System

Abstract

A system is provided.SOLUTION: A system comprising: means for generating a quiz question based on information on a product; means for displaying the generated quiz question on a user terminal; means for receiving an answer from a user through the user terminal; means for evaluating the answer of the user and determining whether the answer is correct; means for determining whether the user can purchase the product based on the determination result; and means for notifying the user of purchase qualification based on the determination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, there has been a problem of certain products being purchased by resellers and not reaching regular consumers. As a result, legitimate consumers seeking the products are dissatisfied, and sellers suffer a decline in their brand image and constant loss of sales opportunities. The increase in such resale activity has created a demand for effective and easy-to-implement measures to prevent resale. Therefore, the present invention aims to provide a system that prevents customers from purchasing products unless they prove their knowledge of the product, thereby preventing the involvement of resellers and ensuring that the products are delivered to actual consumers. [Means for solving the problem]

[0005] The present invention provides a system that generates quiz questions based on product information, displays the generated quiz questions on a user terminal, and receives answers from the user through the user terminal. Specifically, a server automatically generates quiz questions based on product information using a generative AI model and sends the quiz questions to the user terminal. The user answers the quiz questions on their terminal, and the answers are sent to the server. The server evaluates the user's answers and determines whether they are correct or not. Based on the evaluation result, the server determines whether the user is eligible to purchase the product and notifies the user of their eligibility. Furthermore, by allowing the difficulty level and number of quiz questions to be customized, a flexible system is provided.

[0006] "Product information" refers to detailed data and attributes related to a specific product, including information such as the name, features, price, specifications, and use.

[0007] A "quiz question" is a question or set of questions created based on information about a specific product, and is intended to determine whether a consumer has a certain level of knowledge about that product.

[0008] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to automatically generate quiz questions, and is based on machine learning and natural language processing technologies.

[0009] "User terminal" refers to the electronic device used by the user to answer the quiz, including smartphones, tablets, and personal computers.

[0010] "Means for receiving answers" refers to the mechanism or method for sending answers entered through the user terminal to the server and storing them.

[0011] The "means for determining whether the answer is correct or not" refers to an algorithm or program that compares and evaluates whether the user's answer matches a preset correct answer.

[0012] The "means for determining whether or not a user is eligible to purchase" refers to an algorithm or program that determines whether or not a user is eligible to purchase a product based on the evaluation results of the user's quiz answers.

[0013] The "means for notifying the user of eligibility to purchase" refers to a mechanism or method for notifying the user of whether or not the user is eligible to purchase a product.

[0014] "Means for customizing the difficulty level and number of questions" refers to a function or mechanism that allows the difficulty level and number of quiz questions to be set or changed according to the needs of the user or seller. [Brief explanation of the drawings]

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

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

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

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

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

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

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0036] The present invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0037] Quiz Generation

[0038] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0039] View Quiz

[0040] The terminal receives the quiz questions from the server and displays them to the user. The user terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0041] User Answers

[0042] The user enters answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal.

[0043] Evaluating answers

[0044] The server receives the answers submitted by the user and evaluates them against a predefined list of correct answers, determining whether each answer is correct or incorrect.

[0045] Deciding whether to purchase

[0046] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0047] User Notification

[0048] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0049] Specific examples

[0050] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0051] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0052] "What is the screen size of the XYZ Phone in inches?"

[0053] "What is the battery capacity of XYZ Phone?"

[0054] "What OS does XYZ Phone use?"

[0055] "What is the resolution of the main camera on the XYZ Phone?"

[0056] "What year was XYZ Phone released?"

[0057] 2. The device displays these quiz questions to the user.

[0058] 3. The user enters the answer to each quiz question.

[0059] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0060] 5. The server calculates the user's score and grants them the right to purchase the product if they answer all questions correctly.

[0061] 6. The server notifies the user whether they are eligible to purchase.

[0062] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, preventing resale and improving customer satisfaction.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0066] Step 2:

[0067] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0068] Step 3:

[0069] The terminal displays the quiz questions received from the server to the user. The terminal displays the quiz questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question.

[0070] Step 4:

[0071] The user answers the quiz questions on the terminal. The user enters their answer to each quiz question in the input field and completes the answers to all questions.

[0072] Step 5:

[0073] The terminal sends the user's answers to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data to the server.

[0074] Step 6:

[0075] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn to determine whether it matches the correct answer and calculates a score.

[0076] Step 7:

[0077] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[0078] Step 8:

[0079] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[0080] Step 9:

[0081] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[0082] Example 1

[0083] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0084] In traditional online shopping, resale and fraudulent purchases of products have become a problem. These problems are particularly noticeable in the case of limited edition or popular products. Furthermore, sellers want to offer their products to legitimate customers who are knowledgeable about the products, but there is a lack of means to impose such restrictions.

[0085] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0086] In this invention, the server includes a means for generating quiz questions based on product information, a means for generating quiz questions by inputting prompt sentences into a generation AI model, and a means for displaying each generated quiz question on a user terminal in an easy-to-read format and providing an interface for the user to input answers. This makes it possible for only legitimate users who have knowledge of the product to purchase the product.

[0087] "Product information" refers to detailed information about the product, such as its name, features, price, specifications, and use.

[0088] "Quiz questions" are questions in the form of questions generated based on information about the product.

[0089] "User terminal" is a general term for electronic devices such as smartphones, tablets, and personal computers.

[0090] A "generative AI model" is an artificial intelligence model that outputs generated text in natural language based on an input prompt.

[0091] A "prompt sentence" is text that represents the main sentence to be input into a generative AI model.

[0092] The "correct answer list" is a list of correct answers to the generated quiz questions.

[0093] "Evaluating an answer" is the process of comparing the answer submitted by the user with a list of correct answers to determine whether the answer is correct.

[0094] "Eligibility to purchase" is a status indicating that the user meets the conditions necessary to purchase the target product.

[0095] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. This system operates in cooperation with a server, terminals, and users.

[0096] Hardware and software used

[0097] Server: A high-performance cloud server (e.g., AWS EC2 instance)

[0098] Devices: Smartphones (e.g., iPhone, Android devices), tablets (e.g., iPad), PCs (e.g., Windows, Mac)

[0099] Generative AI model: OpenAI GPT-4

[0100] Communication protocol: HTTPS / REST API

[0101] Development languages ​​and frameworks: Python (e.g., Flask, Django), JavaScript (e.g., React, Angular)

[0102] System Operation Overview

[0103] The operation of the system is as follows.

[0104] 1. The server retrieves information about a product. This can be done using a database query or an API request. For example, the server retrieves information about the product "XYZ Phone" (screen size, battery capacity, OS, camera resolution, year of release, etc.).

[0105] 2. The server uses the acquired product information to input prompts into the AI ​​model to generate quiz questions. Specific examples of prompts are as follows:

[0106] Product Name:XYZ Phone

[0107] Quiz question generation:

[0108] 1. What is the screen size of the XYZ Phone?

[0109] 2. What is the battery capacity of XYZ Phone?

[0110] 3. What OS does XYZ Phone use?

[0111] 4. What is the resolution of the main camera on the XYZ Phone?

[0112] 5. What year was XYZ Phone released?

[0113] 3. The quiz questions generated by the server are sent to the terminal. The terminal displays the quiz questions to the user. The display format is user-friendly, providing an interface that makes it easy for the user to input answers.

[0114] 4. The user answers the quiz question using the device interface, for example, "What is the screen size of the XYZ Phone?" by typing "6.5 inches."

[0115] 5. The user's answer is sent from the device to the server. The server receives the user's answer and compares it with a pre-defined list of correct answers. For example, it evaluates the answer "4500mAh" to the question "What is the battery capacity of XYZ Phone?"

[0116] 6. The server determines whether the user can purchase the product based on the evaluation results. This decision process checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly).

[0117] 7. Finally, the server notifies the user whether they are eligible to purchase. If they are eligible, the message "Congratulations! You are now eligible to purchase this product" is displayed. If they are not eligible, the message "Sorry, but you must answer all questions correctly. Please try again" is displayed.

[0118] Specific examples

[0119] For example, consider the case of purchasing an "XYZ Phone."

[0120] 1. The server obtains information about the "XYZ Phone" (screen size 6.5 inches, battery capacity 4500mAh, etc.).

[0121] 2. The server inputs the following prompt sentence to the generated AI model and generates a quiz question.

[0122] Product Name:XYZ Phone

[0123] Quiz question generation:

[0124] 1. What is the screen size of the XYZ Phone?

[0125] 2. What is the battery capacity of XYZ Phone?

[0126] 3. What OS does XYZ Phone use?

[0127] 4. What is the resolution of the main camera on the XYZ Phone?

[0128] 5. What year was XYZ Phone released?

[0129] 3. The generated quiz questions are displayed on the device, and the user enters the answers: "6.5 inches," "4500mAh," "Android," "48 megapixels," and "2023."

[0130] 4. The server receives the user's answer and evaluates it against a list of correct answers.

[0131] 5. The server determines whether the user can purchase the product based on the evaluation results and notifies the user, "Congratulations! You are now eligible to purchase the product."

[0132] This system allows only legitimate users with knowledge of the product to purchase it, preventing resale and improving customer satisfaction.

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1:

[0135] The server retrieves product information from a database or API. Input information includes the product name, features, price, specifications, and use. The server then outputs a set of product information. This information is ready to be used in later processing steps. For example, the server retrieves the screen size, battery capacity, OS, main camera resolution, and release year of the "XYZ Phone."

[0136] Step 2:

[0137] The server uses the product information acquired in step 1 to input prompt sentences into the generative AI model to generate quiz questions. The input here is a specific prompt sentence based on the product information. The generative AI model generates quiz questions based on this prompt sentence and outputs the resulting set of generated quiz questions. For example, it generates a question such as, "What is the screen size of the XYZ Phone in inches?"

[0138] Step 3:

[0139] The server sends the quiz question generated from the prompt sentence to the terminal. The input data is the quiz question output from the generative AI model, and by sending this to the terminal, the terminal receives the quiz question and prepares it for display. The terminal displays the quiz question in an appropriate format on the user interface, allowing the user to view the quiz question.

[0140] Step 4:

[0141] The user inputs answers to the quiz questions displayed on the terminal. The input data is the specific answer given by the user. When the user inputs and sends the answer, the terminal receives the user's answer and is ready to send it to the server. As a specific example, answers such as "6.5 inches" and "4500mAh" are input.

[0142] Step 5:

[0143] The device sends the answer entered by the user to the server. The input is the user's answer, and by sending this to the server, the server receives it and begins processing. For example, a specific answer such as "Android," "48 megapixels," and "2023" is sent to the server.

[0144] Step 6:

[0145] The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The input is the user's answer and the list of correct answers, which are compared to determine whether they are correct or not. The server evaluates the user's answers and outputs the result of whether each answer is correct or not. For example, if the answer "6.5 inches" is correct, it will be evaluated as "correct."

[0146] Step 7:

[0147] The server determines whether the user can purchase the product based on the evaluation result. The input is the evaluation result, and based on this result, it determines whether the user is eligible to purchase the product and outputs the decision. Once the eligibility is confirmed, a notification is generated, such as "Congratulations! You are now eligible to purchase the product."

[0148] Step 8:

[0149] The server notifies the user whether or not they are eligible to purchase. The input is the result of the decision made in step 7, and a notification is sent to the user based on this. The notification contains a different message depending on whether or not they are eligible to purchase. The device receives this notification and displays it to the user. For example, a message such as "Sorry, but you must answer all questions correctly. Please try again" may be displayed.

[0150] This series of steps realizes a system that determines whether a user can legitimately purchase a product through product quiz questions.

[0151] (Application example 1)

[0152] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0153] On conventional online shopping sites, users with no product knowledge can easily purchase products, preventing them from deepening their understanding of the products, resulting in problems such as lower customer satisfaction and purchases for the purpose of resale. Furthermore, there is a lack of ways for users to learn about products while having fun. Therefore, the present invention aims to evaluate and improve users' knowledge through product quizzes, and to increase users' purchasing motivation and improve customer satisfaction by offering special offers.

[0154] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0155] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, and means for granting a bonus if the user passes the quiz. This allows users to enjoy taking quizzes while deepening their knowledge about the product, and by obtaining bonuses through the quiz, it is possible to increase their desire to purchase.

[0156] "Product information" refers to detailed information such as the product name, features, price, specifications, and use.

[0157] "Quiz questions" are questions generated based on product information to test the user's knowledge.

[0158] A "user terminal" is an electronic device (such as a smartphone, tablet, or PC) that a user uses to view quiz questions and enter answers.

[0159] A "generative AI model" is an artificial intelligence model used to automatically generate quiz questions based on product information.

[0160] A "benefit" is a reward given to a user who passes the quiz, and is provided in the form of a discount coupon, free shipping, or the like.

[0161] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0162] The server acquires information about a specific product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0163] The terminal is responsible for displaying the quiz questions received from the server to the user. The user's terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0164] The user inputs answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal. The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The evaluation determines whether each of the user's answers is correct or incorrect.

[0165] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. For example, it checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly). If the user passes the quiz, the server grants a reward. This reward could be a discount coupon or free shipping.

[0166] Finally, the server evaluates whether the user is eligible to purchase the item and notifies the user based on the results. Users who are eligible to purchase the item will be notified with a message such as "Congratulations, you are now eligible to purchase the item" along with a bonus code. Users who are not eligible to purchase the item will be shown a message such as "Sorry, but you must answer all questions correctly. Please try again."

[0167] Specific examples

[0168] Consider the purchase of an electronic device, "XYZ Phone."

[0169] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0170] "What is the screen size of the XYZ Phone in inches?"

[0171] "What is the battery capacity of XYZ Phone?"

[0172] "What OS does XYZ Phone use?"

[0173] "What is the resolution of the main camera on the XYZ Phone?"

[0174] "What year was XYZ Phone released?"

[0175] 2. The device displays these quiz questions to the user.

[0176] 3. The user enters the answer to each quiz question.

[0177] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0178] 5. The server calculates the user's score, and if they answer all questions correctly, they are granted the right to purchase the product and receive a reward.

[0179] 6. The server notifies the user of eligibility and the bonus code.

[0180] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, thereby improving customer satisfaction and preventing resale.

[0181] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0182] Step 1:

[0183] The server obtains information about a specific product (e.g., name, features, price, specifications, use, etc.). The input is obtained from a product information database, and the output is a product information object. Based on this product information, prompt sentences are input into the generative AI model to automatically generate quiz questions. The generative AI model analyzes multiple prompt sentences about the product's name, features, and specifications, and generates corresponding quiz questions.

[0184] Step 2:

[0185] The server sends the generated quiz questions to the user terminal. The input is a list of generated quiz questions, and the output is a set of quiz questions sent to the user terminal. The user terminal receives these quiz questions and displays them in an easy-to-view format for the user. The user interface provides a form that makes it easy for the user to input answers.

[0186] Step 3:

[0187] The user inputs answers to the quiz questions displayed on the terminal. The input is the user's answer, and the output is the user's answer data stored on the user's terminal and sent to the server. The user's terminal receives the user's input in real time and converts it into a format for sending to the server.

[0188] Step 4:

[0189] The server receives the answers submitted by the user and compares them with a pre-defined list of correct answers. The input is the user's answer data and the list of correct answers, and the output is the evaluation result of whether each quiz question was correct or incorrect. The server uses a comparison algorithm to determine whether each user's answer is correct or incorrect.

[0190] Step 5:

[0191] The server calculates a score based on the evaluation results of each user's answer. The input is a list of evaluation results, and the output is the user's total score. The server uses a score calculation algorithm to check whether all answers are correct or meet the set criteria.

[0192] Step 6:

[0193] The server determines whether the user can purchase the product based on the score, and if successful, grants rewards. The input is the user's score, and the output is the result of the purchase eligibility determination and a reward code. Rewards include discount coupons and free shipping options.

