system

Abstract

Provide a system. A means for a user to input their attributes, interests, desired number of pages, etc.; A means for collecting related information from the Internet based on the input data; A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests; A means for automatically generating reports based on the converted information; A means to output the generated report in web or PDF format; A system including:

Description

[Technical Field]

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

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

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

[0004] This system solves the problem that when various targets, such as general consumers and investors, collect information, it takes time to comprehensively search and organize all information, making it difficult to obtain the information they need. As a result, there is a growing need to provide information customized to the reader's attributes and interests. With current systems, it is difficult to automatically generate information tailored to each user's attributes and interests and output it in an appropriate format. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides an information provision system that includes a means for a user to input their own attributes, interests, desired number of pages, etc., a means for collecting related information from the Internet based on the input data, a means for analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests, a means for automatically generating a report based on the converted information, and a means for outputting the generated report in web format or PDF format. This makes it possible to efficiently generate and provide reports that are optimized for the needs of each user.

[0006] "Means for users to input their attributes, interests, desired number of pages, etc." refers to an interface that allows users to input personal information such as age, occupation, areas of interest, desired number of pages, etc.

[0007] "Means for collecting related information from the Internet based on input data" refers to a function for automatically searching and retrieving related information from sources on the Internet based on data input by the user.

[0008] "Means for analyzing collected information and converting it into language expressions that correspond to the user's attributes and interests" refers to a function for analyzing collected data and converting it into a format and expression that best suits the user's attributes and interests.

[0009] "Means for automatically generating reports based on converted information" refers to a function for automatically creating reports in a format according to the user's request using analyzed and converted information.

[0010] "Means for outputting generated reports in web or PDF format" refers to a function for outputting automatically generated reports in web page format or PDF file format so that users can view and save them.

[0011] "Means for converting information by selecting a language style appropriate for the target reader" is a function for analyzing collected information and converting it into an appropriate language style according to the attributes of the selected target reader.

[0012] "Means for storing collected information in a database" refers to a function that provides a database for temporarily or permanently storing information collected from the Internet. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] 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.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] 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.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] 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.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] The present invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. To implement this system, the following programs and processes are mainly required.

[0035] User Input Interface

[0036] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0037] Information gathering

[0038] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect related information from the Internet. This process involves using web crawlers and APIs to collect the latest news, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0039] natural language generation

[0040] The server analyzes the collected data and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0041] Report Generation

[0042] The server then builds the appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapters and paragraphs, and places appropriate images and graphs. The report's content can include relevant breaking news, detailed analytical data, and visual charts.

[0043] Report Output

[0044] The server exports the generated report in web or PDF format. This process is important for easy access by users. The exported report is provided to the user's device as a download link. Users can click this link to download the report and easily obtain the information they need.

[0045] Specific examples

[0046] For example, investor User A enters the following information: "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5." The server uses keywords such as "SoftBank stock price" and "latest stock price news" to collect related information from the Internet. It then analyzes this information and generates a report containing specialized language and specific data customized for investors. Finally, the report is exported in PDF format and made available for users to download.

[0047] In this way, the present invention is a system that efficiently provides information that meets the individual needs of users.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] Terminal: Displays an interface where the user can enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information through this interface and clicks the "Submit" button.

[0051] Step 2:

[0052] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0053] Step 3:

[0054] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0055] Step 4:

[0056] Server: Uses the generated keywords to collect relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, through web crawlers and APIs.

[0057] Step 5:

[0058] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0059] Step 6:

[0060] Server: Analyzes the collected data and converts it into language expressions based on the user's attributes and interests. It uses Natural Language Processing (NLP) models to read the data and embed information into appropriate templates.

[0061] Step 7:

[0062] Server: Uses a natural language generation model (e.g., GPT-4 (registered trademark)) to convert the language style to suit the user's attributes and interests. For example, it generates explanations for investors that use a lot of technical terms and concrete figures.

[0063] Step 8:

[0064] Server: Automatically generates a report based on the converted information. Organizes the report into chapters and paragraphs, and places appropriate images and graphs. Adjusts the content according to the number of pages requested by the user.

[0065] Step 9:

[0066] Server: Export the generated report in Web or PDF format. Save the exported report as a file and generate a link to provide it to users.

[0067] Step 10:

[0068] On the device: A download link for the report will be displayed on the user's screen, allowing the user to click on this link to download the report.

[0069] Step 11:

[0070] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes and interests, allowing for efficient information retrieval.

[0071] Example 1

[0072] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0073] Today, there is a demand for quickly and automatically generating customized information tailored to individual users' attributes and interests and providing it in an easily accessible format. However, existing systems struggle to go beyond simply collecting data entered by users and effectively analyze that data to automatically generate appropriate reports tailored to the user's attributes and interests. Furthermore, the content of the generated reports often falls short of user expectations. Information provided in specialized fields, in particular, requires more specialized and specific content. Furthermore, the output formats of generated reports are limited, making them rarely provided in a format that users can easily access and use.

[0074] 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.

[0075] In this invention, the server includes: means for a user to input their attributes, interests, desired number of pages, etc.; means for collecting related information from the Internet based on the input data; means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests using Natural Language Processing (NLP) technology to analyze the converted data; means for automatically generating a report based on the generated information and determining the chapter structure and paragraphs of the report; means for adding images and graphs to the generated report; means for outputting the generated report in web format or PDF format; and means for providing the user with an access link to the generated report. This makes it possible to efficiently generate information customized to the individual needs of users, automatically create reports containing specialized and specific content, and further provide the reports in a format that the user can easily access.

[0076] A "user" is a person who uses this system to input data such as his or her attributes, interests, and desired number of pages.

[0077] The "Internet" is an information infrastructure that allows information to be accessed and shared through a globally connected network of computers.

[0078] "Related information" is data and content that is appropriate to the user's attributes and interests and is collected from the Internet based on data entered by the user.

[0079] "Analysis" is the process of breaking down collected information and extracting meanings and patterns based on user attributes and interests.

[0080] "Natural Language Processing (NLP) technology" is a technology that enables computers to understand and generate human language, and is used to analyze text data and convert it into appropriate language expressions.

[0081] "Text generation" is the process of automatically generating documents based on analyzed data that are appropriate for the user's attributes and interests.

[0082] A "report" is a document that compiles collected information and generated text and provides it in a user-viewable format.

[0083] "Image" means a visual representation of data added to a report, including, for example, a photograph, illustration, graph, etc.

[0084] A "graph" is a chart such as a bar graph, line graph, or pie chart that visually represents numerical data.

[0085] "Web format" means a format that can be viewed and accessed through an Internet browser.

[0086] "PDF format" is an abbreviation for Portable Document Format, and is a file format for displaying and printing electronic documents while preserving their original layout.

[0087] An "access link" is a URL or hyperlink that allows a user to access a generated report and is a means of directly reaching the specified content by clicking on it.

[0088] The present invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. The main hardware required is a device (smartphone, PC, tablet) for users to input information and a server (cloud server, on-premise server) for data processing and report generation. The software required includes analysis software for natural language processing (NLP) technology and information collection tools using web crawlers and APIs. Specifically, the NLP technology can use Hugging Face's Transformers or GPT-3 (registered trademark) model, and the web crawler can use Beautiful Soup or Scrapy.

[0089] User Input Interface

[0090] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and desired page number. This interface can be implemented in the form of a web page or a mobile app, and is built using HTML, JavaScript (registered trademark), and CSS. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server using the JavaScript fetch function.

[0091] Information gathering

[0092] The server analyzes the received user data using a web framework such as Flask. Based on the results of this analysis, appropriate search keywords are generated. For example, if a user is interested in "SoftBank's stock price trends," keywords such as "SoftBank stock price" and "latest stock price news" are generated. Related information is then collected from the Internet using Beautiful Soup or Scrapy. The latest news and stock price information can be obtained using the News API. The collected data is stored in a database such as PostgreSQL using the psycopg2 library.

[0093] natural language generation

[0094] The server analyzes the collected data using NLP technology. For example, by using Hugging Face's Transformers or GPT-3, the data is converted into language expressions that correspond to the user's attributes and interests. Based on the analysis results, sentences that match the user's attributes and interests are generated.

[0095] Report Generation

[0096] The server then determines the chapters and paragraphs of the report based on the generated text. It uses Markdown or LaTeX templates to build the report, adding images and graphs as needed. Matplotlib and Plotly can be used to create images and graphs.

[0097] Report Output

[0098] The server exports the generated report in PDF or web format. For example, you can generate a PDF using LaTeX, then use the pdfkit library to convert HTML to PDF. Finally, the server provides the user with an access link to the generated report. By clicking the provided link, the user can download the report and easily obtain the required information.

[0099] Specific examples

[0100] For example, investor User A enters "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5 pages." In this case, the server collects related information from the Internet using keywords such as "SoftBank stock price" and "latest stock price news." It then analyzes the collected information and generates a report for investors containing professional language and specific data. This report is exported in PDF format and can finally be downloaded and used by users.

[0101] Prompt Sentence Examples

[0102] "Generate a 5-page report for investors on the latest SoftBank stock price movements."

[0103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0104] Step 1:

[0105] The terminal displays an interface for the user to input information. Specifically, it displays a web page built using HTML, JavaScript, and CSS, and provides input fields in the form for age, occupation, areas of interest, and desired page count. When the user enters data into these fields and clicks the "Submit" button, the input data is collected. Once input is complete, the input data is sent to the server via the HTTPS protocol using the JavaScript fetch function (input data: age, occupation, areas of interest, desired page count; output data: input data sent to the server).

[0106] Step 2:

[0107] The server analyzes the received input data using a web framework such as Flask. For data analysis, it uses methods such as Python's request.get_json() method, which extracts user attribute information (input data: input data received from the device, output data: analyzed user attribute information).

[0108] Step 3:

[0109] The server generates appropriate search keywords based on the analysis results. For example, if a user is interested in "SoftBank's stock price trends," it generates keywords such as "SoftBank stock price" and "latest stock price news." In this step, specific algorithms and machine learning models are used to select the keywords that best fit the user's interests (input data: analyzed user attribute information, output data: generated search keywords).

[0110] Step 4:

[0111] The server uses the generated search keywords to collect related information from the Internet using web scraping tools such as Beautiful Soup or Scrapy. Data related to the user's interests, such as the latest news and stock prices, is obtained from websites and APIs (input data: generated search keywords, output data: collected related information).

[0112] Step 5:

[0113] The server stores the collected information in a database. For storage, a relational database such as PostgreSQL is used, and the database is connected using the Python psycopg2 library (input data: collected related information, output data: information stored in the database).

[0114] Step 6:

[0115] The server analyzes the stored information using Natural Language Processing (NLP) technology, using models such as Hugging Face's Transformers and GPT-3 to convert the collected data into linguistic expressions that correspond to the user's attributes and interests (input data: information stored in the database, output data: analyzed text-generated data).

[0116] Step 7:

[0117] The server automatically generates a report based on the generated text according to the user's desired page count and format. Markdown and LaTeX templates are used to determine the report's chapter structure and paragraphs, and images and graphs are added as needed. Matplotlib and Plotly are used to create images and graphs (input data: parsed text-generated data, output data: generated report).

[0118] Step 8:

[0119] The server exports the generated report in PDF or web format. It can generate PDF using LaTeX and convert HTML to PDF using the pdfkit library (input data: generated report, output data: exported PDF or web format report).

[0120] Step 9:

[0121] The server generates a download link for the exported report and provides it to the user, who can click the link to download and view the report (input data: exported PDF or web format report, output data: download link).

[0122] This process efficiently generates customized information tailored to the user's individual needs and presents it to the user in an easily accessible format.

[0123] (Application example 1)

[0124] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0125] Conventional information report generation systems have limited customization based on user attributes and interests, making them difficult to apply to individual customer service, especially in brick-and-mortar stores. Another problem is that analyzing the collected information is cumbersome, making it difficult to provide information tailored to specific purposes. Furthermore, there was no way to instantly provide the generated reports visually or audibly, making it difficult to provide effective customer service in brick-and-mortar stores.

[0126] 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.

[0127] In this invention, the server includes a means for users to input their attributes, interests, desired number of pages, etc., a means for collecting related information from the Internet based on the input data, and a means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests. This makes it possible to efficiently collect and analyze information according to the individual needs of the user and provide customized reports.

[0128] The system further includes a means for collecting appropriate product information based on customer information, a means for automatically generating customized product descriptions using the collected product information, and a means for providing the automatically generated product descriptions visually or by audio output, thereby enabling personalized product information to be provided to customers in real time in physical stores, thereby achieving effective customer service.

[0129] "Means for users to input their attributes, interests, desired number of pages, etc." refers to a device or system that allows users to input information such as their age, occupation, areas of interest, desired number of pages of the report, etc. through an interface.

[0130] "Means for collecting related information from the Internet based on input data" refers to a device or system that uses the Internet to search for and obtain related information based on attributes and interests obtained from the user.

[0131] "Means for analyzing collected information and converting it into language expressions that correspond to the user's attributes and interests" refers to a device or system that has the function of analyzing collected information and converting it into language expressions that are most suitable for the user's attributes and interests.

[0132] The "means for automatically generating a report based on the converted information" refers to a device or system for automatically creating a report based on the converted information.

[0133] "Means for outputting the generated report in Web format or PDF format" refers to a device or system for outputting the automatically generated report in Web page format or PDF file format on the Internet.

[0134] The "means for collecting appropriate product information based on customer information" refers to a device or system for collecting relevant product information based on the attributes and interests of customers.

[0135] "Means for automatically generating customized product descriptions using collected product information" refers to a device or system that automatically creates product descriptions that are optimal for customers based on collected product information.

[0136] "Means for providing automatically generated product descriptions by visual or audio output" refers to a device or system for presenting the created product descriptions to customers visually (such as on a display) or audio.

[0137] The present invention is a system that generates customized information based on the user's attributes and interests and provides it to customers in a physical store. To realize this system, the following programs and processes are required.

[0138] First, the device provides an interface where the user can enter information such as age, occupation, areas of interest, desired page number, etc. This can be implemented as a web page or mobile app. When the user enters the required information through this interface and clicks the submit button, the data is sent to the server.

[0139] The server analyzes the data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. The collected data is then stored in a database.

[0140] The server then analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template, generating text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0141] Furthermore, an external API is used to collect appropriate product information based on customer information. A customized product description is automatically generated based on the collected product information. This process uses a generative AI model from OpenAI (registered trademark) to generate text based on the generated prompt. This generative AI model is then used to generate product descriptions appropriate for the customer.

[0142] The generated product description can be provided in the format desired by the user (visual or audio output). Specifically, it can be displayed on a display or played back as audio. This function makes it possible to provide information to customers in real time in physical stores.

[0143] For example, if a 30-year-old office worker enters "Interests: Home appliances, technology, desired number of pages: 3," the server will collect information on appropriate home appliances based on this and generate customized product descriptions, allowing customers to obtain the information they need in real time in the store.

[0144] An example prompt is:

[0145] "User information: Age 30, Occupation: Office worker, Interests: Home appliances, technology. Product information: Details of a new smartphone. Based on this, generate a customized product description and recommendation list."

