most suitable product based on user survey results and past purchase history. This algorithm considers user preferences, electronic gift certificate value information, and past purchase history to suggest the optimal product.

[1896] Input: Survey response data, past purchase history, electronic gift ticket information

[1897] Data processing: Algorithmic product selection process

[1898] Output: Optimal product suggestion information

[1899] Step 5:

[1900] The user terminal displays product suggestion information received from the server. The user reviews and approves the suggested products. The approval information is sent to the server.

[1901] Input: Product proposal information

[1902] Data processing: Converting product information to a display format.

[1903] Output: User approval information

[1904] Step 6:

[1905] The server receives authorization information from the user and completes the electronic payment. Once the payment is complete, the server generates a barcode and sends it to the user's terminal in a format usable at the store.

[1906] Input: User authorization information

[1907] Data processing: Electronic payment processing, barcode generation

[1908] Output: Barcode sent to the user terminal

[1909] Step 7:

[1910] The server stores the user's new purchase information in a database and uses it to provide personalized recommendations for future purchases.

[1911] Input: New purchase information

[1912] Data processing: Storage and structuring of purchase information

[1913] Output: Purchase history stored in the database

[1914] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1915] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present and receive questionnaires, suggest products based on the user's preferences, the value of the electronic gift ticket, and emotion recognition by an emotion engine, and approve the products selected by the user. It also includes a function to save the user's purchase history and utilize it for future suggestions.

[1916] System Configuration

[1917] 1. User Information Registration Module

[1918] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database.

[1919] 2. Electronic gift ticket reading module

[1920] The device has the function of reading electronic gift tickets received by the user. The scanned data is analyzed using QR codes and serial numbers to extract the ticket's value and expiration date.

[1921] The server receives the read ticket data, associates it with user information, and stores it in the database.

[1922] 3. Questionnaire Presentation Module

[1923] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[1924] The emotion engine can analyze the user's facial expressions and tone of voice, and adjust the survey content based on the results.

[1925] Users answer a survey and send their answers to the server via their device.

[1926] 4. Product Proposal Module

[1927] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotional data generated by an emotion engine.

[1928] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1929] The device displays detailed information about the products suggested to the user.

[1930] Specific example

[1931] 1. User Information Registration

[1932] Users register through the app or website. For example, they enter their name, email address, and interests.

[1933] The server saves the entered information to the database and generates a user ID.

[1934] 2. Electronic gift ticket reading

[1935] The user scans a 500 yen Starbucks ticket received via LINE Gift within the app.

[1936] The device reads the QR code, extracts the ticket price information, and sends it to the server.

[1937] The server stores ticket data, associating it with user information.

[1938] 3. Presenting the questionnaire

[1939] The device displays personalized surveys to the user.

[1940] The emotion engine uses facial recognition and voice analysis to adjust the displayed survey questions according to the user's emotional state. For example, the questions might change to something like, "You seem a little tired. Would you like to refresh yourself?"

[1941] Users answer a survey and send their answers to the server via their device.

[1942] 4. Product proposal

[1943] Based on survey results, past purchase history, electronic gift ticket value information, and sentiment data obtained from the sentiment engine, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product.

[1944] The server generates detailed information about the product and sends it to the terminal.

[1945] The device displays an image and detailed information about "Caramel Frappuccino (Grande)" to the user.

[1946] 5. User Approval

[1947] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[1948] The terminal sends the user's selection to the server.

[1949] The server generates a barcode and sends it to the terminal in a format that can be used in Starbucks stores.

[1950] The terminal displays a barcode to the user.

[1951] 6. Save purchase history

[1952] The server can store the user's purchase history and sentiment data in a database, which can then be used to improve future recommendations. This makes it possible to provide even more personalized product suggestions.

[1953] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[1954] The following describes the processing flow.

[1955] Step 1:

[1956] Users enter their name, email address, and preferences into a new registration form via the app or website.

[1957] Step 2:

[1958] The terminal sends the entered information to the server.