[0194] Step 7:

[0195] The server notifies the user of their eligibility and the bonus code. The input is the result of the eligibility determination and the bonus code, and the output is a notification message sent to the user's terminal. The notification message contains the message "Congratulations! You have earned the right to purchase the product. Your bonus code is [bonus code]" for successful users, and "We're sorry, but you must answer all questions correctly. Please try again" for unsuccessful users.

[0196] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0197] This invention combines a system that generates quiz questions based on product information and evaluates the user's answers to those questions to determine whether the user can purchase the product, with an emotion engine that recognizes the user's emotions. The program of this system operates according to the roles of the server, terminal, and user. The operation of the system will be explained using specific examples.

[0198] Quiz Generation

[0199] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0200] View Quiz

[0201] The device receives quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine to analyze the user's emotions in real time.

[0202] Emotion recognition

[0203] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it identifies emotions such as joy, sadness, anger, and surprise based on the user's facial recognition data and voice data. This emotion data is sent to the server via the device.

[0204] User Answers

[0205] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. At that time, the emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as necessary.

[0206] Evaluating answers

[0207] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[0208] Deciding whether to purchase

[0209] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0210] User Notification

[0211] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0212] Specific examples

[0213] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0214] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0215] "What is the screen size of the XYZ Phone in inches?"

[0216] "What is the battery capacity of XYZ Phone?"

[0217] "What OS does XYZ Phone use?"

[0218] "What is the resolution of the main camera on the XYZ Phone?"

[0219] "What year was XYZ Phone released?"

[0220] 2. The device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[0221] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[0222] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0223] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[0224] 6. The server notifies the user whether they are eligible to purchase.

[0225] In this way, by evaluating product purchases through quizzes while taking into account the user's emotions, a more interactive and engaging resale prevention system is realized.

[0226] The processing flow will be explained below.

[0227] Step 1:

[0228] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0229] Step 2:

[0230] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0231] Step 3:

[0232] The device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine, which begins analyzing the user's emotions in real time.

[0233] Step 4:

[0234] The user answers the quiz questions on the device. The user enters their answer in the input field for each question and completes the answer for all questions. During this time, the emotion engine analyzes the user's facial expressions and voice to collect emotion data.

[0235] Step 5:

[0236] The emotion engine determines the user's emotions, such as joy, sadness, anger, and surprise, based on the user's facial expressions, and sends this information to the server via the device.

[0237] Step 6:

[0238] The terminal sends the user's answers and emotion data to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data and emotion data to the server.

[0239] Step 7:

[0240] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. The server may also automatically adjust the difficulty of the quiz based on emotional data.

[0241] Step 8:

[0242] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[0243] Step 9:

[0244] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[0245] Step 10:

[0246] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[0247] Example 2

[0248] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0249] In conventional online shopping systems, the purchasing process is simple, and some users may purchase products without understanding the product details, resulting in a decrease in satisfaction. Furthermore, there are few measures to prevent fraudulent purchases for the purpose of resale, which can result in products not reaching legitimate customers. Furthermore, there is a lack of means to provide an interactive purchasing experience that takes user emotions into consideration.

[0250] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0251] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility based on the determination, and means for recognizing the user's emotions and adjusting the difficulty of the quiz questions based on the emotion data. This allows the user to proceed with the purchase after understanding detailed information about the product, making it possible to prevent resale and improve the user experience.

[0252] "Product information" refers to various data related to a product, such as the product's name, features, price, specifications, and use.

[0253] "Quiz questions" are questions or tasks presented to the user, and are constructed based on detailed product information.

[0254] A "generative AI model" is a model that uses artificial intelligence technology to generate new information and answers from user input and data.

[0255] A "user terminal" is an electronic device operated by a user, typically a computer, smartphone, tablet, etc.

[0256] "User's answer" refers to the answer or reaction entered by the user in response to the quiz question.

[0257] The term "means for evaluating" refers to a function in which the server compares the answer provided by the user with the list of correct answers and determines whether it is correct or not.

[0258] "Means for recognizing emotions" refers to technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0259] "Means of notification" refers to the function by which the server notifies the user terminal of the evaluation results and whether or not the user is eligible to purchase.

[0260] "Means for adjusting the difficulty level" refers to a technique for changing the difficulty level of quiz questions based on the user's emotional data.

[0261] "Emotional data" refers to information about the emotional state of a user analyzed from their facial expressions and voice.

[0262] "Eligibility to purchase" is a status indicating whether a user has the right to purchase a particular product.

[0263] This invention is a system that generates quiz questions based on product information and evaluates the answers to determine whether a user can purchase the product. Furthermore, it has a function to recognize the user's emotions in real time and adjust the difficulty of the quiz. A specific embodiment of this system is described below.

[0264] Quiz Generation

[0265] The server obtains detailed information about the product (such as name, features, price, specifications, and use). Possible methods of obtaining this information include querying a database or requesting via an API. The obtained information is input into a generative AI model as a prompt sentence, and quiz questions are automatically generated. For example, "GPT-4" is used as a generative AI model. The server stores the generated quiz questions in a database.

[0266] Specific prompt examples:

[0267] Generate five intermediate difficulty quiz questions based on the information below.

[0268] Product information:

[0269] Product Name: XYZ Phone

[0270] Screen size: 6.5 inches

[0271] Battery capacity: 4500mAh

[0272] OS: Android

[0273] Main camera resolution: 48 megapixels

[0274] Release year: 2023

[0275] View Quiz

[0276] The device connects to the server via the Internet and requests the generated quiz questions. It then renders a user interface (UI) to display the quiz questions received from the server to the user. The UI displays the quiz questions in an easy-to-read format and allows the user to enter answers. The device also collects the user's facial expression and voice data and sends it to the emotion engine.

[0277] Emotion recognition

[0278] The emotion engine analyzes the user's facial expressions and voice data sent from the device. For emotion recognition, it uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API). The emotion engine determines the user's emotional state (happiness, sadness, anger, surprise, etc.) as the analysis result and returns that data to the device.

[0279] User Answers

[0280] The user inputs answers to the quiz questions displayed on the device. The device temporarily stores the user's answers, and when all questions have been answered, transmits them to the server along with emotional data. The server may adjust the difficulty of the quiz based on the user's emotional data.

[0281] Evaluate responses and decide whether to purchase

[0282] The server receives the user's answers and evaluates them by comparing them with a list of correct answers. For example, it checks whether the answer "6.5 inches" matches the list of correct answers. All answers are evaluated and a score is calculated. Emotional data may also be taken into account. Based on the evaluation results, it determines whether the user can purchase the product. If the user meets certain criteria (e.g., answers all questions correctly), they are granted eligibility to purchase.

[0283] User Notification

[0284] The server generates a notification message for the user based on the evaluation results and sends the message to the terminal. The terminal displays the received notification message to the user. The notification includes information about whether the user is eligible to purchase the product and what action to take next.

[0285] This allows users to understand detailed product information before proceeding with the purchase, providing an interactive and engaging purchasing experience. It is also effective in preventing resale.

[0286] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0287] System program processing flow

[0288] Step 1:

[0289] The server retrieves detailed information about the product. This information is collected through a database or API. The retrieved information includes the product name, features, price, specifications, and use. The product information is retrieved using a database query or API request and stored in a local variable.

[0290] Input: a query from a database or API

[0291] Output: Detailed information about the product (name, features, price, specifications, use, etc.)

[0292] Step 2:

[0293] The server inputs the acquired product information into the generative AI model as a prompt sentence. The prompt sentence is sent to the generative AI model (e.g., GPT-4) and provides instructions for generating quiz questions. The generative AI model generates quiz questions based on the prompt sentence and returns the results to the server.

[0294] Input: Prompt text created based on product information

[0295] Output: Quiz questions returned by the generative AI model

[0296] Step 3:

[0297] The server stores the generated quiz questions in a database, which contains information such as the content of each quiz question, a list of correct answers, and difficulty level, making it easy to retrieve the quiz questions for subsequent processing.

[0298] Input: Generated quiz questions

[0299] Output: Quiz questions stored in a database

[0300] Step 4:

[0301] The terminal requests the generated quiz questions from the server, the server retrieves the quiz questions from the database and sends them to the terminal, and the terminal displays the received quiz questions on the user interface.

[0302] Input: Quiz question request received from the server

[0303] Output: Quiz questions displayed in the user interface

[0304] Step 5:

[0305] The device collects the user's facial and voice data and sends it to the emotion engine, which analyzes this data and uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API) to determine the user's emotional state.

[0306] Input: User's facial expression and voice data

[0307] Output: Emotional state analysis by the emotion engine

[0308] Step 6:

[0309] The emotion engine generates the user's emotion data as an analysis result and returns it to the device. The emotion data includes classifications of emotions such as joy, sadness, anger, and surprise.

[0310] Input: User's facial expression and voice data

[0311] Output: Data on the user's emotional state

[0312] Step 7:

[0313] The user enters answers to the quiz questions on the device. The device temporarily stores the answers entered by the user. When the user has entered answers to all the questions, the device sends the answer data and emotion data to the server.

[0314] Input: User's quiz answer

[0315] Output: Answer data and emotion data sent to the server

[0316] Step 8:

[0317] The server receives the user's answers sent from the device and evaluates them by comparing them with a list of correct answers in the database. During the evaluation process, each answer is checked to determine whether it matches the correct answer. Emotional data may also be reflected in the evaluation, if necessary.

[0318] Input: User response data and emotion data

[0319] Output: Evaluated score data

[0320] Step 9:

[0321] The server makes a decision based on the evaluation result to determine whether the user can purchase the product. The server determines whether the user is eligible to purchase the product based on the evaluation criteria (e.g., whether all questions are answered correctly).

[0322] Input: Evaluated score data

[0323] Output: Purchase eligibility check

[0324] Step 10:

[0325] The server generates a notification for the user based on the result of the determination and sends it to the terminal. The terminal displays the received notification to the user. The notification includes information about eligibility and any further actions required.

[0326] Input: Purchase eligibility determination result

[0327] Output: Notification to the user

[0328] By following the above steps, the system provides an interactive experience of evaluating product purchases in a quiz format while recognizing the user's emotions.

[0329] (Application example 2)

[0330] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0331] In conventional online shopping, there are limited ways to increase user interest and engagement in products, especially in preventing resale. It is also difficult to provide an interactive shopping experience that takes user emotions into account. Furthermore, there is no way to help users acquire product knowledge in a fun way.

[0332] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0333] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, means for recognizing emotions by analyzing the user's facial expressions and voice, and means for adjusting the difficulty of the quiz questions using the recognized emotion data. This provides an interactive purchasing experience that takes the user's emotions into consideration, making it possible to prevent resale and improve engagement.

[0334] "Product information" refers to detailed data related to the product, such as the product name, features, price, specifications, and use.

[0335] "Quiz questions" are questions that are automatically created based on product information using a generative AI model.

[0336] A "user terminal" is an electronic device, such as a smartphone, tablet, or PC, that allows a user to answer quizzes and receive information via an interface.

[0337] The "means for recognizing emotions" is a mechanism that analyzes the user's facial expressions and voice data to identify the user's emotions such as joy, sadness, anger, and surprise.

[0338] "Emotion data" is information about emotions analyzed from the user's facial expressions and voice.

[0339] The "means for adjusting the difficulty of quiz questions" is a mechanism for automatically changing the difficulty of quiz questions based on the user's real-time emotional data.

[0340] A "generative AI model" is an algorithm that uses machine learning to generate quiz questions from large amounts of data.

[0341] The "means for notifying the user of eligibility to purchase" is a mechanism for notifying the user of whether or not the user is eligible to purchase a product.

[0342] The "pre-set correct answer list" is a list of correct answers corresponding to each question in the quiz.

[0343] The present invention relates to a system that generates quiz questions based on product information, evaluates the user's answers to the quiz questions and emotional data, and determines whether the user can purchase the product. This system operates according to the roles of the server, terminal, and user.

[0344] Quiz Generation

[0345] The server obtains information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters. A machine learning model (e.g., GPT-3) is suitable as the generative AI model to use.

[0346] View Quiz

[0347] The user device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question. The device also uses a camera and microphone to collect the user's facial expressions and voice, and inputs this data into an emotion engine to analyze the user's emotions in real time. Smartphones and tablets are often used as devices.

[0348] Emotion recognition

[0349] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it can use Microsoft Azure Cognitive Services or Google Cloud Vision API. The analyzed emotion data is sent to the server via the device.

[0350] User Answers

[0351] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. The emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as needed.

[0352] Evaluating answers

[0353] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[0354] Deciding whether to purchase

[0355] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0356] User Notification

[0357] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0358] Specific examples

[0359] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0360] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0361] "What is the screen size of the XYZ Phone in inches?"

[0362] "What is the battery capacity of XYZ Phone?"

[0363] "What OS does XYZ Phone use?"

[0364] "What is the resolution of the main camera on the XYZ Phone?"

[0365] "What year was XYZ Phone released?"

[0366] 2. The user device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[0367] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[0368] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0369] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[0370] 6. The server notifies the user whether they are eligible to purchase.

[0371] Example of a generative AI model prompt

[0372] Generate quiz questions based on your product database, such as: Include information about the product, such as its features, price, specifications, and uses.

[0373] 1. What is the screen size of the product?

[0374] 2. What is the battery capacity of the product?

[0375] 3. What OS does the product use?

[0376] 4. What is the resolution of the product's main camera?

[0377] 5. What year was the product released?

[0378] This invention allows users to enjoyably learn about products while taking their emotions into consideration, and makes it possible for them to make purchasing decisions interactively.

[0379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0380] Step 1:

[0381] The server obtains information about the product. As input, it obtains information such as the product name, features, price, specifications, and use from the product database. As output, it obtains the obtained product information. This data is used to generate the next quiz questions.

[0382] Step 2:

[0383] The server uses the generative AI model to automatically generate quiz questions. As input, the product information obtained in step 1 is passed to the generative AI model as a prompt sentence. The generated quiz questions are obtained as output. An example of a prompt sentence is, "Based on the product database, please generate quiz questions such as the following. Please include information about the product's features, price, specifications, and uses. 1. What is the screen size of the product in inches?"

[0384] Step 3:

[0385] The server sends the generated quiz questions to the user terminal. As input, it uses the quiz questions generated in step 2. As output, it obtains the quiz questions to be sent to the user terminal.

[0386] Step 4:

[0387] The user terminal displays quiz questions to the user. As input, it receives quiz questions sent from the server. As output, it provides a state in which the user can visually confirm the questions. At this time, it also displays an interface for accepting user input.

[0388] Step 5:

[0389] The user device collects the user's facial expression and voice data. As input, it uses a camera and microphone to capture the user's facial expression and voice in real time. As output, it obtains the collected facial expression and voice data. This data is passed to the emotion engine.

[0390] Step 6:

[0391] The emotion engine analyzes the collected data to recognize emotions. As input, it uses the user's facial expression and voice data collected in step 5. As output, it obtains analyzed emotion data, which is sent to the server.

[0392] Step 7:

[0393] The user answers the quiz questions. As input, the user inputs their answer into the input field, referring to the quiz questions displayed on the terminal. As output, the user's answer data is obtained. This data is sent to the server.

[0394] Step 8:

[0395] The server evaluates the user's answers. As input, it uses the user's answer data, a predefined list of correct answers, and the recognized emotion data. As output, it obtains the evaluation result and the user's score. This evaluation includes scoring based on the list of correct answers and the emotion data.

[0396] Step 9:

[0397] The server decides whether the user can purchase the product. As input, it uses the evaluation result from step 8 and the user's score. As output, it gets a decision on whether to purchase the product.

[0398] Step 10:

[0399] The server notifies the user device whether they are eligible to purchase. The input is the result of the decision made in step 9. The output is a message that is displayed to the user, such as "Congratulations, you are now eligible to purchase the product" or "Sorry, you must answer all questions correctly. Please try again."

[0400] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0401] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0402] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0403] [Second embodiment]

[0404] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0405] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0406] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0407] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0408] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0409] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0410] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0411] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0412] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0413] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0414] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0415] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0416] The present invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0417] Quiz Generation

[0418] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0419] View Quiz

[0420] The terminal receives the quiz questions from the server and displays them to the user. The user terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0421] User Answers

[0422] The user enters answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal.