[0146] In this way, the present invention is a system that realizes effective customer service in physical stores by providing customers with individually customized information and product descriptions.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Step 1:

[0149] The terminal provides an interface for the user to input information such as age, occupation, areas of interest, desired number of pages, etc. The user inputs information through this interface and clicks the "Submit" button, which sends the input data (age, occupation, areas of interest, desired number of pages, etc.) from the terminal to the server.

[0150] Step 2:

[0151] The server analyzes the input data received from the user. Specifically, it generates appropriate search keywords based on the user's age, occupation, areas of interest, and desired number of pages. In this analysis step, it extracts relevant keywords using a database and a rule engine. The generated keywords are output.

[0152] Step 3:

[0153] The server uses the generated keywords to gather relevant information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. For example, keywords such as "home appliance technology latest information" are used. The collected information is stored in a database and search results are output.

[0154] Step 4:

[0155] The server analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. This process uses Natural Language Processing (NLP) technology. The NLP model receives the collected information and user attribute data as input and generates customized text as output. This text is then output.

[0156] Step 5:

[0157] The server automatically generates a report based on the converted information. The report is generated using a template, which organizes chapters and paragraphs based on the user's desired page count and format. Specifically, the text generated by NLP is inserted into the report template. The generated report is then output.

[0158] Step 6:

[0159] The server collects appropriate product information based on customer information. It calls an external API to obtain relevant product information and stores it in a database. In this process, it searches for keywords such as "latest smartphone models." The collected product information is output.

[0160] Step 7:

[0161] The server automatically generates a customized product description using the collected product information. It uses OpenAI's generative AI model to generate text based on the prompt. This generative AI model is used to generate a product description appropriate for the customer. The generated product description is output.

[0162] Step 8:

[0163] The server provides the automatically generated product description visually or by audio output. Visual output is achieved by displaying the product on a display screen, and audio output is achieved by using speech synthesis technology. This process provides the generated product description in the format specified by the user. The final information is output and made available to the user.

[0164] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0165] The present invention combines an emotion engine with a system that automatically generates customized information based on a user's attributes and interests and provides it in report format. The programs required to implement this system and their processing details are described below.

[0166] User Input Interface

[0167] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0168] Information gathering

[0169] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect relevant information from sources on the Internet. This process involves using web crawlers and APIs to gather news articles, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0170] emotion recognition

[0171] The emotion engine installed on the server analyzes the user's input data and recognizes the user's emotional state. This emotion data is inferred from the wording and context of the text entered by the user. For example, it identifies emotional states such as "anxiety," "excitement," and "satisfaction."

[0172] natural language generation

[0173] The server analyzes the collected data and emotional data and converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the user's specific attributes, interests, and emotional state. If the user is in a specific emotional state, appropriate wording and information presentation methods are used.

[0174] Report Generation

[0175] The server then creates an appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapter structure and paragraphs, and places appropriate images and graphs. The report includes text that reflects the user's emotional state, allowing for more personalized information provision.

[0176] Report Output

[0177] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user. The user can click this link to download the report from their device and easily obtain the information they need.

[0178] Specific examples

[0179] For example, investor User A might enter "Age: 45, Occupation: Investor, Interests: Stock Price Trends, Desired Page Count: 5 pages." If the emotion engine further recognizes "anxiety" from User A's input, the server will collect information using keywords such as "company name stock price" and "latest stock price news." It then generates a report that reflects the emotion data and includes calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and made available for users to download.

[0180] In this way, the present invention is a system that efficiently provides information according to the individual needs and feelings of the user.

[0181] The processing flow will be explained below.

[0182] Step 1:

[0183] Terminal: The user accesses the interface and is presented with a form to enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information and clicks the "Submit" button.

[0184] Step 2:

[0185] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0186] Step 3:

[0187] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0188] Step 4:

[0189] Server: Uses the generated keywords to gather relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, using web crawlers and APIs.

[0190] Step 5:

[0191] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0192] Step 6:

[0193] Server: Recognizes emotions from user-entered data using an emotion engine. Analyzes user-entered text and identifies emotional states such as "anxious," "excited," or "happy."

[0194] Step 7:

[0195] Server: Based on the collected data and sentiment data, converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. Analyzes the data using Natural Language Processing (NLP) technology and embeds the information in appropriate templates.

[0196] Step 8:

[0197] Server: Uses a natural language generation model (e.g., GPT-4) to convert the language style to match the user's attributes and emotions. For example, if the user is feeling anxious, the language will be adjusted to reduce anxiety.

[0198] Step 9:

[0199] Server: Based on the converted information, the server automatically generates a report with the number of pages requested by the user, constructs the report's chapters and paragraphs, and places appropriate images and graphs.

[0200] Step 10:

[0201] Server: Export the generated report in web or PDF format. Save the exported report as a file and provide a download link to the user.

[0202] Step 11:

[0203] On the device: A download link for the report will be displayed on the user's screen. The user can click the link to download the report.

[0204] Step 12:

[0205] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes, interests, and sentiment, allowing for efficient information gathering.

[0206] Example 2

[0207] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0208] Conventional information provision systems were able to provide customized information based on the user's attributes and interests, but they did not generate reports that took the user's emotional state into consideration. As a result, they were unable to provide information that was in line with the user's emotions, making it difficult to provide appropriate advice or mental care. Furthermore, there were insufficient means for efficiently storing and managing collected information.

[0209] 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.

[0210] In this invention, the server includes: a means for a user to input their attributes, interests, desired page count, etc.; a means for collecting related information from the Internet based on the input data; a means for analyzing the collected information and converting it into language expressions appropriate to the user's attributes and interests; a means for automatically generating a report based on the converted information and the user's emotional state; and a means for outputting the generated report in web or PDF format. This enables the provision of personalized information tailored to the user's individual needs and emotional state, enabling appropriate advice and mental care. Furthermore, efficient storage and management of collected information facilitates the reuse and management of information.

[0211] A "user" is a user who inputs information such as attributes, interests, and desired number of pages into the system.

[0212] "Attributes" refer to personal information such as a user's age, occupation, and areas of interest.

[0213] "Interests" are specific areas or topics that interest a user.

[0214] "Desired number of pages" is the number of pages the user specifies as the length of the generated report.

[0215] A "means" is a method or function for performing a specific process within a system.

[0216] "Means of collecting relevant information from the Internet" refers to methods and tools for collecting necessary information from the Internet. Specifically, this includes using web crawlers and APIs.

[0217] "Means for converting information into linguistic expressions" refers to the process of converting collected information into a form that is easy for users to understand. Specifically, this includes the use of natural language processing technology.

[0218] "Emotional state" refers to an emotion inferred from the information and context entered by the user. Examples include "anxiety," "excitement," and "satisfaction."

[0219] "Means for automatically generating reports" refers to methods or tools that allow a program to automatically generate reports based on a user's attributes, interests, and emotional state.

[0220] "Means for outputting in web or PDF format" refers to methods or tools for saving and outputting the generated report in a format that can be viewed via the Internet or in an electronic document format.

[0221] The system of the present invention allows users to input their attributes, interests, desired number of pages, etc., and then collects and analyzes customized information based on that information, generating and providing reports tailored to their emotions. The system includes a user interface in the form of a web page or mobile app, and data processing and report generation functions on the server.

[0222] User Input Interface

[0223] The device provides an interface for users to enter the necessary information. This interface is implemented in the form of a web page or mobile app. The user enters information such as age, occupation, areas of interest, and the desired number of pages into the form and clicks the "Submit" button. The entered data is sent to the server.

[0224] Information gathering

[0225] The server analyzes the input data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from sources on the Internet. This process uses Python libraries (BeautifulSoup, Scrapy, etc.) and API access libraries (requests, etc.). The collected data is then stored in a database.

[0226] emotion recognition

[0227] The emotion engine on the server analyzes the user's input data and recognizes the user's emotional state. This emotion recognition uses a BERT-based model using Hugging Face's Transformers library. Emotional states include "anxiety," "excitement," and "satisfaction."

[0228] natural language generation

[0229] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. In this step, OpenAI's GPT-3 model is used to generate natural language. The following prompts are used:

[0230] Prompt Sentence Examples

[0231] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0232] Data collected: "Latest stock price news, stock price information of major companies"

[0233] Report Generation

[0234] The server creates an appropriate report based on the number of pages and format specified by the user. It determines chapters and paragraphs based on the generated text, and places images and graphs. The report includes text that reflects the user's emotional state, providing more personalized information. The report is generated as a LaTeX file and can be output in PDF format using the pdflatex command.

[0235] Report Output

[0236] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user, who can click this link to download the report and obtain the required information.

[0237] Specific examples

[0238] For example, if User A, a 45-year-old investor, enters "Age: 45, Occupation: Investor, Interest: Stock Price Trends, Desired Page Count: 5 pages" and the emotion engine recognizes "anxiety," the server collects information using keywords such as "company name stock price" and "latest stock price news." It then generates a report containing calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and can be downloaded and used by the user.

[0239] In this way, the system of the present invention can efficiently provide information according to the individual needs and feelings of the user.

[0240] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0241] Program processing flow

[0242] Step 1:

[0243] User Input Interface

[0244] The user accesses the interface, which can be a web page or a mobile app, using their device. They fill out a form with information such as age, occupation, areas of interest, and the desired number of pages, and then click the "Submit" button. The submitted data is sent to the server via an HTTP POST request.

[0245] Input: Age, occupation, areas of interest, desired number of pages

[0246] Output: The input data is sent to the server

[0247] Step 2:

[0248] Information gathering

[0249] The server analyzes the input data received from the user and generates appropriate search keywords. This analysis is performed using a natural language processing algorithm. The generated keywords are then used to collect related information from sources on the Internet. Specifically, the required data is obtained using Python libraries (BeautifulSoup, Scrapy) and API access libraries (requests). The collected data is then stored in a database.

[0250] Input: User input data (age, occupation, areas of interest, desired number of pages)

[0251] Output: Relevant information (news articles, stock quotes, etc.) is stored in a database

[0252] Step 3:

[0253] emotion recognition

[0254] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state. This analysis uses a BERT-based model using Hugging Face's Transformers library. The emotional state is estimated from the wording and context of the text, such as "anxiety," "excitement," or "satisfaction."

[0255] Input: User-entered data

[0256] Output: User's emotional state (e.g., anxiety)

[0257] Step 4:

[0258] natural language generation

[0259] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. The OpenAI GPT-3 model is used in this step. The following prompts are used to generate the expressions:

[0260] Prompt Sentence Examples

[0261] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0262] Data collected: "Latest stock price news, stock price information of major companies"

[0263] Input: collected data, user's emotional state

[0264] Output: User-optimized text

[0265] Step 5:

[0266] Report Generation

[0267] The server then creates a report from the generated text, according to the page count and formatting specified by the user, by generating a LaTeX file and inserting images and graphs as appropriate, and then generating a PDF version of the report using the pdflatex command.

[0268] Input: Generated text, user-specified format and page count

[0269] Output: Report in PDF format

[0270] Step 6:

[0271] Report Output

[0272] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide to the user, who can click this link to download the report from their device and obtain the required information.

[0273] Input: Generated report

[0274] Output: User accessible links

[0275] The above are the specific processing steps and flow of this system. This system realizes more personalized report generation by providing information according to the user's attributes, interests, and emotions.

[0276] (Application example 2)

[0277] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0278] In modern society, consumers are surrounded by a wide variety of information every day. Particularly when shopping online, choosing the most suitable product from the vast amount of product information can be a challenge. Furthermore, there is a demand for personalized information and guidance that reflects each individual consumer's attributes, interests, and even their emotional state at any given time. However, conventional systems are unable to fully meet these needs, limiting the extent to which they can improve consumer satisfaction. Therefore, there is a need for a system that can simultaneously provide personalized information that takes into account the user's attributes, interests, and emotional state, while optimizing the shopping experience.

[0279] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own attributes, interests, desired number of pages, etc., means for collecting related information from the Internet based on the input data, means for analyzing the collected information and converting it into language expressions corresponding to the user's attributes and interests, means for recognizing the user's emotional state and reflecting it in the analysis results, means for automatically generating a report based on the converted information, means for outputting the generated report in Web format or PDF format, and means for providing a shopping guide and product recommendations based on the user's emotional state. This enables personalized shopping guides and product recommendations according to the user's attributes, interests, and emotional state, thereby improving consumer satisfaction and enabling efficient product selection.

[0280] "User attributes" refers to individual information about an individual, such as age, occupation, gender, and place of residence.

[0281] "Interests" refers to areas or themes that a user is interested in, favorite activities, etc.

[0282] "Desired number of pages" refers to the number of pages of the report desired by the user.

[0283] "Means of collecting relevant information from the Internet" refers to methods for obtaining necessary information from the Internet using web crawlers or APIs.

[0284] "Means for converting into linguistic expression" refers to a method for expressing analyzed data as text in a form suitable for the user.

[0285] "Emotional state" refers to the user's state of mind, and includes emotions such as anxiety, excitement, and satisfaction.

[0286] "Analysis results" refers to the output generated based on collected information and the user's attributes, interests, and emotional state.

[0287] "Means for automatically generating reports" refers to a system or method for compiling collected and analyzed information into a report format.

[0288] "Means for web or PDF output" refers to a method for exporting the generated report as an HTML or PDF file.

[0289] "Shopping Guide" refers to guidelines that provide users with advice and information regarding product selection and purchase.

[0290] "Product recommendation" refers to the process of suggesting appropriate products based on a user's attributes, interests, and emotions.

[0291] This invention is a system that automatically generates customized information based on a user's attributes and interests, and combines it with an emotion engine to provide the generated information in a more personalized format. This system is particularly intended for use in shopping guides and product recommendations within virtual stores.

[0292] Overview of the entire system

[0293] First, the user uses a device (such as a smartphone or head-mounted display) to input their attributes (age, occupation, areas of interest, desired page number, etc.). The device collects this data and sends it to the server.

[0294] The server uses web crawlers and APIs (Application Programming Interfaces) to retrieve data from sources on the Internet to collect related information based on the input data, and the collected data is stored in a database.

[0295] The server then uses an emotion engine to recognize the user's emotional state from the input data. For example, emotional states such as "anxious" or "excited" are analyzed. This emotion data is inferred based on the text entered by the user and other input data.

[0296] After obtaining the emotion data, the server uses Natural Language Processing (NLP) technology to analyze the collected data and emotion data, and generate text according to the user's attributes, interests, and emotions. In particular, a report is generated that incorporates linguistic expressions that match the user's emotional state.

[0297] The server generates reports to provide users with optimal shopping guides and product recommendations, and exports the information in the format of the user's choice (web or PDF), generating links for easy access.

[0298] Hardware and software used

[0299] Hardware: Smartphone, Head-Mounted Display (HMD)

[0300] Software: Python, requests (for data collection), NLPProcessor (for natural language generation), EmotionEngine (for emotion engine), pdf_generator (for PDF generation)

[0301] Specific examples

[0302] For example, consumer User B inputs "Age: 35, Occupation: Designer, Interests: Latest Gadgets, Desired Page Count: 3 pages." If the emotion engine recognizes "excitement" from User B's input, the server collects information using keywords such as "latest gadget reviews" and "innovative technology." It then generates a report that incorporates the emotion data and includes expressions that amplify excitement and information on the latest trends. Finally, the report is exported in PDF format and made available for User B to download and use.

