System

Abstract

To provide a system.SOLUTION: A system includes: means for inputting user attributes; means for generating an answer to the user's question by inputting a specific prompt text into a generative AI model; means for classifying the generated answers by category; a feeling engine for analyzing the feeling of the user; and means for generating personalized child-rearing information on the basis of the attributes, the analyzed feeling, and the classified answers.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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] The worries and problems of raising children vary depending on each individual's family environment, region, culture, etc., and in many cases cannot be solved with general advice or information. In addition, there is an abundance of information, making it difficult to find useful information that is appropriate for one's own situation. [Means for solving the problem]

[0005] As a means for solving this problem, the system of the present invention includes a means for inputting user attributes, a means for generating answers to the user's questions by inputting specific prompt sentences into a generative AI model, a means for classifying the generated answers by category, an emotion engine for analyzing the user's emotions, and a means for generating personalized parenting information based on the attributes, the analyzed emotions, and the classified answers. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12]FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] 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.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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 wide area network (WAN) and / or a local area network (LAN).

[0018] 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.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with an indicator (e.g., 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. The user may be interpreted as a user of the present disclosure.

[0020] 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 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0024] 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.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[0029] "Example 2"

[0030] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[0031] The process flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: The user enters their attributes through the system interface. For example, the user may enter information such as "living in Japan, single parent family, child is 5 years old, living in an urban area."

[0034] Step 2: Next, the user enters a question about parenting, such as "What is the appropriate amount of sleep for a 5-year-old child?"

[0035] Step 3: The entered question is sent to a generative AI question-answering system, which generates an appropriate answer.

[0036] Step 4: The generated answers are classified into categories based on the user's attributes and the content of the question, for example, "sleep," "food," "education," etc.

[0037] Step 5: Based on these categorized answers, the system generates a personalized parenting book that can be borrowed from the digital library, allowing users to efficiently access information that is relevant to them.

[0038] Example 1

[0039] Next, a description will be given of Example 1 of the embodiment 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".

[0040] Conventional child-rearing information systems have difficulty providing personalized information based on the individual attributes of users. In addition, the information provided is general and often does not meet the specific needs of users. Furthermore, searching and obtaining information is cumbersome, making it difficult to efficiently obtain the information required.

[0041] 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.

[0042] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating an e-book containing personalized parenting information based on the classified answers, and a means for making the e-book available for borrowing from a digital library. This makes it possible to efficiently provide personalized parenting information based on the individual attributes of the user.

[0043] "User attributes" refers to information entered by the user, such as country, region, family composition, ages of parents and children, and living environment.

[0044] A "generative AI model" refers to an artificial intelligence model that generates appropriate answers to users' questions.

[0045] A "question answering system" refers to a system that uses a generative AI model to generate answers to users' questions.

[0046] A "categorical classification means" refers to a means for classifying the generated answers into categories such as "sleep," "food," and "education."

[0047] "Personalized parenting information" refers to parenting information that is individually customized based on the user's attributes.

[0048] "E-Book" refers to books provided in digital format, including personalized parenting information.

[0049] A "digital library" refers to a digital platform where e-books can be borrowed online.

[0050] This invention is a system in which a user inputs his / her own attributes, sends questions about child-rearing to a generative AI model, and receives answers. A specific embodiment of this system will be described below.

[0051] First, a user accesses the system interface through a web browser or a mobile application. This interface provides fields for the user to input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). Once the user inputs the attributes, the server receives this data and stores it in a database (e.g., MySQL (registered trademark), PostgreSQL).

[0052] Next, the user enters a parenting question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?") into the interface. This question is sent to the server, which sends the question along with the user's attribute data to a generative AI model (e.g., GPT-4 (registered trademark) from OpenAI (registered trademark). The generative AI model generates an appropriate answer based on the question and attribute data and sends it back to the server.

[0053] The server receives the generated answers and classifies them into categories such as "sleep", "food", "education", etc. This classification makes it easier for users to search for the information later. The classified answers are stored in a database.

[0054] Next, the server generates an e-book containing personalized parenting information based on the classified answers, and uploads the e-book to a digital library (e.g., Google Books API) in PDF or ePub format. The user can then access the digital library and borrow the e-book personalized to them.

[0055] As a concrete example, if the user enters the following attributes:

[0056] Country: Japan

[0057] Region: Urban

[0058] Family structure: Single parent family

[0059] Parents' age: 30

[0060] Child's age: 5 years old

[0061] The user then enters the following question:

[0062] "What is the appropriate amount of sleep for a 5-year-old?"

[0063] This question is then sent to a generative AI model, which generates an answer like this:

[0064] "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours."

[0065] The server categorizes this answer under the "sleep" category and, along with other related answers, generates an e-book containing personalized parenting information that can be borrowed from a digital library.

[0066] Example of a prompt to be input to a generative AI model:

[0067] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[0068] Q: What is the appropriate amount of sleep for a 5 year old?

[0069] By sending this prompt to a generative AI model, an appropriate answer is obtained. In this way, users can efficiently obtain specific parenting information based on their own attributes.

[0070] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0071] Step 1:

[0072] The user enters the attributes.

[0073] Users access the system interface through a web browser or mobile application and input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). The input attribute data is sent to the server.

[0074] Input: User attribute data

[0075] Output: Attribute data sent to the server

[0076] Step 2:

[0077] The server stores the attribute data.

[0078] The server stores the received attribute data in a database (e.g., MySQL, PostgreSQL). This data is used for later processing.

[0079] Input: User attribute data

[0080] Output: Attribute data stored in a database

[0081] Step 3:

[0082] The user enters a question.

[0083] The user inputs a question about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") into the interface. The input question is sent to the server.

[0084] Input: User question

[0085] Output: The question sent to the server.

[0086] Step 4:

[0087] The server sends the question to the generative AI model.

[0088] The server sends the user's question and attribute data to a generative AI model (e.g., OpenAI's GPT-4) in the form of a prompt:

[0089] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[0090] Q: What is the appropriate amount of sleep for a 5 year old?

[0091] Input: User questions and attribute data

[0092] Output: The prompt sent to the generative AI model

[0093] Step 5:

[0094] A generative AI model generates the answer.

[0095] The generative AI model generates an appropriate answer based on the received prompt. For example, it may generate an answer like, "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours." The generated answer is then sent back to the server.

[0096] Input: Prompt statement

[0097] Output: The generated answer

[0098] Step 6:

[0099] The server receives the responses and categorizes them.

[0100] The server receives the answers sent back by the generative AI model and then classifies the answers into categories such as "sleep," "food," "education," etc. The classified answers are then stored in a database.

[0101] Input: Generated Answer

[0102] Output: Answers sorted by category

[0103] Step 7:

[0104] A server generates an e-book containing personalized parenting information.

[0105] The server generates an e-book containing personalized parenting information based on the user's answers, in PDF or ePub format, and uploads it to the digital library.

[0106] Input: Answers sorted by category

[0107] Output: personalized e-book

[0108] Step 8:

[0109] A user borrows an e-book from a digital library.

[0110] Users can access the digital library and borrow e-books that are personalized to them, allowing them to efficiently obtain the information they need.

[0111] Input: Digital Library Access

[0112] Output: Borrowed e-books

[0113] (Application example 1)

[0114] Next, a description will be given of Application Example 1 of Form 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."

[0115] In modern child-rearing, parents need a lot of information, and in particular, personalized advice tailored to the circumstances of each family. However, conventional information sources provide only general information, making it difficult to meet individual needs. In addition, even in child-rearing consultations at brick-and-mortar stores, the number of experts is limited, making it difficult to obtain fast and accurate advice. This causes the problem that parents have to spend a lot of time and effort to obtain appropriate child-rearing information, which increases stress.

[0116] 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.

[0117] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question answering system, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, a means for displaying the generated personalized child-rearing information via a smart device, and a means for suggesting related products and services. This allows users to quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores efficient and effective.

[0118] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[0119] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[0120] A "categorical classification mechanism" is a function that classifies the generated answers into specific categories (e.g., sleep, food, education, etc.).

[0121] "Personalized parenting information" is parenting information that is individually customized based on the user's attributes and questions.

[0122] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[0123] The "means for suggesting related products and services" is a function for suggesting products and services suitable for the user based on the generated child-rearing information.

[0124] A "digital library" is an electronically accessible library or facility that provides books and information in digital format.

[0125] To implement the present invention, a server, a smart device (such as a smartphone or smart glasses), and a generative AI model are used. Specific embodiments are described below.

[0126] Server Roles

[0127] The server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI question-answering system, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means for displaying the generated personalized parenting information via a smart device, and a means for suggesting related products and services.

[0128] The role of smart devices

[0129] The smart device provides an interface for users to input their attributes and questions, and also serves as a device to display the generated personalized parenting information and receive relevant product and service suggestions.

[0130] The role of generative AI models

[0131] The generative AI model generates appropriate answers based on the user's attributes and questions. Specifically, it uses OpenAI's API to generate prompts for user input and retrieve answers.

[0132] Data processing and calculation

[0133] 1. Data entry: Users enter their own attributes (e.g. country, region, family composition, ages of parents and children, environment, etc.) and questions via their smart device.

[0134] 2. Prompt generation: The server generates a prompt based on the input data to send to the generative AI model.

[0135] 3. AI response generation: A generative AI model generates appropriate answers based on the prompts.

[0136] 4. Answer Categorization: The server categorizes the generated answers into categories.

[0137] 5. Generating personalized information: The server generates personalized parenting information based on the classified answers.

[0138] 6. Displaying information: The smart device displays the generated personalized parenting information to the user.

[0139] 7. Product and service suggestion: The server suggests relevant products and services based on the generated parenting information.

[0140] Examples

[0141] The user puts on the smart glasses at a physical store and enters the following information:

[0142] Attributes: "Living in Japan, single parent family, child age 5, living in urban area"

[0143] Question: "What is the appropriate amount of sleep for a 5-year-old?"

[0144] Examples of prompt statements

[0145] User characteristics: Resident in Japan, single parent family, child age 5, living in urban area

[0146] Q: What is the appropriate amount of sleep for a 5 year old?

[0147] Generate a suitable answer.

[0148] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[0149] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0150] Step 1:

[0151] The user uses a smart device to input his / her attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.) and questions. The input data is sent from the smart device to the server.

[0152] Step 2:

[0153] The server generates a prompt to send to the generative AI model based on the received user attributes and question. Specifically, it creates a prompt sentence that combines the user attributes and question in text format.

[0154] Step 3:

[0155] The server sends the generated prompt sentence to the generative AI model, which generates an appropriate answer based on the prompt sentence, and the generated answer is sent back to the server.

[0156] Step 4:

[0157] The server receives the generated answers and classifies them into categories (e.g., sleep, food, education, etc.) The categorized answers are stored in a database.

[0158] Step 5:

[0159] The server generates personalized parenting information based on the categorized answers. Specifically, the server creates individually customized parenting information by combining the user's attributes and the categorized answers.

[0160] Step 6:

[0161] The server transmits the generated personalized child-rearing information to the smart device, which displays the received information to the user.

[0162] Step 7:

[0163] The server proposes related products and services based on the generated parenting information, and the information on the proposed products and services is provided to the user via the smart device.

[0164] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[0165] Example 2

[0166] Next, a second embodiment of the second embodiment will be described. 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."

[0167] Conventional child-rearing support systems do not adequately provide personalized information based on the individual attributes and questions of users. They also lack a way to efficiently manage the generated information and make it easily accessible to users. As a result, users have to spend a lot of time and effort to obtain the information that is most suitable for them.

[0168] 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.

[0169] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating a personalized information collection based on the classified answers, and a means for making it possible to borrow the generated information collection from a digital library. This enables users to efficiently obtain optimal information based on their own attributes and questions.

[0170] "User attributes" refers to personal information and environmental information that users input into the system, including country, region, family composition, parent and child ages, environment, etc.

[0171] A "generative AI model" is a type of artificial intelligence that uses natural language processing technology to generate answers to users' questions.

[0172] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[0173] "Means of generating an answer" refers to the functions and processes for generating answers to users' questions using a generative AI model.

[0174] "Categorization tools" refers to the functions or processes used to categorize the responses generated according to specific themes or topics.

[0175] A "personalized information collection" is a collection of information that is individualized based on a user's attributes and questions.

[0176] A "digital library" is an online platform that provides electronically stored information and materials.

[0177] "Borrowing enablement" refers to the features or processes that allow users to download or access personalized collections of information from the digital library.

[0178] This invention is a system in which a user inputs their own attributes, generates answers to questions about child-rearing using a generative AI model, classifies the answers by category, and generates a personalized collection of information. A specific embodiment of this system is described below.

[0179] User attribute input

[0180] Users input their demographic information through the system's interface, which can be a web page or a mobile application. The demographic information includes country, region, family structure, parent and child ages, environment, etc. This information is then used in subsequent processing to generate personalized answers.

[0181] Input questions about child rearing

[0182] Users use the same interface to input a parenting question, such as "What is an appropriate amount of sleep for a 5-year-old?", which is then used as a prompt to be sent to the generative AI model.

[0183] Submit a question

[0184] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[0185] Generate answers

[0186] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[0187] Categorizing answers

[0188] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[0189] Generate personalized information collections

[0190] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[0191] Borrowing from the Digital Library

[0192] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[0193] Examples of concrete examples and prompts

[0194] For example, if a user inputs the question "What is an appropriate amount of sleep for a 5-year-old child?", the system processes it as follows:

[0195] 1. The user enters the following attribute information: "Living in Japan, single-parent family, child is 5 years old, living in an urban area."

[0196] 2. The user types the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[0197] 3. The device sends this question to a generative AI model (e.g. GPT-4).

[0198] 4. The server uses the generative AI model to generate the answer, "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours."

[0199] 5. The server classifies this answer into the category "Sleep."

[0200] 6. The server generates a personalized collection of information that includes the answer.

[0201] 7. A user borrows this collection of information from a digital library.

[0202] Example prompt:

[0203] "A user living in Japan, single parent household, 5-year-old child, living in an urban area, is asking about the appropriate amount of sleep for a 5-year-old child. Please generate an appropriate answer."

[0204] In this way, the system provides the most relevant information based on the user's attributes and questions.

[0205] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0206] Step 1:

[0207] The user accesses the system interface and inputs his / her own attribute information. The input attribute information includes country, region, family structure, age of parents and children, environment, etc. This information is used in later processing to generate personalized answers. The input attribute information is sent from the terminal to the server.

[0208] Input: User attribute information (country, region, family structure, age of parents and children, environment, etc.)

[0209] Output: Attribute information sent to the server

[0210] Step 2:

[0211] The user uses the same interface to input a parenting question, for example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is used as a prompt to be sent to the generative AI model. The input question is then sent from the device to the server.

[0212] Input: A user question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?")

[0213] Output: The question sent to the server.

[0214] Step 3:

[0215] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[0216] Input: Attribute information and question stored on the server

[0217] Output: The prompt sent to the generative AI model

[0218] Step 4:

[0219] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[0220] Input: The prompt sent to the generative AI model

[0221] Output: The generated answer (e.g. "The appropriate amount of sleep for a 5-year-old child is 10-12 hours")

[0222] Step 5:

[0223] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[0224] Input: Generated Answer

[0225] Output: Answers sorted by category

[0226] Step 6:

[0227] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[0228] Input: Answers sorted by category

[0229] Output: Personalized information collection (PDF format)

[0230] Step 7:

[0231] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[0232] Input: A personalized search query

[0233] Output: A personalized collection of downloaded information

[0234] (Application example 2)

[0235] Next, a description will be given of Application Example 2 of Form 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."

[0236] Conventional child-rearing support systems have problems in that it is difficult to provide personalized advice based on the user's attributes, and they do not recommend related products or books, meaning that users cannot efficiently obtain the information and products they need. Furthermore, there is a lack of means to provide personalized information in a digital format, which means that it is difficult for users to easily carry the information with them.

[0237] 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.

[0238] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means for generating a personalized parenting book based on the classified answers, a means for recommending related products and books based on the generated answers, and a means for providing the personalized parenting book in a digital format. This allows users to obtain personalized advice based on their own attributes, and by receiving recommendations of related products and books, it becomes possible to efficiently obtain necessary information and products. Furthermore, providing personalized information in a digital format makes it easier for users to carry information around.

[0239] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[0240] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[0241] The "categorical classification means" is a function that classifies the generated answers into categories such as sleep, food, education, etc.

[0242] The "Personalized Parenting Book" is a book that compiles information about parenting that is individually customized based on the user's attributes and questions.

[0243] "Means for recommending related products and books" is a function that suggests products and books suitable for the user based on the generated answers.

[0244] "Means of providing in digital format" refers to the function of providing users with a personalized parenting book in a digital format such as an e-book or PDF.

[0245] In order to implement this invention, the server, the terminal, and the user must each fulfill a specific role. Specific embodiments are described below.

[0246] Server Roles

[0247] The server uses the following hardware and software to process and calculate data.

[0248] Hardware: High-performance server machine

[0249] Software: Python, OpenAI API

[0250] The server first provides a means for users to input their attributes. Then, it uses a generative AI-based question-answering system to generate answers to the user's questions. The generated answers are classified into categories. Furthermore, the server recommends related products and books based on the generated answers, and provides personalized parenting books in digital format.

[0251] Terminal Roles

[0252] A terminal (e.g., a smartphone) provides an interface with a user using the following hardware and software:

[0253] Hardware: Smartphone

[0254] Software: Mobile Application

[0255] The terminal provides an interface for the user to input his / her attributes and also provides an interface for the user to input questions about child-rearing, so that the user can easily input questions and receive answers.

[0256] User Roles

[0257] The user uses the terminal to perform the following operations:

[0258] 1. Enter your attributes.

[0259] 2. Enter your parenting questions.

[0260] 3. Review the generated answers.

[0261] 4. Get recommendations for related products and books.

[0262] 5. Receive your personalized parenting book in digital format.

[0263] Examples

[0264] For example, if the user enters the following attributes:

[0265] Country: Japan

[0266] Region: Urban

[0267] Family structure: Single parent household

[0268] Parents' age: 30

[0269] Child's age: 5 years

[0270] The user then enters the following question:

[0271] Q: What is the appropriate amount of sleep for a 5 year old?

[0272] The server sends the following prompt to the generation AI:

[0273] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[0274] Q: What is the appropriate amount of sleep for a 5 year old?