[0423] Evaluating answers

[0424] The server receives the answers submitted by the user and evaluates them against a predefined list of correct answers, determining whether each answer is correct or incorrect.

[0425] Deciding whether to purchase

[0426] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0427] User Notification

[0428] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0429] Specific examples

[0430] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0431] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0432] "What is the screen size of the XYZ Phone in inches?"

[0433] "What is the battery capacity of XYZ Phone?"

[0434] "What OS does XYZ Phone use?"

[0435] "What is the resolution of the main camera on the XYZ Phone?"

[0436] "What year was XYZ Phone released?"

[0437] 2. The device displays these quiz questions to the user.

[0438] 3. The user enters the answer to each quiz question.

[0439] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0440] 5. The server calculates the user's score and grants them the right to purchase the product if they answer all questions correctly.

[0441] 6. The server notifies the user whether they are eligible to purchase.

[0442] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, preventing resale and improving customer satisfaction.

[0443] The processing flow will be explained below.

[0444] Step 1:

[0445] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0446] Step 2:

[0447] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0448] Step 3:

[0449] The terminal displays the quiz questions received from the server to the user. The terminal displays the quiz questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question.

[0450] Step 4:

[0451] The user answers the quiz questions on the terminal. The user enters their answer to each quiz question in the input field and completes the answers to all questions.

[0452] Step 5:

[0453] The terminal sends the user's answers to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data to the server.

[0454] Step 6:

[0455] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn to determine whether it matches the correct answer and calculates a score.

[0456] Step 7:

[0457] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[0458] Step 8:

[0459] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[0460] Step 9:

[0461] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[0462] Example 1

[0463] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0464] In traditional online shopping, resale and fraudulent purchases of products have become a problem. These problems are particularly noticeable in the case of limited edition or popular products. Furthermore, sellers want to offer their products to legitimate customers who are knowledgeable about the products, but there is a lack of means to impose such restrictions.

[0465] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0466] In this invention, the server includes a means for generating quiz questions based on product information, a means for generating quiz questions by inputting prompt sentences into a generation AI model, and a means for displaying each generated quiz question on a user terminal in an easy-to-read format and providing an interface for the user to input answers. This makes it possible for only legitimate users who have knowledge of the product to purchase the product.

[0467] "Product information" refers to detailed information about the product, such as its name, features, price, specifications, and use.

[0468] "Quiz questions" are questions in the form of questions generated based on information about the product.

[0469] "User terminal" is a general term for electronic devices such as smartphones, tablets, and personal computers.

[0470] A "generative AI model" is an artificial intelligence model that outputs generated text in natural language based on an input prompt.

[0471] A "prompt sentence" is text that represents the main sentence to be input into a generative AI model.

[0472] The "correct answer list" is a list of correct answers to the generated quiz questions.

[0473] "Evaluating an answer" is the process of comparing the answer submitted by the user with a list of correct answers to determine whether the answer is correct.

[0474] "Eligibility to purchase" is a status indicating that the user meets the conditions necessary to purchase the target product.

[0475] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. This system operates in cooperation with a server, terminals, and users.

[0476] Hardware and software used

[0477] Server: A high-performance cloud server (e.g., AWS EC2 instance)

[0478] Devices: Smartphones (e.g., iPhone, Android devices), tablets (e.g., iPad), PCs (e.g., Windows, Mac)

[0479] Generative AI model: OpenAI GPT-4

[0480] Communication protocol: HTTPS / REST API

[0481] Development languages ​​and frameworks: Python (e.g., Flask, Django), JavaScript (e.g., React, Angular)

[0482] System Operation Overview

[0483] The operation of the system is as follows.

[0484] 1. The server retrieves information about a product. This can be done using a database query or an API request. For example, the server retrieves information about the product "XYZ Phone" (screen size, battery capacity, OS, camera resolution, year of release, etc.).

[0485] 2. The server uses the acquired product information to input prompts into the AI ​​model to generate quiz questions. Specific examples of prompts are as follows:

[0486] Product Name:XYZ Phone

[0487] Quiz question generation:

[0488] 1. What is the screen size of the XYZ Phone?

[0489] 2. What is the battery capacity of XYZ Phone?

[0490] 3. What OS does XYZ Phone use?

[0491] 4. What is the resolution of the main camera on the XYZ Phone?

[0492] 5. What year was XYZ Phone released?

[0493] 3. The quiz questions generated by the server are sent to the terminal. The terminal displays the quiz questions to the user. The display format is user-friendly, providing an interface that makes it easy for the user to input answers.

[0494] 4. The user answers the quiz question using the device interface, for example, "What is the screen size of the XYZ Phone?" by typing "6.5 inches."

[0495] 5. The user's answer is sent from the device to the server. The server receives the user's answer and compares it with a pre-defined list of correct answers. For example, it evaluates the answer "4500mAh" to the question "What is the battery capacity of XYZ Phone?"

[0496] 6. The server determines whether the user can purchase the product based on the evaluation results. This decision process checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly).

[0497] 7. Finally, the server notifies the user whether they are eligible to purchase. If they are eligible, the message "Congratulations! You are now eligible to purchase this product" is displayed. If they are not eligible, the message "Sorry, but you must answer all questions correctly. Please try again" is displayed.

[0498] Specific examples

[0499] For example, consider the case of purchasing an "XYZ Phone."

[0500] 1. The server obtains information about the "XYZ Phone" (screen size 6.5 inches, battery capacity 4500mAh, etc.).

[0501] 2. The server inputs the following prompt sentence to the generated AI model and generates a quiz question.

[0502] Product Name:XYZ Phone

[0503] Quiz question generation:

[0504] 1. What is the screen size of the XYZ Phone?

[0505] 2. What is the battery capacity of XYZ Phone?

[0506] 3. What OS does XYZ Phone use?

[0507] 4. What is the resolution of the main camera on the XYZ Phone?

[0508] 5. What year was XYZ Phone released?

[0509] 3. The generated quiz questions are displayed on the device, and the user enters the answers: "6.5 inches," "4500mAh," "Android," "48 megapixels," and "2023."

[0510] 4. The server receives the user's answer and evaluates it against a list of correct answers.

[0511] 5. The server determines whether the user can purchase the product based on the evaluation results and notifies the user, "Congratulations! You are now eligible to purchase the product."

[0512] This system allows only legitimate users with knowledge of the product to purchase it, preventing resale and improving customer satisfaction.

[0513] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0514] Step 1:

[0515] The server retrieves product information from a database or API. Input information includes the product name, features, price, specifications, and use. The server then outputs a set of product information. This information is ready to be used in later processing steps. For example, the server retrieves the screen size, battery capacity, OS, main camera resolution, and release year of the "XYZ Phone."

[0516] Step 2:

[0517] The server uses the product information acquired in step 1 to input prompt sentences into the generative AI model to generate quiz questions. The input here is a specific prompt sentence based on the product information. The generative AI model generates quiz questions based on this prompt sentence and outputs the resulting set of generated quiz questions. For example, it generates a question such as, "What is the screen size of the XYZ Phone in inches?"

[0518] Step 3:

[0519] The server sends the quiz question generated from the prompt sentence to the terminal. The input data is the quiz question output from the generative AI model, and by sending this to the terminal, the terminal receives the quiz question and prepares it for display. The terminal displays the quiz question in an appropriate format on the user interface, allowing the user to view the quiz question.

[0520] Step 4:

[0521] The user inputs answers to the quiz questions displayed on the terminal. The input data is the specific answer given by the user. When the user inputs and sends the answer, the terminal receives the user's answer and is ready to send it to the server. As a specific example, answers such as "6.5 inches" and "4500mAh" are input.

[0522] Step 5:

[0523] The device sends the answer entered by the user to the server. The input is the user's answer, and by sending this to the server, the server receives it and begins processing. For example, a specific answer such as "Android," "48 megapixels," and "2023" is sent to the server.

[0524] Step 6:

[0525] The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The input is the user's answer and the list of correct answers, which are compared to determine whether they are correct or not. The server evaluates the user's answers and outputs the result of whether each answer is correct or not. For example, if the answer "6.5 inches" is correct, it will be evaluated as "correct."

[0526] Step 7:

[0527] The server determines whether the user can purchase the product based on the evaluation result. The input is the evaluation result, and based on this result, it determines whether the user is eligible to purchase the product and outputs the decision. Once the eligibility is confirmed, a notification is generated, such as "Congratulations! You are now eligible to purchase the product."

[0528] Step 8:

[0529] The server notifies the user whether or not they are eligible to purchase. The input is the result of the decision made in step 7, and a notification is sent to the user based on this. The notification contains a different message depending on whether or not they are eligible to purchase. The device receives this notification and displays it to the user. For example, a message such as "Sorry, but you must answer all questions correctly. Please try again" may be displayed.

[0530] This series of steps realizes a system that determines whether a user can legitimately purchase a product through product quiz questions.

[0531] (Application example 1)

[0532] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0533] On conventional online shopping sites, users with no product knowledge can easily purchase products, preventing them from deepening their understanding of the products, resulting in problems such as lower customer satisfaction and purchases for the purpose of resale. Furthermore, there is a lack of ways for users to learn about products while having fun. Therefore, the present invention aims to evaluate and improve users' knowledge through product quizzes, and to increase users' purchasing motivation and improve customer satisfaction by offering special offers.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0535] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, and means for granting a bonus if the user passes the quiz. This allows users to enjoy taking quizzes while deepening their knowledge about the product, and by obtaining bonuses through the quiz, it is possible to increase their desire to purchase.

[0536] "Product information" refers to detailed information such as the product name, features, price, specifications, and use.

[0537] "Quiz questions" are questions generated based on product information to test the user's knowledge.

[0538] A "user terminal" is an electronic device (such as a smartphone, tablet, or PC) that a user uses to view quiz questions and enter answers.

[0539] A "generative AI model" is an artificial intelligence model used to automatically generate quiz questions based on product information.

[0540] A "benefit" is a reward given to a user who passes the quiz, and is provided in the form of a discount coupon, free shipping, or the like.

[0541] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0542] The server acquires information about a specific product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0543] The terminal is responsible for displaying the quiz questions received from the server to the user. The user's terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0544] The user inputs answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal. The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The evaluation determines whether each of the user's answers is correct or incorrect.

[0545] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. For example, it checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly). If the user passes the quiz, the server grants a reward. This reward could be a discount coupon or free shipping.

[0546] Finally, the server evaluates whether the user is eligible to purchase the item and notifies the user based on the results. Users who are eligible to purchase the item will be notified with a message such as "Congratulations, you are now eligible to purchase the item" along with a bonus code. Users who are not eligible to purchase the item will be shown a message such as "Sorry, but you must answer all questions correctly. Please try again."

[0547] Specific examples

[0548] Consider the purchase of an electronic device, "XYZ Phone."

[0549] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0550] "What is the screen size of the XYZ Phone in inches?"

[0551] "What is the battery capacity of XYZ Phone?"

[0552] "What OS does XYZ Phone use?"

[0553] "What is the resolution of the main camera on the XYZ Phone?"

[0554] "What year was XYZ Phone released?"

[0555] 2. The device displays these quiz questions to the user.

[0556] 3. The user enters the answer to each quiz question.

[0557] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0558] 5. The server calculates the user's score, and if they answer all questions correctly, they are granted the right to purchase the product and receive a reward.

[0559] 6. The server notifies the user of eligibility and the bonus code.

[0560] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, thereby improving customer satisfaction and preventing resale.

[0561] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0562] Step 1:

[0563] The server obtains information about a specific product (e.g., name, features, price, specifications, use, etc.). The input is obtained from a product information database, and the output is a product information object. Based on this product information, prompt sentences are input into the generative AI model to automatically generate quiz questions. The generative AI model analyzes multiple prompt sentences about the product's name, features, and specifications, and generates corresponding quiz questions.

[0564] Step 2:

[0565] The server sends the generated quiz questions to the user terminal. The input is a list of generated quiz questions, and the output is a set of quiz questions sent to the user terminal. The user terminal receives these quiz questions and displays them in an easy-to-view format for the user. The user interface provides a form that makes it easy for the user to input answers.

[0566] Step 3:

[0567] The user inputs answers to the quiz questions displayed on the terminal. The input is the user's answer, and the output is the user's answer data stored on the user's terminal and sent to the server. The user's terminal receives the user's input in real time and converts it into a format for sending to the server.

[0568] Step 4:

[0569] The server receives the answers submitted by the user and compares them with a pre-defined list of correct answers. The input is the user's answer data and the list of correct answers, and the output is the evaluation result of whether each quiz question was correct or incorrect. The server uses a comparison algorithm to determine whether each user's answer is correct or incorrect.

[0570] Step 5:

[0571] The server calculates a score based on the evaluation results of each user's answer. The input is a list of evaluation results, and the output is the user's total score. The server uses a score calculation algorithm to check whether all answers are correct or meet the set criteria.

[0572] Step 6:

[0573] The server determines whether the user can purchase the product based on the score, and if successful, grants rewards. The input is the user's score, and the output is the result of the purchase eligibility determination and a reward code. Rewards include discount coupons and free shipping options.

[0574] Step 7:

[0575] The server notifies the user of their eligibility and the bonus code. The input is the result of the eligibility determination and the bonus code, and the output is a notification message sent to the user's terminal. The notification message contains the message "Congratulations! You have earned the right to purchase the product. Your bonus code is [bonus code]" for successful users, and "We're sorry, but you must answer all questions correctly. Please try again" for unsuccessful users.

[0576] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0577] This invention combines a system that generates quiz questions based on product information and evaluates the user's answers to those questions to determine whether the user can purchase the product, with an emotion engine that recognizes the user's emotions. The program of this system operates according to the roles of the server, terminal, and user. The operation of the system will be explained using specific examples.

[0578] Quiz Generation

[0579] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0580] View Quiz

[0581] The device receives quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine to analyze the user's emotions in real time.

[0582] Emotion recognition

[0583] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it identifies emotions such as joy, sadness, anger, and surprise based on the user's facial recognition data and voice data. This emotion data is sent to the server via the device.

[0584] User Answers

[0585] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. At that time, the emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as necessary.

[0586] Evaluating answers

[0587] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[0588] Deciding whether to purchase

[0589] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0590] User Notification

[0591] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0592] Specific examples

[0593] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0594] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0595] "What is the screen size of the XYZ Phone in inches?"

[0596] "What is the battery capacity of XYZ Phone?"

[0597] "What OS does XYZ Phone use?"

[0598] "What is the resolution of the main camera on the XYZ Phone?"

[0599] "What year was XYZ Phone released?"

[0600] 2. The device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[0601] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[0602] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0603] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[0604] 6. The server notifies the user whether they are eligible to purchase.

[0605] In this way, by evaluating product purchases through quizzes while taking into account the user's emotions, a more interactive and engaging resale prevention system is realized.

[0606] The processing flow will be explained below.

[0607] Step 1:

[0608] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0609] Step 2:

[0610] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0611] Step 3:

[0612] The device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine, which begins analyzing the user's emotions in real time.

[0613] Step 4:

[0614] The user answers the quiz questions on the device. The user enters their answer in the input field for each question and completes the answer for all questions. During this time, the emotion engine analyzes the user's facial expressions and voice to collect emotion data.

[0615] Step 5:

[0616] The emotion engine determines the user's emotions, such as joy, sadness, anger, and surprise, based on the user's facial expressions, and sends this information to the server via the device.

[0617] Step 6:

[0618] The terminal sends the user's answers and emotion data to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data and emotion data to the server.

[0619] Step 7:

[0620] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. The server may also automatically adjust the difficulty of the quiz based on emotional data.

[0621] Step 8:

[0622] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[0623] Step 9:

[0624] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[0625] Step 10:

[0626] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[0627] Example 2

[0628] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0629] In conventional online shopping systems, the purchasing process is simple, and some users may purchase products without understanding the product details, resulting in a decrease in satisfaction. Furthermore, there are few measures to prevent fraudulent purchases for the purpose of resale, which can result in products not reaching legitimate customers. Furthermore, there is a lack of means to provide an interactive purchasing experience that takes user emotions into consideration.