[0303] Prompt Sentence Examples

[0304] User Attributes:

[0305] Age: 35

[0306] Occupation: Designer

[0307] Interests: Latest gadgets

[0308] Desired number of pages: 3 pages

[0309] Emotion: Excitement

[0310] In this way, the system provides personalized shopping guides and product recommendations that are tailored to the user's individual needs and emotions.

[0311] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0312] Step 1:

[0313] The user uses a device (smartphone, head-mounted display, etc.) to input their attributes (age, occupation, areas of interest, desired number of pages, etc.). The input data includes age, occupation, areas of interest, and desired number of pages. When the user completes the input and clicks the "Submit" button, this data is sent to the server.

[0314] Input: User attribute data (age, occupation, areas of interest, desired number of pages)

[0315] Output: User attribute data sent to the server

[0316] Step 2:

[0317] The server analyzes the data received from the user, generates appropriate search keywords, and determines the scope and type of data to collect. Specifically, it selects the most appropriate information source based on the user's area of ​​interest and the number of pages required.

[0318] Input: User attribute data

[0319] Output: Search keywords, type and range of collected data

[0320] Step 3:

[0321] The server uses the generated search keywords to collect relevant information from sources on the Internet via web crawlers and APIs, and the collected data is stored in a database.

[0322] Input: Search keywords, type and range of collected data

[0323] Output: Relevant information collected

[0324] Step 4:

[0325] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state, inferring emotions such as "anxiety," "excitement," and "satisfaction" from context and word choice.

[0326] Input: User attribute data

[0327] Output: User emotion data

[0328] Step 5:

[0329] The server uses NLP (Natural Language Processing) technology to generate text based on the collected information and emotional data. This text is personalized according to the user's attributes, interests, and emotions. For example, if the emotional state is "excited," expressions that enhance excitement are used.

[0330] Input: Collected relevant information, user emotion data

[0331] Output: Generated personalized text

[0332] Step 6:

[0333] The server then uses the generated text to create a report in the format desired by the user (Web or PDF), based on the number of pages and format desired by the user.

[0334] Input: Generated personalized text, user-preferred page count and format

[0335] Output: The constructed report

[0336] Step 7:

[0337] The server exports the constructed report in the specified format (Web format or PDF format) and generates a link to provide it to the user. The user can click this link to download the report from their terminal and easily obtain the information they need.

[0338] Input: Constructed report

[0339] Output: Web or PDF report, download link

[0340] The above steps realize a system that efficiently and effectively provides information according to the user's attributes, interests, and emotional state.

[0341] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0342] 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 engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0343] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0344] [Second embodiment]

[0345] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0346] 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.

[0347] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0348] 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.

[0349] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0350] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0351] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0352] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0353] 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.

[0354] 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.

[0355] 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.

[0356] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0357] The present invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. To implement this system, the following programs and processes are mainly required.

[0358] User Input Interface

[0359] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0360] Information gathering

[0361] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect related information from the Internet. This process involves using web crawlers and APIs to collect the latest news, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0362] natural language generation

[0363] The server analyzes the collected data and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0364] Report Generation

[0365] The server then builds the appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapters and paragraphs, and places appropriate images and graphs. The report's content can include relevant breaking news, detailed analytical data, and visual charts.

[0366] Report Output

[0367] The server exports the generated report in web or PDF format. This process is important for easy access by users. The exported report is provided to the user's device as a download link. Users can click this link to download the report and easily obtain the information they need.

[0368] Specific examples

[0369] For example, investor User A enters the following information: "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5." The server uses keywords such as "SoftBank stock price" and "latest stock price news" to collect related information from the Internet. It then analyzes this information and generates a report containing specialized language and specific data customized for investors. Finally, the report is exported in PDF format and made available for users to download.

[0370] In this way, the present invention is a system that efficiently provides information that meets the individual needs of users.

[0371] The processing flow will be explained below.

[0372] Step 1:

[0373] Terminal: Displays an interface where the user can enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information through this interface and clicks the "Submit" button.

[0374] Step 2:

[0375] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0376] Step 3:

[0377] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0378] Step 4:

[0379] Server: Uses the generated keywords to collect relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, through web crawlers and APIs.

[0380] Step 5:

[0381] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0382] Step 6:

[0383] Server: Analyzes the collected data and converts it into language expressions based on the user's attributes and interests. It uses Natural Language Processing (NLP) models to read the data and embed information into appropriate templates.

[0384] Step 7:

[0385] Server: Uses a natural language generation model (e.g., GPT-4) to adapt the language style to suit the user's attributes and interests. For example, generate explanations for investors that use a lot of technical jargon and concrete figures.

[0386] Step 8:

[0387] Server: Automatically generates a report based on the converted information. Organizes the report into chapters and paragraphs, and places appropriate images and graphs. Adjusts the content according to the number of pages requested by the user.

[0388] Step 9:

[0389] Server: Export the generated report in Web or PDF format. Save the exported report as a file and generate a link to provide it to users.

[0390] Step 10:

[0391] On the device: A download link for the report will be displayed on the user's screen, allowing the user to click on this link to download the report.

[0392] Step 11:

[0393] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes and interests, allowing for efficient information retrieval.

[0394] Example 1

[0395] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0396] Today, there is a demand for quickly and automatically generating customized information tailored to individual users' attributes and interests and providing it in an easily accessible format. However, existing systems struggle to go beyond simply collecting data entered by users and effectively analyze that data to automatically generate appropriate reports tailored to the user's attributes and interests. Furthermore, the content of the generated reports often falls short of user expectations. Information provided in specialized fields, in particular, requires more specialized and specific content. Furthermore, the output formats of generated reports are limited, making them rarely provided in a format that users can easily access and use.

[0397] 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.

[0398] In this invention, the server includes: means for a user to input their attributes, interests, desired number of pages, etc.; means for collecting related information from the Internet based on the input data; means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests using Natural Language Processing (NLP) technology to analyze the converted data; means for automatically generating a report based on the generated information and determining the chapter structure and paragraphs of the report; means for adding images and graphs to the generated report; means for outputting the generated report in web format or PDF format; and means for providing the user with an access link to the generated report. This makes it possible to efficiently generate information customized to the individual needs of users, automatically create reports containing specialized and specific content, and further provide the reports in a format that the user can easily access.

[0399] A "user" is a person who uses this system to input data such as his or her attributes, interests, and desired number of pages.

[0400] The "Internet" is an information infrastructure that allows information to be accessed and shared through a globally connected network of computers.

[0401] "Related information" is data and content that is appropriate to the user's attributes and interests and is collected from the Internet based on data entered by the user.

[0402] "Analysis" is the process of breaking down collected information and extracting meanings and patterns based on user attributes and interests.

[0403] "Natural Language Processing (NLP) technology" is a technology that enables computers to understand and generate human language, and is used to analyze text data and convert it into appropriate language expressions.

[0404] "Text generation" is the process of automatically generating documents based on analyzed data that are appropriate for the user's attributes and interests.

[0405] A "report" is a document that compiles collected information and generated text and provides it in a user-viewable format.

[0406] "Image" means a visual representation of data added to a report, including, for example, a photograph, illustration, graph, etc.

[0407] A "graph" is a chart such as a bar graph, line graph, or pie chart that visually represents numerical data.

[0408] "Web format" means a format that can be viewed and accessed through an Internet browser.

[0409] "PDF format" is an abbreviation for Portable Document Format, and is a file format for displaying and printing electronic documents while preserving their original layout.

[0410] An "access link" is a URL or hyperlink that allows a user to access a generated report and is a means of directly reaching the specified content by clicking on it.

[0411] This invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. The main hardware required is a device (smartphone, PC, tablet) for users to input information, and a server (cloud server, on-premise server) for data processing and report generation. The software required includes analysis software for natural language processing (NLP) technology, and information collection tools using web crawlers and APIs. Specifically, the NLP technology can use Hugging Face's Transformers or GPT-3 model, and the web crawler can use Beautiful Soup or Scrapy.

[0412] User Input Interface

[0413] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and desired page number. This interface can be implemented in the form of a web page or a mobile app and is built using HTML, JavaScript, and CSS. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server using the JavaScript fetch function.

[0414] Information gathering

[0415] The server analyzes the received user data using a web framework such as Flask. Based on the results of this analysis, appropriate search keywords are generated. For example, if a user is interested in "SoftBank's stock price trends," keywords such as "SoftBank stock price" and "latest stock price news" are generated. Related information is then collected from the Internet using Beautiful Soup or Scrapy. The latest news and stock price information can be obtained using the News API. The collected data is stored in a database such as PostgreSQL using the psycopg2 library.

[0416] natural language generation

[0417] The server analyzes the collected data using NLP technology. For example, by using Hugging Face's Transformers or GPT-3, the data is converted into language expressions that correspond to the user's attributes and interests. Based on the analysis results, sentences that match the user's attributes and interests are generated.

[0418] Report Generation

[0419] The server then determines the chapters and paragraphs of the report based on the generated text. It uses Markdown or LaTeX templates to build the report, adding images and graphs as needed. Matplotlib and Plotly can be used to create images and graphs.

[0420] Report Output

[0421] The server exports the generated report in PDF or web format. For example, you can generate a PDF using LaTeX, then use the pdfkit library to convert HTML to PDF. Finally, the server provides the user with an access link to the generated report. By clicking the provided link, the user can download the report and easily obtain the required information.

[0422] Specific examples

[0423] For example, investor User A enters "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5 pages." In this case, the server collects related information from the Internet using keywords such as "SoftBank stock price" and "latest stock price news." It then analyzes the collected information and generates a report for investors containing professional language and specific data. This report is exported in PDF format and can finally be downloaded and used by users.

[0424] Prompt Sentence Examples

[0425] "Generate a 5-page report for investors on the latest SoftBank stock price movements."

[0426] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0427] Step 1:

[0428] The terminal displays an interface for the user to input information. Specifically, it displays a web page built using HTML, JavaScript, and CSS, and provides input fields in the form for age, occupation, areas of interest, and desired page count. When the user enters data into these fields and clicks the "Submit" button, the input data is collected. Once input is complete, the input data is sent to the server via the HTTPS protocol using the JavaScript fetch function (input data: age, occupation, areas of interest, desired page count; output data: input data sent to the server).

[0429] Step 2:

[0430] The server analyzes the received input data using a web framework such as Flask. For data analysis, it uses methods such as Python's request.get_json() method, which extracts user attribute information (input data: input data received from the device, output data: analyzed user attribute information).

[0431] Step 3:

[0432] The server generates appropriate search keywords based on the analysis results. For example, if a user is interested in "SoftBank's stock price trends," it generates keywords such as "SoftBank stock price" and "latest stock price news." In this step, specific algorithms and machine learning models are used to select the keywords that best fit the user's interests (input data: analyzed user attribute information, output data: generated search keywords).

[0433] Step 4:

[0434] The server uses the generated search keywords to collect related information from the Internet using web scraping tools such as Beautiful Soup or Scrapy. Data related to the user's interests, such as the latest news and stock prices, is obtained from websites and APIs (input data: generated search keywords, output data: collected related information).

[0435] Step 5:

[0436] The server stores the collected information in a database. For storage, a relational database such as PostgreSQL is used, and the database is connected using the Python psycopg2 library (input data: collected related information, output data: information stored in the database).

[0437] Step 6:

[0438] The server analyzes the stored information using Natural Language Processing (NLP) technology, using models such as Hugging Face's Transformers and GPT-3 to convert the collected data into linguistic expressions that correspond to the user's attributes and interests (input data: information stored in the database, output data: analyzed text-generated data).

[0439] Step 7:

[0440] The server automatically generates a report based on the generated text according to the user's desired page count and format. Markdown and LaTeX templates are used to determine the report's chapter structure and paragraphs, and images and graphs are added as needed. Matplotlib and Plotly are used to create images and graphs (input data: parsed text-generated data, output data: generated report).

[0441] Step 8:

[0442] The server exports the generated report in PDF or web format. It can generate PDF using LaTeX and convert HTML to PDF using the pdfkit library (input data: generated report, output data: exported PDF or web format report).

[0443] Step 9:

[0444] The server generates a download link for the exported report and provides it to the user, who can click the link to download and view the report (input data: exported PDF or web format report, output data: download link).

[0445] This process efficiently generates customized information tailored to the user's individual needs and presents it to the user in an easily accessible format.

[0446] (Application example 1)

[0447] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0448] Conventional information report generation systems have limited customization based on user attributes and interests, making them difficult to apply to individual customer service, especially in brick-and-mortar stores. Another problem is that analyzing the collected information is cumbersome, making it difficult to provide information tailored to specific purposes. Furthermore, there was no way to instantly provide the generated reports visually or audibly, making it difficult to provide effective customer service in brick-and-mortar stores.

[0449] 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.

[0450] In this invention, the server includes a means for users to input their attributes, interests, desired number of pages, etc., a means for collecting related information from the Internet based on the input data, and a means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests. This makes it possible to efficiently collect and analyze information according to the individual needs of the user and provide customized reports.

[0451] The system further includes a means for collecting appropriate product information based on customer information, a means for automatically generating customized product descriptions using the collected product information, and a means for providing the automatically generated product descriptions visually or by audio output, thereby enabling personalized product information to be provided to customers in real time in physical stores, thereby achieving effective customer service.

[0452] "Means for users to input their attributes, interests, desired number of pages, etc." refers to a device or system that allows users to input information such as their age, occupation, areas of interest, desired number of pages of the report, etc. through an interface.

[0453] "Means for collecting related information from the Internet based on input data" refers to a device or system that uses the Internet to search for and obtain related information based on attributes and interests obtained from the user.

[0454] "Means for analyzing collected information and converting it into language expressions that correspond to the user's attributes and interests" refers to a device or system that has the function of analyzing collected information and converting it into language expressions that are most suitable for the user's attributes and interests.

[0455] The "means for automatically generating a report based on the converted information" refers to a device or system for automatically creating a report based on the converted information.

[0456] "Means for outputting the generated report in Web format or PDF format" refers to a device or system for outputting the automatically generated report in Web page format or PDF file format on the Internet.

[0457] The "means for collecting appropriate product information based on customer information" refers to a device or system for collecting relevant product information based on the attributes and interests of customers.

[0458] "Means for automatically generating customized product descriptions using collected product information" refers to a device or system that automatically creates product descriptions that are optimal for customers based on collected product information.

[0459] "Means for providing automatically generated product descriptions by visual or audio output" refers to a device or system for presenting the created product descriptions to customers visually (such as on a display) or audio.

[0460] The present invention is a system that generates customized information based on the user's attributes and interests and provides it to customers in a physical store. To realize this system, the following programs and processes are required.

[0461] First, the device provides an interface where the user can enter information such as age, occupation, areas of interest, desired page number, etc. This can be implemented as a web page or mobile app. When the user enters the required information through this interface and clicks the submit button, the data is sent to the server.

[0462] The server analyzes the data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. The collected data is then stored in a database.

[0463] The server then analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template, generating text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0464] In addition, an external API is used to collect appropriate product information based on customer information. A customized product description is automatically generated based on the collected product information. This process uses OpenAI's generative AI model to generate text based on the generated prompt. This generative AI model is then used to generate product descriptions appropriate for the customer.