[0275] answer:

[0276] The generative AI generates appropriate answers based on the prompt text. The generated answers are categorized and related products and books are recommended. Finally, a personalized parenting book is provided to the user in digital format.

[0277] In this way, users can receive personalized advice based on their attributes, and can also receive recommendations for related products and books, allowing them to efficiently obtain the information and products they need. In addition, providing personalized information in a digital format makes it easier for users to carry the information with them.

[0278] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0279] Step 1:

[0280] The server provides an interface for inputting user attributes to the terminal.

[0281] Input: None

[0282] Output: User attribute input interface

[0283] Specific operation: The server displays a form on the terminal where the user can enter information such as country, region, family composition, ages of parents and children, and environment.

[0284] Step 2:

[0285] The user uses the terminal to input his / her attributes.

[0286] Input: User attribute input interface

[0287] Output: User attribute data

[0288] Specific operations: The user enters his / her own attribute information into the form on the terminal and presses the submit button.

[0289] Step 3:

[0290] The server provides an interface for inputting questions about child rearing to the terminal.

[0291] Input: User attribute data

[0292] Output: Question input interface

[0293] Specific operation: The server receives the user attribute data and then displays a form on the terminal for entering questions about child-rearing.

[0294] Step 4:

[0295] A user uses a terminal to input a question about child rearing.

[0296] Input: Question input interface

[0297] Output: Question data

[0298] Specific actions: The user enters a question about child-rearing into a form on the terminal and presses the submit button.

[0299] Step 5:

[0300] The server sends user attribute data and question data to the generative AI to generate an answer.

[0301] Input: User attribute data, question data

[0302] Output: Answer data

[0303] Specific operation: The server generates the following prompt sentence and sends it to the generation AI.

[0304] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[0305] Q: What is the appropriate amount of sleep for a 5 year old?

[0306] answer:

[0307] The generative AI generates an answer based on this prompt and returns it to the server.

[0308] Step 6:

[0309] The server categorizes the generated answers.

[0310] Input: Answer data

[0311] Output: Categorical response data

[0312] Specific behavior: The server classifies the generated answers into categories such as "sleep," "food," and "education."

[0313] Step 7:

[0314] The server recommends related products and books based on the category-specific answer data.

[0315] Input: Categorical response data

[0316] Output: Recommendation data

[0317] Specific operation: The server searches the database for related products and books corresponding to each category and generates a recommendation list.

[0318] Step 8:

[0319] The server generates a personalized parenting book and provides it in a digital format.

[0320] Input: Categorical answer data, recommendation data

[0321] Output: Personalized Parenting Book (digital format)

[0322] Specific operation: The server combines the categorical answer data and the recommendation data to generate a personalized parenting book and provides it to the user in a digital format such as an e-book or PDF.

[0323] Step 9:

[0324] The user receives and views the personalized parenting book using the terminal.

[0325] Input: Personalized Parenting Book (digital format)

[0326] Output: User browsing data

[0327] Specific operations: The user uses the terminal to download and view the provided digital parenting book.

[0328] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0329] "Example 1"

[0330] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[0331] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[0332] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[0333] "Example 2"

[0334] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[0335] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[0336] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[0337] The process flow of each embodiment will be described below.

[0338] "Example 1"

[0339] Step 1: The user enters their attributes (country, region, family composition, ages of parents and children, environment, etc.) and questions into the system.

[0340] Step 2: The system uses a generative AI question-answering system to generate answers to the user's questions.

[0341] Step 3: The system categorizes the generated answers into categories.

[0342] Step 4: The system uses the emotion engine to generate emotion from the user's text or voice input.

[0343] Analyze emotions.

[0344] Step 5: Based on the emotions analyzed by the system, a personalized parenting book is generated based on the categorized answers.

[0345] Step 6: The system provides the user with the personalized parenting book generated by the system.

[0346] Example 1

[0347] Next, a description will be given of Example 1 of the embodiment 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".

[0348] Conventional child-rearing support systems do not provide enough personalized information based on the individual attributes and emotions of users, making it difficult for users to obtain the specific and appropriate advice they need. In addition, the generated information is centralized, and there is a lack of support that corresponds to the user's emotions, which leads to low user satisfaction.

[0349] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, and an emotion engine for analyzing the emotions of the user. This makes it possible to provide specific and appropriate advice based on the individual attributes and emotions of the user.

[0350] "User attributes" refers to personal information and environmental information that users input into the system, and specifically includes country, region, family composition, ages of parents and children, environment, etc.

[0351] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions, and refers to a model based on natural language processing technology.

[0352] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[0353] "Categorization tools" refers to methods or techniques for categorizing the responses generated according to specific themes or topics.

[0354] "Personalized parenting information" refers to parenting information and advice that is customized based on the user's attributes and questions.

[0355] An "emotion engine" refers to technology or a system that analyzes emotions from a user's text or voice input and responds appropriately based on those emotions.

[0356] A "digital library" refers to an online library system that allows users to access and borrow electronically stored books and information.

[0357] The present invention is a system that allows users to input their own attributes and ask questions about child-rearing, and then uses a generative AI model to provide appropriate answers, classify the answers by category, and generate personalized child-rearing information. A specific embodiment of this system is described below.

[0358] User attribute input

[0359] A user uses a terminal (e.g., a PC or smartphone) to access the system's interface. The interface is provided through a web browser or a mobile application. The user inputs attribute information such as country, region, family structure, ages of parents and children, and environment. This information is sent from the terminal to the server and stored in a database.

[0360] Enter your question

[0361] The user inputs a specific question about child rearing. For example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is also sent from the terminal to the server.

[0362] Answer generation by question answering system

[0363] The server sends the received question to a generative AI model (for example, a model based on natural language processing technology). The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." This generative AI model runs on the cloud and generates answers based on large amounts of data.

[0364] Responses categorized

[0365] The server categorizes the generated answers into categories based on the user's attributes and the content of the question. For example, it categorizes the answers into the category of "sleep." This categorization is performed using natural language processing technology.

[0366] Generating personalized parenting information

[0367] The server generates personalized parenting information for the user based on the classified answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the user's attributes.

[0368] Borrowing from the Digital Library

[0369] A user can borrow the generated parenting information from the digital library. The digital library is operated using a cloud storage service (for example, an online storage service). A user accesses the digital library through a terminal and downloads information.

[0370] Emotion analysis using emotion engine

[0371] When the user enters additional questions or comments, the server uses an emotion engine (e.g., a system based on emotion analysis technology) to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired."

[0372] Emotion-Based Personalization

[0373] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions such as "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized according to the user's emotions.

[0374] Examples

[0375] Examples of prompt statements

[0376] The user enters the following prompt text:

[0377] "What is the appropriate amount of sleep for a 5-year-old?"

[0378] In this way, the system provides specific and appropriate advice based on the user's individual attributes and feelings, providing more effective support for the user in raising their children.

[0379] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0380] Step 1: Enter user attributes

[0381] A user uses a terminal to access the system interface and inputs attribute information such as country, region, family structure, ages of parents and children, and environment. The input information is sent from the terminal to the server. The server stores this information in a database. The input data is the user's attribute information, and the output is the attribute information stored in the database.

[0382] Step 2: User enters question

[0383] A user uses a terminal to input a specific question about child-rearing. For example, the user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?" The input question is sent from the terminal to a server. The server receives the question and proceeds to the next processing step. The input data is the user's question, and the output is the question sent to the server.

[0384] Step 3: Generate answers using the question-answering system

[0385] The server sends the received question to the generative AI model. The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generated answer is returned to the server. The input data is the user's question, and the output is the answer generated by the generative AI model.

[0386] Step 4: Categorize responses

[0387] The server classifies the generated answers into categories based on the user's attributes and the content of the question. For example, it classifies them into the category of "sleep." This classification is performed using natural language processing technology. The input data are the generated answers, and the output is the answers classified by category.

[0388] Step 5: Generate personalized parenting information

[0389] The server generates parenting information personalized for the user based on the categorized answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the attributes of the user. The input data are the categorized answers, and the output is personalized parenting information.

[0390] Step 6: Borrow from the Digital Library

[0391] A user can borrow the generated parenting information from the digital library. The user accesses the digital library through a terminal and downloads the information. The digital library is operated using a cloud storage service. The input data is the personalized parenting information, and the output is the information downloaded by the user.

[0392] Step 7: Sentiment Analysis with the Sentiment Engine

[0393] When the user enters additional questions or comments, the server uses the emotion engine to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" or "tired." The input data is the user's text input or voice input, and the output is the analyzed emotion information.

[0394] Step 8: Emotional personalization

[0395] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions of "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized with content according to the user's emotions. The input data is the analyzed emotion information, and the output is parenting information personalized based on the emotions.

[0396] (Application example 1)

[0397] Next, a description will be given of Application Example 1 of Form 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."

[0398] In modern child-rearing, parents need a variety of information, and in particular, personalized advice tailored to each family environment and child's characteristics is required. However, conventional information provision systems have difficulty in providing appropriate advice according to the user's emotions and specific situations. In addition, there is a lack of information provision linked to the purchase of child-rearing related products in brick-and-mortar stores and consultation services, which means that parents cannot efficiently obtain the information and support they need.

[0399] 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.

[0400] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice and solutions based on the analyzed emotions, and a means for linking with child-rearing-related product purchases and consultation services at brick-and-mortar stores. This allows users to receive personalized advice according to their attributes and emotions, and by linking with support at brick-and-mortar stores, more effective child-rearing support is possible.

[0401] "Means for inputting user attributes" refers to an interface that allows users to input information such as their country, region, family structure, ages of parents and children, and environment.

[0402] "Means of generating answers to users' questions by utilizing a question-answering system with generative AI" refers to a system that uses generative AI to generate appropriate answers to questions entered by users.

[0403] "Means for classifying generated answers into categories" refers to a system for classifying answers generated by the generative AI into categories such as sleep, food, and education.

[0404] The "means for generating a personalized parenting book" is a system for generating a parenting book that compiles information most suitable for the user based on answers categorized into categories.

[0405] The "means including an emotion engine for analyzing user's emotions" is a system including an engine for analyzing emotions from a user's text input or voice input.

[0406] The "means for providing personalized advice or solutions based on analyzed emotions" is a system for providing optimal advice or solutions to a user based on emotions analyzed by an emotion engine.

[0407] The "means of linking the purchase of child-rearing related products and consultation services at physical stores" is a system that links with child-rearing related products and consultation services offered at physical stores, allowing users to receive the information and support they need at physical stores.

[0408] A system for implementing this invention has the following configuration. First, a user inputs their own attributes using a smartphone. These attributes include country, region, family structure, ages of parents and children, and environment. Next, the user inputs a question about child-rearing. This question is sent to a question-answering system using generative AI, which generates an appropriate answer.

[0409] The generated answers are categorized into categories such as sleep, food, and education, allowing users to efficiently obtain the information they need. In addition, the emotion engine analyzes emotions from the user's text and voice input. For example, if a user enters "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tired."

[0410] Based on the analyzed emotions, personalized advice and solutions are provided. This allows users to receive the best advice based on their own emotions. In addition, by linking with the purchase of child-rearing related products and consultation services in physical stores, users can receive the support they need at physical stores.

[0411] The following hardware and software are used to realize this system. A smartphone is used as the hardware. Python, OpenAI API, and TextBlob are used as the software. Python is used to implement the program, and OpenAI API is used for the generative AI model question answering system. TextBlob is used for sentiment analysis.

[0412] For example, if a user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?", the generative AI model will generate an appropriate answer. Furthermore, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tiredness" and provide corresponding advice.

[0413] An example of a prompt is as follows:

[0414] "What is the appropriate amount of sleep for a 5-year-old?"

[0415] "My child is having trouble falling asleep"

[0416] "What child-rearing methods are suitable for single-parent families living in urban areas?"

[0417] In this way, users can receive personalized advice based on their attributes and emotions, and by linking it with support at physical stores, it becomes possible to provide even more effective parenting support.

[0418] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0419] Step 1:

[0420] The user inputs his / her own attributes using a smartphone. The input attributes include country, region, family structure, age of parents and children, environment, etc. These attribute data are sent to the server. The server stores the received attribute data in a database.

[0421] Step 2:

[0422] A user inputs a question about child-rearing. For example, a question such as "What is the appropriate amount of sleep for a 5-year-old child?" This question data is sent to the server. The server then sends the received question data to a generative AI model, which generates an appropriate answer.

[0423] Step 3:

[0424] The server categorizes the answers received from the generative AI model into categories, such as sleep, food, education, etc. The categorized answer data is stored in a database.

[0425] Step 4:

[0426] The server uses an emotion engine to analyze emotions from the user's text or voice input. For example, if the user inputs "I'm having trouble because my child won't go to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The analysis results are stored in a database.

[0427] Step 5:

[0428] The server provides personalized advice and solutions based on the analyzed emotions. For example, it generates advice corresponding to emotions such as "trouble" and "tiredness" and provides it to the user. The generated advice data is stored in a database.

[0429] Step 6:

[0430] The server generates a personalized parenting book. The generated parenting book is composed of the user's attribute data, question data, answer data, emotion analysis data, and advice data. The generated parenting book can be borrowed from a digital library.

[0431] Step 7:

[0432] The server is linked to the purchase of child-rearing related products and consultation services at physical stores. When a user purchases a product at a physical store or uses a consultation service, the server provides related information. This allows the user to receive the necessary support at a physical store.

[0433] Example 2

[0434] Next, a second embodiment of the second embodiment will be described. 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."

[0435] Conventional child-rearing support systems do not adequately provide personalized information that takes into account the attributes and emotions of users. As a result, it is difficult for users to obtain information that is appropriate to their own situation and emotions, and effective child-rearing support cannot be achieved. In addition, the information provided is often general and does not meet individual needs.

[0436] 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.

[0437] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means including an emotion engine for analyzing the user's emotions, and a means for generating personalized parenting information based on the analyzed emotions. This makes it possible to provide personalized parenting information based on the user's attributes and emotions.

[0438] "User attributes" refers to information that users input into the system, and includes country, region, family structure, ages of parents and children, environment, etc.

[0439] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions.

[0440] A "question answering system" is a system that receives questions from users and provides appropriate answers to those questions.

[0441] A "categorical classification means" is a method or technique for classifying the generated responses into specific categories (e.g., sleep, food, education, etc.).

[0442] "Personalized parenting information" is information about parenting that is individually customized based on the attributes and feelings of the user.

[0443] An "emotion engine" is a technology or system for analyzing emotions from a user's text or voice input.

[0444] A "digital library" is an online platform that provides electronically accessible books and information resources.

[0445] The present invention is a system for providing personalized parenting information based on the attributes and emotions of a user. The system includes a means for inputting the attributes of a user, a question-answering system using a generative AI model, a means for classifying generated answers by category, a means for generating personalized parenting information, a means including an emotion engine, and a means for generating personalized parenting information based on analyzed emotions.

[0446] User attribute input

[0447] Users use a web browser or a mobile application to input their attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database.

[0448] Enter your question

[0449] The user inputs questions about child rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input questions are sent from the terminal to the server in real time.

[0450] Submit a question and generate an answer

[0451] The terminal sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The server uses the generative AI model to generate an appropriate answer to the question. The generated answer is stored in temporary storage on the server.

[0452] Categorizing answers

[0453] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The classified data is stored in a database.

[0454] Generating personalized parenting information

[0455] The server generates personalized parenting information based on the categorized answers, which is compiled by retrieving relevant information from digital libraries (e.g., Google Books API) and editing it in a way that best suits the user.

[0456] Using the Emotion Engine

[0457] When a user inputs a question by text or voice, the server uses an emotion engine (e.g., IBM Watson (registered trademark) Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble because my child won't go to sleep," the emotion engine analyzes emotions such as "trouble" and "tired."

[0458] Emotion-Based Personalization

[0459] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user indicates emotions such as "trouble" or "tired," the server generates parenting information including advice and solutions corresponding to these emotions. This information is sent to the user's terminal, where the user can view it.

[0460] Examples

[0461] Examples of prompt statements

[0462] "What is the appropriate amount of sleep for a 5-year-old?"

[0463] System processing example

[0464] 1. The user enters the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[0465] 2. The device sends this question to the generative AI model.

[0466] 3. The server uses a generative AI model to generate an answer: "10 to 12 hours of sleep is recommended for a 5-year-old child."

[0467] 4. The server classifies this answer into the "Sleep" category.

[0468] 5. The server generates personalized parenting information along with other answers in the "sleep" category.

[0469] 6. The emotion engine analyzes the emotion of “trouble” from the user’s input.

[0470] 7. The server generates parenting information including advice for dealing with the "trouble" feeling and provides it to the user.

[0471] In this way, the system provides optimal child-rearing information based on the user's attributes and emotions.

[0472] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0473] Step 1:

[0474] Users use a web browser or mobile application to input their attributes (e.g. country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database. The input data is sent to the server in JSON format, and the server parses it and stores it in the database.

[0475] Step 2:

[0476] Users input questions about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input question is sent from the device to the server in real time. The input data is sent to the server in text format, and the server analyzes it and stores it in temporary storage.

[0477] Step 3:

[0478] The device sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The sent question is passed to the generative AI model via an API. The generative AI model generates an appropriate answer to the question and returns the answer to the server. The server stores the generated answer in temporary storage.

[0479] Step 4:

[0480] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The server analyzes the text of the answers and classifies them into the appropriate category. The classified data is stored in a database.

[0481] Step 5:

[0482] The server generates personalized parenting information based on the classified answers. This information is compiled in a way that is optimal for the user by retrieving related information from a digital library (e.g., Google Books API). The server calls the digital library API to retrieve related books and materials, and customizes them based on the user's attributes.

[0483] Step 6:

[0484] When a user inputs a question by text or voice, the server uses an emotion engine (e.g. IBM Watson Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The server calls the emotion engine API, analyzes the input text, and obtains emotion data.

[0485] Step 7:

[0486] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user expresses emotions such as "trouble" or "tiredness," the server generates parenting information including advice and solutions corresponding to these emotions. The server compiles information including the most suitable advice and solutions for the user based on the emotion data, and transmits it to the user's terminal.

[0487] (Application example 2)

[0488] Next, a description will be given of Application Example 2 of Form 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."