[0630] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0631] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility based on the determination, and means for recognizing the user's emotions and adjusting the difficulty of the quiz questions based on the emotion data. This allows the user to proceed with the purchase after understanding detailed information about the product, making it possible to prevent resale and improve the user experience.

[0632] "Product information" refers to various data related to a product, such as the product's name, features, price, specifications, and use.

[0633] "Quiz questions" are questions or tasks presented to the user, and are constructed based on detailed product information.

[0634] A "generative AI model" is a model that uses artificial intelligence technology to generate new information and answers from user input and data.

[0635] A "user terminal" is an electronic device operated by a user, typically a computer, smartphone, tablet, etc.

[0636] "User's answer" refers to the answer or reaction entered by the user in response to the quiz question.

[0637] The term "means for evaluating" refers to a function in which the server compares the answer provided by the user with the list of correct answers and determines whether it is correct or not.

[0638] "Means for recognizing emotions" refers to technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0639] "Means of notification" refers to the function by which the server notifies the user terminal of the evaluation results and whether or not the user is eligible to purchase.

[0640] "Means for adjusting the difficulty level" refers to a technique for changing the difficulty level of quiz questions based on the user's emotional data.

[0641] "Emotional data" refers to information about the emotional state of a user analyzed from their facial expressions and voice.

[0642] "Eligibility to purchase" is a status indicating whether a user has the right to purchase a particular product.

[0643] This invention is a system that generates quiz questions based on product information and evaluates the answers to determine whether a user can purchase the product. Furthermore, it has a function to recognize the user's emotions in real time and adjust the difficulty of the quiz. A specific embodiment of this system is described below.

[0644] Quiz Generation

[0645] The server obtains detailed information about the product (such as name, features, price, specifications, and use). Possible methods of obtaining this information include querying a database or requesting via an API. The obtained information is input into a generative AI model as a prompt sentence, and quiz questions are automatically generated. For example, "GPT-4" is used as a generative AI model. The server stores the generated quiz questions in a database.

[0646] Specific prompt examples:

[0647] Generate five intermediate difficulty quiz questions based on the information below.

[0648] Product information:

[0649] Product Name: XYZ Phone

[0650] Screen size: 6.5 inches

[0651] Battery capacity: 4500mAh

[0652] OS: Android

[0653] Main camera resolution: 48 megapixels

[0654] Release year: 2023

[0655] View Quiz

[0656] The device connects to the server via the Internet and requests the generated quiz questions. It then renders a user interface (UI) to display the quiz questions received from the server to the user. The UI displays the quiz questions in an easy-to-read format and allows the user to enter answers. The device also collects the user's facial expression and voice data and sends it to the emotion engine.

[0657] Emotion recognition

[0658] The emotion engine analyzes the user's facial expressions and voice data sent from the device. For emotion recognition, it uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API). The emotion engine determines the user's emotional state (happiness, sadness, anger, surprise, etc.) as the analysis result and returns that data to the device.

[0659] User Answers

[0660] The user inputs answers to the quiz questions displayed on the device. The device temporarily stores the user's answers, and when all questions have been answered, transmits them to the server along with emotional data. The server may adjust the difficulty of the quiz based on the user's emotional data.

[0661] Evaluate responses and decide whether to purchase

[0662] The server receives the user's answers and evaluates them by comparing them with a list of correct answers. For example, it checks whether the answer "6.5 inches" matches the list of correct answers. All answers are evaluated and a score is calculated. Emotional data may also be taken into account. Based on the evaluation results, it determines whether the user can purchase the product. If the user meets certain criteria (e.g., answers all questions correctly), they are granted eligibility to purchase.

[0663] User Notification

[0664] The server generates a notification message for the user based on the evaluation results and sends the message to the terminal. The terminal displays the received notification message to the user. The notification includes information about whether the user is eligible to purchase the product and what action to take next.

[0665] This allows users to understand detailed product information before proceeding with the purchase, providing an interactive and engaging purchasing experience. It is also effective in preventing resale.

[0666] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0667] System program processing flow

[0668] Step 1:

[0669] The server retrieves detailed information about the product. This information is collected through a database or API. The retrieved information includes the product name, features, price, specifications, and use. The product information is retrieved using a database query or API request and stored in a local variable.

[0670] Input: a query from a database or API

[0671] Output: Detailed information about the product (name, features, price, specifications, use, etc.)

[0672] Step 2:

[0673] The server inputs the acquired product information into the generative AI model as a prompt sentence. The prompt sentence is sent to the generative AI model (e.g., GPT-4) and provides instructions for generating quiz questions. The generative AI model generates quiz questions based on the prompt sentence and returns the results to the server.

[0674] Input: Prompt text created based on product information

[0675] Output: Quiz questions returned by the generative AI model

[0676] Step 3:

[0677] The server stores the generated quiz questions in a database, which contains information such as the content of each quiz question, a list of correct answers, and difficulty level, making it easy to retrieve the quiz questions for subsequent processing.

[0678] Input: Generated quiz questions

[0679] Output: Quiz questions stored in a database

[0680] Step 4:

[0681] The terminal requests the generated quiz questions from the server, the server retrieves the quiz questions from the database and sends them to the terminal, and the terminal displays the received quiz questions on the user interface.

[0682] Input: Quiz question request received from the server

[0683] Output: Quiz questions displayed in the user interface

[0684] Step 5:

[0685] The device collects the user's facial and voice data and sends it to the emotion engine, which analyzes this data and uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API) to determine the user's emotional state.

[0686] Input: User's facial expression and voice data

[0687] Output: Emotional state analysis by the emotion engine

[0688] Step 6:

[0689] The emotion engine generates the user's emotion data as an analysis result and returns it to the device. The emotion data includes classifications of emotions such as joy, sadness, anger, and surprise.

[0690] Input: User's facial expression and voice data

[0691] Output: Data on the user's emotional state

[0692] Step 7:

[0693] The user enters answers to the quiz questions on the device. The device temporarily stores the answers entered by the user. When the user has entered answers to all the questions, the device sends the answer data and emotion data to the server.

[0694] Input: User's quiz answer

[0695] Output: Answer data and emotion data sent to the server

[0696] Step 8:

[0697] The server receives the user's answers sent from the device and evaluates them by comparing them with a list of correct answers in the database. During the evaluation process, each answer is checked to determine whether it matches the correct answer. Emotional data may also be reflected in the evaluation, if necessary.

[0698] Input: User response data and emotion data

[0699] Output: Evaluated score data

[0700] Step 9:

[0701] The server makes a decision based on the evaluation result to determine whether the user can purchase the product. The server determines whether the user is eligible to purchase the product based on the evaluation criteria (e.g., whether all questions are answered correctly).

[0702] Input: Evaluated score data

[0703] Output: Purchase eligibility check

[0704] Step 10:

[0705] The server generates a notification for the user based on the result of the determination and sends it to the terminal. The terminal displays the received notification to the user. The notification includes information about eligibility and any further actions required.

[0706] Input: Purchase eligibility determination result

[0707] Output: Notification to the user

[0708] By following the above steps, the system provides an interactive experience of evaluating product purchases in a quiz format while recognizing the user's emotions.

[0709] (Application example 2)

[0710] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0711] In conventional online shopping, there are limited ways to increase user interest and engagement in products, especially in preventing resale. It is also difficult to provide an interactive shopping experience that takes user emotions into account. Furthermore, there is no way to help users acquire product knowledge in a fun way.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0713] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, means for recognizing emotions by analyzing the user's facial expressions and voice, and means for adjusting the difficulty of the quiz questions using the recognized emotion data. This provides an interactive purchasing experience that takes the user's emotions into consideration, making it possible to prevent resale and improve engagement.

[0714] "Product information" refers to detailed data related to the product, such as the product name, features, price, specifications, and use.

[0715] "Quiz questions" are questions that are automatically created based on product information using a generative AI model.

[0716] A "user terminal" is an electronic device, such as a smartphone, tablet, or PC, that allows a user to answer quizzes and receive information via an interface.

[0717] The "means for recognizing emotions" is a mechanism that analyzes the user's facial expressions and voice data to identify the user's emotions such as joy, sadness, anger, and surprise.

[0718] "Emotion data" is information about emotions analyzed from the user's facial expressions and voice.

[0719] The "means for adjusting the difficulty of quiz questions" is a mechanism for automatically changing the difficulty of quiz questions based on the user's real-time emotional data.

[0720] A "generative AI model" is an algorithm that uses machine learning to generate quiz questions from large amounts of data.

[0721] The "means for notifying the user of eligibility to purchase" is a mechanism for notifying the user of whether or not the user is eligible to purchase a product.

[0722] The "pre-set correct answer list" is a list of correct answers corresponding to each question in the quiz.

[0723] The present invention relates to a system that generates quiz questions based on product information, evaluates the user's answers to the quiz questions and emotional data, and determines whether the user can purchase the product. This system operates according to the roles of the server, terminal, and user.

[0724] Quiz Generation

[0725] The server obtains information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters. A machine learning model (e.g., GPT-3) is suitable as the generative AI model to use.

[0726] View Quiz

[0727] The user device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question. The device also uses a camera and microphone to collect the user's facial expressions and voice, and inputs this data into an emotion engine to analyze the user's emotions in real time. Smartphones and tablets are often used as devices.

[0728] Emotion recognition

[0729] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it can use Microsoft Azure Cognitive Services or Google Cloud Vision API. The analyzed emotion data is sent to the server via the device.

[0730] User Answers

[0731] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. The emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as needed.

[0732] Evaluating answers

[0733] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[0734] Deciding whether to purchase

[0735] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0736] User Notification

[0737] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0738] Specific examples

[0739] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0740] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0741] "What is the screen size of the XYZ Phone in inches?"

[0742] "What is the battery capacity of XYZ Phone?"

[0743] "What OS does XYZ Phone use?"

[0744] "What is the resolution of the main camera on the XYZ Phone?"

[0745] "What year was XYZ Phone released?"

[0746] 2. The user device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[0747] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[0748] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0749] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[0750] 6. The server notifies the user whether they are eligible to purchase.

[0751] Example of a generative AI model prompt

[0752] Generate quiz questions based on your product database, such as: Include information about the product, such as its features, price, specifications, and uses.

[0753] 1. What is the screen size of the product?

[0754] 2. What is the battery capacity of the product?

[0755] 3. What OS does the product use?

[0756] 4. What is the resolution of the product's main camera?

[0757] 5. What year was the product released?

[0758] This invention allows users to enjoyably learn about products while taking their emotions into consideration, and makes it possible for them to make purchasing decisions interactively.

[0759] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0760] Step 1:

[0761] The server obtains information about the product. As input, it obtains information such as the product name, features, price, specifications, and use from the product database. As output, it obtains the obtained product information. This data is used to generate the next quiz questions.

[0762] Step 2:

[0763] The server uses the generative AI model to automatically generate quiz questions. As input, the product information obtained in step 1 is passed to the generative AI model as a prompt sentence. The generated quiz questions are obtained as output. An example of a prompt sentence is, "Based on the product database, please generate quiz questions such as the following. Please include information about the product's features, price, specifications, and uses. 1. What is the screen size of the product in inches?"

[0764] Step 3:

[0765] The server sends the generated quiz questions to the user terminal. As input, it uses the quiz questions generated in step 2. As output, it obtains the quiz questions to be sent to the user terminal.

[0766] Step 4:

[0767] The user terminal displays quiz questions to the user. As input, it receives quiz questions sent from the server. As output, it provides a state in which the user can visually confirm the questions. At this time, it also displays an interface for accepting user input.

[0768] Step 5:

[0769] The user device collects the user's facial expression and voice data. As input, it uses a camera and microphone to capture the user's facial expression and voice in real time. As output, it obtains the collected facial expression and voice data. This data is passed to the emotion engine.

[0770] Step 6:

[0771] The emotion engine analyzes the collected data to recognize emotions. As input, it uses the user's facial expression and voice data collected in step 5. As output, it obtains analyzed emotion data, which is sent to the server.

[0772] Step 7:

[0773] The user answers the quiz questions. As input, the user inputs their answer into the input field, referring to the quiz questions displayed on the terminal. As output, the user's answer data is obtained. This data is sent to the server.

[0774] Step 8:

[0775] The server evaluates the user's answers. As input, it uses the user's answer data, a predefined list of correct answers, and the recognized emotion data. As output, it obtains the evaluation result and the user's score. This evaluation includes scoring based on the list of correct answers and the emotion data.

[0776] Step 9:

[0777] The server decides whether the user can purchase the product. As input, it uses the evaluation result from step 8 and the user's score. As output, it gets a decision on whether to purchase the product.

[0778] Step 10:

[0779] The server notifies the user device whether they are eligible to purchase. The input is the result of the decision made in step 9. The output is a message that is displayed to the user, such as "Congratulations, you are now eligible to purchase the product" or "Sorry, you must answer all questions correctly. Please try again."

[0780] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0781] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0782] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0783] [Third embodiment]

[0784] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0785] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0786] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0787] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0788] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0789] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0790] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0791] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0792] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0793] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0794] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0795] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0796] The present invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0797] Quiz Generation

[0798] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0799] View Quiz

[0800] The terminal receives the quiz questions from the server and displays them to the user. The user terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0801] User Answers

[0802] The user enters answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal.

[0803] Evaluating answers

[0804] The server receives the answers submitted by the user and evaluates them against a predefined list of correct answers, determining whether each answer is correct or incorrect.

[0805] Deciding whether to purchase

[0806] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0807] User Notification

[0808] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0809] Specific examples

[0810] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0811] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0812] "What is the screen size of the XYZ Phone in inches?"

[0813] "What is the battery capacity of XYZ Phone?"

[0814] "What OS does XYZ Phone use?"

[0815] "What is the resolution of the main camera on the XYZ Phone?"

[0816] "What year was XYZ Phone released?"

[0817] 2. The device displays these quiz questions to the user.

[0818] 3. The user enters the answer to each quiz question.

[0819] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0820] 5. The server calculates the user's score and grants them the right to purchase the product if they answer all questions correctly.

[0821] 6. The server notifies the user whether they are eligible to purchase.

[0822] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, preventing resale and improving customer satisfaction.

[0823] The processing flow will be explained below.

[0824] Step 1:

[0825] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0826] Step 2:

[0827] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0828] Step 3:

[0829] The terminal displays the quiz questions received from the server to the user. The terminal displays the quiz questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question.

[0830] Step 4:

[0831] The user answers the quiz questions on the terminal. The user enters their answer to each quiz question in the input field and completes the answers to all questions.

[0832] Step 5:

[0833] The terminal sends the user's answers to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data to the server.

[0834] Step 6:

[0835] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn to determine whether it matches the correct answer and calculates a score.

[0836] Step 7:

[0837] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[0838] Step 8:

[0839] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[0840] Step 9:

[0841] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[0842] Example 1

[0843] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0844] In traditional online shopping, resale and fraudulent purchases of products have become a problem. These problems are particularly noticeable in the case of limited edition or popular products. Furthermore, sellers want to offer their products to legitimate customers who are knowledgeable about the products, but there is a lack of means to impose such restrictions.

[0845] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0846] In this invention, the server includes a means for generating quiz questions based on product information, a means for generating quiz questions by inputting prompt sentences into a generation AI model, and a means for displaying each generated quiz question on a user terminal in an easy-to-read format and providing an interface for the user to input answers. This makes it possible for only legitimate users who have knowledge of the product to purchase the product.

[0847] "Product information" refers to detailed information about the product, such as its name, features, price, specifications, and use.

[0848] "Quiz questions" are questions in the form of questions generated based on information about the product.

[0849] "User terminal" is a general term for electronic devices such as smartphones, tablets, and personal computers.

[0850] A "generative AI model" is an artificial intelligence model that outputs generated text in natural language based on an input prompt.

[0851] A "prompt sentence" is text that represents the main sentence to be input into a generative AI model.