[0465] The generated product description can be provided in the format desired by the user (visual or audio output). Specifically, it can be displayed on a display or played back as audio. This function makes it possible to provide information to customers in real time in physical stores.

[0466] For example, if a 30-year-old office worker enters "Interests: Home appliances, technology, desired number of pages: 3," the server will collect information on appropriate home appliances based on this and generate customized product descriptions, allowing customers to obtain the information they need in real time in the store.

[0467] An example prompt is:

[0468] "User information: Age 30, Occupation: Office worker, Interests: Home appliances, technology. Product information: Details of a new smartphone. Based on this, generate a customized product description and recommendation list."

[0469] In this way, the present invention is a system that realizes effective customer service in physical stores by providing customers with individually customized information and product descriptions.

[0470] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0471] Step 1:

[0472] The terminal provides an interface for the user to input information such as age, occupation, areas of interest, desired number of pages, etc. The user inputs information through this interface and clicks the "Submit" button, which sends the input data (age, occupation, areas of interest, desired number of pages, etc.) from the terminal to the server.

[0473] Step 2:

[0474] The server analyzes the input data received from the user. Specifically, it generates appropriate search keywords based on the user's age, occupation, areas of interest, and desired number of pages. In this analysis step, it extracts relevant keywords using a database and a rule engine. The generated keywords are output.

[0475] Step 3:

[0476] The server uses the generated keywords to gather relevant information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. For example, keywords such as "home appliance technology latest information" are used. The collected information is stored in a database and search results are output.

[0477] Step 4:

[0478] The server analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. This process uses Natural Language Processing (NLP) technology. The NLP model receives the collected information and user attribute data as input and generates customized text as output. This text is then output.

[0479] Step 5:

[0480] The server automatically generates a report based on the converted information. The report is generated using a template, which organizes chapters and paragraphs based on the user's desired page count and format. Specifically, the text generated by NLP is inserted into the report template. The generated report is then output.

[0481] Step 6:

[0482] The server collects appropriate product information based on customer information. It calls an external API to obtain relevant product information and stores it in a database. In this process, it searches for keywords such as "latest smartphone models." The collected product information is output.

[0483] Step 7:

[0484] The server automatically generates a customized product description using the collected product information. It uses OpenAI's generative AI model to generate text based on the prompt. This generative AI model is used to generate a product description appropriate for the customer. The generated product description is output.

[0485] Step 8:

[0486] The server provides the automatically generated product description visually or by audio output. Visual output is achieved by displaying the product on a display screen, and audio output is achieved by using speech synthesis technology. This process provides the generated product description in the format specified by the user. The final information is output and made available to the user.

[0487] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0488] The present invention combines an emotion engine with a system that automatically generates customized information based on a user's attributes and interests and provides it in report format. The programs required to implement this system and their processing details are described below.

[0489] User Input Interface

[0490] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0491] Information gathering

[0492] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect relevant information from sources on the Internet. This process involves using web crawlers and APIs to gather news articles, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0493] emotion recognition

[0494] The emotion engine installed on the server analyzes the user's input data and recognizes the user's emotional state. This emotion data is inferred from the wording and context of the text entered by the user. For example, it identifies emotional states such as "anxiety," "excitement," and "satisfaction."

[0495] natural language generation

[0496] The server analyzes the collected data and emotional data and converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the user's specific attributes, interests, and emotional state. If the user is in a specific emotional state, appropriate wording and information presentation methods are used.

[0497] Report Generation

[0498] The server then creates an appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapter structure and paragraphs, and places appropriate images and graphs. The report includes text that reflects the user's emotional state, allowing for more personalized information provision.

[0499] Report Output

[0500] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user. The user can click this link to download the report from their device and easily obtain the information they need.

[0501] Specific examples

[0502] For example, investor User A might enter "Age: 45, Occupation: Investor, Interests: Stock Price Trends, Desired Page Count: 5 pages." If the emotion engine further recognizes "anxiety" from User A's input, the server will collect information using keywords such as "company name stock price" and "latest stock price news." It then generates a report that reflects the emotion data and includes calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and made available for users to download.

[0503] In this way, the present invention is a system that efficiently provides information according to the individual needs and feelings of the user.

[0504] The processing flow will be explained below.

[0505] Step 1:

[0506] Terminal: The user accesses the interface and is presented with a form to enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information and clicks the "Submit" button.

[0507] Step 2:

[0508] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0509] Step 3:

[0510] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0511] Step 4:

[0512] Server: Uses the generated keywords to gather relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, using web crawlers and APIs.

[0513] Step 5:

[0514] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0515] Step 6:

[0516] Server: Recognizes emotions from user-entered data using an emotion engine. Analyzes user-entered text and identifies emotional states such as "anxious," "excited," or "happy."

[0517] Step 7:

[0518] Server: Based on the collected data and sentiment data, converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. Analyzes the data using Natural Language Processing (NLP) technology and embeds the information in appropriate templates.

[0519] Step 8:

[0520] Server: Uses a natural language generation model (e.g., GPT-4) to convert the language style to match the user's attributes and emotions. For example, if the user is feeling anxious, the language will be adjusted to reduce anxiety.

[0521] Step 9:

[0522] Server: Based on the converted information, the server automatically generates a report with the number of pages requested by the user, constructs the report's chapters and paragraphs, and places appropriate images and graphs.

[0523] Step 10:

[0524] Server: Export the generated report in web or PDF format. Save the exported report as a file and provide a download link to the user.

[0525] Step 11:

[0526] On the device: A download link for the report will be displayed on the user's screen. The user can click the link to download the report.

[0527] Step 12:

[0528] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes, interests, and sentiment, allowing for efficient information gathering.

[0529] Example 2

[0530] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0531] Conventional information provision systems were able to provide customized information based on the user's attributes and interests, but they did not generate reports that took the user's emotional state into consideration. As a result, they were unable to provide information that was in line with the user's emotions, making it difficult to provide appropriate advice or mental care. Furthermore, there were insufficient means for efficiently storing and managing collected information.

[0532] 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.

[0533] In this invention, the server includes: a means for a user to input their attributes, interests, desired page count, etc.; a means for collecting related information from the Internet based on the input data; a means for analyzing the collected information and converting it into language expressions appropriate to the user's attributes and interests; a means for automatically generating a report based on the converted information and the user's emotional state; and a means for outputting the generated report in web or PDF format. This enables the provision of personalized information tailored to the user's individual needs and emotional state, enabling appropriate advice and mental care. Furthermore, efficient storage and management of collected information facilitates the reuse and management of information.

[0534] A "user" is a user who inputs information such as attributes, interests, and desired number of pages into the system.

[0535] "Attributes" refer to personal information such as a user's age, occupation, and areas of interest.

[0536] "Interests" are specific areas or topics that interest a user.

[0537] "Desired number of pages" is the number of pages the user specifies as the length of the generated report.

[0538] A "means" is a method or function for performing a specific process within a system.

[0539] "Means of collecting relevant information from the Internet" refers to methods and tools for collecting necessary information from the Internet. Specifically, this includes using web crawlers and APIs.

[0540] "Means for converting information into linguistic expressions" refers to the process of converting collected information into a form that is easy for users to understand. Specifically, this includes the use of natural language processing technology.

[0541] "Emotional state" refers to an emotion inferred from the information and context entered by the user. Examples include "anxiety," "excitement," and "satisfaction."

[0542] "Means for automatically generating reports" refers to methods or tools that allow a program to automatically generate reports based on a user's attributes, interests, and emotional state.

[0543] "Means for outputting in web or PDF format" refers to methods or tools for saving and outputting the generated report in a format that can be viewed via the Internet or in an electronic document format.

[0544] The system of the present invention allows users to input their attributes, interests, desired number of pages, etc., and then collects and analyzes customized information based on that information, generating and providing reports tailored to their emotions. The system includes a user interface in the form of a web page or mobile app, and data processing and report generation functions on the server.

[0545] User Input Interface

[0546] The device provides an interface for users to enter the necessary information. This interface is implemented in the form of a web page or mobile app. The user enters information such as age, occupation, areas of interest, and the desired number of pages into the form and clicks the "Submit" button. The entered data is sent to the server.

[0547] Information gathering

[0548] The server analyzes the input data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from sources on the Internet. This process uses Python libraries (BeautifulSoup, Scrapy, etc.) and API access libraries (requests, etc.). The collected data is then stored in a database.

[0549] emotion recognition

[0550] The emotion engine on the server analyzes the user's input data and recognizes the user's emotional state. This emotion recognition uses a BERT-based model using Hugging Face's Transformers library. Emotional states include "anxiety," "excitement," and "satisfaction."

[0551] natural language generation

[0552] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. In this step, OpenAI's GPT-3 model is used to generate natural language. The following prompts are used:

[0553] Prompt Sentence Examples

[0554] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0555] Data collected: "Latest stock price news, stock price information of major companies"

[0556] Report Generation

[0557] The server creates an appropriate report based on the number of pages and format specified by the user. It determines chapters and paragraphs based on the generated text, and places images and graphs. The report includes text that reflects the user's emotional state, providing more personalized information. The report is generated as a LaTeX file and can be output in PDF format using the pdflatex command.

[0558] Report Output

[0559] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user, who can click this link to download the report and obtain the required information.

[0560] Specific examples

[0561] For example, if User A, a 45-year-old investor, enters "Age: 45, Occupation: Investor, Interest: Stock Price Trends, Desired Page Count: 5 pages" and the emotion engine recognizes "anxiety," the server collects information using keywords such as "company name stock price" and "latest stock price news." It then generates a report containing calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and can be downloaded and used by the user.

[0562] In this way, the system of the present invention can efficiently provide information according to the individual needs and feelings of the user.

[0563] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0564] Program processing flow

[0565] Step 1:

[0566] User Input Interface

[0567] The user accesses the interface, which can be a web page or a mobile app, using their device. They fill out a form with information such as age, occupation, areas of interest, and the desired number of pages, and then click the "Submit" button. The submitted data is sent to the server via an HTTP POST request.

[0568] Input: Age, occupation, areas of interest, desired number of pages

[0569] Output: The input data is sent to the server

[0570] Step 2:

[0571] Information gathering

[0572] The server analyzes the input data received from the user and generates appropriate search keywords. This analysis is performed using a natural language processing algorithm. The generated keywords are then used to collect related information from sources on the Internet. Specifically, the required data is obtained using Python libraries (BeautifulSoup, Scrapy) and API access libraries (requests). The collected data is then stored in a database.

[0573] Input: User input data (age, occupation, areas of interest, desired number of pages)

[0574] Output: Relevant information (news articles, stock quotes, etc.) is stored in a database

[0575] Step 3:

[0576] emotion recognition

[0577] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state. This analysis uses a BERT-based model using Hugging Face's Transformers library. The emotional state is estimated from the wording and context of the text, such as "anxiety," "excitement," or "satisfaction."

[0578] Input: User-entered data

[0579] Output: User's emotional state (e.g., anxiety)

[0580] Step 4:

[0581] natural language generation

[0582] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. The OpenAI GPT-3 model is used in this step. The following prompts are used to generate the expressions:

[0583] Prompt Sentence Examples

[0584] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0585] Data collected: "Latest stock price news, stock price information of major companies"

[0586] Input: collected data, user's emotional state

[0587] Output: User-optimized text

[0588] Step 5:

[0589] Report Generation

[0590] The server then creates a report from the generated text, according to the page count and formatting specified by the user, by generating a LaTeX file and inserting images and graphs as appropriate, and then generating a PDF version of the report using the pdflatex command.

[0591] Input: Generated text, user-specified format and page count

[0592] Output: Report in PDF format

[0593] Step 6:

[0594] Report Output

[0595] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide to the user, who can click this link to download the report from their device and obtain the required information.

[0596] Input: Generated report

[0597] Output: User accessible links

[0598] The above are the specific processing steps and flow of this system. This system realizes more personalized report generation by providing information according to the user's attributes, interests, and emotions.

[0599] (Application example 2)

[0600] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0601] In modern society, consumers are surrounded by a wide variety of information every day. Particularly when shopping online, choosing the most suitable product from the vast amount of product information can be a challenge. Furthermore, there is a demand for personalized information and guidance that reflects each individual consumer's attributes, interests, and even their emotional state at any given time. However, conventional systems are unable to fully meet these needs, limiting the extent to which they can improve consumer satisfaction. Therefore, there is a need for a system that can simultaneously provide personalized information that takes into account the user's attributes, interests, and emotional state, while optimizing the shopping experience.

[0602] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own attributes, interests, desired number of pages, etc., means for collecting related information from the Internet based on the input data, means for analyzing the collected information and converting it into language expressions corresponding to the user's attributes and interests, means for recognizing the user's emotional state and reflecting it in the analysis results, means for automatically generating a report based on the converted information, means for outputting the generated report in Web format or PDF format, and means for providing a shopping guide and product recommendations based on the user's emotional state. This enables personalized shopping guides and product recommendations according to the user's attributes, interests, and emotional state, thereby improving consumer satisfaction and enabling efficient product selection.

[0603] "User attributes" refers to individual information about an individual, such as age, occupation, gender, and place of residence.

[0604] "Interests" refers to areas or themes that a user is interested in, favorite activities, etc.

[0605] "Desired number of pages" refers to the number of pages of the report desired by the user.

[0606] "Means of collecting relevant information from the Internet" refers to methods for obtaining necessary information from the Internet using web crawlers or APIs.

[0607] "Means for converting into linguistic expression" refers to a method for expressing analyzed data as text in a form suitable for the user.

[0608] "Emotional state" refers to the user's state of mind, and includes emotions such as anxiety, excitement, and satisfaction.

[0609] "Analysis results" refers to the output generated based on collected information and the user's attributes, interests, and emotional state.

[0610] "Means for automatically generating reports" refers to a system or method for compiling collected and analyzed information into a report format.

[0611] "Means for web or PDF output" refers to a method for exporting the generated report as an HTML or PDF file.

[0612] "Shopping Guide" refers to guidelines that provide users with advice and information regarding product selection and purchase.

[0613] "Product recommendation" refers to the process of suggesting appropriate products based on a user's attributes, interests, and emotions.

[0614] This invention is a system that automatically generates customized information based on a user's attributes and interests, and combines it with an emotion engine to provide the generated information in a more personalized format. This system is particularly intended for use in shopping guides and product recommendations within virtual stores.

[0615] Overview of the entire system

[0616] First, the user uses a device (such as a smartphone or head-mounted display) to input their attributes (age, occupation, areas of interest, desired page number, etc.). The device collects this data and sends it to the server.

[0617] The server uses web crawlers and APIs (Application Programming Interfaces) to retrieve data from sources on the Internet to collect related information based on the input data, and the collected data is stored in a database.

[0618] The server then uses an emotion engine to recognize the user's emotional state from the input data. For example, emotional states such as "anxious" or "excited" are analyzed. This emotion data is inferred based on the text entered by the user and other input data.

[0619] After obtaining the emotion data, the server uses Natural Language Processing (NLP) technology to analyze the collected data and emotion data, and generate text according to the user's attributes, interests, and emotions. In particular, a report is generated that incorporates linguistic expressions that match the user's emotional state.