[0489] In today's child-rearing environment, parents need a lot of information, and in particular they need personalized advice tailored to the circumstances of each family and the age of their children. However, with conventional information provision systems, it is difficult to provide appropriate advice tailored to the user's emotions and specific circumstances. Furthermore, even in brick-and-mortar stores, there are limited ways for parents to easily obtain professional child-rearing advice. This means that parents have to spend a lot of time and effort to obtain appropriate information, which increases the burden of child-rearing, which is an issue.

[0490] 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.

[0491] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice based on the analyzed emotions, a means for allowing a user to borrow a personalized parenting book from a digital library, and a means for a user to input a question and obtain an answer using a smart device in a physical store. This allows a user to easily obtain personalized advice based on their own attributes and emotions, and allows them to receive professional parenting support even in a physical store.

[0492] "Means for inputting user attributes" refers to a device or software that provides an interface for users to input their own attribute information (e.g. country, region, family structure, ages of parents and children, environment, etc.).

[0493] "Means for generating answers to questions from users by utilizing a question-answering system with generative AI" refers to a device or software that uses generative artificial intelligence to generate appropriate answers to questions entered by users.

[0494] A "means for categorizing generated answers" is a device or software for categorizing generated answers into specific categories (e.g., sleep, food, education, etc.).

[0495] The "means for generating a personalized parenting book" refers to a device or software that generates an individually customized parenting guidebook based on the user's attribute information and the generated answers.

[0496] The "means including an emotion engine for analyzing user's emotions" refers to a device or software including an engine for analyzing emotions from a user's text input or voice input.

[0497] The "means for providing personalized advice based on analyzed emotions" refers to a device or software that provides individually customized advice to a user based on analyzed emotion information.

[0498] The "means for enabling a personalized parenting book to be borrowed from a digital library" refers to a device or software that enables a user to borrow a generated personalized parenting guidebook from a digital library.

[0499] "A means for users to enter questions and receive answers using a smart device in a physical store" refers to a device or software that enables users to enter questions using a smart device such as a smartphone or tablet in a physical store and receive answers from generative AI.

[0500] A system for implementing this invention includes means for inputting user attributes, means for generating answers to user questions using a generative AI question-answering system, means for classifying the generated answers by category, means including an emotion engine for analyzing the user's emotions, means for providing personalized advice based on the analyzed emotions, means for allowing a user to borrow a personalized parenting book from a digital library, and means for a user to input questions and obtain answers using a smart device in a physical store.

[0501] System Configuration

[0502] Hardware

[0503] Server: A server for running the question answering system and the emotion engine.

[0504] Smart device: A device such as a smartphone or tablet that allows users to enter questions.

[0505] software

[0506] Generative AI models: AI models designed to generate answers to questions, such as OpenAI's GPT-4.

[0507] Sentiment engine: Software for analyzing user emotions, such as Microsoft® Azure® Text Analytics for Sentiment Analysis.

[0508] Digital library system: A system that manages personalized parenting books and allows users to borrow them.

[0509] Data processing and calculation

[0510] 1. Input of user attributes: Users use their smart devices to input their own attribute information (e.g. country, region, family composition, ages of parents and children, environment, etc.).

[0511] 2. Question input: Users use their smart device to input questions about child-rearing.

[0512] 3. Answer generation: The server uses a generative AI model to generate an answer to the user's question.

[0513] 4. Sentiment Analysis: The server uses an emotion engine to analyze the sentiment from the user's question.

[0514] 5. Answer Categorization: The server categorizes the generated answers into categories.

[0515] 6. Generating a personalized book: The server generates a personalized parenting book based on the user's attribute information and analyzed emotions.

[0516] 7. Borrowing from a digital library: Users can borrow the generated parenting book from a digital library.

[0517] Examples

[0518] User attributes

[0519] Living in Japan, single parent family, child age 5, living in urban area

[0520] Example questions

[0521] "What is the appropriate amount of sleep for a 5-year-old?"

[0522] Examples of AI responses

[0523] "For a 5-year-old child, 10 to 12 hours of sleep is usually recommended."

[0524] Emotion analysis results

[0525] "Trouble" or "Tired"

[0526] Examples of prompt statements

[0527] I live in Japan, I'm a single parent, my child is 5 years old, and I live in an urban area. What is the appropriate amount of sleep for a 5 year old child?

[0528] In this way, users can easily receive personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[0529] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0530] Step 1:

[0531] A user uses a smart device to input his / her own attribute information (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input attribute information is sent to the server. The server stores this attribute information in a database.

[0532] Step 2:

[0533] A user inputs a question about parenting using a smart device. The input question is sent to the server. The server sends the question to a generative AI model and creates a prompt to generate an answer.

[0534] Step 3:

[0535] The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate an answer to the question based on the prompt, which is then sent back to the server.

[0536] Step 4:

[0537] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) and stores the categorized answers in a database.

[0538] Step 5:

[0539] The server uses an emotion engine (e.g., Microsoft Azure's Text Analytics for Sentiment Analysis) to analyze the emotion from the user's question. The analyzed emotion information is stored in a database.

[0540] Step 6:

[0541] The server generates a personalized parenting book based on the user's attribute information, the generated answers, and the analyzed emotion information. The generated parenting book is stored in a digital library system.

[0542] Step 7:

[0543] Users can access the digital library system using their smart devices and borrow personalized parenting books, allowing them to easily obtain the information they need.

[0544] In this way, users can easily obtain personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[0545] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0546] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0547] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0548] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0549] [Second embodiment]

[0550] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0551] 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.

[0552] 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 wide area network (WAN) and / or a local area network (LAN).

[0553] 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.

[0554] 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 the voice according to instructions from the processor 46.

[0555] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0556] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0557] Fig. 4 shows an example of 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0562] "Example 1"

[0563] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[0564] "Example 2"

[0565] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[0566] The process flow of each embodiment will be described below.

[0567] "Example 1"

[0568] Step 1: The user enters their attributes through the system interface. For example, the user may enter information such as "living in Japan, single parent family, child is 5 years old, living in an urban area."

[0569] Step 2: Next, the user enters a question about parenting, such as "What is the appropriate amount of sleep for a 5-year-old child?"

[0570] Step 3: The entered question is sent to a generative AI question-answering system, which generates an appropriate answer.

[0571] Step 4: The generated answers are classified into categories based on the user's attributes and the content of the question, for example, "sleep," "food," "education," etc.

[0572] Step 5: Based on these categorized answers, the system generates a personalized parenting book that can be borrowed from the digital library, allowing users to efficiently access information that is relevant to them.

[0573] Example 1

[0574] Next, a description will be given of Example 1 of Form 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".

[0575] Conventional child-rearing information systems have difficulty providing personalized information based on the individual attributes of users. In addition, the information provided is general and often does not meet the specific needs of users. Furthermore, searching and obtaining information is cumbersome, making it difficult to efficiently obtain the information required.

[0576] 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.

[0577] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating an e-book containing personalized parenting information based on the classified answers, and a means for making the e-book available for borrowing from a digital library. This makes it possible to efficiently provide personalized parenting information based on the individual attributes of the user.

[0578] "User attributes" refers to information entered by the user, such as country, region, family composition, ages of parents and children, and living environment.

[0579] A "generative AI model" refers to an artificial intelligence model that generates appropriate answers to users' questions.

[0580] A "question answering system" refers to a system that uses a generative AI model to generate answers to users' questions.

[0581] A "categorical classification means" refers to a means for classifying the generated answers into categories such as "sleep," "food," and "education."

[0582] "Personalized parenting information" refers to parenting information that is individually customized based on the user's attributes.

[0583] "E-Book" refers to books provided in digital format, including personalized parenting information.

[0584] A "digital library" refers to a digital platform where e-books can be borrowed online.

[0585] This invention is a system in which a user inputs his / her own attributes, sends questions about child-rearing to a generative AI model, and receives answers. A specific embodiment of this system will be described below.

[0586] First, a user accesses the system's interface through a web browser or a mobile application. This interface provides fields for users to input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). Once the user inputs the attributes, the server receives this data and stores it in a database (e.g., MySQL, PostgreSQL).

[0587] Next, the user enters a parenting question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?") into the interface. This question is sent to the server, which sends the question along with the user's attribute data to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model generates an appropriate answer based on the question and attribute data and sends it back to the server.

[0588] The server receives the generated answers and classifies them into categories such as "sleep", "food", "education", etc. This classification makes it easier for users to search for the information later. The classified answers are stored in a database.

[0589] Next, the server generates an e-book containing personalized parenting information based on the classified answers, and uploads the e-book to a digital library (e.g., Google Books API). The user can then access the digital library and borrow the personalized e-book.

[0590] As a concrete example, if the user enters the following attributes:

[0591] Country: Japan

[0592] Region: Urban

[0593] Family structure: Single parent family

[0594] Parents' age: 30

[0595] Child's age: 5 years old

[0596] The user then enters the following question:

[0597] "What is the appropriate amount of sleep for a 5-year-old?"

[0598] This question is then sent to a generative AI model, which generates an answer like this:

[0599] "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours."

[0600] The server categorizes this answer under the "sleep" category and, along with other related answers, generates an e-book containing personalized parenting information that can be borrowed from a digital library.

[0601] Example of a prompt to be input to a generative AI model:

[0602] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[0603] Q: What is the appropriate amount of sleep for a 5 year old?

[0604] By sending this prompt to a generative AI model, an appropriate answer is obtained. In this way, users can efficiently obtain specific parenting information based on their own attributes.

[0605] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0606] Step 1:

[0607] The user enters the attributes.

[0608] Users access the system interface through a web browser or mobile application and input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). The input attribute data is sent to the server.

[0609] Input: User attribute data

[0610] Output: Attribute data sent to the server

[0611] Step 2:

[0612] The server stores the attribute data.

[0613] The server stores the received attribute data in a database (e.g., MySQL, PostgreSQL). This data is used for later processing.

[0614] Input: User attribute data

[0615] Output: Attribute data stored in a database

[0616] Step 3:

[0617] The user enters a question.

[0618] The user inputs a question about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") into the interface. The input question is sent to the server.

[0619] Input: User question

[0620] Output: The question sent to the server.

[0621] Step 4:

[0622] The server sends the question to the generative AI model.

[0623] The server sends the user's question and attribute data to a generative AI model (e.g., OpenAI's GPT-4) in the form of a prompt:

[0624] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[0625] Q: What is the appropriate amount of sleep for a 5 year old?

[0626] Input: User questions and attribute data

[0627] Output: The prompt sent to the generative AI model

[0628] Step 5:

[0629] A generative AI model generates the answer.

[0630] The generative AI model generates an appropriate answer based on the received prompt. For example, it may generate an answer like, "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours." The generated answer is then sent back to the server.

[0631] Input: Prompt statement

[0632] Output: The generated answer

[0633] Step 6:

[0634] The server receives the responses and categorizes them.

[0635] The server receives the answers sent back by the generative AI model and then classifies the answers into categories such as "sleep," "food," "education," etc. The classified answers are then stored in a database.

[0636] Input: Generated Answer

[0637] Output: Answers sorted by category

[0638] Step 7:

[0639] A server generates an e-book containing personalized parenting information.

[0640] The server generates an e-book containing personalized parenting information based on the user's answers, in PDF or ePub format, and uploads it to the digital library.

[0641] Input: Answers sorted by category

[0642] Output: personalized e-book

[0643] Step 8:

[0644] A user borrows an e-book from a digital library.

[0645] Users can access the digital library and borrow e-books that are personalized to them, allowing them to efficiently obtain the information they need.

[0646] Input: Digital Library Access

[0647] Output: Borrowed e-books

[0648] (Application example 1)

[0649] Next, a description will be given of Application Example 1 of Form 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".

[0650] In modern child-rearing, parents need a lot of information, and in particular, personalized advice tailored to the circumstances of each family. However, conventional information sources provide only general information, making it difficult to meet individual needs. In addition, even in child-rearing consultations at brick-and-mortar stores, the number of experts is limited, making it difficult to obtain fast and accurate advice. This causes the problem that parents have to spend a lot of time and effort to obtain appropriate child-rearing information, which increases stress.

[0651] 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.

[0652] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question answering system, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, a means for displaying the generated personalized child-rearing information via a smart device, and a means for suggesting related products and services. This allows users to quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores efficient and effective.

[0653] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[0654] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[0655] A "categorical classification mechanism" is a function that classifies the generated answers into specific categories (e.g., sleep, food, education, etc.).

[0656] "Personalized parenting information" is parenting information that is individually customized based on the user's attributes and questions.

[0657] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[0658] The "means for suggesting related products and services" is a function for suggesting products and services suitable for the user based on the generated child-rearing information.

[0659] A "digital library" is an electronically accessible library or facility that provides books and information in digital format.

[0660] To implement the present invention, a server, a smart device (such as a smartphone or smart glasses), and a generative AI model are used. Specific embodiments are described below.

[0661] Server Roles

[0662] The server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI question-answering system, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means for displaying the generated personalized parenting information via a smart device, and a means for suggesting related products and services.

[0663] The role of smart devices

[0664] The smart device provides an interface for users to input their attributes and questions, and also serves as a device to display the generated personalized parenting information and receive relevant product and service suggestions.

[0665] The role of generative AI models

[0666] The generative AI model generates appropriate answers based on the user's attributes and questions. Specifically, it uses OpenAI's API to generate prompts for user input and retrieve answers.

[0667] Data processing and calculation

[0668] 1. Data entry: Users enter their own attributes (e.g. country, region, family composition, ages of parents and children, environment, etc.) and questions via their smart device.

[0669] 2. Prompt generation: The server generates a prompt based on the input data to send to the generative AI model.

[0670] 3. AI response generation: A generative AI model generates appropriate answers based on the prompts.

[0671] 4. Answer Categorization: The server categorizes the generated answers into categories.

[0672] 5. Generating personalized information: The server generates personalized parenting information based on the classified answers.

[0673] 6. Displaying information: The smart device displays the generated personalized parenting information to the user.

[0674] 7. Product and service suggestion: The server suggests relevant products and services based on the generated parenting information.

[0675] Examples

[0676] The user puts on the smart glasses at a physical store and enters the following information:

[0677] Attributes: "Living in Japan, single parent family, child age 5, living in urban area"

[0678] Question: "What is the appropriate amount of sleep for a 5-year-old?"

[0679] Examples of prompt statements

[0680] User characteristics: Resident in Japan, single parent family, child age 5, living in urban area

[0681] Q: What is the appropriate amount of sleep for a 5 year old?

[0682] Generate a suitable answer.

[0683] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[0684] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0685] Step 1:

[0686] The user uses a smart device to input his / her attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.) and questions. The input data is sent from the smart device to the server.

[0687] Step 2:

[0688] The server generates a prompt to send to the generative AI model based on the received user attributes and question. Specifically, it creates a prompt sentence that combines the user attributes and question in text format.

[0689] Step 3:

[0690] The server sends the generated prompt sentence to the generative AI model, which generates an appropriate answer based on the prompt sentence, and the generated answer is sent back to the server.

[0691] Step 4:

[0692] The server receives the generated answers and classifies them into categories (e.g., sleep, food, education, etc.) The categorized answers are stored in a database.

[0693] Step 5:

[0694] The server generates personalized parenting information based on the categorized answers. Specifically, the server creates individually customized parenting information by combining the user's attributes and the categorized answers.

[0695] Step 6:

[0696] The server transmits the generated personalized child-rearing information to the smart device, which displays the received information to the user.

[0697] Step 7:

[0698] The server proposes related products and services based on the generated parenting information, and the information on the proposed products and services is provided to the user via the smart device.

[0699] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[0700] Example 2

[0701] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0702] Conventional child-rearing support systems do not adequately provide personalized information based on the individual attributes and questions of users. They also lack a way to efficiently manage the generated information and make it easily accessible to users. As a result, users have to spend a lot of time and effort to obtain the information that is most suitable for them.

[0703] 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.

[0704] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating a personalized information collection based on the classified answers, and a means for making it possible to borrow the generated information collection from a digital library. This enables users to efficiently obtain optimal information based on their own attributes and questions.

[0705] "User attributes" refers to personal information and environmental information that users input into the system, including country, region, family composition, parent and child ages, environment, etc.

[0706] A "generative AI model" is a type of artificial intelligence that uses natural language processing technology to generate answers to users' questions.

[0707] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[0708] "Means of generating an answer" refers to the functions and processes for generating answers to users' questions using a generative AI model.

[0709] "Categorization tools" refers to the functions or processes used to categorize the responses generated according to specific themes or topics.

[0710] A "personalized information collection" is a collection of information that is individualized based on a user's attributes and questions.

[0711] A "digital library" is an online platform that provides electronically stored information and materials.

[0712] "Borrowing enablement" refers to the features or processes that allow users to download or access personalized collections of information from the digital library.

[0713] This invention is a system in which a user inputs their own attributes, generates answers to questions about child-rearing using a generative AI model, classifies the answers by category, and generates a personalized collection of information. A specific embodiment of this system is described below.

[0714] User attribute input

[0715] Users input their demographic information through the system's interface, which can be a web page or a mobile application. The demographic information includes country, region, family structure, parent and child ages, environment, etc. This information is then used in subsequent processing to generate personalized answers.

[0716] Input questions about child rearing

[0717] Users use the same interface to input a parenting question, such as "What is an appropriate amount of sleep for a 5-year-old?", which is then used as a prompt to be sent to the generative AI model.

[0718] Submit a question

[0719] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[0720] Generate answers

[0721] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[0722] Categorizing answers

[0723] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[0724] Generate personalized information collections

[0725] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[0726] Borrowing from the Digital Library

[0727] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[0728] Examples of concrete examples and prompts

[0729] For example, if a user inputs the question "What is an appropriate amount of sleep for a 5-year-old child?", the system processes it as follows:

[0730] 1. The user enters the following attribute information: "Living in Japan, single-parent family, child is 5 years old, living in an urban area."

[0731] 2. The user types the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[0732] 3. The device sends this question to a generative AI model (e.g. GPT-4).

[0733] 4. The server uses the generative AI model to generate the answer, "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours."

[0734] 5. The server classifies this answer into the category "Sleep."

[0735] 6. The server generates a personalized collection of information that includes the answer.

[0736] 7. A user borrows this collection of information from a digital library.

[0737] Example prompt:

[0738] "A user living in Japan, single parent household, 5-year-old child, living in an urban area, is asking about the appropriate amount of sleep for a 5-year-old child. Please generate an appropriate answer."