[0852] The "correct answer list" is a list of correct answers to the generated quiz questions.

[0853] "Evaluating an answer" is the process of comparing the answer submitted by the user with a list of correct answers to determine whether the answer is correct.

[0854] "Eligibility to purchase" is a status indicating that the user meets the conditions necessary to purchase the target product.

[0855] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. This system operates in cooperation with a server, terminals, and users.

[0856] Hardware and software used

[0857] Server: A high-performance cloud server (e.g., AWS EC2 instance)

[0858] Devices: Smartphones (e.g., iPhone, Android devices), tablets (e.g., iPad), PCs (e.g., Windows, Mac)

[0859] Generative AI model: OpenAI GPT-4

[0860] Communication protocol: HTTPS / REST API

[0861] Development languages ​​and frameworks: Python (e.g., Flask, Django), JavaScript (e.g., React, Angular)

[0862] System Operation Overview

[0863] The operation of the system is as follows.

[0864] 1. The server retrieves information about a product. This can be done using a database query or an API request. For example, the server retrieves information about the product "XYZ Phone" (screen size, battery capacity, OS, camera resolution, year of release, etc.).

[0865] 2. The server uses the acquired product information to input prompts into the AI ​​model to generate quiz questions. Specific examples of prompts are as follows:

[0866] Product Name:XYZ Phone

[0867] Quiz question generation:

[0868] 1. What is the screen size of the XYZ Phone?

[0869] 2. What is the battery capacity of XYZ Phone?

[0870] 3. What OS does XYZ Phone use?

[0871] 4. What is the resolution of the main camera on the XYZ Phone?

[0872] 5. What year was XYZ Phone released?

[0873] 3. The quiz questions generated by the server are sent to the terminal. The terminal displays the quiz questions to the user. The display format is user-friendly, providing an interface that makes it easy for the user to input answers.

[0874] 4. The user answers the quiz question using the device interface, for example, "What is the screen size of the XYZ Phone?" by typing "6.5 inches."

[0875] 5. The user's answer is sent from the device to the server. The server receives the user's answer and compares it with a pre-defined list of correct answers. For example, it evaluates the answer "4500mAh" to the question "What is the battery capacity of XYZ Phone?"

[0876] 6. The server determines whether the user can purchase the product based on the evaluation results. This decision process checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly).

[0877] 7. Finally, the server notifies the user whether they are eligible to purchase. If they are eligible, the message "Congratulations! You are now eligible to purchase this product" is displayed. If they are not eligible, the message "Sorry, but you must answer all questions correctly. Please try again" is displayed.

[0878] Specific examples

[0879] For example, consider the case of purchasing an "XYZ Phone."

[0880] 1. The server obtains information about the "XYZ Phone" (screen size 6.5 inches, battery capacity 4500mAh, etc.).

[0881] 2. The server inputs the following prompt sentence to the generated AI model and generates a quiz question.

[0882] Product Name:XYZ Phone

[0883] Quiz question generation:

[0884] 1. What is the screen size of the XYZ Phone?

[0885] 2. What is the battery capacity of XYZ Phone?

[0886] 3. What OS does XYZ Phone use?

[0887] 4. What is the resolution of the main camera on the XYZ Phone?

[0888] 5. What year was XYZ Phone released?

[0889] 3. The generated quiz questions are displayed on the device, and the user enters the answers: "6.5 inches," "4500mAh," "Android," "48 megapixels," and "2023."

[0890] 4. The server receives the user's answer and evaluates it against a list of correct answers.

[0891] 5. The server determines whether the user can purchase the product based on the evaluation results and notifies the user, "Congratulations! You are now eligible to purchase the product."

[0892] This system allows only legitimate users with knowledge of the product to purchase it, preventing resale and improving customer satisfaction.

[0893] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0894] Step 1:

[0895] The server retrieves product information from a database or API. Input information includes the product name, features, price, specifications, and use. The server then outputs a set of product information. This information is ready to be used in later processing steps. For example, the server retrieves the screen size, battery capacity, OS, main camera resolution, and release year of the "XYZ Phone."

[0896] Step 2:

[0897] The server uses the product information acquired in step 1 to input prompt sentences into the generative AI model to generate quiz questions. The input here is a specific prompt sentence based on the product information. The generative AI model generates quiz questions based on this prompt sentence and outputs the resulting set of generated quiz questions. For example, it generates a question such as, "What is the screen size of the XYZ Phone in inches?"

[0898] Step 3:

[0899] The server sends the quiz question generated from the prompt sentence to the terminal. The input data is the quiz question output from the generative AI model, and by sending this to the terminal, the terminal receives the quiz question and prepares it for display. The terminal displays the quiz question in an appropriate format on the user interface, allowing the user to view the quiz question.

[0900] Step 4:

[0901] The user inputs answers to the quiz questions displayed on the terminal. The input data is the specific answer given by the user. When the user inputs and sends the answer, the terminal receives the user's answer and is ready to send it to the server. As a specific example, answers such as "6.5 inches" and "4500mAh" are input.

[0902] Step 5:

[0903] The device sends the answer entered by the user to the server. The input is the user's answer, and by sending this to the server, the server receives it and begins processing. For example, a specific answer such as "Android," "48 megapixels," and "2023" is sent to the server.

[0904] Step 6:

[0905] The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The input is the user's answer and the list of correct answers, which are compared to determine whether they are correct or not. The server evaluates the user's answers and outputs the result of whether each answer is correct or not. For example, if the answer "6.5 inches" is correct, it will be evaluated as "correct."

[0906] Step 7:

[0907] The server determines whether the user can purchase the product based on the evaluation result. The input is the evaluation result, and based on this result, it determines whether the user is eligible to purchase the product and outputs the decision. Once the eligibility is confirmed, a notification is generated, such as "Congratulations! You are now eligible to purchase the product."

[0908] Step 8:

[0909] The server notifies the user whether or not they are eligible to purchase. The input is the result of the decision made in step 7, and a notification is sent to the user based on this. The notification contains a different message depending on whether or not they are eligible to purchase. The device receives this notification and displays it to the user. For example, a message such as "Sorry, but you must answer all questions correctly. Please try again" may be displayed.

[0910] This series of steps realizes a system that determines whether a user can legitimately purchase a product through product quiz questions.

[0911] (Application example 1)

[0912] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0913] On conventional online shopping sites, users with no product knowledge can easily purchase products, preventing them from deepening their understanding of the products, resulting in problems such as lower customer satisfaction and purchases for the purpose of resale. Furthermore, there is a lack of ways for users to learn about products while having fun. Therefore, the present invention aims to evaluate and improve users' knowledge through product quizzes, and to increase users' purchasing motivation and improve customer satisfaction by offering special offers.

[0914] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0915] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, and means for granting a bonus if the user passes the quiz. This allows users to enjoy taking quizzes while deepening their knowledge about the product, and by obtaining bonuses through the quiz, it is possible to increase their desire to purchase.

[0916] "Product information" refers to detailed information such as the product name, features, price, specifications, and use.

[0917] "Quiz questions" are questions generated based on product information to test the user's knowledge.

[0918] A "user terminal" is an electronic device (such as a smartphone, tablet, or PC) that a user uses to view quiz questions and enter answers.

[0919] A "generative AI model" is an artificial intelligence model used to automatically generate quiz questions based on product information.

[0920] A "benefit" is a reward given to a user who passes the quiz, and is provided in the form of a discount coupon, free shipping, or the like.

[0921] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[0922] The server acquires information about a specific product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0923] The terminal is responsible for displaying the quiz questions received from the server to the user. The user's terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[0924] The user inputs answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal. The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The evaluation determines whether each of the user's answers is correct or incorrect.

[0925] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. For example, it checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly). If the user passes the quiz, the server grants a reward. This reward could be a discount coupon or free shipping.

[0926] Finally, the server evaluates whether the user is eligible to purchase the item and notifies the user based on the results. Users who are eligible to purchase the item will be notified with a message such as "Congratulations, you are now eligible to purchase the item" along with a bonus code. Users who are not eligible to purchase the item will be shown a message such as "Sorry, but you must answer all questions correctly. Please try again."

[0927] Specific examples

[0928] Consider the purchase of an electronic device, "XYZ Phone."

[0929] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0930] "What is the screen size of the XYZ Phone in inches?"

[0931] "What is the battery capacity of XYZ Phone?"

[0932] "What OS does XYZ Phone use?"

[0933] "What is the resolution of the main camera on the XYZ Phone?"

[0934] "What year was XYZ Phone released?"

[0935] 2. The device displays these quiz questions to the user.

[0936] 3. The user enters the answer to each quiz question.

[0937] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0938] 5. The server calculates the user's score, and if they answer all questions correctly, they are granted the right to purchase the product and receive a reward.

[0939] 6. The server notifies the user of eligibility and the bonus code.

[0940] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, thereby improving customer satisfaction and preventing resale.

[0941] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0942] Step 1:

[0943] The server obtains information about a specific product (e.g., name, features, price, specifications, use, etc.). The input is obtained from a product information database, and the output is a product information object. Based on this product information, prompt sentences are input into the generative AI model to automatically generate quiz questions. The generative AI model analyzes multiple prompt sentences about the product's name, features, and specifications, and generates corresponding quiz questions.

[0944] Step 2:

[0945] The server sends the generated quiz questions to the user terminal. The input is a list of generated quiz questions, and the output is a set of quiz questions sent to the user terminal. The user terminal receives these quiz questions and displays them in an easy-to-view format for the user. The user interface provides a form that makes it easy for the user to input answers.

[0946] Step 3:

[0947] The user inputs answers to the quiz questions displayed on the terminal. The input is the user's answer, and the output is the user's answer data stored on the user's terminal and sent to the server. The user's terminal receives the user's input in real time and converts it into a format for sending to the server.

[0948] Step 4:

[0949] The server receives the answers submitted by the user and compares them with a pre-defined list of correct answers. The input is the user's answer data and the list of correct answers, and the output is the evaluation result of whether each quiz question was correct or incorrect. The server uses a comparison algorithm to determine whether each user's answer is correct or incorrect.

[0950] Step 5:

[0951] The server calculates a score based on the evaluation results of each user's answer. The input is a list of evaluation results, and the output is the user's total score. The server uses a score calculation algorithm to check whether all answers are correct or meet the set criteria.

[0952] Step 6:

[0953] The server determines whether the user can purchase the product based on the score, and if successful, grants rewards. The input is the user's score, and the output is the result of the purchase eligibility determination and a reward code. Rewards include discount coupons and free shipping options.

[0954] Step 7:

[0955] The server notifies the user of their eligibility and the bonus code. The input is the result of the eligibility determination and the bonus code, and the output is a notification message sent to the user's terminal. The notification message contains the message "Congratulations! You have earned the right to purchase the product. Your bonus code is [bonus code]" for successful users, and "We're sorry, but you must answer all questions correctly. Please try again" for unsuccessful users.

[0956] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0957] This invention combines a system that generates quiz questions based on product information and evaluates the user's answers to those questions to determine whether the user can purchase the product, with an emotion engine that recognizes the user's emotions. The program of this system operates according to the roles of the server, terminal, and user. The operation of the system will be explained using specific examples.

[0958] Quiz Generation

[0959] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[0960] View Quiz

[0961] The device receives quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine to analyze the user's emotions in real time.

[0962] Emotion recognition

[0963] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it identifies emotions such as joy, sadness, anger, and surprise based on the user's facial recognition data and voice data. This emotion data is sent to the server via the device.

[0964] User Answers

[0965] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. At that time, the emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as necessary.

[0966] Evaluating answers

[0967] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[0968] Deciding whether to purchase

[0969] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[0970] User Notification

[0971] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[0972] Specific examples

[0973] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[0974] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[0975] "What is the screen size of the XYZ Phone in inches?"

[0976] "What is the battery capacity of XYZ Phone?"

[0977] "What OS does XYZ Phone use?"

[0978] "What is the resolution of the main camera on the XYZ Phone?"

[0979] "What year was XYZ Phone released?"

[0980] 2. The device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[0981] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[0982] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[0983] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[0984] 6. The server notifies the user whether they are eligible to purchase.

[0985] In this way, by evaluating product purchases through quizzes while taking into account the user's emotions, a more interactive and engaging resale prevention system is realized.

[0986] The processing flow will be explained below.

[0987] Step 1:

[0988] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[0989] Step 2:

[0990] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[0991] Step 3:

[0992] The device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine, which begins analyzing the user's emotions in real time.

[0993] Step 4:

[0994] The user answers the quiz questions on the device. The user enters their answer in the input field for each question and completes the answer for all questions. During this time, the emotion engine analyzes the user's facial expressions and voice to collect emotion data.

[0995] Step 5:

[0996] The emotion engine determines the user's emotions, such as joy, sadness, anger, and surprise, based on the user's facial expressions, and sends this information to the server via the device.

[0997] Step 6:

[0998] The terminal sends the user's answers and emotion data to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data and emotion data to the server.

[0999] Step 7:

[1000] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. The server may also automatically adjust the difficulty of the quiz based on emotional data.

[1001] Step 8:

[1002] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[1003] Step 9:

[1004] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[1005] Step 10:

[1006] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[1007] Example 2

[1008] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1009] In conventional online shopping systems, the purchasing process is simple, and some users may purchase products without understanding the product details, resulting in a decrease in satisfaction. Furthermore, there are few measures to prevent fraudulent purchases for the purpose of resale, which can result in products not reaching legitimate customers. Furthermore, there is a lack of means to provide an interactive purchasing experience that takes user emotions into consideration.

[1010] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1011] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility based on the determination, and means for recognizing the user's emotions and adjusting the difficulty of the quiz questions based on the emotion data. This allows the user to proceed with the purchase after understanding detailed information about the product, making it possible to prevent resale and improve the user experience.

[1012] "Product information" refers to various data related to a product, such as the product's name, features, price, specifications, and use.

[1013] "Quiz questions" are questions or tasks presented to the user, and are constructed based on detailed product information.

[1014] A "generative AI model" is a model that uses artificial intelligence technology to generate new information and answers from user input and data.

[1015] A "user terminal" is an electronic device operated by a user, typically a computer, smartphone, tablet, etc.

[1016] "User's answer" refers to the answer or reaction entered by the user in response to the quiz question.

[1017] The term "means for evaluating" refers to a function in which the server compares the answer provided by the user with the list of correct answers and determines whether it is correct or not.

[1018] "Means for recognizing emotions" refers to technology that analyzes a user's facial expressions and voice to determine their emotional state.

[1019] "Means of notification" refers to the function by which the server notifies the user terminal of the evaluation results and whether or not the user is eligible to purchase.

[1020] "Means for adjusting the difficulty level" refers to a technique for changing the difficulty level of quiz questions based on the user's emotional data.

[1021] "Emotional data" refers to information about the emotional state of a user analyzed from their facial expressions and voice.

[1022] "Eligibility to purchase" is a status indicating whether a user has the right to purchase a particular product.

[1023] This invention is a system that generates quiz questions based on product information and evaluates the answers to determine whether a user can purchase the product. Furthermore, it has a function to recognize the user's emotions in real time and adjust the difficulty of the quiz. A specific embodiment of this system is described below.

[1024] Quiz Generation

[1025] The server obtains detailed information about the product (such as name, features, price, specifications, and use). Possible methods of obtaining this information include querying a database or requesting via an API. The obtained information is input into a generative AI model as a prompt sentence, and quiz questions are automatically generated. For example, "GPT-4" is used as a generative AI model. The server stores the generated quiz questions in a database.

[1026] Specific prompt examples:

[1027] Generate five intermediate difficulty quiz questions based on the information below.

[1028] Product information:

[1029] Product Name: XYZ Phone

[1030] Screen size: 6.5 inches

[1031] Battery capacity: 4500mAh

[1032] OS: Android

[1033] Main camera resolution: 48 megapixels

[1034] Release year: 2023

[1035] View Quiz

[1036] The device connects to the server via the Internet and requests the generated quiz questions. It then renders a user interface (UI) to display the quiz questions received from the server to the user. The UI displays the quiz questions in an easy-to-read format and allows the user to enter answers. The device also collects the user's facial expression and voice data and sends it to the emotion engine.