[0620] The server generates reports to provide users with optimal shopping guides and product recommendations, and exports the information in the format of the user's choice (web or PDF), generating links for easy access.

[0621] Hardware and software used

[0622] Hardware: Smartphone, Head-Mounted Display (HMD)

[0623] Software: Python, requests (for data collection), NLPProcessor (for natural language generation), EmotionEngine (for emotion engine), pdf_generator (for PDF generation)

[0624] Specific examples

[0625] For example, consumer User B inputs "Age: 35, Occupation: Designer, Interests: Latest Gadgets, Desired Page Count: 3 pages." If the emotion engine recognizes "excitement" from User B's input, the server collects information using keywords such as "latest gadget reviews" and "innovative technology." It then generates a report that incorporates the emotion data and includes expressions that amplify excitement and information on the latest trends. Finally, the report is exported in PDF format and made available for User B to download and use.

[0626] Prompt Sentence Examples

[0627] User Attributes:

[0628] Age: 35

[0629] Occupation: Designer

[0630] Interests: Latest gadgets

[0631] Desired number of pages: 3 pages

[0632] Emotion: Excitement

[0633] In this way, the system provides personalized shopping guides and product recommendations that are tailored to the user's individual needs and emotions.

[0634] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0635] Step 1:

[0636] The user uses a device (smartphone, head-mounted display, etc.) to input their attributes (age, occupation, areas of interest, desired number of pages, etc.). The input data includes age, occupation, areas of interest, and desired number of pages. When the user completes the input and clicks the "Submit" button, this data is sent to the server.

[0637] Input: User attribute data (age, occupation, areas of interest, desired number of pages)

[0638] Output: User attribute data sent to the server

[0639] Step 2:

[0640] The server analyzes the data received from the user, generates appropriate search keywords, and determines the scope and type of data to collect. Specifically, it selects the most appropriate information source based on the user's area of ​​interest and the number of pages required.

[0641] Input: User attribute data

[0642] Output: Search keywords, type and range of collected data

[0643] Step 3:

[0644] The server uses the generated search keywords to collect relevant information from sources on the Internet via web crawlers and APIs, and the collected data is stored in a database.

[0645] Input: Search keywords, type and range of collected data

[0646] Output: Relevant information collected

[0647] Step 4:

[0648] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state, inferring emotions such as "anxiety," "excitement," and "satisfaction" from context and word choice.

[0649] Input: User attribute data

[0650] Output: User emotion data

[0651] Step 5:

[0652] The server uses NLP (Natural Language Processing) technology to generate text based on the collected information and emotional data. This text is personalized according to the user's attributes, interests, and emotions. For example, if the emotional state is "excited," expressions that enhance excitement are used.

[0653] Input: Collected relevant information, user emotion data

[0654] Output: Generated personalized text

[0655] Step 6:

[0656] The server then uses the generated text to create a report in the format desired by the user (Web or PDF), based on the number of pages and format desired by the user.

[0657] Input: Generated personalized text, user-preferred page count and format

[0658] Output: The constructed report

[0659] Step 7:

[0660] The server exports the constructed report in the specified format (Web format or PDF format) and generates a link to provide it to the user. The user can click this link to download the report from their terminal and easily obtain the information they need.

[0661] Input: Constructed report

[0662] Output: Web or PDF report, download link

[0663] The above steps realize a system that efficiently and effectively provides information according to the user's attributes, interests, and emotional state.

[0664] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0665] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0666] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0667] [Third embodiment]

[0668] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0669] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0670] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0671] 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.

[0672] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0673] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0674] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0675] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0676] 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.

[0677] 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.

[0678] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0679] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0680] The present invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. To implement this system, the following programs and processes are mainly required.

[0681] User Input Interface

[0682] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0683] Information gathering

[0684] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect related information from the Internet. This process involves using web crawlers and APIs to collect the latest news, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0685] natural language generation

[0686] The server analyzes the collected data and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0687] Report Generation

[0688] The server then builds the appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapters and paragraphs, and places appropriate images and graphs. The report's content can include relevant breaking news, detailed analytical data, and visual charts.

[0689] Report Output

[0690] The server exports the generated report in web or PDF format. This process is important for easy access by users. The exported report is provided to the user's device as a download link. Users can click this link to download the report and easily obtain the information they need.

[0691] Specific examples

[0692] For example, investor User A enters the following information: "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5." The server uses keywords such as "SoftBank stock price" and "latest stock price news" to collect related information from the Internet. It then analyzes this information and generates a report containing specialized language and specific data customized for investors. Finally, the report is exported in PDF format and made available for users to download.

[0693] In this way, the present invention is a system that efficiently provides information that meets the individual needs of users.

[0694] The processing flow will be explained below.

[0695] Step 1:

[0696] Terminal: Displays an interface where the user can enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information through this interface and clicks the "Submit" button.

[0697] Step 2:

[0698] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0699] Step 3:

[0700] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0701] Step 4:

[0702] Server: Uses the generated keywords to collect relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, through web crawlers and APIs.

[0703] Step 5:

[0704] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0705] Step 6:

[0706] Server: Analyzes the collected data and converts it into language expressions based on the user's attributes and interests. It uses Natural Language Processing (NLP) models to read the data and embed information into appropriate templates.

[0707] Step 7:

[0708] Server: Uses a natural language generation model (e.g., GPT-4) to adapt the language style to suit the user's attributes and interests. For example, generate explanations for investors that use a lot of technical jargon and concrete figures.

[0709] Step 8:

[0710] Server: Automatically generates a report based on the converted information. Organizes the report into chapters and paragraphs, and places appropriate images and graphs. Adjusts the content according to the number of pages requested by the user.

[0711] Step 9:

[0712] Server: Export the generated report in Web or PDF format. Save the exported report as a file and generate a link to provide it to users.

[0713] Step 10:

[0714] On the device: A download link for the report will be displayed on the user's screen, allowing the user to click on this link to download the report.

[0715] Step 11:

[0716] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes and interests, allowing for efficient information retrieval.

[0717] Example 1

[0718] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0719] Today, there is a demand for quickly and automatically generating customized information tailored to individual users' attributes and interests and providing it in an easily accessible format. However, existing systems struggle to go beyond simply collecting data entered by users and effectively analyze that data to automatically generate appropriate reports tailored to the user's attributes and interests. Furthermore, the content of the generated reports often falls short of user expectations. Information provided in specialized fields, in particular, requires more specialized and specific content. Furthermore, the output formats of generated reports are limited, making them rarely provided in a format that users can easily access and use.

[0720] 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.

[0721] In this invention, the server includes: means for a user to input their attributes, interests, desired number of pages, etc.; means for collecting related information from the Internet based on the input data; means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests using Natural Language Processing (NLP) technology to analyze the converted data; means for automatically generating a report based on the generated information and determining the chapter structure and paragraphs of the report; means for adding images and graphs to the generated report; means for outputting the generated report in web format or PDF format; and means for providing the user with an access link to the generated report. This makes it possible to efficiently generate information customized to the individual needs of users, automatically create reports containing specialized and specific content, and further provide the reports in a format that the user can easily access.

[0722] A "user" is a person who uses this system to input data such as his or her attributes, interests, and desired number of pages.

[0723] The "Internet" is an information infrastructure that allows information to be accessed and shared through a globally connected network of computers.

[0724] "Related information" is data and content that is appropriate to the user's attributes and interests and is collected from the Internet based on data entered by the user.

[0725] "Analysis" is the process of breaking down collected information and extracting meanings and patterns based on user attributes and interests.

[0726] "Natural Language Processing (NLP) technology" is a technology that enables computers to understand and generate human language, and is used to analyze text data and convert it into appropriate language expressions.

[0727] "Text generation" is the process of automatically generating documents based on analyzed data that are appropriate for the user's attributes and interests.

[0728] A "report" is a document that compiles collected information and generated text and provides it in a user-viewable format.

[0729] "Image" means a visual representation of data added to a report, including, for example, a photograph, illustration, graph, etc.

[0730] A "graph" is a chart such as a bar graph, line graph, or pie chart that visually represents numerical data.

[0731] "Web format" means a format that can be viewed and accessed through an Internet browser.

[0732] "PDF format" is an abbreviation for Portable Document Format, and is a file format for displaying and printing electronic documents while preserving their original layout.

[0733] An "access link" is a URL or hyperlink that allows a user to access a generated report and is a means of directly reaching the specified content by clicking on it.

[0734] This invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. The main hardware required is a device (smartphone, PC, tablet) for users to input information, and a server (cloud server, on-premise server) for data processing and report generation. The software required includes analysis software for natural language processing (NLP) technology, and information collection tools using web crawlers and APIs. Specifically, the NLP technology can use Hugging Face's Transformers or GPT-3 model, and the web crawler can use Beautiful Soup or Scrapy.

[0735] User Input Interface

[0736] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and desired page number. This interface can be implemented in the form of a web page or a mobile app and is built using HTML, JavaScript, and CSS. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server using the JavaScript fetch function.

[0737] Information gathering

[0738] The server analyzes the received user data using a web framework such as Flask. Based on the results of this analysis, appropriate search keywords are generated. For example, if a user is interested in "SoftBank's stock price trends," keywords such as "SoftBank stock price" and "latest stock price news" are generated. Related information is then collected from the Internet using Beautiful Soup or Scrapy. The latest news and stock price information can be obtained using the News API. The collected data is stored in a database such as PostgreSQL using the psycopg2 library.

[0739] natural language generation

[0740] The server analyzes the collected data using NLP technology. For example, by using Hugging Face's Transformers or GPT-3, the data is converted into language expressions that correspond to the user's attributes and interests. Based on the analysis results, sentences that match the user's attributes and interests are generated.

[0741] Report Generation

[0742] The server then determines the chapters and paragraphs of the report based on the generated text. It uses Markdown or LaTeX templates to build the report, adding images and graphs as needed. Matplotlib and Plotly can be used to create images and graphs.

[0743] Report Output

[0744] The server exports the generated report in PDF or web format. For example, you can generate a PDF using LaTeX, then use the pdfkit library to convert HTML to PDF. Finally, the server provides the user with an access link to the generated report. By clicking the provided link, the user can download the report and easily obtain the required information.

[0745] Specific examples

[0746] For example, investor User A enters "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5 pages." In this case, the server collects related information from the Internet using keywords such as "SoftBank stock price" and "latest stock price news." It then analyzes the collected information and generates a report for investors containing professional language and specific data. This report is exported in PDF format and can finally be downloaded and used by users.

[0747] Prompt Sentence Examples

[0748] "Generate a 5-page report for investors on the latest SoftBank stock price movements."

[0749] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0750] Step 1:

[0751] The terminal displays an interface for the user to input information. Specifically, it displays a web page built using HTML, JavaScript, and CSS, and provides input fields in the form for age, occupation, areas of interest, and desired page count. When the user enters data into these fields and clicks the "Submit" button, the input data is collected. Once input is complete, the input data is sent to the server via the HTTPS protocol using the JavaScript fetch function (input data: age, occupation, areas of interest, desired page count; output data: input data sent to the server).

[0752] Step 2:

[0753] The server analyzes the received input data using a web framework such as Flask. For data analysis, it uses methods such as Python's request.get_json() method, which extracts user attribute information (input data: input data received from the device, output data: analyzed user attribute information).

[0754] Step 3:

[0755] The server generates appropriate search keywords based on the analysis results. For example, if a user is interested in "SoftBank's stock price trends," it generates keywords such as "SoftBank stock price" and "latest stock price news." In this step, specific algorithms and machine learning models are used to select the keywords that best fit the user's interests (input data: analyzed user attribute information, output data: generated search keywords).

[0756] Step 4:

[0757] The server uses the generated search keywords to collect related information from the Internet using web scraping tools such as Beautiful Soup or Scrapy. Data related to the user's interests, such as the latest news and stock prices, is obtained from websites and APIs (input data: generated search keywords, output data: collected related information).

[0758] Step 5:

[0759] The server stores the collected information in a database. For storage, a relational database such as PostgreSQL is used, and the database is connected using the Python psycopg2 library (input data: collected related information, output data: information stored in the database).

[0760] Step 6:

[0761] The server analyzes the stored information using Natural Language Processing (NLP) technology, using models such as Hugging Face's Transformers and GPT-3 to convert the collected data into linguistic expressions that correspond to the user's attributes and interests (input data: information stored in the database, output data: analyzed text-generated data).

[0762] Step 7:

[0763] The server automatically generates a report based on the generated text according to the user's desired page count and format. Markdown and LaTeX templates are used to determine the report's chapter structure and paragraphs, and images and graphs are added as needed. Matplotlib and Plotly are used to create images and graphs (input data: parsed text-generated data, output data: generated report).

[0764] Step 8:

[0765] The server exports the generated report in PDF or web format. It can generate PDF using LaTeX and convert HTML to PDF using the pdfkit library (input data: generated report, output data: exported PDF or web format report).

[0766] Step 9:

[0767] The server generates a download link for the exported report and provides it to the user, who can click the link to download and view the report (input data: exported PDF or web format report, output data: download link).

[0768] This process efficiently generates customized information tailored to the user's individual needs and presents it to the user in an easily accessible format.

[0769] (Application example 1)

[0770] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0771] Conventional information report generation systems have limited customization based on user attributes and interests, making them difficult to apply to individual customer service, especially in brick-and-mortar stores. Another problem is that analyzing the collected information is cumbersome, making it difficult to provide information tailored to specific purposes. Furthermore, there was no way to instantly provide the generated reports visually or audibly, making it difficult to provide effective customer service in brick-and-mortar stores.

[0772] 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.

[0773] In this invention, the server includes a means for users to input their attributes, interests, desired number of pages, etc., a means for collecting related information from the Internet based on the input data, and a means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests. This makes it possible to efficiently collect and analyze information according to the individual needs of the user and provide customized reports.

[0774] The system further includes a means for collecting appropriate product information based on customer information, a means for automatically generating customized product descriptions using the collected product information, and a means for providing the automatically generated product descriptions visually or by audio output, thereby enabling personalized product information to be provided to customers in real time in physical stores, thereby achieving effective customer service.

[0775] "Means for users to input their attributes, interests, desired number of pages, etc." refers to a device or system that allows users to input information such as their age, occupation, areas of interest, desired number of pages of the report, etc. through an interface.

[0776] "Means for collecting related information from the Internet based on input data" refers to a device or system that uses the Internet to search for and obtain related information based on attributes and interests obtained from the user.

[0777] "Means for analyzing collected information and converting it into language expressions that correspond to the user's attributes and interests" refers to a device or system that has the function of analyzing collected information and converting it into language expressions that are most suitable for the user's attributes and interests.

[0778] The "means for automatically generating a report based on the converted information" refers to a device or system for automatically creating a report based on the converted information.

[0779] "Means for outputting the generated report in Web format or PDF format" refers to a device or system for outputting the automatically generated report in Web page format or PDF file format on the Internet.

[0780] The "means for collecting appropriate product information based on customer information" refers to a device or system for collecting relevant product information based on the attributes and interests of customers.

[0781] "Means for automatically generating customized product descriptions using collected product information" refers to a device or system that automatically creates product descriptions that are optimal for customers based on collected product information.