[0739] In this way, the system provides the most relevant information based on the user's attributes and questions.

[0740] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0741] Step 1:

[0742] The user accesses the system interface and inputs his / her own attribute information. The input attribute information includes country, region, family structure, age of parents and children, environment, etc. This information is used in later processing to generate personalized answers. The input attribute information is sent from the terminal to the server.

[0743] Input: User attribute information (country, region, family structure, age of parents and children, environment, etc.)

[0744] Output: Attribute information sent to the server

[0745] Step 2:

[0746] The user uses the same interface to input a parenting question, for example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is used as a prompt to be sent to the generative AI model. The input question is then sent from the device to the server.

[0747] Input: A user question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?")

[0748] Output: The question sent to the server.

[0749] Step 3:

[0750] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[0751] Input: Attribute information and question stored on the server

[0752] Output: The prompt sent to the generative AI model

[0753] Step 4:

[0754] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[0755] Input: The prompt sent to the generative AI model

[0756] Output: The generated answer (e.g. "The appropriate amount of sleep for a 5-year-old child is 10-12 hours")

[0757] Step 5:

[0758] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[0759] Input: Generated Answer

[0760] Output: Answers sorted by category

[0761] Step 6:

[0762] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[0763] Input: Answers sorted by category

[0764] Output: Personalized information collection (PDF format)

[0765] Step 7:

[0766] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[0767] Input: A personalized search query

[0768] Output: A personalized collection of downloaded information

[0769] (Application example 2)

[0770] Next, a description will be given of Application Example 2 of Form 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".

[0771] Conventional child-rearing support systems have problems in that it is difficult to provide personalized advice based on the user's attributes, and they do not recommend related products or books, meaning that users cannot efficiently obtain the information and products they need. Furthermore, there is a lack of means to provide personalized information in a digital format, which means that it is difficult for users to easily carry the information with them.

[0772] 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.

[0773] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means for generating a personalized parenting book based on the classified answers, a means for recommending related products and books based on the generated answers, and a means for providing the personalized parenting book in a digital format. This allows users to obtain personalized advice based on their own attributes, and by receiving recommendations of related products and books, it becomes possible to efficiently obtain necessary information and products. Furthermore, providing personalized information in a digital format makes it easier for users to carry information around.

[0774] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[0775] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[0776] The "categorical classification means" is a function that classifies the generated answers into categories such as sleep, food, education, etc.

[0777] The "Personalized Parenting Book" is a book that compiles information about parenting that is individually customized based on the user's attributes and questions.

[0778] "Means for recommending related products and books" is a function that suggests products and books suitable for the user based on the generated answers.

[0779] "Means of providing in digital format" refers to the function of providing users with a personalized parenting book in a digital format such as an e-book or PDF.

[0780] In order to implement this invention, the server, the terminal, and the user must each fulfill a specific role. Specific embodiments are described below.

[0781] Server Roles

[0782] The server uses the following hardware and software to process and calculate data.

[0783] Hardware: High-performance server machine

[0784] Software: Python, OpenAI API

[0785] The server first provides a means for users to input their attributes. Then, it uses a generative AI-based question-answering system to generate answers to the user's questions. The generated answers are classified into categories. Furthermore, the server recommends related products and books based on the generated answers, and provides personalized parenting books in digital format.

[0786] Terminal Roles

[0787] A terminal (e.g., a smartphone) provides an interface with a user using the following hardware and software:

[0788] Hardware: Smartphone

[0789] Software: Mobile Application

[0790] The terminal provides an interface for the user to input his / her attributes and also provides an interface for the user to input questions about child-rearing, so that the user can easily input questions and receive answers.

[0791] User Roles

[0792] The user uses the terminal to perform the following operations:

[0793] 1. Enter your attributes.

[0794] 2. Enter your parenting questions.

[0795] 3. Review the generated answers.

[0796] 4. Get recommendations for related products and books.

[0797] 5. Receive your personalized parenting book in digital format.

[0798] Examples

[0799] For example, if the user enters the following attributes:

[0800] Country: Japan

[0801] Region: Urban

[0802] Family structure: Single parent household

[0803] Parents' age: 30

[0804] Child's age: 5 years

[0805] The user then enters the following question:

[0806] Q: What is the appropriate amount of sleep for a 5 year old?

[0807] The server sends the following prompt to the generation AI:

[0808] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[0809] Q: What is the appropriate amount of sleep for a 5 year old?

[0810] answer:

[0811] The generative AI generates appropriate answers based on the prompt text. The generated answers are categorized and related products and books are recommended. Finally, a personalized parenting book is provided to the user in digital format.

[0812] In this way, users can receive personalized advice based on their attributes, and can also receive recommendations for related products and books, allowing them to efficiently obtain the information and products they need. In addition, providing personalized information in a digital format makes it easier for users to carry the information with them.

[0813] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0814] Step 1:

[0815] The server provides an interface for inputting user attributes to the terminal.

[0816] Input: None

[0817] Output: User attribute input interface

[0818] Specific operation: The server displays a form on the terminal where the user can enter information such as country, region, family composition, ages of parents and children, and environment.

[0819] Step 2:

[0820] The user uses the terminal to input his / her attributes.

[0821] Input: User attribute input interface

[0822] Output: User attribute data

[0823] Specific operations: The user enters his / her own attribute information into the form on the terminal and presses the submit button.

[0824] Step 3:

[0825] The server provides an interface for inputting questions about child rearing to the terminal.

[0826] Input: User attribute data

[0827] Output: Question input interface

[0828] Specific operation: The server receives the user attribute data and then displays a form on the terminal for entering questions about child-rearing.

[0829] Step 4:

[0830] A user uses a terminal to input a question about child rearing.

[0831] Input: Question input interface

[0832] Output: Question data

[0833] Specific actions: The user enters a question about child-rearing into a form on the terminal and presses the submit button.

[0834] Step 5:

[0835] The server sends user attribute data and question data to the generative AI to generate an answer.

[0836] Input: User attribute data, question data

[0837] Output: Answer data

[0838] Specific operation: The server generates the following prompt sentence and sends it to the generation AI.

[0839] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[0840] Q: What is the appropriate amount of sleep for a 5 year old?

[0841] answer:

[0842] The generative AI generates an answer based on this prompt and returns it to the server.

[0843] Step 6:

[0844] The server categorizes the generated answers.

[0845] Input: Answer data

[0846] Output: Categorical response data

[0847] Specific behavior: The server classifies the generated answers into categories such as "sleep," "food," and "education."

[0848] Step 7:

[0849] The server recommends related products and books based on the category-specific answer data.

[0850] Input: Categorical response data

[0851] Output: Recommendation data

[0852] Specific operation: The server searches the database for related products and books corresponding to each category and generates a recommendation list.

[0853] Step 8:

[0854] The server generates a personalized parenting book and provides it in a digital format.

[0855] Input: Categorical answer data, recommendation data

[0856] Output: Personalized Parenting Book (digital format)

[0857] Specific operation: The server combines the categorical answer data and the recommendation data to generate a personalized parenting book and provides it to the user in a digital format such as an e-book or PDF.

[0858] Step 9:

[0859] The user receives and views the personalized parenting book using the terminal.

[0860] Input: Personalized Parenting Book (digital format)

[0861] Output: User browsing data

[0862] Specific operations: The user uses the terminal to download and view the provided digital parenting book.

[0863] In addition, an emotion engine that estimates the emotion of the user may be further combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0864] "Example 1"

[0865] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[0866] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[0867] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[0868] "Example 2"

[0869] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[0870] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[0871] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[0872] The process flow of each embodiment will be described below.

[0873] "Example 1"

[0874] Step 1: The user enters their attributes (country, region, family composition, ages of parents and children, environment, etc.) and questions into the system.

[0875] Step 2: The system uses a generative AI question-answering system to generate answers to the user's questions.

[0876] Step 3: The system categorizes the generated answers into categories.

[0877] Step 4: The system uses the emotion engine to analyze emotions from the user's text and / or voice input.

[0878] Step 5: Based on the emotions analyzed by the system, a personalized parenting book is generated based on the categorized answers.

[0879] Step 6: The system provides the user with the personalized parenting book generated by the system.

[0880] Example 1

[0881] Next, a description will be given of Example 1 of Form 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".

[0882] Conventional child-rearing support systems do not provide enough personalized information based on the individual attributes and emotions of users, making it difficult for users to obtain the specific and appropriate advice they need. In addition, the generated information is centralized, and there is a lack of support that corresponds to the user's emotions, which leads to low user satisfaction.

[0883] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, and an emotion engine for analyzing the emotions of the user. This makes it possible to provide specific and appropriate advice based on the individual attributes and emotions of the user.

[0884] "User attributes" refers to personal information and environmental information that users input into the system, and specifically includes country, region, family composition, ages of parents and children, environment, etc.

[0885] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions, and refers to a model based on natural language processing technology.

[0886] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[0887] "Categorization tools" refers to methods or techniques for categorizing the responses generated according to specific themes or topics.

[0888] "Personalized parenting information" refers to parenting information and advice that is customized based on the user's attributes and questions.

[0889] An "emotion engine" refers to technology or a system that analyzes emotions from a user's text or voice input and responds appropriately based on those emotions.

[0890] A "digital library" refers to an online library system that allows users to access and borrow electronically stored books and information.

[0891] The present invention is a system that allows users to input their own attributes and ask questions about child-rearing, and then uses a generative AI model to provide appropriate answers, classify the answers by category, and generate personalized child-rearing information. A specific embodiment of this system is described below.

[0892] User attribute input

[0893] A user uses a terminal (e.g., a PC or smartphone) to access the system's interface. The interface is provided through a web browser or a mobile application. The user inputs attribute information such as country, region, family structure, ages of parents and children, and environment. This information is sent from the terminal to the server and stored in a database.

[0894] Enter your question

[0895] The user inputs a specific question about child rearing. For example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is also sent from the terminal to the server.

[0896] Answer generation by question answering system

[0897] The server sends the received question to a generative AI model (for example, a model based on natural language processing technology). The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." This generative AI model runs on the cloud and generates answers based on large amounts of data.

[0898] Responses categorized

[0899] The server categorizes the generated answers into categories based on the user's attributes and the content of the question. For example, it categorizes the answers into the category of "sleep." This categorization is performed using natural language processing technology.

[0900] Generating personalized parenting information

[0901] The server generates personalized parenting information for the user based on the classified answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the user's attributes.

[0902] Borrowing from the Digital Library

[0903] A user can borrow the generated parenting information from the digital library. The digital library is operated using a cloud storage service (for example, an online storage service). A user accesses the digital library through a terminal and downloads information.

[0904] Emotion analysis using emotion engine

[0905] When the user enters additional questions or comments, the server uses an emotion engine (e.g., a system based on emotion analysis technology) to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired."

[0906] Emotion-Based Personalization

[0907] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions such as "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized according to the user's emotions.

[0908] Examples

[0909] Examples of prompt statements

[0910] The user enters the following prompt text:

[0911] "What is the appropriate amount of sleep for a 5-year-old?"

[0912] In this way, the system provides specific and appropriate advice based on the user's individual attributes and feelings, providing more effective support for the user in raising their children.

[0913] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0914] Step 1: Enter user attributes

[0915] A user uses a terminal to access the system interface and inputs attribute information such as country, region, family structure, ages of parents and children, and environment. The input information is sent from the terminal to the server. The server stores this information in a database. The input data is the user's attribute information, and the output is the attribute information stored in the database.

[0916] Step 2: User enters question

[0917] A user uses a terminal to input a specific question about child-rearing. For example, the user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?" The input question is sent from the terminal to a server. The server receives the question and proceeds to the next processing step. The input data is the user's question, and the output is the question sent to the server.

[0918] Step 3: Generate answers using the question-answering system

[0919] The server sends the received question to the generative AI model. The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generated answer is returned to the server. The input data is the user's question, and the output is the answer generated by the generative AI model.

[0920] Step 4: Categorize responses

[0921] The server classifies the generated answers into categories based on the user's attributes and the content of the question. For example, it classifies them into the category of "sleep." This classification is performed using natural language processing technology. The input data are the generated answers, and the output is the answers classified by category.

[0922] Step 5: Generate personalized parenting information

[0923] The server generates parenting information personalized for the user based on the categorized answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the attributes of the user. The input data are the categorized answers, and the output is personalized parenting information.

[0924] Step 6: Borrow from the Digital Library

[0925] A user can borrow the generated parenting information from the digital library. The user accesses the digital library through a terminal and downloads the information. The digital library is operated using a cloud storage service. The input data is the personalized parenting information, and the output is the information downloaded by the user.

[0926] Step 7: Sentiment Analysis with the Sentiment Engine

[0927] When the user enters additional questions or comments, the server uses the emotion engine to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" or "tired." The input data is the user's text input or voice input, and the output is the analyzed emotion information.

[0928] Step 8: Emotional personalization

[0929] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions of "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized with content according to the user's emotions. The input data is the analyzed emotion information, and the output is parenting information personalized based on the emotions.

[0930] (Application example 1)

[0931] Next, a description will be given of Application Example 1 of Form 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".

[0932] In modern child-rearing, parents need a variety of information, and in particular, personalized advice tailored to each family environment and child's characteristics is required. However, conventional information provision systems have difficulty in providing appropriate advice according to the user's emotions and specific situations. In addition, there is a lack of information provision linked to the purchase of child-rearing related products in brick-and-mortar stores and consultation services, which means that parents cannot efficiently obtain the information and support they need.

[0933] 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.

[0934] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice and solutions based on the analyzed emotions, and a means for linking with child-rearing-related product purchases and consultation services at brick-and-mortar stores. This allows users to receive personalized advice according to their attributes and emotions, and by linking with support at brick-and-mortar stores, more effective child-rearing support is possible.

[0935] "Means for inputting user attributes" refers to an interface that allows users to input information such as their country, region, family structure, ages of parents and children, and environment.

[0936] "Means of generating answers to users' questions by utilizing a question-answering system with generative AI" refers to a system that uses generative AI to generate appropriate answers to questions entered by users.

[0937] "Means for classifying generated answers into categories" refers to a system for classifying answers generated by the generative AI into categories such as sleep, food, and education.

[0938] The "means for generating a personalized parenting book" is a system for generating a parenting book that compiles information most suitable for the user based on answers categorized into categories.

[0939] The "means including an emotion engine for analyzing user's emotions" is a system including an engine for analyzing emotions from a user's text input or voice input.

[0940] The "means for providing personalized advice or solutions based on analyzed emotions" is a system for providing optimal advice or solutions to a user based on emotions analyzed by an emotion engine.

[0941] The "means of linking the purchase of child-rearing related products and consultation services at physical stores" is a system that links with child-rearing related products and consultation services offered at physical stores, allowing users to receive the information and support they need at physical stores.

[0942] A system for implementing this invention has the following configuration. First, a user inputs their own attributes using a smartphone. These attributes include country, region, family structure, ages of parents and children, and environment. Next, the user inputs a question about child-rearing. This question is sent to a question-answering system using generative AI, which generates an appropriate answer.

[0943] The generated answers are categorized into categories such as sleep, food, and education, allowing users to efficiently obtain the information they need. In addition, the emotion engine analyzes emotions from the user's text and voice input. For example, if a user enters "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tired."

[0944] Based on the analyzed emotions, personalized advice and solutions are provided. This allows users to receive the best advice based on their own emotions. In addition, by linking with the purchase of child-rearing related products and consultation services in physical stores, users can receive the support they need at physical stores.

[0945] The following hardware and software are used to realize this system. A smartphone is used as the hardware. Python, OpenAI API, and TextBlob are used as the software. Python is used to implement the program, and OpenAI API is used for the generative AI model question answering system. TextBlob is used for sentiment analysis.

[0946] For example, if a user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?", the generative AI model will generate an appropriate answer. Furthermore, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tiredness" and provide corresponding advice.

[0947] An example of a prompt is as follows:

[0948] "What is the appropriate amount of sleep for a 5-year-old?"

[0949] "My child is having trouble falling asleep"

[0950] "What child-rearing methods are suitable for single-parent families living in urban areas?"

[0951] In this way, users can receive personalized advice based on their attributes and emotions, and by linking it with support at physical stores, it becomes possible to provide even more effective parenting support.

[0952] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0953] Step 1:

[0954] The user inputs his / her own attributes using a smartphone. The input attributes include country, region, family structure, age of parents and children, environment, etc. These attribute data are sent to the server. The server stores the received attribute data in a database.

[0955] Step 2:

[0956] A user inputs a question about child-rearing. For example, a question such as "What is the appropriate amount of sleep for a 5-year-old child?" This question data is sent to the server. The server then sends the received question data to a generative AI model, which generates an appropriate answer.

[0957] Step 3:

[0958] The server categorizes the answers received from the generative AI model into categories, such as sleep, food, education, etc. The categorized answer data is stored in a database.

[0959] Step 4:

[0960] The server uses an emotion engine to analyze emotions from the user's text or voice input. For example, if the user inputs "I'm having trouble because my child won't go to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The analysis results are stored in a database.

[0961] Step 5:

[0962] The server provides personalized advice and solutions based on the analyzed emotions. For example, it generates advice corresponding to emotions such as "trouble" and "tiredness" and provides it to the user. The generated advice data is stored in a database.

[0963] Step 6:

[0964] The server generates a personalized parenting book. The generated parenting book is composed of the user's attribute data, question data, answer data, emotion analysis data, and advice data. The generated parenting book can be borrowed from a digital library.

[0965] Step 7:

[0966] The server is linked to the purchase of child-rearing related products and consultation services at physical stores. When a user purchases a product at a physical store or uses a consultation service, the server provides related information. This allows the user to receive the necessary support at a physical store.

[0967] Example 2

[0968] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0969] Conventional child-rearing support systems do not adequately provide personalized information that takes into account the attributes and emotions of users. As a result, it is difficult for users to obtain information that is appropriate to their own situation and emotions, and effective child-rearing support cannot be achieved. In addition, the information provided is often general and does not meet individual needs.

[0970] 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.

[0971] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means including an emotion engine for analyzing the user's emotions, and a means for generating personalized parenting information based on the analyzed emotions. This makes it possible to provide personalized parenting information based on the user's attributes and emotions.

[0972] "User attributes" refers to information that users input into the system, and includes country, region, family structure, ages of parents and children, environment, etc.