[1959] Step 3:

[1960] The server stores the received user information in a database, generates a user ID, and notifies the user.

[1961] Step 4:

[1962] Users scan the electronic gift ticket they received via LINE Gift using the QR code scanning function within the app.

[1963] Step 5:

[1964] The terminal recognizes the QR code or serial number, extracts ticket data (amount, expiration date, etc.), and sends it to the server.

[1965] Step 6:

[1966] The server analyzes the received ticket data, associates it with user information, and stores it in the database.

[1967] Step 7:

[1968] The server generates personalized survey questions based on the user's past purchase history.

[1969] Step 8:

[1970] The terminal displays a survey to the user. The survey includes questions such as the type of drink (coffee, tea, frappuccino), sweetness level (not sweet, regular, sweet), and size (short, tall, grande).

[1971] Step 9:

[1972] The emotion engine uses facial recognition and voice analysis to evaluate the user's emotions in real time. Based on this evaluation, it adjusts the survey questions. For example, it might change the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[1973] Step 10:

[1974] Users answer a survey and send their answers to the server via their device.

[1975] Step 11:

[1976] The server uses an algorithm to select the most suitable product based on user survey results, past purchase history, electronic gift ticket value information, and emotion engine evaluation data.

[1977] Step 12:

[1978] The server generates detailed information about the selected product (name, price, calories, options, etc.) and sends it to the terminal.

[1979] Step 13:

[1980] The device displays detailed information about the product suggested to the user. For example, it displays an image and description of a "Caramel Frappuccino (Grande)".

[1981] Step 14:

[1982] The user selects one product from the suggested options and presses the approve button.

[1983] Step 15:

[1984] The terminal sends the user's selection to the server.

[1985] Step 16:

[1986] The server records information about the selected product in a database and generates a barcode that can be used in Starbucks stores.

[1987] Step 17:

[1988] The server sends the generated barcode to the terminal.

[1989] Step 18:

[1990] The terminal displays a barcode to the user.

[1991] Step 19:

[1992] The server saves the user's purchase history and sentiment data to a database along with a thank-you message, and uses this data to make future suggestions.

[1993] Step 20:

[1994] The emotion engine analyzes emotional data throughout the user's entire experience and provides feedback data for further personalization.

[1995] (Example 2)

[1996] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1997] In conventional systems, when users purchase products using electronic gift tickets, personalized product suggestions that take into account the user's preferences and emotional state are not provided, which often leads to lower user satisfaction. Furthermore, there is no mechanism to dynamically adjust survey content and product suggestions using user emotional data, resulting in a challenge in accurately responding to user needs.

[1998] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving a response, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and emotional data from an emotional engine, means for the user to select and approve the suggested products, and means for saving the user's purchase history and emotional data and utilizing them for future suggestions. This makes it possible to make personalized product suggestions based on the user's preferences and emotional state, thereby improving user satisfaction.

[1999] "User information" refers to individual information about a user, such as their name, email address, preferences, purchase history, and sentiment data.

[2000] An "electronic gift ticket" is a ticket issued in electronic format that can be exchanged for goods or services based on a specific amount or expiration date.

[2001] A "survey" is a series of questions presented to a user, used to understand their preferences and needs.

[2002] An "emotion engine" is a technological system that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[2003] "Product suggestion" is the process of presenting products suitable for the user based on the user's preferences, the value information of the electronic gift certificate, and sentiment data.

[2004] "Purchase history" refers to a record of products a user has purchased in the past, and this information is stored to be used for future recommendations.

[2005] A "personalized survey" is a survey that is individually tailored based on a user's past purchase history and sentiment data.

[2006] The "optimal product" is a product selected by an algorithm that comprehensively considers user preferences, the value information of the electronic gift certificate, and emotional data.