[0782] "Means for providing automatically generated product descriptions by visual or audio output" refers to a device or system for presenting the created product descriptions to customers visually (such as on a display) or audio.

[0783] The present invention is a system that generates customized information based on the user's attributes and interests and provides it to customers in a physical store. To realize this system, the following programs and processes are required.

[0784] First, the device provides an interface where the user can enter information such as age, occupation, areas of interest, desired page number, etc. This can be implemented as a web page or mobile app. When the user enters the required information through this interface and clicks the submit button, the data is sent to the server.

[0785] The server analyzes the data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. The collected data is then stored in a database.

[0786] The server then analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template, generating text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[0787] In addition, an external API is used to collect appropriate product information based on customer information. A customized product description is automatically generated based on the collected product information. This process uses OpenAI's generative AI model to generate text based on the generated prompt. This generative AI model is then used to generate product descriptions appropriate for the customer.

[0788] The generated product description can be provided in the format desired by the user (visual or audio output). Specifically, it can be displayed on a display or played back as audio. This function makes it possible to provide information to customers in real time in physical stores.

[0789] For example, if a 30-year-old office worker enters "Interests: Home appliances, technology, desired number of pages: 3," the server will collect information on appropriate home appliances based on this and generate customized product descriptions, allowing customers to obtain the information they need in real time in the store.

[0790] An example prompt is:

[0791] "User information: Age 30, Occupation: Office worker, Interests: Home appliances, technology. Product information: Details of a new smartphone. Based on this, generate a customized product description and recommendation list."

[0792] In this way, the present invention is a system that realizes effective customer service in physical stores by providing customers with individually customized information and product descriptions.

[0793] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0794] Step 1:

[0795] The terminal provides an interface for the user to input information such as age, occupation, areas of interest, desired number of pages, etc. The user inputs information through this interface and clicks the "Submit" button, which sends the input data (age, occupation, areas of interest, desired number of pages, etc.) from the terminal to the server.

[0796] Step 2:

[0797] The server analyzes the input data received from the user. Specifically, it generates appropriate search keywords based on the user's age, occupation, areas of interest, and desired number of pages. In this analysis step, it extracts relevant keywords using a database and a rule engine. The generated keywords are output.

[0798] Step 3:

[0799] The server uses the generated keywords to gather relevant information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. For example, keywords such as "home appliance technology latest information" are used. The collected information is stored in a database and search results are output.

[0800] Step 4:

[0801] The server analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. This process uses Natural Language Processing (NLP) technology. The NLP model receives the collected information and user attribute data as input and generates customized text as output. This text is then output.

[0802] Step 5:

[0803] The server automatically generates a report based on the converted information. The report is generated using a template, which organizes chapters and paragraphs based on the user's desired page count and format. Specifically, the text generated by NLP is inserted into the report template. The generated report is then output.

[0804] Step 6:

[0805] The server collects appropriate product information based on customer information. It calls an external API to obtain relevant product information and stores it in a database. In this process, it searches for keywords such as "latest smartphone models." The collected product information is output.

[0806] Step 7:

[0807] The server automatically generates a customized product description using the collected product information. It uses OpenAI's generative AI model to generate text based on the prompt. This generative AI model is used to generate a product description appropriate for the customer. The generated product description is output.

[0808] Step 8:

[0809] The server provides the automatically generated product description visually or by audio output. Visual output is achieved by displaying the product on a display screen, and audio output is achieved by using speech synthesis technology. This process provides the generated product description in the format specified by the user. The final information is output and made available to the user.

[0810] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0811] The present invention combines an emotion engine with a system that automatically generates customized information based on a user's attributes and interests and provides it in report format. The programs required to implement this system and their processing details are described below.

[0812] User Input Interface

[0813] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[0814] Information gathering

[0815] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect relevant information from sources on the Internet. This process involves using web crawlers and APIs to gather news articles, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[0816] emotion recognition

[0817] The emotion engine installed on the server analyzes the user's input data and recognizes the user's emotional state. This emotion data is inferred from the wording and context of the text entered by the user. For example, it identifies emotional states such as "anxiety," "excitement," and "satisfaction."

[0818] natural language generation

[0819] The server analyzes the collected data and emotional data and converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the user's specific attributes, interests, and emotional state. If the user is in a specific emotional state, appropriate wording and information presentation methods are used.

[0820] Report Generation

[0821] The server then creates an appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapter structure and paragraphs, and places appropriate images and graphs. The report includes text that reflects the user's emotional state, allowing for more personalized information provision.

[0822] Report Output

[0823] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user. The user can click this link to download the report from their device and easily obtain the information they need.

[0824] Specific examples

[0825] For example, investor User A might enter "Age: 45, Occupation: Investor, Interests: Stock Price Trends, Desired Page Count: 5 pages." If the emotion engine further recognizes "anxiety" from User A's input, the server will collect information using keywords such as "company name stock price" and "latest stock price news." It then generates a report that reflects the emotion data and includes calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and made available for users to download.

[0826] In this way, the present invention is a system that efficiently provides information according to the individual needs and feelings of the user.

[0827] The processing flow will be explained below.

[0828] Step 1:

[0829] Terminal: The user accesses the interface and is presented with a form to enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information and clicks the "Submit" button.

[0830] Step 2:

[0831] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[0832] Step 3:

[0833] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[0834] Step 4:

[0835] Server: Uses the generated keywords to gather relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, using web crawlers and APIs.

[0836] Step 5:

[0837] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[0838] Step 6:

[0839] Server: Recognizes emotions from user-entered data using an emotion engine. Analyzes user-entered text and identifies emotional states such as "anxious," "excited," or "happy."

[0840] Step 7:

[0841] Server: Based on the collected data and sentiment data, converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. Analyzes the data using Natural Language Processing (NLP) technology and embeds the information in appropriate templates.

[0842] Step 8:

[0843] Server: Uses a natural language generation model (e.g., GPT-4) to convert the language style to match the user's attributes and emotions. For example, if the user is feeling anxious, the language will be adjusted to reduce anxiety.

[0844] Step 9:

[0845] Server: Based on the converted information, the server automatically generates a report with the number of pages requested by the user, constructs the report's chapters and paragraphs, and places appropriate images and graphs.

[0846] Step 10:

[0847] Server: Export the generated report in web or PDF format. Save the exported report as a file and provide a download link to the user.

[0848] Step 11:

[0849] On the device: A download link for the report will be displayed on the user's screen. The user can click the link to download the report.

[0850] Step 12:

[0851] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes, interests, and sentiment, allowing for efficient information gathering.

[0852] Example 2

[0853] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0854] Conventional information provision systems were able to provide customized information based on the user's attributes and interests, but they did not generate reports that took the user's emotional state into consideration. As a result, they were unable to provide information that was in line with the user's emotions, making it difficult to provide appropriate advice or mental care. Furthermore, there were insufficient means for efficiently storing and managing collected information.

[0855] 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.

[0856] In this invention, the server includes: a means for a user to input their attributes, interests, desired page count, etc.; a means for collecting related information from the Internet based on the input data; a means for analyzing the collected information and converting it into language expressions appropriate to the user's attributes and interests; a means for automatically generating a report based on the converted information and the user's emotional state; and a means for outputting the generated report in web or PDF format. This enables the provision of personalized information tailored to the user's individual needs and emotional state, enabling appropriate advice and mental care. Furthermore, efficient storage and management of collected information facilitates the reuse and management of information.

[0857] A "user" is a user who inputs information such as attributes, interests, and desired number of pages into the system.

[0858] "Attributes" refer to personal information such as a user's age, occupation, and areas of interest.

[0859] "Interests" are specific areas or topics that interest a user.

[0860] "Desired number of pages" is the number of pages the user specifies as the length of the generated report.

[0861] A "means" is a method or function for performing a specific process within a system.

[0862] "Means of collecting relevant information from the Internet" refers to methods and tools for collecting necessary information from the Internet. Specifically, this includes using web crawlers and APIs.

[0863] "Means for converting information into linguistic expressions" refers to the process of converting collected information into a form that is easy for users to understand. Specifically, this includes the use of natural language processing technology.

[0864] "Emotional state" refers to an emotion inferred from the information and context entered by the user. Examples include "anxiety," "excitement," and "satisfaction."

[0865] "Means for automatically generating reports" refers to methods or tools that allow a program to automatically generate reports based on a user's attributes, interests, and emotional state.

[0866] "Means for outputting in web or PDF format" refers to methods or tools for saving and outputting the generated report in a format that can be viewed via the Internet or in an electronic document format.

[0867] The system of the present invention allows users to input their attributes, interests, desired number of pages, etc., and then collects and analyzes customized information based on that information, generating and providing reports tailored to their emotions. The system includes a user interface in the form of a web page or mobile app, and data processing and report generation functions on the server.

[0868] User Input Interface

[0869] The device provides an interface for users to enter the necessary information. This interface is implemented in the form of a web page or mobile app. The user enters information such as age, occupation, areas of interest, and the desired number of pages into the form and clicks the "Submit" button. The entered data is sent to the server.

[0870] Information gathering

[0871] The server analyzes the input data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from sources on the Internet. This process uses Python libraries (BeautifulSoup, Scrapy, etc.) and API access libraries (requests, etc.). The collected data is then stored in a database.

[0872] emotion recognition

[0873] The emotion engine on the server analyzes the user's input data and recognizes the user's emotional state. This emotion recognition uses a BERT-based model using Hugging Face's Transformers library. Emotional states include "anxiety," "excitement," and "satisfaction."

[0874] natural language generation

[0875] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. In this step, OpenAI's GPT-3 model is used to generate natural language. The following prompts are used:

[0876] Prompt Sentence Examples

[0877] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0878] Data collected: "Latest stock price news, stock price information of major companies"

[0879] Report Generation

[0880] The server creates an appropriate report based on the number of pages and format specified by the user. It determines chapters and paragraphs based on the generated text, and places images and graphs. The report includes text that reflects the user's emotional state, providing more personalized information. The report is generated as a LaTeX file and can be output in PDF format using the pdflatex command.

[0881] Report Output

[0882] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user, who can click this link to download the report and obtain the required information.

[0883] Specific examples

[0884] For example, if User A, a 45-year-old investor, enters "Age: 45, Occupation: Investor, Interest: Stock Price Trends, Desired Page Count: 5 pages" and the emotion engine recognizes "anxiety," the server collects information using keywords such as "company name stock price" and "latest stock price news." It then generates a report containing calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and can be downloaded and used by the user.

[0885] In this way, the system of the present invention can efficiently provide information according to the individual needs and feelings of the user.

[0886] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0887] Program processing flow

[0888] Step 1:

[0889] User Input Interface

[0890] The user accesses the interface, which can be a web page or a mobile app, using their device. They fill out a form with information such as age, occupation, areas of interest, and the desired number of pages, and then click the "Submit" button. The submitted data is sent to the server via an HTTP POST request.

[0891] Input: Age, occupation, areas of interest, desired number of pages

[0892] Output: The input data is sent to the server

[0893] Step 2:

[0894] Information gathering

[0895] The server analyzes the input data received from the user and generates appropriate search keywords. This analysis is performed using a natural language processing algorithm. The generated keywords are then used to collect related information from sources on the Internet. Specifically, the required data is obtained using Python libraries (BeautifulSoup, Scrapy) and API access libraries (requests). The collected data is then stored in a database.

[0896] Input: User input data (age, occupation, areas of interest, desired number of pages)

[0897] Output: Relevant information (news articles, stock quotes, etc.) is stored in a database

[0898] Step 3:

[0899] emotion recognition

[0900] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state. This analysis uses a BERT-based model using Hugging Face's Transformers library. The emotional state is estimated from the wording and context of the text, such as "anxiety," "excitement," or "satisfaction."

[0901] Input: User-entered data

[0902] Output: User's emotional state (e.g., anxiety)

[0903] Step 4:

[0904] natural language generation

[0905] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. The OpenAI GPT-3 model is used in this step. The following prompts are used to generate the expressions:

[0906] Prompt Sentence Examples

[0907] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[0908] Data collected: "Latest stock price news, stock price information of major companies"

[0909] Input: collected data, user's emotional state

[0910] Output: User-optimized text

[0911] Step 5:

[0912] Report Generation

[0913] The server then creates a report from the generated text, according to the page count and formatting specified by the user, by generating a LaTeX file and inserting images and graphs as appropriate, and then generating a PDF version of the report using the pdflatex command.

[0914] Input: Generated text, user-specified format and page count

[0915] Output: Report in PDF format

[0916] Step 6:

[0917] Report Output

[0918] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide to the user, who can click this link to download the report from their device and obtain the required information.

[0919] Input: Generated report

[0920] Output: User accessible links

[0921] The above are the specific processing steps and flow of this system. This system realizes more personalized report generation by providing information according to the user's attributes, interests, and emotions.

[0922] (Application example 2)

[0923] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0924] In modern society, consumers are surrounded by a wide variety of information every day. Particularly when shopping online, choosing the most suitable product from the vast amount of product information can be a challenge. Furthermore, there is a demand for personalized information and guidance that reflects each individual consumer's attributes, interests, and even their emotional state at any given time. However, conventional systems are unable to fully meet these needs, limiting the extent to which they can improve consumer satisfaction. Therefore, there is a need for a system that can simultaneously provide personalized information that takes into account the user's attributes, interests, and emotional state, while optimizing the shopping experience.

[0925] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own attributes, interests, desired number of pages, etc., means for collecting related information from the Internet based on the input data, means for analyzing the collected information and converting it into language expressions corresponding to the user's attributes and interests, means for recognizing the user's emotional state and reflecting it in the analysis results, means for automatically generating a report based on the converted information, means for outputting the generated report in Web format or PDF format, and means for providing a shopping guide and product recommendations based on the user's emotional state. This enables personalized shopping guides and product recommendations according to the user's attributes, interests, and emotional state, thereby improving consumer satisfaction and enabling efficient product selection.

[0926] "User attributes" refers to individual information about an individual, such as age, occupation, gender, and place of residence.

[0927] "Interests" refers to areas or themes that a user is interested in, favorite activities, etc.

[0928] "Desired number of pages" refers to the number of pages of the report desired by the user.

[0929] "Means of collecting relevant information from the Internet" refers to methods for obtaining necessary information from the Internet using web crawlers or APIs.

[0930] "Means for converting into linguistic expression" refers to a method for expressing analyzed data as text in a form suitable for the user.

[0931] "Emotional state" refers to the user's state of mind, and includes emotions such as anxiety, excitement, and satisfaction.

[0932] "Analysis results" refers to the output generated based on collected information and the user's attributes, interests, and emotional state.

[0933] "Means for automatically generating reports" refers to a system or method for compiling collected and analyzed information into a report format.

[0934] "Means for web or PDF output" refers to a method for exporting the generated report as an HTML or PDF file.

[0935] "Shopping Guide" refers to guidelines that provide users with advice and information regarding product selection and purchase.

[0936] "Product recommendation" refers to the process of suggesting appropriate products based on a user's attributes, interests, and emotions.

[0937] This invention is a system that automatically generates customized information based on a user's attributes and interests, and combines it with an emotion engine to provide the generated information in a more personalized format. This system is particularly intended for use in shopping guides and product recommendations within virtual stores.