[0973] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions.

[0974] A "question answering system" is a system that receives questions from users and provides appropriate answers to those questions.

[0975] A "categorical classification means" is a method or technique for classifying the generated responses into specific categories (e.g., sleep, food, education, etc.).

[0976] "Personalized parenting information" is information about parenting that is individually customized based on the attributes and feelings of the user.

[0977] An "emotion engine" is a technology or system for analyzing emotions from a user's text or voice input.

[0978] A "digital library" is an online platform that provides electronically accessible books and information resources.

[0979] The present invention is a system for providing personalized parenting information based on the attributes and emotions of a user. The system includes a means for inputting the attributes of a user, a question-answering system using a generative AI model, a means for classifying generated answers by category, a means for generating personalized parenting information, a means including an emotion engine, and a means for generating personalized parenting information based on analyzed emotions.

[0980] User attribute input

[0981] Users use a web browser or a mobile application to input their attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database.

[0982] Enter your question

[0983] The user inputs questions about child rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input questions are sent from the terminal to the server in real time.

[0984] Submit a question and generate an answer

[0985] The terminal sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The server uses the generative AI model to generate an appropriate answer to the question. The generated answer is stored in temporary storage on the server.

[0986] Categorizing answers

[0987] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The classified data is stored in a database.

[0988] Generating personalized parenting information

[0989] The server generates personalized parenting information based on the categorized answers, which is compiled by retrieving relevant information from digital libraries (e.g., Google Books API) and editing it in a way that best suits the user.

[0990] Using the Emotion Engine

[0991] When a user inputs a question by text or voice, the server uses an emotion engine (e.g. IBM Watson Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble because my child won't go to sleep," the emotion engine will analyze emotions such as "trouble" and "tired."

[0992] Emotion-Based Personalization

[0993] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user indicates emotions such as "trouble" or "tired," the server generates parenting information including advice and solutions corresponding to these emotions. This information is sent to the user's terminal, where the user can view it.

[0994] Examples

[0995] Examples of prompt statements

[0996] "What is the appropriate amount of sleep for a 5-year-old?"

[0997] System processing example

[0998] 1. The user enters the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[0999] 2. The device sends this question to the generative AI model.

[1000] 3. The server uses a generative AI model to generate an answer: "10 to 12 hours of sleep is recommended for a 5-year-old child."

[1001] 4. The server classifies this answer into the "Sleep" category.

[1002] 5. The server generates personalized parenting information along with other answers in the "sleep" category.

[1003] 6. The emotion engine analyzes the emotion of “trouble” from the user’s input.

[1004] 7. The server generates parenting information including advice for dealing with the "trouble" feeling and provides it to the user.

[1005] In this way, the system provides optimal child-rearing information based on the user's attributes and emotions.

[1006] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1007] Step 1:

[1008] Users use a web browser or mobile application to input their attributes (e.g. country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database. The input data is sent to the server in JSON format, and the server parses it and stores it in the database.

[1009] Step 2:

[1010] Users input questions about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input question is sent from the device to the server in real time. The input data is sent to the server in text format, and the server analyzes it and stores it in temporary storage.

[1011] Step 3:

[1012] The device sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The sent question is passed to the generative AI model via an API. The generative AI model generates an appropriate answer to the question and returns the answer to the server. The server stores the generated answer in temporary storage.

[1013] Step 4:

[1014] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The server analyzes the text of the answers and classifies them into the appropriate category. The classified data is stored in a database.

[1015] Step 5:

[1016] The server generates personalized parenting information based on the classified answers. This information is compiled in a way that is optimal for the user by retrieving related information from a digital library (e.g., Google Books API). The server calls the digital library API to retrieve related books and materials, and customizes them based on the user's attributes.

[1017] Step 6:

[1018] When a user inputs a question by text or voice, the server uses an emotion engine (e.g. IBM Watson Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The server calls the emotion engine API, analyzes the input text, and obtains emotion data.

[1019] Step 7:

[1020] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user expresses emotions such as "trouble" or "tiredness," the server generates parenting information including advice and solutions corresponding to these emotions. The server compiles information including the most suitable advice and solutions for the user based on the emotion data, and transmits it to the user's terminal.

[1021] (Application example 2)

[1022] Next, a description will be given of Application Example 2 of Form 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".

[1023] In today's child-rearing environment, parents need a lot of information, and in particular they need personalized advice tailored to the circumstances of each family and the age of their children. However, with conventional information provision systems, it is difficult to provide appropriate advice tailored to the user's emotions and specific circumstances. Furthermore, even in brick-and-mortar stores, there are limited ways for parents to easily obtain professional child-rearing advice. This means that parents have to spend a lot of time and effort to obtain appropriate information, which increases the burden of child-rearing, which is an issue.

[1024] 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.

[1025] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice based on the analyzed emotions, a means for allowing a user to borrow a personalized parenting book from a digital library, and a means for a user to input a question and obtain an answer using a smart device in a physical store. This allows a user to easily obtain personalized advice based on their own attributes and emotions, and allows them to receive professional parenting support even in a physical store.

[1026] "Means for inputting user attributes" refers to a device or software that provides an interface for users to input their own attribute information (e.g. country, region, family structure, ages of parents and children, environment, etc.).

[1027] "Means for generating answers to questions from users by utilizing a question-answering system with generative AI" refers to a device or software that uses generative artificial intelligence to generate appropriate answers to questions entered by users.

[1028] A "means for categorizing generated answers" is a device or software for categorizing generated answers into specific categories (e.g., sleep, food, education, etc.).

[1029] The "means for generating a personalized parenting book" refers to a device or software that generates an individually customized parenting guidebook based on the user's attribute information and the generated answers.

[1030] The "means including an emotion engine for analyzing user's emotions" refers to a device or software including an engine for analyzing emotions from a user's text input or voice input.

[1031] The "means for providing personalized advice based on analyzed emotions" refers to a device or software that provides individually customized advice to a user based on analyzed emotion information.

[1032] The "means for enabling a personalized parenting book to be borrowed from a digital library" refers to a device or software that enables a user to borrow a generated personalized parenting guidebook from a digital library.

[1033] "A means for users to enter questions and receive answers using a smart device in a physical store" refers to a device or software that enables users to enter questions using a smart device such as a smartphone or tablet in a physical store and receive answers from generative AI.

[1034] A system for implementing this invention includes means for inputting user attributes, means for generating answers to user questions using a generative AI question-answering system, means for classifying the generated answers by category, means including an emotion engine for analyzing the user's emotions, means for providing personalized advice based on the analyzed emotions, means for allowing a user to borrow a personalized parenting book from a digital library, and means for a user to input questions and obtain answers using a smart device in a physical store.

[1035] System Configuration

[1036] Hardware

[1037] Server: A server for running the question answering system and the emotion engine.

[1038] Smart device: A device such as a smartphone or tablet that allows users to enter questions.

[1039] software

[1040] Generative AI models: AI models designed to generate answers to questions, such as OpenAI's GPT-4.

[1041] Sentiment engine: Software for analyzing user emotions, such as Microsoft Azure's Text Analytics for Sentiment Analysis.

[1042] Digital library system: A system that manages personalized parenting books and allows users to borrow them.

[1043] Data processing and calculation

[1044] 1. Input of user attributes: Users use their smart devices to input their own attribute information (e.g. country, region, family composition, ages of parents and children, environment, etc.).

[1045] 2. Question input: Users use their smart device to input questions about child-rearing.

[1046] 3. Answer generation: The server uses a generative AI model to generate an answer to the user's question.

[1047] 4. Sentiment Analysis: The server uses an emotion engine to analyze the sentiment from the user's question.

[1048] 5. Answer Categorization: The server categorizes the generated answers into categories.

[1049] 6. Generating a personalized book: The server generates a personalized parenting book based on the user's attribute information and analyzed emotions.

[1050] 7. Borrowing from a digital library: Users can borrow the generated parenting book from a digital library.

[1051] Examples

[1052] User attributes

[1053] Living in Japan, single parent family, child age 5, living in urban area

[1054] Example questions

[1055] "What is the appropriate amount of sleep for a 5-year-old?"

[1056] Examples of AI responses

[1057] "For a 5-year-old child, 10 to 12 hours of sleep is usually recommended."

[1058] Emotion analysis results

[1059] "Trouble" or "Tired"

[1060] Examples of prompt statements

[1061] I live in Japan, I'm a single parent, my child is 5 years old, and I live in an urban area. What is the appropriate amount of sleep for a 5 year old child?

[1062] In this way, users can easily receive personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[1063] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1064] Step 1:

[1065] A user uses a smart device to input his / her own attribute information (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input attribute information is sent to the server. The server stores this attribute information in a database.

[1066] Step 2:

[1067] A user inputs a question about parenting using a smart device. The input question is sent to the server. The server sends the question to a generative AI model and creates a prompt to generate an answer.

[1068] Step 3:

[1069] The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate an answer to the question based on the prompt, which is then sent back to the server.

[1070] Step 4:

[1071] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) and stores the categorized answers in a database.

[1072] Step 5:

[1073] The server uses an emotion engine (e.g., Microsoft Azure's Text Analytics for Sentiment Analysis) to analyze the emotion from the user's question. The analyzed emotion information is stored in a database.

[1074] Step 6:

[1075] The server generates a personalized parenting book based on the user's attribute information, the generated answers, and the analyzed emotion information. The generated parenting book is stored in a digital library system.

[1076] Step 7:

[1077] Users can access the digital library system using their smart devices and borrow personalized parenting books, allowing them to easily obtain the information they need.

[1078] In this way, users can easily obtain personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[1079] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[1080] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1081] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1082] 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 smart glasses 214.

[1083] [Third embodiment]

[1084] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1085] 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.

[1086] 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 wide area network (WAN) and / or a local area network (LAN).

[1087] 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.

[1088] 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 the voice according to instructions from the processor 46.

[1089] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1090] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1091] Fig. 6 shows an example of 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.

[1092] 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.

[1093] 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.

[1094] In the headset type terminal 314, 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.

[1095] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1096] "Example 1"

[1097] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[1098] "Example 2"

[1099] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[1100] The process flow of each embodiment will be described below.

[1101] "Example 1"

[1102] Step 1: The user enters their attributes through the system interface. For example, the user may enter information such as "living in Japan, single parent family, child is 5 years old, living in an urban area."

[1103] Step 2: Next, the user enters a question about parenting, such as "What is the appropriate amount of sleep for a 5-year-old child?"

[1104] Step 3: The question is sent to a generative AI question-answering system, which then applies

[1105] Generate appropriate answers.

[1106] Step 4: The generated answers are classified into categories based on the user's attributes and the content of the question, for example, "sleep," "food," "education," etc.

[1107] Step 5: Based on these categorized answers, the system generates a personalized parenting book that can be borrowed from the digital library, allowing users to efficiently access information that is relevant to them.

[1108] Example 1

[1109] Next, a description will be given of Example 1 of the embodiment 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".

[1110] Conventional child-rearing information systems have difficulty providing personalized information based on the individual attributes of users. In addition, the information provided is general and often does not meet the specific needs of users. Furthermore, searching and obtaining information is cumbersome, making it difficult to efficiently obtain the information required.

[1111] 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.

[1112] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating an e-book containing personalized parenting information based on the classified answers, and a means for making the e-book available for borrowing from a digital library. This makes it possible to efficiently provide personalized parenting information based on the individual attributes of the user.

[1113] "User attributes" refers to information entered by the user, such as country, region, family composition, ages of parents and children, and living environment.

[1114] A "generative AI model" refers to an artificial intelligence model that generates appropriate answers to users' questions.

[1115] A "question answering system" refers to a system that uses a generative AI model to generate answers to users' questions.

[1116] A "categorical classification means" refers to a means for classifying the generated answers into categories such as "sleep," "food," and "education."

[1117] "Personalized parenting information" refers to parenting information that is individually customized based on the user's attributes.

[1118] "E-Book" refers to books provided in digital format, including personalized parenting information.

[1119] A "digital library" refers to a digital platform where e-books can be borrowed online.

[1120] This invention is a system in which a user inputs his / her own attributes, sends questions about child-rearing to a generative AI model, and receives answers. A specific embodiment of this system will be described below.

[1121] First, a user accesses the system's interface through a web browser or a mobile application. This interface provides fields for users to input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). Once the user inputs the attributes, the server receives this data and stores it in a database (e.g., MySQL, PostgreSQL).

[1122] Next, the user enters a parenting question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?") into the interface. This question is sent to the server, which sends the question along with the user's attribute data to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model generates an appropriate answer based on the question and attribute data and sends it back to the server.

[1123] The server receives the generated answers and classifies them into categories such as "sleep", "food", "education", etc. This classification makes it easier for users to search for the information later. The classified answers are stored in a database.

[1124] Next, the server generates an e-book containing personalized parenting information based on the classified answers, and uploads the e-book to a digital library (e.g., Google Books API). The user can then access the digital library and borrow the personalized e-book.

[1125] As a concrete example, if the user enters the following attributes:

[1126] Country: Japan

[1127] Region: Urban

[1128] Family structure: Single parent family

[1129] Parents' age: 30

[1130] Child's age: 5 years old

[1131] The user then enters the following question:

[1132] "What is the appropriate amount of sleep for a 5-year-old?"

[1133] This question is then sent to a generative AI model, which generates an answer like this:

[1134] "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours."

[1135] The server categorizes this answer under the "sleep" category and, along with other related answers, generates an e-book containing personalized parenting information that can be borrowed from a digital library.

[1136] Example of a prompt to be input to a generative AI model:

[1137] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[1138] Q: What is the appropriate amount of sleep for a 5 year old?

[1139] By sending this prompt to a generative AI model, an appropriate answer is obtained. In this way, users can efficiently obtain specific parenting information based on their own attributes.

[1140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1141] Step 1:

[1142] The user enters the attributes.

[1143] Users access the system interface through a web browser or mobile application and input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). The input attribute data is sent to the server.

[1144] Input: User attribute data

[1145] Output: Attribute data sent to the server

[1146] Step 2:

[1147] The server stores the attribute data.

[1148] The server stores the received attribute data in a database (e.g., MySQL, PostgreSQL). This data is used for later processing.

[1149] Input: User attribute data

[1150] Output: Attribute data stored in a database

[1151] Step 3:

[1152] The user enters a question.

[1153] The user inputs a question about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") into the interface. The input question is sent to the server.

[1154] Input: User question

[1155] Output: The question sent to the server.

[1156] Step 4:

[1157] The server sends the question to the generative AI model.

[1158] The server sends the user's question and attribute data to a generative AI model (e.g., OpenAI's GPT-4) in the form of a prompt:

[1159] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[1160] Q: What is the appropriate amount of sleep for a 5 year old?

[1161] Input: User questions and attribute data

[1162] Output: The prompt sent to the generative AI model

[1163] Step 5:

[1164] A generative AI model generates the answer.

[1165] The generative AI model generates an appropriate answer based on the received prompt. For example, it may generate an answer like, "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours." The generated answer is then sent back to the server.

[1166] Input: Prompt statement

[1167] Output: The generated answer

[1168] Step 6:

[1169] The server receives the responses and categorizes them.

[1170] The server receives the answers sent back by the generative AI model and then classifies the answers into categories such as "sleep," "food," "education," etc. The classified answers are then stored in a database.

[1171] Input: Generated Answer

[1172] Output: Answers sorted by category

[1173] Step 7:

[1174] A server generates an e-book containing personalized parenting information.

[1175] The server generates an e-book containing personalized parenting information based on the user's answers, in PDF or ePub format, and uploads it to the digital library.

[1176] Input: Answers sorted by category

[1177] Output: personalized e-book

[1178] Step 8:

[1179] A user borrows an e-book from a digital library.

[1180] Users can access the digital library and borrow e-books that are personalized to them, allowing them to efficiently obtain the information they need.

[1181] Input: Digital Library Access

[1182] Output: Borrowed e-books

[1183] (Application example 1)

[1184] Next, a description will be given of Application Example 1 of Form 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".

[1185] In modern child-rearing, parents need a lot of information, and in particular, personalized advice tailored to the circumstances of each family. However, conventional information sources provide only general information, making it difficult to meet individual needs. In addition, even in child-rearing consultations at brick-and-mortar stores, the number of experts is limited, making it difficult to obtain fast and accurate advice. This causes the problem that parents have to spend a lot of time and effort to obtain appropriate child-rearing information, which increases stress.

[1186] 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.

[1187] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question answering system, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, a means for displaying the generated personalized child-rearing information via a smart device, and a means for suggesting related products and services. This allows users to quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores efficient and effective.

[1188] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[1189] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[1190] A "categorical classification mechanism" is a function that classifies the generated answers into specific categories (e.g., sleep, food, education, etc.).

[1191] "Personalized parenting information" is parenting information that is individually customized based on the user's attributes and questions.

[1192] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[1193] The "means for suggesting related products and services" is a function for suggesting products and services suitable for the user based on the generated child-rearing information.

[1194] A "digital library" is an electronically accessible library or facility that provides books and information in digital format.

[1195] To implement the present invention, a server, a smart device (such as a smartphone or smart glasses), and a generative AI model are used. Specific embodiments are described below.

[1196] Server Roles

[1197] The server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI question-answering system, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means for displaying the generated personalized parenting information via a smart device, and a means for suggesting related products and services.

[1198] The role of smart devices

[1199] The smart device provides an interface for users to input their attributes and questions, and also serves as a device to display the generated personalized parenting information and receive relevant product and service suggestions.

[1200] The role of generative AI models

[1201] The generative AI model generates appropriate answers based on the user's attributes and questions. Specifically, it uses OpenAI's API to generate prompts for user input and retrieve answers.

[1202] Data processing and calculation

[1203] 1. Data entry: Users enter their own attributes (e.g. country, region, family composition, ages of parents and children, environment, etc.) and questions via their smart device.

[1204] 2. Prompt generation: The server generates a prompt based on the input data to send to the generative AI model.

[1205] 3. AI response generation: A generative AI model generates appropriate answers based on the prompts.

[1206] 4. Answer Categorization: The server categorizes the generated answers into categories.

[1207] 5. Generating personalized information: The server generates personalized parenting information based on the classified answers.

[1208] 6. Displaying information: The smart device displays the generated personalized parenting information to the user.