[1037] Emotion recognition

[1038] The emotion engine analyzes the user's facial expressions and voice data sent from the device. For emotion recognition, it uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API). The emotion engine determines the user's emotional state (happiness, sadness, anger, surprise, etc.) as the analysis result and returns that data to the device.

[1039] User Answers

[1040] The user inputs answers to the quiz questions displayed on the device. The device temporarily stores the user's answers, and when all questions have been answered, transmits them to the server along with emotional data. The server may adjust the difficulty of the quiz based on the user's emotional data.

[1041] Evaluate responses and decide whether to purchase

[1042] The server receives the user's answers and evaluates them by comparing them with a list of correct answers. For example, it checks whether the answer "6.5 inches" matches the list of correct answers. All answers are evaluated and a score is calculated. Emotional data may also be taken into account. Based on the evaluation results, it determines whether the user can purchase the product. If the user meets certain criteria (e.g., answers all questions correctly), they are granted eligibility to purchase.

[1043] User Notification

[1044] The server generates a notification message for the user based on the evaluation results and sends the message to the terminal. The terminal displays the received notification message to the user. The notification includes information about whether the user is eligible to purchase the product and what action to take next.

[1045] This allows users to understand detailed product information before proceeding with the purchase, providing an interactive and engaging purchasing experience. It is also effective in preventing resale.

[1046] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1047] System program processing flow

[1048] Step 1:

[1049] The server retrieves detailed information about the product. This information is collected through a database or API. The retrieved information includes the product name, features, price, specifications, and use. The product information is retrieved using a database query or API request and stored in a local variable.

[1050] Input: a query from a database or API

[1051] Output: Detailed information about the product (name, features, price, specifications, use, etc.)

[1052] Step 2:

[1053] The server inputs the acquired product information into the generative AI model as a prompt sentence. The prompt sentence is sent to the generative AI model (e.g., GPT-4) and provides instructions for generating quiz questions. The generative AI model generates quiz questions based on the prompt sentence and returns the results to the server.

[1054] Input: Prompt text created based on product information

[1055] Output: Quiz questions returned by the generative AI model

[1056] Step 3:

[1057] The server stores the generated quiz questions in a database, which contains information such as the content of each quiz question, a list of correct answers, and difficulty level, making it easy to retrieve the quiz questions for subsequent processing.

[1058] Input: Generated quiz questions

[1059] Output: Quiz questions stored in a database

[1060] Step 4:

[1061] The terminal requests the generated quiz questions from the server, the server retrieves the quiz questions from the database and sends them to the terminal, and the terminal displays the received quiz questions on the user interface.

[1062] Input: Quiz question request received from the server

[1063] Output: Quiz questions displayed in the user interface

[1064] Step 5:

[1065] The device collects the user's facial and voice data and sends it to the emotion engine, which analyzes this data and uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API) to determine the user's emotional state.

[1066] Input: User's facial expression and voice data

[1067] Output: Emotional state analysis by the emotion engine

[1068] Step 6:

[1069] The emotion engine generates the user's emotion data as an analysis result and returns it to the device. The emotion data includes classifications of emotions such as joy, sadness, anger, and surprise.

[1070] Input: User's facial expression and voice data

[1071] Output: Data on the user's emotional state

[1072] Step 7:

[1073] The user enters answers to the quiz questions on the device. The device temporarily stores the answers entered by the user. When the user has entered answers to all the questions, the device sends the answer data and emotion data to the server.

[1074] Input: User's quiz answer

[1075] Output: Answer data and emotion data sent to the server

[1076] Step 8:

[1077] The server receives the user's answers sent from the device and evaluates them by comparing them with a list of correct answers in the database. During the evaluation process, each answer is checked to determine whether it matches the correct answer. Emotional data may also be reflected in the evaluation, if necessary.

[1078] Input: User response data and emotion data

[1079] Output: Evaluated score data

[1080] Step 9:

[1081] The server makes a decision based on the evaluation result to determine whether the user can purchase the product. The server determines whether the user is eligible to purchase the product based on the evaluation criteria (e.g., whether all questions are answered correctly).

[1082] Input: Evaluated score data

[1083] Output: Purchase eligibility check

[1084] Step 10:

[1085] The server generates a notification for the user based on the result of the determination and sends it to the terminal. The terminal displays the received notification to the user. The notification includes information about eligibility and any further actions required.

[1086] Input: Purchase eligibility determination result

[1087] Output: Notification to the user

[1088] By following the above steps, the system provides an interactive experience of evaluating product purchases in a quiz format while recognizing the user's emotions.

[1089] (Application example 2)

[1090] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1091] In conventional online shopping, there are limited ways to increase user interest and engagement in products, especially in preventing resale. It is also difficult to provide an interactive shopping experience that takes user emotions into account. Furthermore, there is no way to help users acquire product knowledge in a fun way.

[1092] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1093] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, means for recognizing emotions by analyzing the user's facial expressions and voice, and means for adjusting the difficulty of the quiz questions using the recognized emotion data. This provides an interactive purchasing experience that takes the user's emotions into consideration, making it possible to prevent resale and improve engagement.

[1094] "Product information" refers to detailed data related to the product, such as the product name, features, price, specifications, and use.

[1095] "Quiz questions" are questions that are automatically created based on product information using a generative AI model.

[1096] A "user terminal" is an electronic device, such as a smartphone, tablet, or PC, that allows a user to answer quizzes and receive information via an interface.

[1097] The "means for recognizing emotions" is a mechanism that analyzes the user's facial expressions and voice data to identify the user's emotions such as joy, sadness, anger, and surprise.

[1098] "Emotion data" is information about emotions analyzed from the user's facial expressions and voice.

[1099] The "means for adjusting the difficulty of quiz questions" is a mechanism for automatically changing the difficulty of quiz questions based on the user's real-time emotional data.

[1100] A "generative AI model" is an algorithm that uses machine learning to generate quiz questions from large amounts of data.

[1101] The "means for notifying the user of eligibility to purchase" is a mechanism for notifying the user of whether or not the user is eligible to purchase a product.

[1102] The "pre-set correct answer list" is a list of correct answers corresponding to each question in the quiz.

[1103] The present invention relates to a system that generates quiz questions based on product information, evaluates the user's answers to the quiz questions and emotional data, and determines whether the user can purchase the product. This system operates according to the roles of the server, terminal, and user.

[1104] Quiz Generation

[1105] The server obtains information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters. A machine learning model (e.g., GPT-3) is suitable as the generative AI model to use.

[1106] View Quiz

[1107] The user device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question. The device also uses a camera and microphone to collect the user's facial expressions and voice, and inputs this data into an emotion engine to analyze the user's emotions in real time. Smartphones and tablets are often used as devices.

[1108] Emotion recognition

[1109] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it can use Microsoft Azure Cognitive Services or Google Cloud Vision API. The analyzed emotion data is sent to the server via the device.

[1110] User Answers

[1111] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. The emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as needed.

[1112] Evaluating answers

[1113] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[1114] Deciding whether to purchase

[1115] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[1116] User Notification

[1117] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[1118] Specific examples

[1119] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[1120] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[1121] "What is the screen size of the XYZ Phone in inches?"

[1122] "What is the battery capacity of XYZ Phone?"

[1123] "What OS does XYZ Phone use?"

[1124] "What is the resolution of the main camera on the XYZ Phone?"

[1125] "What year was XYZ Phone released?"

[1126] 2. The user device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[1127] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[1128] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[1129] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[1130] 6. The server notifies the user whether they are eligible to purchase.

[1131] Example of a generative AI model prompt

[1132] Generate quiz questions based on your product database, such as: Include information about the product, such as its features, price, specifications, and uses.

[1133] 1. What is the screen size of the product?

[1134] 2. What is the battery capacity of the product?

[1135] 3. What OS does the product use?

[1136] 4. What is the resolution of the product's main camera?

[1137] 5. What year was the product released?

[1138] This invention allows users to enjoyably learn about products while taking their emotions into consideration, and makes it possible for them to make purchasing decisions interactively.

[1139] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1140] Step 1:

[1141] The server obtains information about the product. As input, it obtains information such as the product name, features, price, specifications, and use from the product database. As output, it obtains the obtained product information. This data is used to generate the next quiz questions.

[1142] Step 2:

[1143] The server uses the generative AI model to automatically generate quiz questions. As input, the product information obtained in step 1 is passed to the generative AI model as a prompt sentence. The generated quiz questions are obtained as output. An example of a prompt sentence is, "Based on the product database, please generate quiz questions such as the following. Please include information about the product's features, price, specifications, and uses. 1. What is the screen size of the product in inches?"

[1144] Step 3:

[1145] The server sends the generated quiz questions to the user terminal. As input, it uses the quiz questions generated in step 2. As output, it obtains the quiz questions to be sent to the user terminal.

[1146] Step 4:

[1147] The user terminal displays quiz questions to the user. As input, it receives quiz questions sent from the server. As output, it provides a state in which the user can visually confirm the questions. At this time, it also displays an interface for accepting user input.

[1148] Step 5:

[1149] The user device collects the user's facial expression and voice data. As input, it uses a camera and microphone to capture the user's facial expression and voice in real time. As output, it obtains the collected facial expression and voice data. This data is passed to the emotion engine.

[1150] Step 6:

[1151] The emotion engine analyzes the collected data to recognize emotions. As input, it uses the user's facial expression and voice data collected in step 5. As output, it obtains analyzed emotion data, which is sent to the server.

[1152] Step 7:

[1153] The user answers the quiz questions. As input, the user inputs their answer into the input field, referring to the quiz questions displayed on the terminal. As output, the user's answer data is obtained. This data is sent to the server.

[1154] Step 8:

[1155] The server evaluates the user's answers. As input, it uses the user's answer data, a predefined list of correct answers, and the recognized emotion data. As output, it obtains the evaluation result and the user's score. This evaluation includes scoring based on the list of correct answers and the emotion data.

[1156] Step 9:

[1157] The server decides whether the user can purchase the product. As input, it uses the evaluation result from step 8 and the user's score. As output, it gets a decision on whether to purchase the product.

[1158] Step 10:

[1159] The server notifies the user device whether they are eligible to purchase. The input is the result of the decision made in step 9. The output is a message that is displayed to the user, such as "Congratulations, you are now eligible to purchase the product" or "Sorry, you must answer all questions correctly. Please try again."

[1160] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1161] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1162] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1163] [Fourth embodiment]

[1164] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1165] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1166] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1167] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1168] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1169] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1170] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1171] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1172] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1173] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1174] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1175] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1176] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1177] The present invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[1178] Quiz Generation

[1179] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[1180] View Quiz

[1181] The terminal receives the quiz questions from the server and displays them to the user. The user terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[1182] User Answers

[1183] The user enters answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal.

[1184] Evaluating answers

[1185] The server receives the answers submitted by the user and evaluates them against a predefined list of correct answers, determining whether each answer is correct or incorrect.

[1186] Deciding whether to purchase

[1187] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[1188] User Notification

[1189] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[1190] Specific examples

[1191] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[1192] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[1193] "What is the screen size of the XYZ Phone in inches?"

[1194] "What is the battery capacity of XYZ Phone?"

[1195] "What OS does XYZ Phone use?"

[1196] "What is the resolution of the main camera on the XYZ Phone?"

[1197] "What year was XYZ Phone released?"

[1198] 2. The device displays these quiz questions to the user.

[1199] 3. The user enters the answer to each quiz question.

[1200] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[1201] 5. The server calculates the user's score and grants them the right to purchase the product if they answer all questions correctly.

[1202] 6. The server notifies the user whether they are eligible to purchase.

[1203] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, preventing resale and improving customer satisfaction.

[1204] The processing flow will be explained below.

[1205] Step 1:

[1206] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[1207] Step 2:

[1208] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[1209] Step 3:

[1210] The terminal displays the quiz questions received from the server to the user. The terminal displays the quiz questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question.

[1211] Step 4:

[1212] The user answers the quiz questions on the terminal. The user enters their answer to each quiz question in the input field and completes the answers to all questions.

[1213] Step 5:

[1214] The terminal sends the user's answers to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data to the server.

[1215] Step 6:

[1216] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn to determine whether it matches the correct answer and calculates a score.

[1217] Step 7:

[1218] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[1219] Step 8:

[1220] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[1221] Step 9:

[1222] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[1223] Example 1

[1224] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1225] In traditional online shopping, resale and fraudulent purchases of products have become a problem. These problems are particularly noticeable in the case of limited edition or popular products. Furthermore, sellers want to offer their products to legitimate customers who are knowledgeable about the products, but there is a lack of means to impose such restrictions.

[1226] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1227] In this invention, the server includes a means for generating quiz questions based on product information, a means for generating quiz questions by inputting prompt sentences into a generation AI model, and a means for displaying each generated quiz question on a user terminal in an easy-to-read format and providing an interface for the user to input answers. This makes it possible for only legitimate users who have knowledge of the product to purchase the product.

[1228] "Product information" refers to detailed information about the product, such as its name, features, price, specifications, and use.

[1229] "Quiz questions" are questions in the form of questions generated based on information about the product.

[1230] "User terminal" is a general term for electronic devices such as smartphones, tablets, and personal computers.

[1231] A "generative AI model" is an artificial intelligence model that outputs generated text in natural language based on an input prompt.

[1232] A "prompt sentence" is text that represents the main sentence to be input into a generative AI model.

[1233] The "correct answer list" is a list of correct answers to the generated quiz questions.

[1234] "Evaluating an answer" is the process of comparing the answer submitted by the user with a list of correct answers to determine whether the answer is correct.

[1235] "Eligibility to purchase" is a status indicating that the user meets the conditions necessary to purchase the target product.

[1236] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. This system operates in cooperation with a server, terminals, and users.

[1237] Hardware and software used

[1238] Server: A high-performance cloud server (e.g., AWS EC2 instance)

[1239] Devices: Smartphones (e.g., iPhone, Android devices), tablets (e.g., iPad), PCs (e.g., Windows, Mac)

[1240] Generative AI model: OpenAI GPT-4

[1241] Communication protocol: HTTPS / REST API

[1242] Development languages ​​and frameworks: Python (e.g., Flask, Django), JavaScript (e.g., React, Angular)

[1243] System Operation Overview

[1244] The operation of the system is as follows.

[1245] 1. The server retrieves information about a product. This can be done using a database query or an API request. For example, the server retrieves information about the product "XYZ Phone" (screen size, battery capacity, OS, camera resolution, year of release, etc.).

[1246] 2. The server uses the acquired product information to input prompts into the AI ​​model to generate quiz questions. Specific examples of prompts are as follows:

[1247] Product Name:XYZ Phone

[1248] Quiz question generation:

[1249] 1. What is the screen size of the XYZ Phone?

[1250] 2. What is the battery capacity of XYZ Phone?

[1251] 3. What OS does XYZ Phone use?

[1252] 4. What is the resolution of the main camera on the XYZ Phone?

[1253] 5. What year was XYZ Phone released?

[1254] 3. The quiz questions generated by the server are sent to the terminal. The terminal displays the quiz questions to the user. The display format is user-friendly, providing an interface that makes it easy for the user to input answers.

[1255] 4. The user answers the quiz question using the device interface, for example, "What is the screen size of the XYZ Phone?" by typing "6.5 inches."

[1256] 5. The user's answer is sent from the device to the server. The server receives the user's answer and compares it with a pre-defined list of correct answers. For example, it evaluates the answer "4500mAh" to the question "What is the battery capacity of XYZ Phone?"

[1257] 6. The server determines whether the user can purchase the product based on the evaluation results. This decision process checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly).

[1258] 7. Finally, the server notifies the user whether they are eligible to purchase. If they are eligible, the message "Congratulations! You are now eligible to purchase this product" is displayed. If they are not eligible, the message "Sorry, but you must answer all questions correctly. Please try again" is displayed.

[1259] Specific examples

[1260] For example, consider the case of purchasing an "XYZ Phone."