[0938] Overview of the entire system

[0939] First, the user uses a device (such as a smartphone or head-mounted display) to input their attributes (age, occupation, areas of interest, desired page number, etc.). The device collects this data and sends it to the server.

[0940] The server uses web crawlers and APIs (Application Programming Interfaces) to retrieve data from sources on the Internet to collect related information based on the input data, and the collected data is stored in a database.

[0941] The server then uses an emotion engine to recognize the user's emotional state from the input data. For example, emotional states such as "anxious" or "excited" are analyzed. This emotion data is inferred based on the text entered by the user and other input data.

[0942] After obtaining the emotion data, the server uses Natural Language Processing (NLP) technology to analyze the collected data and emotion data, and generate text according to the user's attributes, interests, and emotions. In particular, a report is generated that incorporates linguistic expressions that match the user's emotional state.

[0943] The server generates reports to provide users with optimal shopping guides and product recommendations, and exports the information in the format of the user's choice (web or PDF), generating links for easy access.

[0944] Hardware and software used

[0945] Hardware: Smartphone, Head-Mounted Display (HMD)

[0946] Software: Python, requests (for data collection), NLPProcessor (for natural language generation), EmotionEngine (for emotion engine), pdf_generator (for PDF generation)

[0947] Specific examples

[0948] For example, consumer User B inputs "Age: 35, Occupation: Designer, Interests: Latest Gadgets, Desired Page Count: 3 pages." If the emotion engine recognizes "excitement" from User B's input, the server collects information using keywords such as "latest gadget reviews" and "innovative technology." It then generates a report that incorporates the emotion data and includes expressions that amplify excitement and information on the latest trends. Finally, the report is exported in PDF format and made available for User B to download and use.

[0949] Prompt Sentence Examples

[0950] User Attributes:

[0951] Age: 35

[0952] Occupation: Designer

[0953] Interests: Latest gadgets

[0954] Desired number of pages: 3 pages

[0955] Emotion: Excitement

[0956] In this way, the system provides personalized shopping guides and product recommendations that are tailored to the user's individual needs and emotions.

[0957] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0958] Step 1:

[0959] The user uses a device (smartphone, head-mounted display, etc.) to input their attributes (age, occupation, areas of interest, desired number of pages, etc.). The input data includes age, occupation, areas of interest, and desired number of pages. When the user completes the input and clicks the "Submit" button, this data is sent to the server.

[0960] Input: User attribute data (age, occupation, areas of interest, desired number of pages)

[0961] Output: User attribute data sent to the server

[0962] Step 2:

[0963] The server analyzes the data received from the user, generates appropriate search keywords, and determines the scope and type of data to collect. Specifically, it selects the most appropriate information source based on the user's area of ​​interest and the number of pages required.

[0964] Input: User attribute data

[0965] Output: Search keywords, type and range of collected data

[0966] Step 3:

[0967] The server uses the generated search keywords to collect relevant information from sources on the Internet via web crawlers and APIs, and the collected data is stored in a database.

[0968] Input: Search keywords, type and range of collected data

[0969] Output: Relevant information collected

[0970] Step 4:

[0971] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state, inferring emotions such as "anxiety," "excitement," and "satisfaction" from context and word choice.

[0972] Input: User attribute data

[0973] Output: User emotion data

[0974] Step 5:

[0975] The server uses NLP (Natural Language Processing) technology to generate text based on the collected information and emotional data. This text is personalized according to the user's attributes, interests, and emotions. For example, if the emotional state is "excited," expressions that enhance excitement are used.

[0976] Input: Collected relevant information, user emotion data

[0977] Output: Generated personalized text

[0978] Step 6:

[0979] The server then uses the generated text to create a report in the format desired by the user (Web or PDF), based on the number of pages and format desired by the user.

[0980] Input: Generated personalized text, user-preferred page count and format

[0981] Output: The constructed report

[0982] Step 7:

[0983] The server exports the constructed report in the specified format (Web format or PDF format) and generates a link to provide it to the user. The user can click this link to download the report from their terminal and easily obtain the information they need.

[0984] Input: Constructed report

[0985] Output: Web or PDF report, download link

[0986] The above steps realize a system that efficiently and effectively provides information according to the user's attributes, interests, and emotional state.

[0987] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0988] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0989] 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.

[0990] [Fourth embodiment]

[0991] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0992] 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.

[0993] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0994] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0995] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0996] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0997] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0998] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0999] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1000] 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.

[1001] 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.

[1002] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1003] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1004] The present invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. To implement this system, the following programs and processes are mainly required.

[1005] User Input Interface

[1006] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[1007] Information gathering

[1008] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect related information from the Internet. This process involves using web crawlers and APIs to collect the latest news, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[1009] natural language generation

[1010] The server analyzes the collected data and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[1011] Report Generation

[1012] The server then builds the appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapters and paragraphs, and places appropriate images and graphs. The report's content can include relevant breaking news, detailed analytical data, and visual charts.

[1013] Report Output

[1014] The server exports the generated report in web or PDF format. This process is important for easy access by users. The exported report is provided to the user's device as a download link. Users can click this link to download the report and easily obtain the information they need.

[1015] Specific examples

[1016] For example, investor User A enters the following information: "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5." The server uses keywords such as "SoftBank stock price" and "latest stock price news" to collect related information from the Internet. It then analyzes this information and generates a report containing specialized language and specific data customized for investors. Finally, the report is exported in PDF format and made available for users to download.

[1017] In this way, the present invention is a system that efficiently provides information that meets the individual needs of users.

[1018] The processing flow will be explained below.

[1019] Step 1:

[1020] Terminal: Displays an interface where the user can enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information through this interface and clicks the "Submit" button.

[1021] Step 2:

[1022] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[1023] Step 3:

[1024] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[1025] Step 4:

[1026] Server: Uses the generated keywords to collect relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, through web crawlers and APIs.

[1027] Step 5:

[1028] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[1029] Step 6:

[1030] Server: Analyzes the collected data and converts it into language expressions based on the user's attributes and interests. It uses Natural Language Processing (NLP) models to read the data and embed information into appropriate templates.

[1031] Step 7:

[1032] Server: Uses a natural language generation model (e.g., GPT-4) to adapt the language style to suit the user's attributes and interests. For example, generate explanations for investors that use a lot of technical jargon and concrete figures.

[1033] Step 8:

[1034] Server: Automatically generates a report based on the converted information. Organizes the report into chapters and paragraphs, and places appropriate images and graphs. Adjusts the content according to the number of pages requested by the user.

[1035] Step 9:

[1036] Server: Export the generated report in Web or PDF format. Save the exported report as a file and generate a link to provide it to users.

[1037] Step 10:

[1038] On the device: A download link for the report will be displayed on the user's screen, allowing the user to click on this link to download the report.

[1039] Step 11:

[1040] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes and interests, allowing for efficient information retrieval.

[1041] Example 1

[1042] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1043] Today, there is a demand for quickly and automatically generating customized information tailored to individual users' attributes and interests and providing it in an easily accessible format. However, existing systems struggle to go beyond simply collecting data entered by users and effectively analyze that data to automatically generate appropriate reports tailored to the user's attributes and interests. Furthermore, the content of the generated reports often falls short of user expectations. Information provided in specialized fields, in particular, requires more specialized and specific content. Furthermore, the output formats of generated reports are limited, making them rarely provided in a format that users can easily access and use.

[1044] 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.

[1045] In this invention, the server includes: means for a user to input their attributes, interests, desired number of pages, etc.; means for collecting related information from the Internet based on the input data; means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests using Natural Language Processing (NLP) technology to analyze the converted data; means for automatically generating a report based on the generated information and determining the chapter structure and paragraphs of the report; means for adding images and graphs to the generated report; means for outputting the generated report in web format or PDF format; and means for providing the user with an access link to the generated report. This makes it possible to efficiently generate information customized to the individual needs of users, automatically create reports containing specialized and specific content, and further provide the reports in a format that the user can easily access.

[1046] A "user" is a person who uses this system to input data such as his or her attributes, interests, and desired number of pages.

[1047] The "Internet" is an information infrastructure that allows information to be accessed and shared through a globally connected network of computers.

[1048] "Related information" is data and content that is appropriate to the user's attributes and interests and is collected from the Internet based on data entered by the user.

[1049] "Analysis" is the process of breaking down collected information and extracting meanings and patterns based on user attributes and interests.

[1050] "Natural Language Processing (NLP) technology" is a technology that enables computers to understand and generate human language, and is used to analyze text data and convert it into appropriate language expressions.

[1051] "Text generation" is the process of automatically generating documents based on analyzed data that are appropriate for the user's attributes and interests.

[1052] A "report" is a document that compiles collected information and generated text and provides it in a user-viewable format.

[1053] "Image" means a visual representation of data added to a report, including, for example, a photograph, illustration, graph, etc.

[1054] A "graph" is a chart such as a bar graph, line graph, or pie chart that visually represents numerical data.

[1055] "Web format" means a format that can be viewed and accessed through an Internet browser.

[1056] "PDF format" is an abbreviation for Portable Document Format, and is a file format for displaying and printing electronic documents while preserving their original layout.

[1057] An "access link" is a URL or hyperlink that allows a user to access a generated report and is a means of directly reaching the specified content by clicking on it.

[1058] This invention is a system that automatically generates customized information based on a user's attributes and interests and provides it in the form of a report. The main hardware required is a device (smartphone, PC, tablet) for users to input information, and a server (cloud server, on-premise server) for data processing and report generation. The software required includes analysis software for natural language processing (NLP) technology, and information collection tools using web crawlers and APIs. Specifically, the NLP technology can use Hugging Face's Transformers or GPT-3 model, and the web crawler can use Beautiful Soup or Scrapy.

[1059] User Input Interface

[1060] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and desired page number. This interface can be implemented in the form of a web page or a mobile app and is built using HTML, JavaScript, and CSS. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server using the JavaScript fetch function.

[1061] Information gathering

[1062] The server analyzes the received user data using a web framework such as Flask. Based on the results of this analysis, appropriate search keywords are generated. For example, if a user is interested in "SoftBank's stock price trends," keywords such as "SoftBank stock price" and "latest stock price news" are generated. Related information is then collected from the Internet using Beautiful Soup or Scrapy. The latest news and stock price information can be obtained using the News API. The collected data is stored in a database such as PostgreSQL using the psycopg2 library.

[1063] natural language generation

[1064] The server analyzes the collected data using NLP technology. For example, by using Hugging Face's Transformers or GPT-3, the data is converted into language expressions that correspond to the user's attributes and interests. Based on the analysis results, sentences that match the user's attributes and interests are generated.

[1065] Report Generation

[1066] The server then determines the chapters and paragraphs of the report based on the generated text. It uses Markdown or LaTeX templates to build the report, adding images and graphs as needed. Matplotlib and Plotly can be used to create images and graphs.

[1067] Report Output

[1068] The server exports the generated report in PDF or web format. For example, you can generate a PDF using LaTeX, then use the pdfkit library to convert HTML to PDF. Finally, the server provides the user with an access link to the generated report. By clicking the provided link, the user can download the report and easily obtain the required information.

[1069] Specific examples

[1070] For example, investor User A enters "Age: 45, Occupation: Investor, Interests: SoftBank stock price trends, Desired number of pages: 5 pages." In this case, the server collects related information from the Internet using keywords such as "SoftBank stock price" and "latest stock price news." It then analyzes the collected information and generates a report for investors containing professional language and specific data. This report is exported in PDF format and can finally be downloaded and used by users.

[1071] Prompt Sentence Examples

[1072] "Generate a 5-page report for investors on the latest SoftBank stock price movements."

[1073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1074] Step 1:

[1075] The terminal displays an interface for the user to input information. Specifically, it displays a web page built using HTML, JavaScript, and CSS, and provides input fields in the form for age, occupation, areas of interest, and desired page count. When the user enters data into these fields and clicks the "Submit" button, the input data is collected. Once input is complete, the input data is sent to the server via the HTTPS protocol using the JavaScript fetch function (input data: age, occupation, areas of interest, desired page count; output data: input data sent to the server).

[1076] Step 2:

[1077] The server analyzes the received input data using a web framework such as Flask. For data analysis, it uses methods such as Python's request.get_json() method, which extracts user attribute information (input data: input data received from the device, output data: analyzed user attribute information).

[1078] Step 3:

[1079] The server generates appropriate search keywords based on the analysis results. For example, if a user is interested in "SoftBank's stock price trends," it generates keywords such as "SoftBank stock price" and "latest stock price news." In this step, specific algorithms and machine learning models are used to select the keywords that best fit the user's interests (input data: analyzed user attribute information, output data: generated search keywords).

[1080] Step 4:

[1081] The server uses the generated search keywords to collect related information from the Internet using web scraping tools such as Beautiful Soup or Scrapy. Data related to the user's interests, such as the latest news and stock prices, is obtained from websites and APIs (input data: generated search keywords, output data: collected related information).

[1082] Step 5:

[1083] The server stores the collected information in a database. For storage, a relational database such as PostgreSQL is used, and the database is connected using the Python psycopg2 library (input data: collected related information, output data: information stored in the database).

[1084] Step 6:

[1085] The server analyzes the stored information using Natural Language Processing (NLP) technology, using models such as Hugging Face's Transformers and GPT-3 to convert the collected data into linguistic expressions that correspond to the user's attributes and interests (input data: information stored in the database, output data: analyzed text-generated data).

[1086] Step 7:

[1087] The server automatically generates a report based on the generated text according to the user's desired page count and format. Markdown and LaTeX templates are used to determine the report's chapter structure and paragraphs, and images and graphs are added as needed. Matplotlib and Plotly are used to create images and graphs (input data: parsed text-generated data, output data: generated report).

[1088] Step 8:

[1089] The server exports the generated report in PDF or web format. It can generate PDF using LaTeX and convert HTML to PDF using the pdfkit library (input data: generated report, output data: exported PDF or web format report).

[1090] Step 9:

[1091] The server generates a download link for the exported report and provides it to the user, who can click the link to download and view the report (input data: exported PDF or web format report, output data: download link).

[1092] This process efficiently generates customized information tailored to the user's individual needs and presents it to the user in an easily accessible format.

[1093] (Application example 1)

[1094] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1095] Conventional information report generation systems have limited customization based on user attributes and interests, making them difficult to apply to individual customer service, especially in brick-and-mortar stores. Another problem is that analyzing the collected information is cumbersome, making it difficult to provide information tailored to specific purposes. Furthermore, there was no way to instantly provide the generated reports visually or audibly, making it difficult to provide effective customer service in brick-and-mortar stores.

[1096] 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.

[1097] In this invention, the server includes a means for users to input their attributes, interests, desired number of pages, etc., a means for collecting related information from the Internet based on the input data, and a means for analyzing the collected information and converting it into language expressions according to the user's attributes and interests. This makes it possible to efficiently collect and analyze information according to the individual needs of the user and provide customized reports.

[1098] The system further includes a means for collecting appropriate product information based on customer information, a means for automatically generating customized product descriptions using the collected product information, and a means for providing the automatically generated product descriptions visually or by audio output, thereby enabling personalized product information to be provided to customers in real time in physical stores, thereby achieving effective customer service.