[1209] 7. Product and service suggestion: The server suggests relevant products and services based on the generated parenting information.

[1210] Examples

[1211] The user puts on the smart glasses at a physical store and enters the following information:

[1212] Attributes: "Living in Japan, single parent family, child age 5, living in urban area"

[1213] Question: "What is the appropriate amount of sleep for a 5-year-old?"

[1214] Examples of prompt statements

[1215] User characteristics: Resident in Japan, single parent family, child age 5, living in urban area

[1216] Q: What is the appropriate amount of sleep for a 5 year old?

[1217] Generate a suitable answer.

[1218] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[1219] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1220] Step 1:

[1221] The user uses a smart device to input his / her attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.) and questions. The input data is sent from the smart device to the server.

[1222] Step 2:

[1223] The server generates a prompt to send to the generative AI model based on the received user attributes and question. Specifically, it creates a prompt sentence that combines the user attributes and question in text format.

[1224] Step 3:

[1225] The server sends the generated prompt sentence to the generative AI model, which generates an appropriate answer based on the prompt sentence, and the generated answer is sent back to the server.

[1226] Step 4:

[1227] The server receives the generated answers and classifies them into categories (e.g., sleep, food, education, etc.) The categorized answers are stored in a database.

[1228] Step 5:

[1229] The server generates personalized parenting information based on the categorized answers. Specifically, the server creates individually customized parenting information by combining the user's attributes and the categorized answers.

[1230] Step 6:

[1231] The server transmits the generated personalized child-rearing information to the smart device, which displays the received information to the user.

[1232] Step 7:

[1233] The server proposes related products and services based on the generated parenting information, and the information on the proposed products and services is provided to the user via the smart device.

[1234] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[1235] Example 2

[1236] Next, a second embodiment of the second form will be described. 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".

[1237] Conventional child-rearing support systems do not adequately provide personalized information based on the individual attributes and questions of users. They also lack a way to efficiently manage the generated information and make it easily accessible to users. As a result, users have to spend a lot of time and effort to obtain the information that is most suitable for them.

[1238] 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.

[1239] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating a personalized information collection based on the classified answers, and a means for making it possible to borrow the generated information collection from a digital library. This enables users to efficiently obtain optimal information based on their own attributes and questions.

[1240] "User attributes" refers to personal information and environmental information that users input into the system, including country, region, family composition, parent and child ages, environment, etc.

[1241] A "generative AI model" is a type of artificial intelligence that uses natural language processing technology to generate answers to users' questions.

[1242] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[1243] "Means of generating an answer" refers to the functions and processes for generating answers to users' questions using a generative AI model.

[1244] "Categorization tools" refers to the functions or processes used to categorize the responses generated according to specific themes or topics.

[1245] A "personalized information collection" is a collection of information that is individualized based on a user's attributes and questions.

[1246] A "digital library" is an online platform that provides electronically stored information and materials.

[1247] "Borrowing enablement" refers to the features or processes that allow users to download or access personalized collections of information from the digital library.

[1248] This invention is a system in which a user inputs their own attributes, generates answers to questions about child-rearing using a generative AI model, classifies the answers by category, and generates a personalized collection of information. A specific embodiment of this system is described below.

[1249] User attribute input

[1250] Users input their demographic information through the system's interface, which can be a web page or a mobile application. The demographic information includes country, region, family structure, parent and child ages, environment, etc. This information is then used in subsequent processing to generate personalized answers.

[1251] Input questions about child rearing

[1252] Users use the same interface to input a parenting question, such as "What is an appropriate amount of sleep for a 5-year-old?", which is then used as a prompt to be sent to the generative AI model.

[1253] Submit a question

[1254] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[1255] Generate answers

[1256] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[1257] Categorizing answers

[1258] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[1259] Generate personalized information collections

[1260] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[1261] Borrowing from the Digital Library

[1262] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[1263] Examples of concrete examples and prompts

[1264] For example, if a user inputs the question "What is an appropriate amount of sleep for a 5-year-old child?", the system processes it as follows:

[1265] 1. The user enters the following attribute information: "Living in Japan, single-parent family, child is 5 years old, living in an urban area."

[1266] 2. The user types the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[1267] 3. The device sends this question to a generative AI model (e.g. GPT-4).

[1268] 4. The server uses the generative AI model to generate the answer, "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours."

[1269] 5. The server classifies this answer into the category "Sleep."

[1270] 6. The server generates a personalized collection of information that includes the answer.

[1271] 7. A user borrows this collection of information from a digital library.

[1272] Example prompt:

[1273] "A user living in Japan, single parent household, 5-year-old child, living in an urban area, is asking about the appropriate amount of sleep for a 5-year-old child. Please generate an appropriate answer."

[1274] In this way, the system provides the most relevant information based on the user's attributes and questions.

[1275] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1276] Step 1:

[1277] The user accesses the system interface and inputs his / her own attribute information. The input attribute information includes country, region, family structure, age of parents and children, environment, etc. This information is used in later processing to generate personalized answers. The input attribute information is sent from the terminal to the server.

[1278] Input: User attribute information (country, region, family structure, age of parents and children, environment, etc.)

[1279] Output: Attribute information sent to the server

[1280] Step 2:

[1281] The user uses the same interface to input a parenting question, for example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is used as a prompt to be sent to the generative AI model. The input question is then sent from the device to the server.

[1282] Input: A user question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?")

[1283] Output: The question sent to the server.

[1284] Step 3:

[1285] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[1286] Input: Attribute information and question stored on the server

[1287] Output: The prompt sent to the generative AI model

[1288] Step 4:

[1289] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[1290] Input: The prompt sent to the generative AI model

[1291] Output: The generated answer (e.g. "The appropriate amount of sleep for a 5-year-old child is 10-12 hours")

[1292] Step 5:

[1293] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[1294] Input: Generated Answer

[1295] Output: Answers sorted by category

[1296] Step 6:

[1297] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[1298] Input: Answers sorted by category

[1299] Output: Personalized information collection (PDF format)

[1300] Step 7:

[1301] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[1302] Input: A personalized search query

[1303] Output: A personalized collection of downloaded information

[1304] (Application example 2)

[1305] Next, a description will be given of Application Example 2 of Form 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".

[1306] Conventional child-rearing support systems have problems in that it is difficult to provide personalized advice based on the user's attributes, and they do not recommend related products or books, meaning that users cannot efficiently obtain the information and products they need. Furthermore, there is a lack of means to provide personalized information in a digital format, which means that it is difficult for users to easily carry the information with them.

[1307] 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.

[1308] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means for generating a personalized parenting book based on the classified answers, a means for recommending related products and books based on the generated answers, and a means for providing the personalized parenting book in a digital format. This allows users to obtain personalized advice based on their own attributes, and by receiving recommendations of related products and books, it becomes possible to efficiently obtain necessary information and products. Furthermore, providing personalized information in a digital format makes it easier for users to carry information around.

[1309] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[1310] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[1311] The "categorical classification means" is a function that classifies the generated answers into categories such as sleep, food, education, etc.

[1312] The "Personalized Parenting Book" is a book that compiles information about parenting that is individually customized based on the user's attributes and questions.

[1313] "Means for recommending related products and books" is a function that suggests products and books suitable for the user based on the generated answers.

[1314] "Means of providing in digital format" refers to the function of providing users with a personalized parenting book in a digital format such as an e-book or PDF.

[1315] In order to implement this invention, the server, the terminal, and the user must each fulfill a specific role. Specific embodiments are described below.

[1316] Server Roles

[1317] The server uses the following hardware and software to process and calculate data.

[1318] Hardware: High-performance server machine

[1319] Software: Python, OpenAI API

[1320] The server first provides a means for users to input their attributes. Then, it uses a generative AI-based question-answering system to generate answers to the user's questions. The generated answers are classified into categories. Furthermore, the server recommends related products and books based on the generated answers, and provides personalized parenting books in digital format.

[1321] Terminal Roles

[1322] A terminal (e.g., a smartphone) provides an interface with a user using the following hardware and software:

[1323] Hardware: Smartphone

[1324] Software: Mobile Application

[1325] The terminal provides an interface for the user to input his / her attributes and also provides an interface for the user to input questions about child-rearing, so that the user can easily input questions and receive answers.

[1326] User Roles

[1327] The user uses the terminal to perform the following operations:

[1328] 1. Enter your attributes.

[1329] 2. Enter your parenting questions.

[1330] 3. Review the generated answers.

[1331] 4. Get recommendations for related products and books.

[1332] 5. Receive your personalized parenting book in digital format.

[1333] Examples

[1334] For example, if the user enters the following attributes:

[1335] Country: Japan

[1336] Region: Urban

[1337] Family structure: Single parent household

[1338] Parents' age: 30

[1339] Child's age: 5 years

[1340] The user then enters the following question:

[1341] Q: What is the appropriate amount of sleep for a 5 year old?

[1342] The server sends the following prompt to the generation AI:

[1343] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[1344] Q: What is the appropriate amount of sleep for a 5 year old?

[1345] answer:

[1346] The generative AI generates appropriate answers based on the prompt text. The generated answers are categorized and related products and books are recommended. Finally, a personalized parenting book is provided to the user in digital format.

[1347] In this way, users can receive personalized advice based on their attributes, and can also receive recommendations for related products and books, allowing them to efficiently obtain the information and products they need. In addition, providing personalized information in a digital format makes it easier for users to carry the information with them.

[1348] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1349] Step 1:

[1350] The server provides an interface for inputting user attributes to the terminal.

[1351] Input: None

[1352] Output: User attribute input interface

[1353] Specific operation: The server displays a form on the terminal where the user can enter information such as country, region, family composition, ages of parents and children, and environment.

[1354] Step 2:

[1355] The user uses the terminal to input his / her attributes.

[1356] Input: User attribute input interface

[1357] Output: User attribute data

[1358] Specific operations: The user enters his / her own attribute information into the form on the terminal and presses the submit button.

[1359] Step 3:

[1360] The server provides an interface for inputting questions about child rearing to the terminal.

[1361] Input: User attribute data

[1362] Output: Question input interface

[1363] Specific operation: The server receives the user attribute data and then displays a form on the terminal for entering questions about child-rearing.

[1364] Step 4:

[1365] A user uses a terminal to input a question about child rearing.

[1366] Input: Question input interface

[1367] Output: Question data

[1368] Specific actions: The user enters a question about child-rearing into a form on the terminal and presses the submit button.

[1369] Step 5:

[1370] The server sends user attribute data and question data to the generative AI to generate an answer.

[1371] Input: User attribute data, question data

[1372] Output: Answer data

[1373] Specific operation: The server generates the following prompt sentence and sends it to the generation AI.

[1374] User attributes: {"Country": "Japan", "Region": "Urban", "Family structure": "Single parent family", "Parent age": 30, "Child age": 5}

[1375] Q: What is the appropriate amount of sleep for a 5 year old?

[1376] answer:

[1377] The generative AI generates an answer based on this prompt and returns it to the server.

[1378] Step 6:

[1379] The server categorizes the generated answers.

[1380] Input: Answer data

[1381] Output: Categorical response data

[1382] Specific behavior: The server classifies the generated answers into categories such as "sleep," "food," and "education."

[1383] Step 7:

[1384] The server recommends related products and books based on the category-specific answer data.

[1385] Input: Categorical response data

[1386] Output: Recommendation data

[1387] Specific operation: The server searches the database for related products and books corresponding to each category and generates a recommendation list.

[1388] Step 8:

[1389] The server generates a personalized parenting book and provides it in a digital format.

[1390] Input: Categorical answer data, recommendation data

[1391] Output: Personalized Parenting Book (digital format)

[1392] Specific operation: The server combines the categorical answer data and the recommendation data to generate a personalized parenting book and provides it to the user in a digital format such as an e-book or PDF.

[1393] Step 9:

[1394] The user receives and views the personalized parenting book using the terminal.

[1395] Input: Personalized Parenting Book (digital format)

[1396] Output: User browsing data

[1397] Specific operations: The user uses the terminal to download and view the provided digital parenting book.

[1398] In addition, an emotion engine that estimates the emotion of the user may be further combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[1399] "Example 1"

[1400] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[1401] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[1402] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[1403] "Example 2"

[1404] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for classifying the generated answers by category, a means for generating a personalized parenting book based on the classified answers, and an emotion engine for recognizing the user's emotions.

[1405] The emotion engine analyzes emotions from the user's text or voice input. For example, if a user inputs the text "I'm having trouble because my child won't go to sleep," the emotion engine will analyze the user's emotions, such as "trouble" or "tiredness," from this text.

[1406] Furthermore, the emotion engine generates a personalized parenting book based on the analyzed emotions. For example, if the user expresses emotions such as "trouble" or "tiredness," the emotion engine generates a parenting book that includes advice and solutions corresponding to these emotions. In this way, the system provides a personalized parenting book that corresponds to the user's emotions, and more effectively supports the user in parenting.

[1407] The process flow of each embodiment will be described below.

[1408] "Example 1"

[1409] Step 1: The user enters their attributes (country, region, family composition, ages of parents and children, environment, etc.) and questions into the system.

[1410] Step 2: The system uses a generative AI question-answering system to generate answers to the user's questions.

[1411] Step 3: The system categorizes the generated answers into categories.

[1412] Step 4: The system uses the emotion engine to analyze emotions from the user's text and / or voice input.

[1413] Step 5: Based on the emotions analyzed by the system, a personalized parenting book is generated based on the categorized answers.

[1414] Step 6: The system provides the user with the personalized parenting book generated by the system.

[1415] Example 1

[1416] Next, a description will be given of Example 1 of the embodiment 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".

[1417] Conventional child-rearing support systems do not provide enough personalized information based on the individual attributes and emotions of users, making it difficult for users to obtain the specific and appropriate advice they need. In addition, the generated information is centralized, and there is a lack of support that corresponds to the user's emotions, which leads to low user satisfaction.

[1418] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, and an emotion engine for analyzing the emotions of the user. This makes it possible to provide specific and appropriate advice based on the individual attributes and emotions of the user.

[1419] "User attributes" refers to personal information and environmental information that users input into the system, and specifically includes country, region, family composition, ages of parents and children, environment, etc.

[1420] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions, and refers to a model based on natural language processing technology.

[1421] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[1422] "Categorization tools" refers to methods or techniques for categorizing the responses generated according to specific themes or topics.

[1423] "Personalized parenting information" refers to parenting information and advice that is customized based on the user's attributes and questions.

[1424] An "emotion engine" refers to technology or a system that analyzes emotions from a user's text or voice input and responds appropriately based on those emotions.

[1425] A "digital library" refers to an online library system that allows users to access and borrow electronically stored books and information.

[1426] The present invention is a system that allows users to input their own attributes and ask questions about child-rearing, and then uses a generative AI model to provide appropriate answers, classify the answers by category, and generate personalized child-rearing information. A specific embodiment of this system is described below.

[1427] User attribute input

[1428] A user uses a terminal (e.g., a PC or smartphone) to access the system's interface. The interface is provided through a web browser or a mobile application. The user inputs attribute information such as country, region, family structure, ages of parents and children, and environment. This information is sent from the terminal to the server and stored in a database.

[1429] Enter your question

[1430] The user inputs a specific question about child rearing. For example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is also sent from the terminal to the server.

[1431] Answer generation by question answering system

[1432] The server sends the received question to a generative AI model (for example, a model based on natural language processing technology). The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." This generative AI model runs on the cloud and generates answers based on large amounts of data.

[1433] Responses categorized

[1434] The server categorizes the generated answers into categories based on the user's attributes and the content of the question. For example, it categorizes the answers into the category of "sleep." This categorization is performed using natural language processing technology.

[1435] Generating personalized parenting information

[1436] The server generates personalized parenting information for the user based on the classified answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the user's attributes.

[1437] Borrowing from the Digital Library

[1438] A user can borrow the generated parenting information from the digital library. The digital library is operated using a cloud storage service (for example, an online storage service). A user accesses the digital library through a terminal and downloads information.

[1439] Emotion analysis using emotion engine

[1440] When the user enters additional questions or comments, the server uses an emotion engine (e.g., a system based on emotion analysis technology) to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired."

[1441] Emotion-Based Personalization

[1442] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions such as "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized according to the user's emotions.

[1443] Examples

[1444] Examples of prompt statements

[1445] The user enters the following prompt text:

[1446] "What is the appropriate amount of sleep for a 5-year-old?"

[1447] In this way, the system provides specific and appropriate advice based on the user's individual attributes and feelings, providing more effective support for the user in raising their children.

[1448] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1449] Step 1: Enter user attributes

[1450] A user uses a terminal to access the system interface and inputs attribute information such as country, region, family structure, ages of parents and children, and environment. The input information is sent from the terminal to the server. The server stores this information in a database. The input data is the user's attribute information, and the output is the attribute information stored in the database.

[1451] Step 2: User enters question

[1452] A user uses a terminal to input a specific question about child-rearing. For example, the user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?" The input question is sent from the terminal to a server. The server receives the question and proceeds to the next processing step. The input data is the user's question, and the output is the question sent to the server.

[1453] Step 3: Generate answers using the question-answering system

[1454] The server sends the received question to the generative AI model. The generative AI model generates an appropriate answer to the question. For example, it generates an answer such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generated answer is returned to the server. The input data is the user's question, and the output is the answer generated by the generative AI model.

[1455] Step 4: Categorize responses

[1456] The server classifies the generated answers into categories based on the user's attributes and the content of the question. For example, it classifies them into the category of "sleep." This classification is performed using natural language processing technology. The input data are the generated answers, and the output is the answers classified by category.

[1457] Step 5: Generate personalized parenting information

[1458] The server generates parenting information personalized for the user based on the categorized answers. For example, it generates information in PDF format that compiles multiple answers about "sleep." This information is customized according to the attributes of the user. The input data are the categorized answers, and the output is personalized parenting information.

[1459] Step 6: Borrow from the Digital Library

[1460] A user can borrow the generated parenting information from the digital library. The user accesses the digital library through a terminal and downloads the information. The digital library is operated using a cloud storage service. The input data is the personalized parenting information, and the output is the information downloaded by the user.

[1461] Step 7: Sentiment Analysis with the Sentiment Engine

[1462] When the user enters additional questions or comments, the server uses the emotion engine to analyze emotions from the user's text input or voice input. For example, if the user enters the text "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" or "tired." The input data is the user's text input or voice input, and the output is the analyzed emotion information.