[1261] 1. The server obtains information about the "XYZ Phone" (screen size 6.5 inches, battery capacity 4500mAh, etc.).

[1262] 2. The server inputs the following prompt sentence to the generated AI model and generates a quiz question.

[1263] Product Name:XYZ Phone

[1264] Quiz question generation:

[1265] 1. What is the screen size of the XYZ Phone?

[1266] 2. What is the battery capacity of XYZ Phone?

[1267] 3. What OS does XYZ Phone use?

[1268] 4. What is the resolution of the main camera on the XYZ Phone?

[1269] 5. What year was XYZ Phone released?

[1270] 3. The generated quiz questions are displayed on the device, and the user enters the answers: "6.5 inches," "4500mAh," "Android," "48 megapixels," and "2023."

[1271] 4. The server receives the user's answer and evaluates it against a list of correct answers.

[1272] 5. The server determines whether the user can purchase the product based on the evaluation results and notifies the user, "Congratulations! You are now eligible to purchase the product."

[1273] This system allows only legitimate users with knowledge of the product to purchase it, preventing resale and improving customer satisfaction.

[1274] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1275] Step 1:

[1276] The server retrieves product information from a database or API. Input information includes the product name, features, price, specifications, and use. The server then outputs a set of product information. This information is ready to be used in later processing steps. For example, the server retrieves the screen size, battery capacity, OS, main camera resolution, and release year of the "XYZ Phone."

[1277] Step 2:

[1278] The server uses the product information acquired in step 1 to input prompt sentences into the generative AI model to generate quiz questions. The input here is a specific prompt sentence based on the product information. The generative AI model generates quiz questions based on this prompt sentence and outputs the resulting set of generated quiz questions. For example, it generates a question such as, "What is the screen size of the XYZ Phone in inches?"

[1279] Step 3:

[1280] The server sends the quiz question generated from the prompt sentence to the terminal. The input data is the quiz question output from the generative AI model, and by sending this to the terminal, the terminal receives the quiz question and prepares it for display. The terminal displays the quiz question in an appropriate format on the user interface, allowing the user to view the quiz question.

[1281] Step 4:

[1282] The user inputs answers to the quiz questions displayed on the terminal. The input data is the specific answer given by the user. When the user inputs and sends the answer, the terminal receives the user's answer and is ready to send it to the server. As a specific example, answers such as "6.5 inches" and "4500mAh" are input.

[1283] Step 5:

[1284] The device sends the answer entered by the user to the server. The input is the user's answer, and by sending this to the server, the server receives it and begins processing. For example, a specific answer such as "Android," "48 megapixels," and "2023" is sent to the server.

[1285] Step 6:

[1286] The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The input is the user's answer and the list of correct answers, which are compared to determine whether they are correct or not. The server evaluates the user's answers and outputs the result of whether each answer is correct or not. For example, if the answer "6.5 inches" is correct, it will be evaluated as "correct."

[1287] Step 7:

[1288] The server determines whether the user can purchase the product based on the evaluation result. The input is the evaluation result, and based on this result, it determines whether the user is eligible to purchase the product and outputs the decision. Once the eligibility is confirmed, a notification is generated, such as "Congratulations! You are now eligible to purchase the product."

[1289] Step 8:

[1290] The server notifies the user whether or not they are eligible to purchase. The input is the result of the decision made in step 7, and a notification is sent to the user based on this. The notification contains a different message depending on whether or not they are eligible to purchase. The device receives this notification and displays it to the user. For example, a message such as "Sorry, but you must answer all questions correctly. Please try again" may be displayed.

[1291] This series of steps realizes a system that determines whether a user can legitimately purchase a product through product quiz questions.

[1292] (Application example 1)

[1293] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1294] On conventional online shopping sites, users with no product knowledge can easily purchase products, preventing them from deepening their understanding of the products, resulting in problems such as lower customer satisfaction and purchases for the purpose of resale. Furthermore, there is a lack of ways for users to learn about products while having fun. Therefore, the present invention aims to evaluate and improve users' knowledge through product quizzes, and to increase users' purchasing motivation and improve customer satisfaction by offering special offers.

[1295] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1296] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, and means for granting a bonus if the user passes the quiz. This allows users to enjoy taking quizzes while deepening their knowledge about the product, and by obtaining bonuses through the quiz, it is possible to increase their desire to purchase.

[1297] "Product information" refers to detailed information such as the product name, features, price, specifications, and use.

[1298] "Quiz questions" are questions generated based on product information to test the user's knowledge.

[1299] A "user terminal" is an electronic device (such as a smartphone, tablet, or PC) that a user uses to view quiz questions and enter answers.

[1300] A "generative AI model" is an artificial intelligence model used to automatically generate quiz questions based on product information.

[1301] A "benefit" is a reward given to a user who passes the quiz, and is provided in the form of a discount coupon, free shipping, or the like.

[1302] This invention is a system that generates quiz questions based on product information and evaluates the user's answers to the quiz to determine whether the user can purchase the product. The program of this system operates in cooperation with a server, terminals, and users.

[1303] The server acquires information about a specific product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[1304] The terminal is responsible for displaying the quiz questions received from the server to the user. The user's terminal can be an electronic device such as a smartphone, tablet, or PC. The terminal displays the quiz questions in an easy-to-read format and provides an interface for the user to enter their answers.

[1305] The user inputs answers to the quiz questions displayed on the terminal, and the answers are sent to the server via the terminal. The server receives the answers sent by the user and evaluates them by comparing them with a pre-set list of correct answers. The evaluation determines whether each of the user's answers is correct or incorrect.

[1306] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. For example, it checks whether the user's score meets a predetermined standard (e.g., answering all questions correctly). If the user passes the quiz, the server grants a reward. This reward could be a discount coupon or free shipping.

[1307] Finally, the server evaluates whether the user is eligible to purchase the item and notifies the user based on the results. Users who are eligible to purchase the item will be notified with a message such as "Congratulations, you are now eligible to purchase the item" along with a bonus code. Users who are not eligible to purchase the item will be shown a message such as "Sorry, but you must answer all questions correctly. Please try again."

[1308] Specific examples

[1309] Consider the purchase of an electronic device, "XYZ Phone."

[1310] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[1311] "What is the screen size of the XYZ Phone in inches?"

[1312] "What is the battery capacity of XYZ Phone?"

[1313] "What OS does XYZ Phone use?"

[1314] "What is the resolution of the main camera on the XYZ Phone?"

[1315] "What year was XYZ Phone released?"

[1316] 2. The device displays these quiz questions to the user.

[1317] 3. The user enters the answer to each quiz question.

[1318] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[1319] 5. The server calculates the user's score, and if they answer all questions correctly, they are granted the right to purchase the product and receive a reward.

[1320] 6. The server notifies the user of eligibility and the bonus code.

[1321] This system allows sellers to ensure that only users who have knowledge of the product can purchase it, thereby improving customer satisfaction and preventing resale.

[1322] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1323] Step 1:

[1324] The server obtains information about a specific product (e.g., name, features, price, specifications, use, etc.). The input is obtained from a product information database, and the output is a product information object. Based on this product information, prompt sentences are input into the generative AI model to automatically generate quiz questions. The generative AI model analyzes multiple prompt sentences about the product's name, features, and specifications, and generates corresponding quiz questions.

[1325] Step 2:

[1326] The server sends the generated quiz questions to the user terminal. The input is a list of generated quiz questions, and the output is a set of quiz questions sent to the user terminal. The user terminal receives these quiz questions and displays them in an easy-to-view format for the user. The user interface provides a form that makes it easy for the user to input answers.

[1327] Step 3:

[1328] The user inputs answers to the quiz questions displayed on the terminal. The input is the user's answer, and the output is the user's answer data stored on the user's terminal and sent to the server. The user's terminal receives the user's input in real time and converts it into a format for sending to the server.

[1329] Step 4:

[1330] The server receives the answers submitted by the user and compares them with a pre-defined list of correct answers. The input is the user's answer data and the list of correct answers, and the output is the evaluation result of whether each quiz question was correct or incorrect. The server uses a comparison algorithm to determine whether each user's answer is correct or incorrect.

[1331] Step 5:

[1332] The server calculates a score based on the evaluation results of each user's answer. The input is a list of evaluation results, and the output is the user's total score. The server uses a score calculation algorithm to check whether all answers are correct or meet the set criteria.

[1333] Step 6:

[1334] The server determines whether the user can purchase the product based on the score, and if successful, grants rewards. The input is the user's score, and the output is the result of the purchase eligibility determination and a reward code. Rewards include discount coupons and free shipping options.

[1335] Step 7:

[1336] The server notifies the user of their eligibility and the bonus code. The input is the result of the eligibility determination and the bonus code, and the output is a notification message sent to the user's terminal. The notification message contains the message "Congratulations! You have earned the right to purchase the product. Your bonus code is [bonus code]" for successful users, and "We're sorry, but you must answer all questions correctly. Please try again" for unsuccessful users.

[1337] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1338] This invention combines a system that generates quiz questions based on product information and evaluates the user's answers to those questions to determine whether the user can purchase the product, with an emotion engine that recognizes the user's emotions. The program of this system operates according to the roles of the server, terminal, and user. The operation of the system will be explained using specific examples.

[1339] Quiz Generation

[1340] The server acquires information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters.

[1341] View Quiz

[1342] The device receives quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine to analyze the user's emotions in real time.

[1343] Emotion recognition

[1344] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it identifies emotions such as joy, sadness, anger, and surprise based on the user's facial recognition data and voice data. This emotion data is sent to the server via the device.

[1345] User Answers

[1346] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. At that time, the emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as necessary.

[1347] Evaluating answers

[1348] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[1349] Deciding whether to purchase

[1350] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[1351] User Notification

[1352] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[1353] Specific examples

[1354] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[1355] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[1356] "What is the screen size of the XYZ Phone in inches?"

[1357] "What is the battery capacity of XYZ Phone?"

[1358] "What OS does XYZ Phone use?"

[1359] "What is the resolution of the main camera on the XYZ Phone?"

[1360] "What year was XYZ Phone released?"

[1361] 2. The device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[1362] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[1363] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[1364] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[1365] 6. The server notifies the user whether they are eligible to purchase.

[1366] In this way, by evaluating product purchases through quizzes while taking into account the user's emotions, a more interactive and engaging resale prevention system is realized.

[1367] The processing flow will be explained below.

[1368] Step 1:

[1369] The server generates quiz questions based on product information, such as the product name, features, price, specifications, and use, and uses a generative AI model to automatically generate a quiz based on the specified number of questions and difficulty level.

[1370] Step 2:

[1371] The server sends the generated quiz questions to the user's device, and the server transfers the quiz data to the device via API, allowing the user to receive the quiz questions.

[1372] Step 3:

[1373] The device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface where the user can enter answers to each question. The device also inputs the user's facial expressions and voice into an emotion engine, which begins analyzing the user's emotions in real time.

[1374] Step 4:

[1375] The user answers the quiz questions on the device. The user enters their answer in the input field for each question and completes the answer for all questions. During this time, the emotion engine analyzes the user's facial expressions and voice to collect emotion data.

[1376] Step 5:

[1377] The emotion engine determines the user's emotions, such as joy, sadness, anger, and surprise, based on the user's facial expressions, and sends this information to the server via the device.

[1378] Step 6:

[1379] The terminal sends the user's answers and emotion data to the server. After the user has entered answers to all the quiz questions, they press the send button to send the answer data and emotion data to the server.

[1380] Step 7:

[1381] The server receives the user's answers and evaluates them against a list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. The server may also automatically adjust the difficulty of the quiz based on emotional data.

[1382] Step 8:

[1383] The server tally up the user's score based on the evaluation results and decides whether the user can purchase the product. If the user answers all questions correctly, the user is given the right to purchase the product.

[1384] Step 9:

[1385] The server notifies the user of their eligibility to purchase. Based on the results of the determination, the server generates a congratulatory message for eligible users and a message encouraging users who are not eligible to purchase to try again, and sends these messages to the terminal.

[1386] Step 10:

[1387] The device will display the notification received from the server to the user. If the item is available for purchase, the user will be prompted to proceed with the purchase. If not, the user will be presented with an option to try again.

[1388] Example 2

[1389] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1390] In conventional online shopping systems, the purchasing process is simple, and some users may purchase products without understanding the product details, resulting in a decrease in satisfaction. Furthermore, there are few measures to prevent fraudulent purchases for the purpose of resale, which can result in products not reaching legitimate customers. Furthermore, there is a lack of means to provide an interactive purchasing experience that takes user emotions into consideration.

[1391] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1392] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility based on the determination, and means for recognizing the user's emotions and adjusting the difficulty of the quiz questions based on the emotion data. This allows the user to proceed with the purchase after understanding detailed information about the product, making it possible to prevent resale and improve the user experience.

[1393] "Product information" refers to various data related to a product, such as the product's name, features, price, specifications, and use.

[1394] "Quiz questions" are questions or tasks presented to the user, and are constructed based on detailed product information.

[1395] A "generative AI model" is a model that uses artificial intelligence technology to generate new information and answers from user input and data.

[1396] A "user terminal" is an electronic device operated by a user, typically a computer, smartphone, tablet, etc.

[1397] "User's answer" refers to the answer or reaction entered by the user in response to the quiz question.

[1398] The term "means for evaluating" refers to a function in which the server compares the answer provided by the user with the list of correct answers and determines whether it is correct or not.

[1399] "Means for recognizing emotions" refers to technology that analyzes a user's facial expressions and voice to determine their emotional state.

[1400] "Means of notification" refers to the function by which the server notifies the user terminal of the evaluation results and whether or not the user is eligible to purchase.

[1401] "Means for adjusting the difficulty level" refers to a technique for changing the difficulty level of quiz questions based on the user's emotional data.

[1402] "Emotional data" refers to information about the emotional state of a user analyzed from their facial expressions and voice.

[1403] "Eligibility to purchase" is a status indicating whether a user has the right to purchase a particular product.

[1404] This invention is a system that generates quiz questions based on product information and evaluates the answers to determine whether a user can purchase the product. Furthermore, it has a function to recognize the user's emotions in real time and adjust the difficulty of the quiz. A specific embodiment of this system is described below.

[1405] Quiz Generation

[1406] The server obtains detailed information about the product (such as name, features, price, specifications, and use). Possible methods of obtaining this information include querying a database or requesting via an API. The obtained information is input into a generative AI model as a prompt sentence, and quiz questions are automatically generated. For example, "GPT-4" is used as a generative AI model. The server stores the generated quiz questions in a database.

[1407] Specific prompt examples:

[1408] Generate five intermediate difficulty quiz questions based on the information below.

[1409] Product information:

[1410] Product Name: XYZ Phone

[1411] Screen size: 6.5 inches

[1412] Battery capacity: 4500mAh

[1413] OS: Android

[1414] Main camera resolution: 48 megapixels

[1415] Release year: 2023

[1416] View Quiz

[1417] The device connects to the server via the Internet and requests the generated quiz questions. It then renders a user interface (UI) to display the quiz questions received from the server to the user. The UI displays the quiz questions in an easy-to-read format and allows the user to enter answers. The device also collects the user's facial expression and voice data and sends it to the emotion engine.

[1418] Emotion recognition

[1419] The emotion engine analyzes the user's facial expressions and voice data sent from the device. For emotion recognition, it uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API). The emotion engine determines the user's emotional state (happiness, sadness, anger, surprise, etc.) as the analysis result and returns that data to the device.

[1420] User Answers

[1421] The user inputs answers to the quiz questions displayed on the device. The device temporarily stores the user's answers, and when all questions have been answered, transmits them to the server along with emotional data. The server may adjust the difficulty of the quiz based on the user's emotional data.

[1422] Evaluate responses and decide whether to purchase

[1423] The server receives the user's answers and evaluates them by comparing them with a list of correct answers. For example, it checks whether the answer "6.5 inches" matches the list of correct answers. All answers are evaluated and a score is calculated. Emotional data may also be taken into account. Based on the evaluation results, it determines whether the user can purchase the product. If the user meets certain criteria (e.g., answers all questions correctly), they are granted eligibility to purchase.