[2007] This invention relates to a system for users to purchase products that match their preferences and emotions using electronic gift tickets. The system has functions to register user information, read electronic gift tickets, present questionnaires, and receive responses. Furthermore, it has a function to suggest products based on the user's preferences, the amount of the electronic gift ticket, and emotion recognition by an emotion engine, and to approve the products selected by the user. It also has a function to save the user's purchase history and utilize it for future suggestions.

[2008] System configuration and details

[2009] 1. User Information Registration Module

[2010] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in a database. This step uses a database management system such as MySQL or PostgreSQL.

[2011] For example, a user registers through an app or website, entering their name, email address, and preferences. The server stores this information in a database and generates a user ID.

[2012] 2. Electronic gift ticket reading module

[2013] The device has the functionality to read electronic gift tickets received by the user. It analyzes the QR code and serial number to extract the ticket's value and expiration date. This is done using QR code reading libraries such as ZBar and ZXing.

[2014] For example, a user scans a 500 yen Starbucks ticket received via LINE Gift within the app. The device reads the QR code and sends the ticket data to the server.

[2015] 3. Questionnaire Presentation Module

[2016] The device displays a personalized survey to the user. The survey includes questions about the type of drink, sweetness level, size, and so on.

[2017] The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the survey content based on the results. For example, if it determines that the user is tired, it changes the question to something like, "You seem a little tired. Would you like to refresh yourself?"

[2018] For example, a user answers a survey and sends their answers to a server via their device.

[2019] 4. Product Proposal Module

[2020] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data generated by an emotion engine. This process utilizes machine learning models and recommendation engines such as TensorFlow and Scikit-Learn.

[2021] For example, the server determines that "Caramel Frappuccino (Grande)" is the most suitable product and sends its detailed information to the terminal. The terminal then displays this information to the user.

[2022] 5. User Approval Module

[2023] The user selects "Caramel Frappuccino (Grande)" and presses the confirm button.

[2024] The terminal sends the user's selection to the server. The server generates a barcode and sends it to the terminal. The user can use this barcode to purchase products in the store.

[2025] 6. Purchase history storage module

[2026] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations. This will enable even more personalized product suggestions.

[2027] Examples of specific cases and prompt statements

[2028] Specific example:

[2029] For example, the terminal displays the question, "You seem a little tired. Would you like to refresh yourself?" and the user replies that they would like to refresh themselves. Based on this, the server suggests a "Caramel Frappuccino (Grande)," and if the user selects it, a barcode is generated that can be used in the store.

[2030] Example of a prompt:

[2031] Please describe a system that allows users to register new user information, scan electronic gift tickets, answer questionnaires, and receive product recommendations. In particular, please explain in detail how the emotion engine adjusts the displayed questionnaire content.

[2032] In this way, by implementing the present invention, users can effectively utilize electronic gift tickets and easily purchase products that suit their tastes and feelings.

[2033] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2034] Program processing flow

[2035] Step 1: Register User Information

[2036] 1.1 Input: The user enters their name, email address, preferences, purchase history, and sentiment data.

[2037] Specific operation: The user launches the app from their smartphone or PC and enters information into the input form.

[2038] Output: The entered user information is sent to the server.

[2039] 1.2 Data Processing and Calculation: The server applies a data format to the user information it receives in order to register it in the database.

[2040] Specific operation: The server saves the data received in the HTTP request to a database management system (e.g., MySQL, PostgreSQL).

[2041] Output: User information stored in the database.

[2042] Step 2: Read the electronic gift ticket

[2043] 2.1 Input: The user scans the electronic gift ticket (QR code or serial number).

[2044] Specific operation: The user uses the camera on their smartphone app to scan the electronic gift ticket.

[2045] 2.2 Data Processing and Calculation: The terminal analyzes the QR code or serial number and extracts the ticket price and expiration date.

[2046] Specific operation: The device analyzes the data using QR code reading software (e.g., ZBar, ZXing).

[2047] Output: Extracted ticket information.

[2048] 2.3 Input: The extracted ticket information is sent to the server.