[1463] Step 8: Emotional personalization

[1464] The server generates personalized parenting information based on the analyzed emotions. For example, if the user indicates emotions of "distress" or "tired," the emotion engine generates parenting information that includes advice and solutions corresponding to these emotions. This information is customized with content according to the user's emotions. The input data is the analyzed emotion information, and the output is parenting information personalized based on the emotions.

[1465] (Application example 1)

[1466] Next, a description will be given of Application Example 1 of Form 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".

[1467] In today's child-rearing environment, parents need a wide variety of information, and in particular they need personalized advice tailored to their individual family environments and children's characteristics. However, with conventional information provision systems, it is difficult to provide appropriate advice tailored to the user's emotions and specific circumstances. In addition, there is a lack of information provision linked to the purchase of child-rearing related products in brick-and-mortar stores and consultation services, which means that parents cannot efficiently obtain the information and support they need.

[1468] 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.

[1469] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice and solutions based on the analyzed emotions, and a means for linking with child-rearing-related product purchases and consultation services at brick-and-mortar stores. This allows users to receive personalized advice according to their attributes and emotions, and by linking with support at brick-and-mortar stores, more effective child-rearing support is possible.

[1470] "Means for inputting user attributes" refers to an interface that allows users to input information such as their country, region, family structure, ages of parents and children, and environment.

[1471] "Means of generating answers to users' questions by utilizing a question-answering system with generative AI" refers to a system that uses generative AI to generate appropriate answers to questions entered by users.

[1472] "Means for classifying generated answers into categories" refers to a system for classifying answers generated by the generative AI into categories such as sleep, food, and education.

[1473] The "means for generating a personalized parenting book" is a system for generating a parenting book that compiles information most suitable for the user based on answers categorized into categories.

[1474] The "means including an emotion engine for analyzing user's emotions" is a system including an engine for analyzing emotions from a user's text input or voice input.

[1475] The "means for providing personalized advice or solutions based on analyzed emotions" is a system for providing optimal advice or solutions to a user based on emotions analyzed by an emotion engine.

[1476] The "means of linking the purchase of child-rearing related products and consultation services at physical stores" is a system that links with child-rearing related products and consultation services offered at physical stores, allowing users to receive the information and support they need at physical stores.

[1477] A system for implementing this invention has the following configuration. First, a user inputs their own attributes using a smartphone. These attributes include country, region, family structure, ages of parents and children, and environment. Next, the user inputs a question about child-rearing. This question is sent to a question-answering system using generative AI, which generates an appropriate answer.

[1478] The generated answers are categorized into categories such as sleep, food, and education, allowing users to efficiently obtain the information they need. In addition, the emotion engine analyzes emotions from the user's text and voice input. For example, if a user enters "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tired."

[1479] Based on the analyzed emotions, personalized advice and solutions are provided. This allows users to receive the best advice based on their own emotions. In addition, by linking with the purchase of child-rearing related products and consultation services in physical stores, users can receive the support they need at physical stores.

[1480] The following hardware and software are used to realize this system. A smartphone is used as the hardware. Python, OpenAI API, and TextBlob are used as the software. Python is used to implement the program, and OpenAI API is used for the generative AI model question answering system. TextBlob is used for sentiment analysis.

[1481] For example, if a user inputs a question such as "What is the appropriate amount of sleep for a 5-year-old child?", the generative AI model will generate an appropriate answer. Furthermore, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine will analyze emotions such as "trouble" and "tiredness" and provide corresponding advice.

[1482] An example of a prompt is as follows:

[1483] "What is the appropriate amount of sleep for a 5-year-old?"

[1484] "My child is having trouble falling asleep"

[1485] "What child-rearing methods are suitable for single-parent families living in urban areas?"

[1486] In this way, users can receive personalized advice based on their attributes and emotions, and by linking it with support at physical stores, it becomes possible to provide even more effective parenting support.

[1487] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1488] Step 1:

[1489] The user inputs his / her own attributes using a smartphone. The input attributes include country, region, family structure, age of parents and children, environment, etc. These attribute data are sent to the server. The server stores the received attribute data in a database.

[1490] Step 2:

[1491] A user inputs a question about child-rearing. For example, a question such as "What is the appropriate amount of sleep for a 5-year-old child?" This question data is sent to the server. The server then sends the received question data to a generative AI model, which generates an appropriate answer.

[1492] Step 3:

[1493] The server categorizes the answers received from the generative AI model into categories, such as sleep, food, education, etc. The categorized answer data is stored in a database.

[1494] Step 4:

[1495] The server uses an emotion engine to analyze emotions from the user's text or voice input. For example, if the user inputs "I'm having trouble because my child won't go to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The analysis results are stored in a database.

[1496] Step 5:

[1497] The server provides personalized advice and solutions based on the analyzed emotions. For example, it generates advice corresponding to emotions such as "trouble" and "tiredness" and provides it to the user. The generated advice data is stored in a database.

[1498] Step 6:

[1499] The server generates a personalized parenting book. The generated parenting book is composed of the user's attribute data, question data, answer data, emotion analysis data, and advice data. The generated parenting book can be borrowed from a digital library.

[1500] Step 7:

[1501] The server is linked to the purchase of child-rearing related products and consultation services at physical stores. When a user purchases a product at a physical store or uses a consultation service, the server provides related information. This allows the user to receive the necessary support at a physical store.

[1502] Example 2

[1503] Next, a second embodiment of the second form will be described. 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".

[1504] Conventional child-rearing support systems do not adequately provide personalized information that takes into account the attributes and emotions of users. As a result, it is difficult for users to obtain information that is appropriate to their own situation and emotions, and effective child-rearing support cannot be achieved. In addition, the information provided is often general and does not meet individual needs.

[1505] 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.

[1506] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means including an emotion engine for analyzing the user's emotions, and a means for generating personalized parenting information based on the analyzed emotions. This makes it possible to provide personalized parenting information based on the user's attributes and emotions.

[1507] "User attributes" refers to information that users input into the system, and includes country, region, family structure, ages of parents and children, environment, etc.

[1508] A "generative AI model" is a system that uses artificial intelligence technology to generate answers to users' questions.

[1509] A "question answering system" is a system that receives questions from users and provides appropriate answers to those questions.

[1510] A "categorical classification means" is a method or technique for classifying the generated responses into specific categories (e.g., sleep, food, education, etc.).

[1511] "Personalized parenting information" is information about parenting that is individually customized based on the attributes and feelings of the user.

[1512] An "emotion engine" is a technology or system for analyzing emotions from a user's text or voice input.

[1513] A "digital library" is an online platform that provides electronically accessible books and information resources.

[1514] The present invention is a system for providing personalized parenting information based on the attributes and emotions of a user. The system includes a means for inputting the attributes of a user, a question-answering system using a generative AI model, a means for classifying generated answers by category, a means for generating personalized parenting information, a means including an emotion engine, and a means for generating personalized parenting information based on analyzed emotions.

[1515] User attribute input

[1516] Users use a web browser or a mobile application to input their attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database.

[1517] Enter your question

[1518] The user inputs questions about child rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input questions are sent from the terminal to the server in real time.

[1519] Submit a question and generate an answer

[1520] The terminal sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The server uses the generative AI model to generate an appropriate answer to the question. The generated answer is stored in temporary storage on the server.

[1521] Categorizing answers

[1522] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The classified data is stored in a database.

[1523] Generating personalized parenting information

[1524] The server generates personalized parenting information based on the categorized answers, which is compiled by retrieving relevant information from digital libraries (e.g., Google Books API) and editing it in a way that best suits the user.

[1525] Using the Emotion Engine

[1526] When a user inputs a question by text or voice, the server uses an emotion engine (e.g. IBM Watson Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble because my child won't go to sleep," the emotion engine will analyze emotions such as "trouble" and "tired."

[1527] Emotion-Based Personalization

[1528] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user indicates emotions such as "trouble" or "tired," the server generates parenting information including advice and solutions corresponding to these emotions. This information is sent to the user's terminal, where the user can view it.

[1529] Examples

[1530] Examples of prompt statements

[1531] "What is the appropriate amount of sleep for a 5-year-old?"

[1532] System processing example

[1533] 1. The user enters the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[1534] 2. The device sends this question to the generative AI model.

[1535] 3. The server uses a generative AI model to generate an answer: "10 to 12 hours of sleep is recommended for a 5-year-old child."

[1536] 4. The server classifies this answer into the "Sleep" category.

[1537] 5. The server generates personalized parenting information along with other answers in the "sleep" category.

[1538] 6. The emotion engine analyzes the emotion of “trouble” from the user’s input.

[1539] 7. The server generates parenting information including advice for dealing with the "trouble" feeling and provides it to the user.

[1540] In this way, the system provides optimal child-rearing information based on the user's attributes and emotions.

[1541] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1542] Step 1:

[1543] Users use a web browser or mobile application to input their attributes (e.g. country, region, family structure, ages of parents and children, environment, etc.). The input data is sent from the device to the server and stored in a database. The input data is sent to the server in JSON format, and the server parses it and stores it in the database.

[1544] Step 2:

[1545] Users input questions about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") through the system's question-answering interface. The input question is sent from the device to the server in real time. The input data is sent to the server in text format, and the server analyzes it and stores it in temporary storage.

[1546] Step 3:

[1547] The device sends the question entered by the user to a generative AI model (e.g., OpenAI's GPT-4). The sent question is passed to the generative AI model via an API. The generative AI model generates an appropriate answer to the question and returns the answer to the server. The server stores the generated answer in temporary storage.

[1548] Step 4:

[1549] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Natural language processing techniques (e.g., SpaCy and NLTK) are used for this classification. The server analyzes the text of the answers and classifies them into the appropriate category. The classified data is stored in a database.

[1550] Step 5:

[1551] The server generates personalized parenting information based on the classified answers. This information is compiled in a way that is optimal for the user by retrieving related information from a digital library (e.g., Google Books API). The server calls the digital library API to retrieve related books and materials, and customizes them based on the user's attributes.

[1552] Step 6:

[1553] When a user inputs a question by text or voice, the server uses an emotion engine (e.g. IBM Watson Tone Analyzer) to analyze the user's emotion from the input. For example, if a user inputs "I'm having trouble getting my child to sleep," the emotion engine analyzes emotions such as "trouble" and "tired." The server calls the emotion engine API, analyzes the input text, and obtains emotion data.

[1554] Step 7:

[1555] The server generates further personalized parenting information based on the emotions analyzed by the emotion engine. For example, if the user expresses emotions such as "trouble" or "tiredness," the server generates parenting information including advice and solutions corresponding to these emotions. The server compiles information including the most suitable advice and solutions for the user based on the emotion data, and transmits it to the user's terminal.

[1556] (Application example 2)

[1557] Next, a description will be given of Application Example 2 of Form 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".

[1558] In today's child-rearing environment, parents need a lot of information, and in particular they need personalized advice tailored to the circumstances of each family and the age of their children. However, with conventional information provision systems, it is difficult to provide appropriate advice tailored to the user's emotions and specific circumstances. Furthermore, even in brick-and-mortar stores, there are limited ways for parents to easily obtain professional child-rearing advice. This means that parents have to spend a lot of time and effort to obtain appropriate information, which increases the burden of child-rearing, which is an issue.

[1559] 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.

[1560] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means including an emotion engine for analyzing the user's emotions, a means for providing personalized advice based on the analyzed emotions, a means for allowing a user to borrow a personalized parenting book from a digital library, and a means for a user to input a question and obtain an answer using a smart device in a physical store. This allows a user to easily obtain personalized advice based on their own attributes and emotions, and allows them to receive professional parenting support even in a physical store.

[1561] "Means for inputting user attributes" refers to a device or software that provides an interface for users to input their own attribute information (e.g. country, region, family structure, ages of parents and children, environment, etc.).

[1562] "Means for generating answers to questions from users by utilizing a question-answering system with generative AI" refers to a device or software that uses generative artificial intelligence to generate appropriate answers to questions entered by users.

[1563] A "means for categorizing generated answers" is a device or software for categorizing generated answers into specific categories (e.g., sleep, food, education, etc.).

[1564] The "means for generating a personalized parenting book" refers to a device or software that generates an individually customized parenting guidebook based on the user's attribute information and the generated answers.

[1565] The "means including an emotion engine for analyzing user's emotions" refers to a device or software including an engine for analyzing emotions from a user's text input or voice input.

[1566] The "means for providing personalized advice based on analyzed emotions" refers to a device or software that provides individually customized advice to a user based on analyzed emotion information.

[1567] The "means for enabling a personalized parenting book to be borrowed from a digital library" refers to a device or software that enables a user to borrow a generated personalized parenting guidebook from a digital library.

[1568] "A means for users to enter questions and receive answers using a smart device in a physical store" refers to a device or software that enables users to enter questions using a smart device such as a smartphone or tablet in a physical store and receive answers from generative AI.

[1569] A system for implementing this invention includes means for inputting user attributes, means for generating answers to user questions using a generative AI question-answering system, means for classifying the generated answers by category, means including an emotion engine for analyzing the user's emotions, means for providing personalized advice based on the analyzed emotions, means for allowing a user to borrow a personalized parenting book from a digital library, and means for a user to input questions and obtain answers using a smart device in a physical store.

[1570] System Configuration

[1571] Hardware

[1572] Server: A server for running the question answering system and the emotion engine.

[1573] Smart device: A device such as a smartphone or tablet that allows users to enter questions.

[1574] software

[1575] Generative AI models: AI models designed to generate answers to questions, such as OpenAI's GPT-4.

[1576] Sentiment engine: Software for analyzing user emotions, such as Microsoft Azure's Text Analytics for Sentiment Analysis.

[1577] Digital library system: A system that manages personalized parenting books and allows users to borrow them.

[1578] Data processing and calculation

[1579] 1. Input of user attributes: Users use their smart devices to input their own attribute information (e.g. country, region, family composition, ages of parents and children, environment, etc.).

[1580] 2. Question input: Users use their smart device to input questions about child-rearing.

[1581] 3. Answer generation: The server uses a generative AI model to generate an answer to the user's question.

[1582] 4. Sentiment Analysis: The server uses an emotion engine to analyze the sentiment from the user's question.

[1583] 5. Answer Categorization: The server categorizes the generated answers into categories.

[1584] 6. Generating a personalized book: The server generates a personalized parenting book based on the user's attribute information and analyzed emotions.

[1585] 7. Borrowing from a digital library: Users can borrow the generated parenting book from a digital library.

[1586] Examples

[1587] User attributes

[1588] Living in Japan, single parent family, child age 5, living in urban area

[1589] Example questions

[1590] "What is the appropriate amount of sleep for a 5-year-old?"

[1591] Examples of AI responses

[1592] "For a 5-year-old child, 10 to 12 hours of sleep is usually recommended."

[1593] Emotion analysis results

[1594] "Trouble" or "Tired"

[1595] Examples of prompt statements

[1596] I live in Japan, I'm a single parent, my child is 5 years old, and I live in an urban area. What is the appropriate amount of sleep for a 5 year old child?

[1597] In this way, users can easily receive personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[1598] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1599] Step 1:

[1600] A user uses a smart device to input his / her own attribute information (e.g., country, region, family structure, ages of parents and children, environment, etc.). The input attribute information is sent to the server. The server stores this attribute information in a database.

[1601] Step 2:

[1602] A user inputs a question about parenting using a smart device. The input question is sent to the server. The server sends the question to a generative AI model and creates a prompt to generate an answer.

[1603] Step 3:

[1604] The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate an answer to the question based on the prompt, which is then sent back to the server.

[1605] Step 4:

[1606] The server classifies the generated answers into categories (e.g., sleep, food, education, etc.) and stores the categorized answers in a database.

[1607] Step 5:

[1608] The server uses an emotion engine (e.g., Microsoft Azure's Text Analytics for Sentiment Analysis) to analyze the emotion from the user's question. The analyzed emotion information is stored in a database.

[1609] Step 6:

[1610] The server generates a personalized parenting book based on the user's attribute information, the generated answers, and the analyzed emotion information. The generated parenting book is stored in a digital library system.

[1611] Step 7:

[1612] Users can access the digital library system using their smart devices and borrow personalized parenting books, allowing them to easily obtain the information they need.

[1613] In this way, users can easily obtain personalized advice based on their attributes and emotions, and can receive professional parenting support even in physical stores.

[1614] 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 voice indicating a user input for 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.

[1615] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1616] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1617] 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.

[1618] [Fourth embodiment]

[1619] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1620] 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.

[1621] 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 wide area network (WAN) and / or a local area network (LAN).

[1622] 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. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1623] 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 the voice according to instructions from the processor 46.

[1624] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1625] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1626] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. 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.

[1627] Fig. 8 shows an example of 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.

[1628] 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.

[1629] 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.

[1630] In the robot 414, 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.

[1631] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1632] "Example 1"

[1633] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[1634] "Example 2"

[1635] The system of the present invention provides an interface where users can input their own attributes (e.g., living in Japan, single-parent family, child is 5 years old, living in an urban area, etc.). Next, the user inputs a question about child-rearing (e.g., "What is an appropriate amount of sleep for a 5-year-old child?", etc.). This question is sent to a generative AI-based question-answering system, which generates an appropriate answer. The generated answers are classified into categories (e.g., sleep, food, education, etc.) based on the user's attributes and the content of the question. Based on these classified answers, the system generates a personalized child-rearing book. This book can be borrowed from a digital library, allowing users to efficiently obtain information that is appropriate for them.

[1636] The process flow of each embodiment will be described below.

[1637] "Example 1"

[1638] Step 1: The user enters their attributes through the system interface. For example, the user may enter information such as "living in Japan, single parent family, child is 5 years old, living in an urban area."

[1639] Step 2: Next, the user enters a question about parenting, such as "What is the appropriate amount of sleep for a 5-year-old child?"

[1640] Step 3: The entered question is sent to a generative AI question-answering system, which generates an appropriate answer.

[1641] Step 4: The generated answers are classified into categories based on the user's attributes and the content of the question, for example, "sleep," "food," "education," etc.

[1642] Step 5: Based on these categorized answers, the system generates a personalized parenting book that can be borrowed from the digital library, allowing users to efficiently access information that is relevant to them.

[1643] Example 1

[1644] Next, a description will be given of Example 1 of the embodiment 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".