[1424] User Notification

[1425] The server generates a notification message for the user based on the evaluation results and sends the message to the terminal. The terminal displays the received notification message to the user. The notification includes information about whether the user is eligible to purchase the product and what action to take next.

[1426] This allows users to understand detailed product information before proceeding with the purchase, providing an interactive and engaging purchasing experience. It is also effective in preventing resale.

[1427] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1428] System program processing flow

[1429] Step 1:

[1430] The server retrieves detailed information about the product. This information is collected through a database or API. The retrieved information includes the product name, features, price, specifications, and use. The product information is retrieved using a database query or API request and stored in a local variable.

[1431] Input: a query from a database or API

[1432] Output: Detailed information about the product (name, features, price, specifications, use, etc.)

[1433] Step 2:

[1434] The server inputs the acquired product information into the generative AI model as a prompt sentence. The prompt sentence is sent to the generative AI model (e.g., GPT-4) and provides instructions for generating quiz questions. The generative AI model generates quiz questions based on the prompt sentence and returns the results to the server.

[1435] Input: Prompt text created based on product information

[1436] Output: Quiz questions returned by the generative AI model

[1437] Step 3:

[1438] The server stores the generated quiz questions in a database, which contains information such as the content of each quiz question, a list of correct answers, and difficulty level, making it easy to retrieve the quiz questions for subsequent processing.

[1439] Input: Generated quiz questions

[1440] Output: Quiz questions stored in a database

[1441] Step 4:

[1442] The terminal requests the generated quiz questions from the server, the server retrieves the quiz questions from the database and sends them to the terminal, and the terminal displays the received quiz questions on the user interface.

[1443] Input: Quiz question request received from the server

[1444] Output: Quiz questions displayed in the user interface

[1445] Step 5:

[1446] The device collects the user's facial and voice data and sends it to the emotion engine, which analyzes this data and uses a facial recognition library (e.g., OpenCV) or a voice recognition library (e.g., Google Speech-to-Text API) to determine the user's emotional state.

[1447] Input: User's facial expression and voice data

[1448] Output: Emotional state analysis by the emotion engine

[1449] Step 6:

[1450] The emotion engine generates the user's emotion data as an analysis result and returns it to the device. The emotion data includes classifications of emotions such as joy, sadness, anger, and surprise.

[1451] Input: User's facial expression and voice data

[1452] Output: Data on the user's emotional state

[1453] Step 7:

[1454] The user enters answers to the quiz questions on the device. The device temporarily stores the answers entered by the user. When the user has entered answers to all the questions, the device sends the answer data and emotion data to the server.

[1455] Input: User's quiz answer

[1456] Output: Answer data and emotion data sent to the server

[1457] Step 8:

[1458] The server receives the user's answers sent from the device and evaluates them by comparing them with a list of correct answers in the database. During the evaluation process, each answer is checked to determine whether it matches the correct answer. Emotional data may also be reflected in the evaluation, if necessary.

[1459] Input: User response data and emotion data

[1460] Output: Evaluated score data

[1461] Step 9:

[1462] The server makes a decision based on the evaluation result to determine whether the user can purchase the product. The server determines whether the user is eligible to purchase the product based on the evaluation criteria (e.g., whether all questions are answered correctly).

[1463] Input: Evaluated score data

[1464] Output: Purchase eligibility check

[1465] Step 10:

[1466] The server generates a notification for the user based on the result of the determination and sends it to the terminal. The terminal displays the received notification to the user. The notification includes information about eligibility and any further actions required.

[1467] Input: Purchase eligibility determination result

[1468] Output: Notification to the user

[1469] By following the above steps, the system provides an interactive experience of evaluating product purchases in a quiz format while recognizing the user's emotions.

[1470] (Application example 2)

[1471] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1472] In conventional online shopping, there are limited ways to increase user interest and engagement in products, especially in preventing resale. It is also difficult to provide an interactive shopping experience that takes user emotions into account. Furthermore, there is no way to help users acquire product knowledge in a fun way.

[1473] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1474] In this invention, the server includes means for generating quiz questions based on information about the product, means for displaying the generated quiz questions on a user terminal, means for receiving answers from the user via the user terminal, means for evaluating the user's answers and determining whether they are correct or not, means for determining whether the user is eligible to purchase the product based on the determination result, means for notifying the user of their eligibility to purchase based on the determination, means for recognizing emotions by analyzing the user's facial expressions and voice, and means for adjusting the difficulty of the quiz questions using the recognized emotion data. This provides an interactive purchasing experience that takes the user's emotions into consideration, making it possible to prevent resale and improve engagement.

[1475] "Product information" refers to detailed data related to the product, such as the product name, features, price, specifications, and use.

[1476] "Quiz questions" are questions that are automatically created based on product information using a generative AI model.

[1477] A "user terminal" is an electronic device, such as a smartphone, tablet, or PC, that allows a user to answer quizzes and receive information via an interface.

[1478] The "means for recognizing emotions" is a mechanism that analyzes the user's facial expressions and voice data to identify the user's emotions such as joy, sadness, anger, and surprise.

[1479] "Emotion data" is information about emotions analyzed from the user's facial expressions and voice.

[1480] The "means for adjusting the difficulty of quiz questions" is a mechanism for automatically changing the difficulty of quiz questions based on the user's real-time emotional data.

[1481] A "generative AI model" is an algorithm that uses machine learning to generate quiz questions from large amounts of data.

[1482] The "means for notifying the user of eligibility to purchase" is a mechanism for notifying the user of whether or not the user is eligible to purchase a product.

[1483] The "pre-set correct answer list" is a list of correct answers corresponding to each question in the quiz.

[1484] The present invention relates to a system that generates quiz questions based on product information, evaluates the user's answers to the quiz questions and emotional data, and determines whether the user can purchase the product. This system operates according to the roles of the server, terminal, and user.

[1485] Quiz Generation

[1486] The server obtains information about the product (e.g., product name, features, price, specifications, use, etc.) and automatically generates quiz questions using a generative AI model. The difficulty and number of questions generated can be customized based on pre-set parameters. A machine learning model (e.g., GPT-3) is suitable as the generative AI model to use.

[1487] View Quiz

[1488] The user device receives the quiz questions from the server and displays them to the user. The device displays the questions in an easy-to-read format and provides an interface that allows the user to enter answers to each question. The device also uses a camera and microphone to collect the user's facial expressions and voice, and inputs this data into an emotion engine to analyze the user's emotions in real time. Smartphones and tablets are often used as devices.

[1489] Emotion recognition

[1490] The emotion engine analyzes the user's facial expressions and voice to determine their emotions. For example, it can use Microsoft Azure Cognitive Services or Google Cloud Vision API. The analyzed emotion data is sent to the server via the device.

[1491] User Answers

[1492] The user answers quiz questions on the device. The user enters their answer in the input field for each quiz question and completes the answer for all questions. The emotion engine recognizes the user's emotions in real time and automatically adjusts the difficulty of the quiz questions as needed.

[1493] Evaluating answers

[1494] The server receives the answers submitted by the user and evaluates them by comparing them with a predefined list of correct answers. The server checks each answer in turn, determines whether it matches the correct answer, and calculates a score. It may also influence the evaluation based on emotional data.

[1495] Deciding whether to purchase

[1496] The server determines whether the user can purchase the product based on the evaluation result of the user's answers. In this process, it is checked whether the user's score meets a predetermined standard (for example, whether all questions are answered correctly).

[1497] User Notification

[1498] The server evaluates eligibility and notifies the user based on the results. If eligible, the notification includes a message such as "Congratulations, you are now eligible to purchase this item." If not eligible, the notification displays a message such as "Sorry, you must answer all questions correctly. Please try again."

[1499] Specific examples

[1500] As a specific example, consider the purchase of a smartphone product called "XYZ Phone."

[1501] 1. Based on information about the "XYZ Phone," the server uses a generative AI model to generate five intermediate-level quiz questions, as shown below.

[1502] "What is the screen size of the XYZ Phone in inches?"

[1503] "What is the battery capacity of XYZ Phone?"

[1504] "What OS does XYZ Phone use?"

[1505] "What is the resolution of the main camera on the XYZ Phone?"

[1506] "What year was XYZ Phone released?"

[1507] 2. The user device displays these quiz questions to the user and begins analyzing the user's facial expressions and voice using an emotion engine.

[1508] 3. The user enters answers to each quiz question. During this time, the emotion engine collects the user's emotional data in real time and automatically adjusts the difficulty of the quiz as needed.

[1509] 4. The server receives the user's answer and evaluates it based on a list of correct answers (e.g., "6.5 inches," "4500mAh," "Android," "48 megapixels," "2023").

[1510] 5. The server calculates the user's score based on the evaluation results that take into account the emotional data, and if all answers are correct, grants the user the right to purchase the product.

[1511] 6. The server notifies the user whether they are eligible to purchase.

[1512] Example of a generative AI model prompt

[1513] Generate quiz questions based on your product database, such as: Include information about the product, such as its features, price, specifications, and uses.

[1514] 1. What is the screen size of the product?

[1515] 2. What is the battery capacity of the product?

[1516] 3. What OS does the product use?

[1517] 4. What is the resolution of the product's main camera?

[1518] 5. What year was the product released?

[1519] This invention allows users to enjoyably learn about products while taking their emotions into consideration, and makes it possible for them to make purchasing decisions interactively.

[1520] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1521] Step 1:

[1522] The server obtains information about the product. As input, it obtains information such as the product name, features, price, specifications, and use from the product database. As output, it obtains the obtained product information. This data is used to generate the next quiz questions.

[1523] Step 2:

[1524] The server uses the generative AI model to automatically generate quiz questions. As input, the product information obtained in step 1 is passed to the generative AI model as a prompt sentence. The generated quiz questions are obtained as output. An example of a prompt sentence is, "Based on the product database, please generate quiz questions such as the following. Please include information about the product's features, price, specifications, and uses. 1. What is the screen size of the product in inches?"

[1525] Step 3:

[1526] The server sends the generated quiz questions to the user terminal. As input, it uses the quiz questions generated in step 2. As output, it obtains the quiz questions to be sent to the user terminal.

[1527] Step 4:

[1528] The user terminal displays quiz questions to the user. As input, it receives quiz questions sent from the server. As output, it provides a state in which the user can visually confirm the questions. At this time, it also displays an interface for accepting user input.

[1529] Step 5:

[1530] The user device collects the user's facial expression and voice data. As input, it uses a camera and microphone to capture the user's facial expression and voice in real time. As output, it obtains the collected facial expression and voice data. This data is passed to the emotion engine.

[1531] Step 6:

[1532] The emotion engine analyzes the collected data to recognize emotions. As input, it uses the user's facial expression and voice data collected in step 5. As output, it obtains analyzed emotion data, which is sent to the server.

[1533] Step 7:

[1534] The user answers the quiz questions. As input, the user inputs their answer into the input field, referring to the quiz questions displayed on the terminal. As output, the user's answer data is obtained. This data is sent to the server.

[1535] Step 8:

[1536] The server evaluates the user's answers. As input, it uses the user's answer data, a predefined list of correct answers, and the recognized emotion data. As output, it obtains the evaluation result and the user's score. This evaluation includes scoring based on the list of correct answers and the emotion data.

[1537] Step 9:

[1538] The server decides whether the user can purchase the product. As input, it uses the evaluation result from step 8 and the user's score. As output, it gets a decision on whether to purchase the product.

[1539] Step 10:

[1540] The server notifies the user device whether they are eligible to purchase. The input is the result of the decision made in step 9. The output is a message that is displayed to the user, such as "Congratulations, you are now eligible to purchase the product" or "Sorry, you must answer all questions correctly. Please try again."

[1541] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1542] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1543] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1544] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1545] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1546] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1547] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1548] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1549] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1550] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1551] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1552] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1553] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1554] 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.

[1555] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1556] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1557] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1558] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1559] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1560] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1561] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1562] The following is further disclosed regarding the above embodiment.

[1563] (Claim 1)

[1564] A means for generating quiz questions based on information about the product;

[1565] a means for displaying the generated quiz questions on a user terminal;

[1566] means for receiving a response from the user through the user terminal;

[1567] means for evaluating the user's answer and determining whether it is correct;

[1568] means for determining whether the user is allowed to purchase the product based on the determination result;

[1569] means for notifying the user of eligibility for purchase based on the determination;

[1570] A system including:

[1571] (Claim 2)

[1572] The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

[1573] (Claim 3)

[1574] 2. The system according to claim 1, further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions.

[1575] "Example 1"

[1576] (Claim 1)

[1577] A means for generating quiz questions based on information about the product;

[1578] a means for displaying the generated quiz questions on a user terminal;

[1579] means for receiving a response from the user through the user terminal;

[1580] means for evaluating the user's answer and determining whether it is correct;

[1581] means for determining whether the user is allowed to purchase the product based on the determination result;

[1582] means for notifying the user of eligibility for purchase based on the determination;

[1583] A means for inputting a prompt sentence into a generation AI model based on the acquired product information and generating quiz questions;

[1584] a means for displaying each of the generated quiz questions on a user terminal in an easy-to-read format and providing an interface for the user to input answers;

[1585] A system including:

[1586] (Claim 2)

[1587] The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

[1588] (Claim 3)

[1589] 2. The system according to claim 1, further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions.

[1590] "Application Example 1"

[1591] (Claim 1)

[1592] A means for generating quiz questions based on information about the product;

[1593] a means for displaying the generated quiz questions on a user terminal;

[1594] means for receiving a response from the user through the user terminal;

[1595] means for evaluating the user's answer and determining whether it is correct;

[1596] means for determining whether the user is allowed to purchase the product based on the determination result;

[1597] means for notifying the user of eligibility for purchase based on the determination;

[1598] means for awarding a reward if the user passes the quiz;

[1599] A system including:

[1600] (Claim 2)

[1601] The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

[1602] (Claim 3)

[1603] 2. The system according to claim 1, further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions.

[1604] "Example 2: Combining Emotion Engines"

[1605] (Claim 1)

[1606] A means for generating quiz questions based on information about the product;

[1607] a means for displaying the generated quiz questions on a user terminal;

[1608] means for receiving a response from the user through the user terminal;

[1609] means for evaluating the user's answer and determining whether it is correct;

[1610] means for determining whether the user is allowed to purchase the product based on the determination result;

[1611] means for notifying the user of eligibility for purchase based on the determination;

[1612] means for recognizing a user's emotion and adjusting the difficulty of the quiz questions based on the emotion data;

[1613] A system including:

[1614] (Claim 2)

[1615] The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

[1616] (Claim 3)

[1617] 2. The system according to claim 1, further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions.

[1618] "Application example 2 when combining emotion engines"

[1619] (Claim 1)

[1620] A means for generating quiz questions based on information about the product;

[1621] a means for displaying the generated quiz questions on a user terminal;

[1622] means for receiving a response from the user through the user terminal;

[1623] means for evaluating the user's answer and determining whether it is correct;

[1624] means for determining whether the user is allowed to purchase the product based on the determination result;

[1625] means for notifying the user of eligibility for purchase based on the determination;

[1626] A means for recognizing emotions by analyzing the user's facial expressions and voice;

[1627] a means for adjusting the difficulty of the quiz questions using the recognized emotion data;

[1628] A system including:

[1629] (Claim 2)

[1630] The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

[1631] (Claim 3)

[1632] 2. The system according to claim 1, further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions. [Explanation of symbols]

[1633] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for generating quiz questions based on information about the product; a means for displaying the generated quiz questions on a user terminal; means for receiving a response from the user through the user terminal; means for evaluating the user's answer and determining whether it is correct; means for determining whether the user is allowed to purchase the product based on the determination result; means for notifying the user of eligibility for purchase based on the determination; A system including:

2. The system according to claim 1, wherein the means for generating quiz questions based on information about the product automatically generates quiz questions using a generation AI model.

3. The system according to claim 1 , further comprising means for enabling customization of the difficulty level and number of questions of the quiz questions.

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