[2049] Specific action: The terminal sends the analyzed ticket information to the server.

[2050] Output: Ticket information sent to the server.

[2051] 2.4 Data Processing and Calculation: The server stores the received ticket information in the database, associating it with user information.

[2052] Specific operation: The server links the received ticket information with the user ID and saves it to the database.

[2053] Output: Ticket information stored in the database.

[2054] Step 3: Presenting the questionnaire

[2055] 3.1 Input: The server obtains the data necessary to provide users with personalized surveys (preferences, past purchase history, sentiment data).

[2056] Specific operation: The server retrieves user preferences, purchase history, and sentiment data from the database.

[2057] 3.2 Data Processing and Calculation: The server generates survey questions based on the acquired data.

[2058] Specific operation: The server generates survey questions using an algorithm and adjusts them based on sentiment data.

[2059] Output: Personalized survey.

[2060] 3.3 Input: The generated questionnaire is sent to the device.

[2061] Specific operation: The server sends the survey data to the terminal.

[2062] Output: The survey content displayed on the device.

[2063] 3.4 Input: The user answers the survey.

[2064] Specific action: The user enters their answers into the survey form and presses the submit button.

[2065] 3.5 Data Processing and Calculation: The terminal sends the user's survey responses to the server.

[2066] Specific action: The device sends the response data to the server.

[2067] Output: Survey responses sent to the server.

[2068] Step 4: Product Proposal

[2069] 4.1 Input: The server receives survey responses, purchase history, electronic gift certificate amount information, and sentiment data.

[2070] Specific operation: The server receives the user's survey responses and related data.

[2071] 4.2 Data Processing and Calculation: The server uses an algorithm to select the optimal product.

[2072] Specific operation: The server uses machine learning models and recommendation engines (e.g., TensorFlow, Scikit-Learn) to select the most suitable products.

[2073] Output: Detailed information on the selected products.

[2074] 4.3 Input: Detailed information about the selected product is sent to the terminal.

[2075] Specific operation: The server sends detailed product information to the terminal.

[2076] Output: Product information displayed on the terminal.

[2077] Step 5: User Approval

[2078] 5.1 Input: The user selects and approves the suggested product.

[2079] Specific actions: The user clicks the "Select Product" button and then clicks the "Approve" button.

[2080] 5.2 Data Processing and Calculation: The terminal sends the user's selected data to the server.

[2081] Specific operation: The terminal sends the selected data to the server as an HTTP request.

[2082] Output: Selected data sent to the server.

[2083] 5.3 Data Processing and Calculation: The server generates a barcode and sends it to the terminal.

[2084] Specific operation: The server generates barcodes using a barcode generation library (e.g., Barcode4J, ZXing).

[2085] Output: The generated barcode.

[2086] 5.4 Input: The generated barcode is sent to the terminal.

[2087] Specific operation: The server sends barcode data to the terminal.

[2088] Output: The barcode displayed on the terminal.

[2089] Step 6: Saving Purchase History

[2090] 6.1 Input: The server receives the user's purchase history and sentiment data.

[2091] Specific operation: The server receives purchase history and sentiment data.

[2092] 6.2 Data Processing and Calculation: The server saves the received data to a database and uses it for future proposals.

[2093] Specific operation: The server stores purchase history data and sentiment data in a database.

[2094] Output: Purchase history and sentiment data stored in the database.

[2095] (Application Example 2)

[2096] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2097] In today's world, when users use electronic gift tickets to purchase products that match their preferences and emotions, it is difficult to provide personalized recommendations. This can lead to wasted time and a poor purchasing experience. Furthermore, existing systems do not consider the user's emotional state when making product recommendations, thus failing to increase user satisfaction.