[1645] Conventional child-rearing information systems have difficulty providing personalized information based on the individual attributes of users. In addition, the information provided is general and often does not meet the specific needs of users. Furthermore, searching and obtaining information is cumbersome, making it difficult to efficiently obtain the information required.

[1646] 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.

[1647] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating an e-book containing personalized parenting information based on the classified answers, and a means for making the e-book available for borrowing from a digital library. This makes it possible to efficiently provide personalized parenting information based on the individual attributes of the user.

[1648] "User attributes" refers to information entered by the user, such as country, region, family composition, ages of parents and children, and living environment.

[1649] A "generative AI model" refers to an artificial intelligence model that generates appropriate answers to users' questions.

[1650] A "question answering system" refers to a system that uses a generative AI model to generate answers to users' questions.

[1651] A "categorical classification means" refers to a means for classifying the generated answers into categories such as "sleep," "food," and "education."

[1652] "Personalized parenting information" refers to parenting information that is individually customized based on the user's attributes.

[1653] "E-Book" refers to books provided in digital format, including personalized parenting information.

[1654] A "digital library" refers to a digital platform where e-books can be borrowed online.

[1655] This invention is a system in which a user inputs his / her own attributes, sends questions about child-rearing to a generative AI model, and receives answers. A specific embodiment of this system will be described below.

[1656] First, a user accesses the system's interface through a web browser or a mobile application. This interface provides fields for users to input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). Once the user inputs the attributes, the server receives this data and stores it in a database (e.g., MySQL, PostgreSQL).

[1657] Next, the user enters a parenting question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?") into the interface. This question is sent to the server, which sends the question along with the user's attribute data to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model generates an appropriate answer based on the question and attribute data and sends it back to the server.

[1658] The server receives the generated answers and classifies them into categories such as "sleep", "food", "education", etc. This classification makes it easier for users to search for the information later. The classified answers are stored in a database.

[1659] Next, the server generates an e-book containing personalized parenting information based on the classified answers, and uploads the e-book to a digital library (e.g., Google Books API). The user can then access the digital library and borrow the personalized e-book.

[1660] As a concrete example, if the user enters the following attributes:

[1661] Country: Japan

[1662] Region: Urban

[1663] Family structure: Single parent family

[1664] Parents' age: 30

[1665] Child's age: 5 years old

[1666] The user then enters the following question:

[1667] "What is the appropriate amount of sleep for a 5-year-old?"

[1668] This question is then sent to a generative AI model, which generates an answer like this:

[1669] "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours."

[1670] The server categorizes this answer under the "sleep" category and, along with other related answers, generates an e-book containing personalized parenting information that can be borrowed from a digital library.

[1671] Example of a prompt to be input to a generative AI model:

[1672] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[1673] Q: What is the appropriate amount of sleep for a 5 year old?

[1674] By sending this prompt to a generative AI model, an appropriate answer is obtained. In this way, users can efficiently obtain specific parenting information based on their own attributes.

[1675] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1676] Step 1:

[1677] The user enters the attributes.

[1678] Users access the system interface through a web browser or mobile application and input their attributes (e.g., country, region, family structure, parent and child ages, living environment, etc.). The input attribute data is sent to the server.

[1679] Input: User attribute data

[1680] Output: Attribute data sent to the server

[1681] Step 2:

[1682] The server stores the attribute data.

[1683] The server stores the received attribute data in a database (e.g., MySQL, PostgreSQL). This data is used for later processing.

[1684] Input: User attribute data

[1685] Output: Attribute data stored in a database

[1686] Step 3:

[1687] The user enters a question.

[1688] The user inputs a question about child-rearing (e.g., "What is the appropriate amount of sleep for a 5-year-old child?") into the interface. The input question is sent to the server.

[1689] Input: User question

[1690] Output: The question sent to the server.

[1691] Step 4:

[1692] The server sends the question to the generative AI model.

[1693] The server sends the user's question and attribute data to a generative AI model (e.g., OpenAI's GPT-4) in the form of a prompt:

[1694] User demographics: Living in Japan, single parent family, child age 5, living in urban area

[1695] Q: What is the appropriate amount of sleep for a 5 year old?

[1696] Input: User questions and attribute data

[1697] Output: The prompt sent to the generative AI model

[1698] Step 5:

[1699] A generative AI model generates the answer.

[1700] The generative AI model generates an appropriate answer based on the received prompt. For example, it may generate an answer like, "The appropriate amount of sleep for a 5-year-old child is generally 10 to 12 hours." The generated answer is then sent back to the server.

[1701] Input: Prompt statement

[1702] Output: The generated answer

[1703] Step 6:

[1704] The server receives the responses and categorizes them.

[1705] The server receives the answers sent back by the generative AI model and then classifies the answers into categories such as "sleep," "food," "education," etc. The classified answers are then stored in a database.

[1706] Input: Generated Answer

[1707] Output: Answers sorted by category

[1708] Step 7:

[1709] A server generates an e-book containing personalized parenting information.

[1710] The server generates an e-book containing personalized parenting information based on the user's answers, in PDF or ePub format, and uploads it to the digital library.

[1711] Input: Answers sorted by category

[1712] Output: personalized e-book

[1713] Step 8:

[1714] A user borrows an e-book from a digital library.

[1715] Users can access the digital library and borrow e-books that are personalized to them, allowing them to efficiently obtain the information they need.

[1716] Input: Digital Library Access

[1717] Output: Borrowed e-books

[1718] (Application example 1)

[1719] Next, a description will be given of Application Example 1 of Form 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".

[1720] In modern child-rearing, parents need a lot of information, and in particular, personalized advice tailored to the circumstances of each family. However, conventional information sources provide only general information, making it difficult to meet individual needs. In addition, even in child-rearing consultations at brick-and-mortar stores, the number of experts is limited, making it difficult to obtain fast and accurate advice. This causes the problem that parents have to spend a lot of time and effort to obtain appropriate child-rearing information, which increases stress.

[1721] 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.

[1722] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question answering system, a means for classifying the generated answers by category, a means for generating personalized child-rearing information based on the classified answers, a means for displaying the generated personalized child-rearing information via a smart device, and a means for suggesting related products and services. This allows users to quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores efficient and effective.

[1723] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[1724] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[1725] A "categorical classification mechanism" is a function that classifies the generated answers into specific categories (e.g., sleep, food, education, etc.).

[1726] "Personalized parenting information" is parenting information that is individually customized based on the user's attributes and questions.

[1727] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[1728] The "means for suggesting related products and services" is a function for suggesting products and services suitable for the user based on the generated child-rearing information.

[1729] A "digital library" is an electronically accessible library or facility that provides books and information in digital format.

[1730] To implement the present invention, a server, a smart device (such as a smartphone or smart glasses), and a generative AI model are used. Specific embodiments are described below.

[1731] Server Roles

[1732] The server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI question-answering system, a means for classifying the generated answers by category, a means for generating personalized parenting information based on the classified answers, a means for displaying the generated personalized parenting information via a smart device, and a means for suggesting related products and services.

[1733] The role of smart devices

[1734] The smart device provides an interface for users to input their attributes and questions, and also serves as a device to display the generated personalized parenting information and receive relevant product and service suggestions.

[1735] The role of generative AI models

[1736] The generative AI model generates appropriate answers based on the user's attributes and questions. Specifically, it uses OpenAI's API to generate prompts for user input and retrieve answers.

[1737] Data processing and calculation

[1738] 1. Data entry: Users enter their own attributes (e.g. country, region, family composition, ages of parents and children, environment, etc.) and questions via their smart device.

[1739] 2. Prompt generation: The server generates a prompt based on the input data to send to the generative AI model.

[1740] 3. AI response generation: A generative AI model generates appropriate answers based on the prompts.

[1741] 4. Answer Categorization: The server categorizes the generated answers into categories.

[1742] 5. Generating personalized information: The server generates personalized parenting information based on the classified answers.

[1743] 6. Displaying information: The smart device displays the generated personalized parenting information to the user.

[1744] 7. Product and service suggestion: The server suggests relevant products and services based on the generated parenting information.

[1745] Examples

[1746] The user puts on the smart glasses at a physical store and enters the following information:

[1747] Attributes: "Living in Japan, single parent family, child age 5, living in urban area"

[1748] Question: "What is the appropriate amount of sleep for a 5-year-old?"

[1749] Examples of prompt statements

[1750] User characteristics: Resident in Japan, single parent family, child age 5, living in urban area

[1751] Q: What is the appropriate amount of sleep for a 5 year old?

[1752] Generate a suitable answer.

[1753] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[1754] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1755] Step 1:

[1756] The user uses a smart device to input his / her attributes (e.g., country, region, family structure, ages of parents and children, environment, etc.) and questions. The input data is sent from the smart device to the server.

[1757] Step 2:

[1758] The server generates a prompt to send to the generative AI model based on the received user attributes and question. Specifically, it creates a prompt sentence that combines the user attributes and question in text format.

[1759] Step 3:

[1760] The server sends the generated prompt sentence to the generative AI model, which generates an appropriate answer based on the prompt sentence, and the generated answer is sent back to the server.

[1761] Step 4:

[1762] The server receives the generated answers and classifies them into categories (e.g., sleep, food, education, etc.) The categorized answers are stored in a database.

[1763] Step 5:

[1764] The server generates personalized parenting information based on the categorized answers. Specifically, the server creates individually customized parenting information by combining the user's attributes and the categorized answers.

[1765] Step 6:

[1766] The server transmits the generated personalized child-rearing information to the smart device, which displays the received information to the user.

[1767] Step 7:

[1768] The server proposes related products and services based on the generated parenting information, and the information on the proposed products and services is provided to the user via the smart device.

[1769] In this way, users can quickly obtain personalized child-rearing information based on their own attributes, making child-rearing consultations at physical stores more efficient and effective.

[1770] Example 2

[1771] Next, a second embodiment of the second embodiment will be described. 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".

[1772] Conventional child-rearing support systems do not adequately provide personalized information based on the individual attributes and questions of users. They also lack a way to efficiently manage the generated information and make it easily accessible to users. As a result, users have to spend a lot of time and effort to obtain the information that is most suitable for them.

[1773] 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.

[1774] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a question answering system based on a generative AI model, a means for classifying the generated answers by category, a means for generating a personalized information collection based on the classified answers, and a means for making it possible to borrow the generated information collection from a digital library. This enables users to efficiently obtain optimal information based on their own attributes and questions.

[1775] "User attributes" refers to personal information and environmental information that users input into the system, including country, region, family composition, parent and child ages, environment, etc.

[1776] A "generative AI model" is a type of artificial intelligence that uses natural language processing technology to generate answers to users' questions.

[1777] A "question answering system" is a system that receives questions from users and generates appropriate answers using a generative AI model.

[1778] "Means of generating an answer" refers to the functions and processes for generating answers to users' questions using a generative AI model.

[1779] "Categorization tools" refers to the functions or processes used to categorize the responses generated according to specific themes or topics.

[1780] A "personalized information collection" is a collection of information that is individualized based on a user's attributes and questions.

[1781] A "digital library" is an online platform that provides electronically stored information and materials.

[1782] "Borrowing enablement" refers to the features or processes that allow users to download or access personalized collections of information from the digital library.

[1783] This invention is a system in which a user inputs their own attributes, generates answers to questions about child-rearing using a generative AI model, classifies the answers by category, and generates a personalized collection of information. A specific embodiment of this system is described below.

[1784] User attribute input

[1785] Users input their demographic information through the system's interface, which can be a web page or a mobile application. The demographic information includes country, region, family structure, parent and child ages, environment, etc. This information is then used in subsequent processing to generate personalized answers.

[1786] Input questions about child rearing

[1787] Users use the same interface to input a parenting question, such as "What is an appropriate amount of sleep for a 5-year-old?", which is then used as a prompt to be sent to the generative AI model.

[1788] Submit a question

[1789] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[1790] Generate answers

[1791] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[1792] Categorizing answers

[1793] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[1794] Generate personalized information collections

[1795] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[1796] Borrowing from the Digital Library

[1797] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[1798] Examples of concrete examples and prompts

[1799] For example, if a user inputs the question "What is an appropriate amount of sleep for a 5-year-old child?", the system processes it as follows:

[1800] 1. The user enters the following attribute information: "Living in Japan, single-parent family, child is 5 years old, living in an urban area."

[1801] 2. The user types the question, "What is an appropriate amount of sleep for a 5-year-old child?"

[1802] 3. The device sends this question to a generative AI model (e.g. GPT-4).

[1803] 4. The server uses the generative AI model to generate the answer, "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours."

[1804] 5. The server classifies this answer into the category "Sleep."

[1805] 6. The server generates a personalized collection of information that includes the answer.

[1806] 7. A user borrows this collection of information from a digital library.

[1807] Example prompt:

[1808] "A user living in Japan, single parent household, 5-year-old child, living in an urban area, is asking about the appropriate amount of sleep for a 5-year-old child. Please generate an appropriate answer."

[1809] In this way, the system provides the most relevant information based on the user's attributes and questions.

[1810] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1811] Step 1:

[1812] The user accesses the system interface and inputs his / her own attribute information. The input attribute information includes country, region, family structure, age of parents and children, environment, etc. This information is used in later processing to generate personalized answers. The input attribute information is sent from the terminal to the server.

[1813] Input: User attribute information (country, region, family structure, age of parents and children, environment, etc.)

[1814] Output: Attribute information sent to the server

[1815] Step 2:

[1816] The user uses the same interface to input a parenting question, for example, "What is the appropriate amount of sleep for a 5-year-old child?" This question is used as a prompt to be sent to the generative AI model. The input question is then sent from the device to the server.

[1817] Input: A user question (e.g., "What is an appropriate amount of sleep for a 5-year-old child?")

[1818] Output: The question sent to the server.

[1819] Step 3:

[1820] The terminal collects the questions and attribute information entered by the user and sends them to a generative AI model. This system uses generative AI models such as OpenAI's GPT-4. The data is encrypted using the HTTPS protocol.

[1821] Input: Attribute information and question stored on the server

[1822] Output: The prompt sent to the generative AI model

[1823] Step 4:

[1824] The server inputs the received question and attribute information into the generative AI model to generate an answer. The generated answer is returned as text data such as "The appropriate amount of sleep for a 5-year-old child is 10 to 12 hours." The generative AI model uses natural language processing technology to generate the optimal answer.

[1825] Input: The prompt sent to the generative AI model

[1826] Output: The generated answer (e.g. "The appropriate amount of sleep for a 5-year-old child is 10-12 hours")

[1827] Step 5:

[1828] The server categorizes the generated answers into categories such as "sleep," "food," "education," etc. This categorization is stored in a database and helps generate personalized collections later.

[1829] Input: Generated Answer

[1830] Output: Answers sorted by category

[1831] Step 6:

[1832] The server generates a personalized collection of information for the user based on the classified answers. This collection is generated in PDF format and made available for download by the user. The collection contains information that is most appropriate for the user's attributes and questions.

[1833] Input: Answers sorted by category

[1834] Output: Personalized information collection (PDF format)

[1835] Step 7:

[1836] Users access the system's digital library and log in with their own account. They search the generated collection of information and click the "borrow" button to download it. This allows users to efficiently obtain information that is suited to them.

[1837] Input: A personalized search query

[1838] Output: A personalized collection of downloaded information

[1839] (Application example 2)

[1840] Next, a description will be given of Application Example 2 of Form 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".

[1841] Conventional child-rearing support systems have problems in that it is difficult to provide personalized advice based on the user's attributes, and they do not recommend related products or books, meaning that users cannot efficiently obtain the information and products they need. Furthermore, there is a lack of means to provide personalized information in a digital format, which means that it is difficult for users to easily carry the information with them.

[1842] 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.

[1843] In this invention, the server includes a means for inputting user attributes, a means for generating answers to user questions using a generative AI-based question-answering system, a means for categorizing the generated answers, a means for generating a personalized parenting book based on the classified answers, a means for recommending related products and books based on the generated answers, and a means for providing the personalized parenting book in a digital format. This allows users to obtain personalized advice based on their own attributes, and by receiving recommendations of related products and books, it becomes possible to efficiently obtain necessary information and products. Furthermore, providing personalized information in a digital format makes it easier for users to carry information around.

[1844] "User attributes" refers to information entered by the user, such as country, region, family structure, ages of parents and children, and environment.

[1845] A "generative AI question answering system" is an artificial intelligence system that generates appropriate answers to users' questions.

[1846] The "categorical classification means" is a function that classifies the generated answers into categories such as sleep, food, education, etc.

[1847] The "Personalized Parenting Book" is a book that compiles information about parenting that is individually customized based on the user's attributes and questions.

[1848] "Means for recommending related products and books" is a function that suggests products and books suitable for the user based on the generated answers.

[1849] "Means of providing in digital format" refers to the function of providing users with a personalized parenting book in a digital format such as an e-book or PDF.

[1850] In order to implement this invention, the server, the terminal, and the user must each fulfill a specific role. Specific embodiments are described below.

[1851] Server Roles

[1852] The server uses the following hardware and software to process and calculate data.

[1853] Hardware: High-performance server machine

[1854] Software: Python, OpenAI API

[1855] The server first provides a means for users to input their attributes. Then, it uses a generative AI-based question-answering system to generate answers to the user's questions. The generated answers are classified into categories. Furthermore, the server recommends related products and books based on the generated answers, and provides personalized parenting books in digital format.

[1856] Terminal Roles

[1857] A terminal (e.g., a smartphone) provides an interface with a user using the following hardware and software:

[1858] Hardware: Smartphone

[1859] Software: Mobile Application

[1860] The terminal provides an interface for the user to input his / her attributes and also provides an interface for the user to input questions about child-rearing, so that the user can easily input questions and receive answers.

[1861] User Roles

[1862] The user uses the terminal to perform the following operations:

[1863] 1. Enter your attributes.

[1864] 2. Enter your ...

Claims

1. A means for inputting user attributes; A means for generating an answer to the user's question by inputting a specific prompt sentence into a generative AI model; means for categorizing the generated answers; an emotion engine for analyzing the emotion of the user; A means for generating personalized parenting information based on the attributes, the analyzed emotions, and the classified answers; Including, the system.

2. The system of claim 1 , wherein the attributes include a country in which the user lives, a region in which the user lives, a family structure including the user, an age of the user's parents, and an age of the user's children.

3. The system of claim 1 , further comprising means for displaying the parenting information on a smart device.

Images