[2098] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2099] In this invention, the server includes means for registering user information, means for reading electronic gift tickets, means for presenting a questionnaire to the user and receiving responses, means for suggesting products based on the user's preferences, the amount information of the electronic gift ticket, and the emotion recognition results, means for the user to select and approve the suggested products, means for saving the user's purchase history and emotion data and using them for future suggestions, and means for suggesting products using a generation AI model based on the generated prompt text. As a result, the user can efficiently select and purchase products that match their preferences and emotions, thereby realizing a highly satisfying shopping experience.

[2100] "Means for registering user information" refers to a function for registering information such as the user's name, email address, preferences, purchase history, and sentiment data on the server.

[2101] "Methods for reading electronic gift tickets" refer to functions that analyze QR codes or serial numbers to extract the ticket's value and expiration date.

[2102] "A means of presenting a survey to a user and receiving their response" refers to a function that displays a personalized survey to a user and receives their response.

[2103] "A means of suggesting products based on user preferences, electronic gift ticket value information, and emotion recognition results" refers to a function that uses user survey results, past purchase history, electronic gift ticket value information, and emotion data from an emotion engine to algorithmically select and suggest the most suitable products.

[2104] "A means for users to select and approve suggested products" refers to a function that allows users to review detailed information about suggested products, select them, and approve their purchase.

[2105] "Means for saving users' purchase history and sentiment data and using them for future recommendations" refers to a function that saves users' purchase history and sentiment data in a database and uses it to make personalized product recommendations for future purchases.

[2106] "A means of suggesting products using a generative AI model based on generated prompt sentences" refers to a function that generates prompt sentences according to the user's situation and suggests the most suitable product using a generative AI model (e.g., GPT-3 or GPT-4).

[2107] The system implementing the present invention is designed to perform a series of steps, from user information registration and reading of electronic gift tickets to presenting and receiving responses to questionnaires, product suggestions, user product approval, saving of purchase history, and product suggestions using a generative AI model. The specific operation method is described below.

[2108] The system consists of the following elements:

[2109] 1. User Information Registration Module

[2110] The server receives information such as the user's name, email address, preferences, purchase history, and sentiment data, and registers it in the database. This module is responsible for saving information entered by the user through the app or website when they start using the application to the database.

[2111] 2. Electronic gift ticket reading module

[2112] The terminal has the function of reading electronic gift tickets received by the user. When the user scans a QR code or serial number, the terminal analyzes the information and sends it to the server. The server stores the received ticket data in a database, associating it with the user's information.

[2113] 3. Questionnaire Presentation Module

[2114] The device displays personalized surveys to the user. The survey questions are generated based on the user's preferences and past purchase history. An emotion engine performs facial recognition and voice analysis of the user, adjusting the survey content based on the results. For example, it could display a question such as, "You seem a little tired. Would you like to refresh yourself?"

[2115] 4. Product Proposal Module

[2116] The server uses an algorithm to select the optimal product based on the user's survey results, past purchase history, electronic gift ticket value information, and sentiment data from the sentiment engine. This process uses a generative AI model to suggest products based on prompt messages. The generated prompt messages are in the following format:

[2117] You have received an electronic gift certificate worth 500 yen. The user says they want coffee. Facial analysis suggests they are a little tired. Please suggest a refreshing drink.

[2118] Based on the results of this AI model, the server selects the most suitable product, generates detailed information about that product, and sends it to the terminal.

[2119] 5. User Approval Module

[2120] The terminal displays detailed information about the products suggested to the user. The user reviews the information, selects a product, and presses the approve button, at which point the information is sent to the server. The server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays the barcode to the user, enabling its use in physical stores.

[2121] 6. Purchase history storage module

[2122] The server stores the user's purchase history and sentiment data in a database. This data is used to personalize product recommendations for future purchases.

[2123] By combining these elements, the present invention realizes a system that allows users to easily purchase products that match their preferences and emotions using electronic gift tickets. This system enables users to enjoy a more satisfying and personalized purchasing experience.

[2124] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2125] Step 1:

[2126] Users register through the app or website.

[2127] Input: Information such as the user's name, email address, and preferences entered in the app or website.

[2128] Data processing and calculation: The terminal sends input information to the server, which receives the information and stores it in the database. It also generates a user ID.

[2129] Output: Registration success notification and generation of a unique user ID.

[2130] Specific operation: The server stores the registered information in a database, generates a user ID, and notifies the terminal.

[2131] Step 2:

[2132] The user scans the electronic gift ticket received within the app.

[2133] Input: Scanned image of a QR code or serial number.

[2134] Data processing and calculation: The terminal analyzes QR codes and serial numbers to extract ticket price information and expiration dates. The results are sent to the server.

[2135] Output: Analyzed ticket data.

[2136] Specific operation: The terminal reads the code using a barcode reader or OpenCV, the server stores that information in a database, and associates it with user information.

[2137] Step 3:

[2138] The device displays personalized surveys to the user.

[2139] Input: Past purchase history, user preference data, sentiment recognition data.

[2140] Data processing and calculation: The server generates survey content based on this data and sends it to the terminal. The terminal uses an emotion engine to perform facial recognition and voice analysis of the user and adaptively adjust the survey.

[2141] Output: Personalized survey.

[2142] Specific operation: The terminal displays the survey content to the user, and the user answers it. The answers are then sent back to the server.

[2143] Step 4:

[2144] The server suggests the most suitable product based on survey results, past purchase history, electronic gift certificate value information, and emotion recognition results.

[2145] Inputs: Survey results, past purchase history, electronic gift certificate amount information, sentiment data.

[2146] Data processing and calculation: The server processes this data using algorithms to select the optimal product. It also generates product suggestions based on prompt text using a generative AI model.

[2147] Output: Suggestions for the most suitable products.

[2148] Specific operation: The server uses the generated prompt message (e.g., "You have received an electronic gift ticket worth 500 yen. The user says they want coffee. Facial analysis results indicate they are a little tired. Please suggest a refreshing drink.") to make product suggestions and send the results to the terminal.

[2149] Step 5:

[2150] The user reviews the details of the suggested products, selects a product, and approves it.

[2151] Input: Product information displayed on the terminal.

[2152] Data processing and calculation: User selection information is sent from the terminal to the server, which then records it.

[2153] Output: User selection and approval of products.

[2154] Specific operation: When the user selects an item and presses the approval button, the server processes the purchase, generates a barcode, and sends it to the terminal. The terminal displays this barcode to the user, enabling its use in physical stores.

[2155] Step 6:

[2156] The server stores the user's purchase history and sentiment data, which will be used to improve future recommendations.

[2157] Input: User purchase information and sentiment data.

[2158] Data processing and calculations: The server stores this data in a database and uses it for personalized suggestions in the future.

[2159] Output: Saved purchase history and sentiment data.

[2160] Specific operation: The server stores purchase history and sentiment data, and retains it in a database in a format that can be used for future product recommendations.

[2161] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2162] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2163] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2164] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2165] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2166] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2167] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2168] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2169] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2170] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2171] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2172] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2173] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2174] 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.

[2175] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2176] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2177] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2178] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2179] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2180] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2181] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2182] The following is further disclosed regarding the embodiments described above.

[2183] (Claim 1)

[2184] Means of registering user information,

[2185] A means of reading electronic gift tickets,

[2186] A means of presenting a survey to users and receiving their responses,

[2187] A method for suggesting products based on user preferences and the value information of electronic gift certificates,

[2188] A means for the user to select and approve the suggested products,

[2189] A means of saving the user's purchase history and using it for future recommendations,

[2190] A system that includes this.

[2191] (Claim 2)

[2192] The system according to claim 1, further comprising means for generating a personalized questionnaire based on the user's past purchase history.

[2193] (Claim 3)

[2194] The system according to claim 1, further comprising a means for using an algorithm to select the optimal product based on the user's preferences and the amount information of the electronic gift ticket.

[2195] "Example 1"

[2196] (Claim 1)

[2197] Means of registering user information,

[2198] A means of reading electronic gift tickets,

[2199] A means of presenting a survey to users and receiving their responses,

[2200] A method for suggesting products based on user preferences and the value information of electronic gift certificates,

[2201] A means for the user to select and approve the suggested products,

[2202] A means for displaying the generated barcode,

[2203] A means of saving the user's purchase history and using it for future recommendations,

[2204] A system that includes this.

[2205] (Claim 2)

[2206] The system according to claim 1, further comprising means for generating a personalized questionnaire based on the user's past purchase history.

[2207] (Claim 3)

[2208] The system according to claim 1, further comprising a means for using an algorithm to select the optimal product based on the user's preferences and the amount information of the electronic gift ticket.

[2209] "Application Example 1"

[2210] (Claim 1)

[2211] Means of registering user information,

[2212] A means of reading electronic gift tickets,

[2213] A means of presenting a survey to users and receiving their responses,

[2214] A method for suggesting products based on user preferences and the value information of electronic gift certificates,

[2215] A means for the user to select and approve the suggested products,

[2216] A means of saving the user's purchase history and using it for future recommendations,

[2217] A means of completing a purchase using an electronic payment service, generating a barcode, and displaying it on the user's terminal,

[2218] A system that includes this.

[2219] (Claim 2)

[2220] The system according to claim 1, further comprising means for generating a personalized questionnaire based on the user's past purchase history.

[2221] (Claim 3)

[2222] The system according to claim 1, further comprising a means for using an algorithm to select the optimal product based on the user's preferences and the amount information of the electronic gift ticket.

[2223] "Example 2 of combining an emotion engine"

[2224] (Claim 1)

[2225] Means of registering user information,

[2226] A means of reading electronic gift tickets,

[2227] A means of presenting a survey to users and receiving their responses,

[2228] A method for suggesting products based on user preferences, electronic gift ticket value information, and emotional data from an emotion engine,

[2229] A means for the user to select and approve the suggested products,

[2230] A means of saving users' purchase history and sentiment data and using it for future recommendations,

[2231] A system that includes this.

[2232] (Claim 2)

[2233] The system according to claim 1, further comprising means for generating a personalized questionnaire based on the user's past purchase history and adjusting the questionnaire content based on sentiment analysis by an emotion engine.

[2234] (Claim 3)

[2235] The system according to claim 1, further comprising means for algorithmically selecting the optimal product based on user preferences, electronic gift ticket amount information, and emotion data from an emotion engine.

[2236] "Application example 2 when combining with an emotional engine"

[2237] (Claim 1)

[2238] Means of registering user information,

[2239] A means of reading electronic gift tickets,

[2240] A means of presenting a survey to users and receiving their responses,

[2241] A method for suggesting products based on user preferences, electronic gift ticket value information, and emotion recognition results,

[2242] A means for the user to select and approve the suggested products,

[2243] A means of saving users' purchase history and sentiment data and using it for future recommendations,

[2244] A method for suggesting products using a generative AI model based on the generated prompt text,

[2245] A system that includes this.

[2246] (Claim 2)

[2247] The system according to claim 1, further comprising means for generating personalized questionnaires based on the user's past purchase history and sentiment data.

[2248] (Claim 3)

[2249] The system according to claim 1, further comprising means for algorithmically selecting the optimal product based on the user's preferences, the amount information of the electronic gift ticket, and the emotion recognition results. [Explanation of Symbols]

[2250] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of registering user information, A means of reading electronic gift tickets, A means of presenting a survey to users and receiving their responses, A method for suggesting products based on user preferences and the value information of electronic gift certificates, A means for the user to select and approve the suggested products, A means of saving the user's purchase history and using it for future recommendations, A system that includes this.

2. The system according to claim 1, further comprising means for generating a personalized questionnaire based on the user's past purchase history.

3. The system according to claim 1, further comprising means for selecting the optimal product using an algorithm based on the user's preferences and the amount information of the electronic gift ticket.

Images