[1099] "Means for users to input their attributes, interests, desired number of pages, etc." refers to a device or system that allows users to input information such as their age, occupation, areas of interest, desired number of pages of the report, etc. through an interface.

[1100] "Means for collecting related information from the Internet based on input data" refers to a device or system that uses the Internet to search for and obtain related information based on attributes and interests obtained from the user.

[1101] "Means for analyzing collected information and converting it into language expressions that correspond to the user's attributes and interests" refers to a device or system that has the function of analyzing collected information and converting it into language expressions that are most suitable for the user's attributes and interests.

[1102] The "means for automatically generating a report based on the converted information" refers to a device or system for automatically creating a report based on the converted information.

[1103] "Means for outputting the generated report in Web format or PDF format" refers to a device or system for outputting the automatically generated report in Web page format or PDF file format on the Internet.

[1104] The "means for collecting appropriate product information based on customer information" refers to a device or system for collecting relevant product information based on the attributes and interests of customers.

[1105] "Means for automatically generating customized product descriptions using collected product information" refers to a device or system that automatically creates product descriptions that are optimal for customers based on collected product information.

[1106] "Means for providing automatically generated product descriptions by visual or audio output" refers to a device or system for presenting the created product descriptions to customers visually (such as on a display) or audio.

[1107] The present invention is a system that generates customized information based on the user's attributes and interests and provides it to customers in a physical store. To realize this system, the following programs and processes are required.

[1108] First, the device provides an interface where the user can enter information such as age, occupation, areas of interest, desired page number, etc. This can be implemented as a web page or mobile app. When the user enters the required information through this interface and clicks the submit button, the data is sent to the server.

[1109] The server analyzes the data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. The collected data is then stored in a database.

[1110] The server then analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template, generating text appropriate for the specific attributes and interests. For example, simple expressions are used for junior high school students, while technical terms and specific numerical data are used for investors.

[1111] In addition, an external API is used to collect appropriate product information based on customer information. A customized product description is automatically generated based on the collected product information. This process uses OpenAI's generative AI model to generate text based on the generated prompt. This generative AI model is then used to generate product descriptions appropriate for the customer.

[1112] The generated product description can be provided in the format desired by the user (visual or audio output). Specifically, it can be displayed on a display or played back as audio. This function makes it possible to provide information to customers in real time in physical stores.

[1113] For example, if a 30-year-old office worker enters "Interests: Home appliances, technology, desired number of pages: 3," the server will collect information on appropriate home appliances based on this and generate customized product descriptions, allowing customers to obtain the information they need in real time in the store.

[1114] An example prompt is:

[1115] "User information: Age 30, Occupation: Office worker, Interests: Home appliances, technology. Product information: Details of a new smartphone. Based on this, generate a customized product description and recommendation list."

[1116] In this way, the present invention is a system that realizes effective customer service in physical stores by providing customers with individually customized information and product descriptions.

[1117] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1118] Step 1:

[1119] The terminal provides an interface for the user to input information such as age, occupation, areas of interest, desired number of pages, etc. The user inputs information through this interface and clicks the "Submit" button, which sends the input data (age, occupation, areas of interest, desired number of pages, etc.) from the terminal to the server.

[1120] Step 2:

[1121] The server analyzes the input data received from the user. Specifically, it generates appropriate search keywords based on the user's age, occupation, areas of interest, and desired number of pages. In this analysis step, it extracts relevant keywords using a database and a rule engine. The generated keywords are output.

[1122] Step 3:

[1123] The server uses the generated keywords to gather relevant information from the Internet. This process involves using web crawlers and APIs to gather the latest news, product information, technology-related data, etc. For example, keywords such as "home appliance technology latest information" are used. The collected information is stored in a database and search results are output.

[1124] Step 4:

[1125] The server analyzes the collected information and converts it into language expressions that correspond to the user's attributes and interests. This process uses Natural Language Processing (NLP) technology. The NLP model receives the collected information and user attribute data as input and generates customized text as output. This text is then output.

[1126] Step 5:

[1127] The server automatically generates a report based on the converted information. The report is generated using a template, which organizes chapters and paragraphs based on the user's desired page count and format. Specifically, the text generated by NLP is inserted into the report template. The generated report is then output.

[1128] Step 6:

[1129] The server collects appropriate product information based on customer information. It calls an external API to obtain relevant product information and stores it in a database. In this process, it searches for keywords such as "latest smartphone models." The collected product information is output.

[1130] Step 7:

[1131] The server automatically generates a customized product description using the collected product information. It uses OpenAI's generative AI model to generate text based on the prompt. This generative AI model is used to generate a product description appropriate for the customer. The generated product description is output.

[1132] Step 8:

[1133] The server provides the automatically generated product description visually or by audio output. Visual output is achieved by displaying the product on a display screen, and audio output is achieved by using speech synthesis technology. This process provides the generated product description in the format specified by the user. The final information is output and made available to the user.

[1134] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1135] The present invention combines an emotion engine with a system that automatically generates customized information based on a user's attributes and interests and provides it in report format. The programs required to implement this system and their processing details are described below.

[1136] User Input Interface

[1137] First, an interface is provided on the device for the user to enter information such as age, occupation, areas of interest, and the desired number of pages. This interface can be implemented in the form of a web page or a mobile app. The user enters the required information through this interface and clicks the "Submit" button. The entered data is then sent to the server.

[1138] Information gathering

[1139] The server analyzes the input data received from the user and generates appropriate search keywords. It then uses the generated keywords to collect relevant information from sources on the Internet. This process involves using web crawlers and APIs to gather news articles, stock quotes, technology-related data, etc. The collected data is then stored in a database.

[1140] emotion recognition

[1141] The emotion engine installed on the server analyzes the user's input data and recognizes the user's emotional state. This emotion data is inferred from the wording and context of the text entered by the user. For example, it identifies emotional states such as "anxiety," "excitement," and "satisfaction."

[1142] natural language generation

[1143] The server analyzes the collected data and emotional data and converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. In this step, Natural Language Processing (NLP) technology is used to embed the data into an optimal template and generate text appropriate for the user's specific attributes, interests, and emotional state. If the user is in a specific emotional state, appropriate wording and information presentation methods are used.

[1144] Report Generation

[1145] The server then creates an appropriate report based on the user's desired page count and format. Based on the generated natural language text, it determines the report's chapter structure and paragraphs, and places appropriate images and graphs. The report includes text that reflects the user's emotional state, allowing for more personalized information provision.

[1146] Report Output

[1147] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user. The user can click this link to download the report from their device and easily obtain the information they need.

[1148] Specific examples

[1149] For example, investor User A might enter "Age: 45, Occupation: Investor, Interests: Stock Price Trends, Desired Page Count: 5 pages." If the emotion engine further recognizes "anxiety" from User A's input, the server will collect information using keywords such as "company name stock price" and "latest stock price news." It then generates a report that reflects the emotion data and includes calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and made available for users to download.

[1150] In this way, the present invention is a system that efficiently provides information according to the individual needs and feelings of the user.

[1151] The processing flow will be explained below.

[1152] Step 1:

[1153] Terminal: The user accesses the interface and is presented with a form to enter their age, occupation, areas of interest, and desired number of pages. The user enters the required information and clicks the "Submit" button.

[1154] Step 2:

[1155] Terminal: Sends data entered by the user to the server, including age, occupation, areas of interest, and desired page number.

[1156] Step 3:

[1157] Server: Analyzes the received user data and generates appropriate search keywords. For example, if a user is interested in "stock price trends," it generates keywords such as "company name stock price" and "latest stock price news."

[1158] Step 4:

[1159] Server: Uses the generated keywords to gather relevant information from sources on the Internet, such as news articles, stock quotes, and technical documents, using web crawlers and APIs.

[1160] Step 5:

[1161] Server: Stores the collected information in a database. The stored data includes the information body and metadata (collection date, source, keywords, etc.).

[1162] Step 6:

[1163] Server: Recognizes emotions from user-entered data using an emotion engine. Analyzes user-entered text and identifies emotional states such as "anxious," "excited," or "happy."

[1164] Step 7:

[1165] Server: Based on the collected data and sentiment data, converts it into linguistic expressions that correspond to the user's attributes, interests, and emotions. Analyzes the data using Natural Language Processing (NLP) technology and embeds the information in appropriate templates.

[1166] Step 8:

[1167] Server: Uses a natural language generation model (e.g., GPT-4) to convert the language style to match the user's attributes and emotions. For example, if the user is feeling anxious, the language will be adjusted to reduce anxiety.

[1168] Step 9:

[1169] Server: Based on the converted information, the server automatically generates a report with the number of pages requested by the user, constructs the report's chapters and paragraphs, and places appropriate images and graphs.

[1170] Step 10:

[1171] Server: Export the generated report in web or PDF format. Save the exported report as a file and provide a download link to the user.

[1172] Step 11:

[1173] On the device: A download link for the report will be displayed on the user's screen. The user can click the link to download the report.

[1174] Step 12:

[1175] Users: Click the link to download the report and view the information they need. The generated report is optimized for the user's attributes, interests, and sentiment, allowing for efficient information gathering.

[1176] Example 2

[1177] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1178] Conventional information provision systems were able to provide customized information based on the user's attributes and interests, but they did not generate reports that took the user's emotional state into consideration. As a result, they were unable to provide information that was in line with the user's emotions, making it difficult to provide appropriate advice or mental care. Furthermore, there were insufficient means for efficiently storing and managing collected information.

[1179] 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.

[1180] In this invention, the server includes: a means for a user to input their attributes, interests, desired page count, etc.; a means for collecting related information from the Internet based on the input data; a means for analyzing the collected information and converting it into language expressions appropriate to the user's attributes and interests; a means for automatically generating a report based on the converted information and the user's emotional state; and a means for outputting the generated report in web or PDF format. This enables the provision of personalized information tailored to the user's individual needs and emotional state, enabling appropriate advice and mental care. Furthermore, efficient storage and management of collected information facilitates the reuse and management of information.

[1181] A "user" is a user who inputs information such as attributes, interests, and desired number of pages into the system.

[1182] "Attributes" refer to personal information such as a user's age, occupation, and areas of interest.

[1183] "Interests" are specific areas or topics that interest a user.

[1184] "Desired number of pages" is the number of pages the user specifies as the length of the generated report.

[1185] A "means" is a method or function for performing a specific process within a system.

[1186] "Means of collecting relevant information from the Internet" refers to methods and tools for collecting necessary information from the Internet. Specifically, this includes using web crawlers and APIs.

[1187] "Means for converting information into linguistic expressions" refers to the process of converting collected information into a form that is easy for users to understand. Specifically, this includes the use of natural language processing technology.

[1188] "Emotional state" refers to an emotion inferred from the information and context entered by the user. Examples include "anxiety," "excitement," and "satisfaction."

[1189] "Means for automatically generating reports" refers to methods or tools that allow a program to automatically generate reports based on a user's attributes, interests, and emotional state.

[1190] "Means for outputting in web or PDF format" refers to methods or tools for saving and outputting the generated report in a format that can be viewed via the Internet or in an electronic document format.

[1191] The system of the present invention allows users to input their attributes, interests, desired number of pages, etc., and then collects and analyzes customized information based on that information, generating and providing reports tailored to their emotions. The system includes a user interface in the form of a web page or mobile app, and data processing and report generation functions on the server.

[1192] User Input Interface

[1193] The device provides an interface for users to enter the necessary information. This interface is implemented in the form of a web page or mobile app. The user enters information such as age, occupation, areas of interest, and the desired number of pages into the form and clicks the "Submit" button. The entered data is sent to the server.

[1194] Information gathering

[1195] The server analyzes the input data received from the user and generates appropriate search keywords. The generated keywords are then used to collect related information from sources on the Internet. This process uses Python libraries (BeautifulSoup, Scrapy, etc.) and API access libraries (requests, etc.). The collected data is then stored in a database.

[1196] emotion recognition

[1197] The emotion engine on the server analyzes the user's input data and recognizes the user's emotional state. This emotion recognition uses a BERT-based model using Hugging Face's Transformers library. Emotional states include "anxiety," "excitement," and "satisfaction."

[1198] natural language generation

[1199] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. In this step, OpenAI's GPT-3 model is used to generate natural language. The following prompts are used:

[1200] Prompt Sentence Examples

[1201] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[1202] Data collected: "Latest stock price news, stock price information of major companies"

[1203] Report Generation

[1204] The server creates an appropriate report based on the number of pages and format specified by the user. It determines chapters and paragraphs based on the generated text, and places images and graphs. The report includes text that reflects the user's emotional state, providing more personalized information. The report is generated as a LaTeX file and can be output in PDF format using the pdflatex command.

[1205] Report Output

[1206] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide it to the user, who can click this link to download the report and obtain the required information.

[1207] Specific examples

[1208] For example, if User A, a 45-year-old investor, enters "Age: 45, Occupation: Investor, Interest: Stock Price Trends, Desired Page Count: 5 pages" and the emotion engine recognizes "anxiety," the server collects information using keywords such as "company name stock price" and "latest stock price news." It then generates a report containing calming expressions to reduce anxiety and advice on risk management. Finally, the report is exported in PDF format and can be downloaded and used by the user.

[1209] In this way, the system of the present invention can efficiently provide information according to the individual needs and feelings of the user.

[1210] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1211] Program processing flow

[1212] Step 1:

[1213] User Input Interface

[1214] The user accesses the interface, which can be a web page or a mobile app, using their device. They fill out a form with information such as age, occupation, areas of interest, and the desired number of pages, and then click the "Submit" button. The submitted data is sent to the server via an HTTP POST request.

[1215] Input: Age, occupation, areas of interest, desired number of pages

[1216] Output: The input data is sent to the server

[1217] Step 2:

[1218] Information gathering

[1219] The server analyzes the input data received from the user and generates appropriate search keywords. This analysis is performed using a natural language processing algorithm. The generated keywords are then used to collect related information from sources on the Internet. Specifically, the required data is obtained using Python libraries (BeautifulSoup, Scrapy) and API access libraries (requests). The collected data is then stored in a database.

[1220] Input: User input data (age, occupation, areas of interest, desired number of pages)

[1221] Output: Relevant information (news articles, stock quotes, etc.) is stored in a database

[1222] Step 3:

[1223] emotion recognition

[1224] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state. This analysis uses a BERT-based model using Hugging Face's Transformers library. The emotional state is estimated from the wording and context of the text, such as "anxiety," "excitement," or "satisfaction."

[1225] Input: User-entered data

[1226] Output: User's emotional state (e.g., anxiety)

[1227] Step 4:

[1228] natural language generation

[1229] The server generates language expressions based on the collected data and emotional data, according to the user's attributes, interests, and emotional state. The OpenAI GPT-3 model is used in this step. The following prompts are used to generate the expressions:

[1230] Prompt Sentence Examples

[1231] Prompt: "Write a five-page report about the anxiety experienced by a 45-year-old investor interested in stock market trends."

[1232] Data collected: "Latest stock price news, stock price information of major companies"

[1233] Input: collected data, user's emotional state

[1234] Output: User-optimized text

[1235] Step 5:

[1236] Report Generation

[1237] The server then creates a report from the generated text, according to the page count and formatting specified by the user, by generating a LaTeX file and inserting images and graphs as appropriate, and then generating a PDF version of the report using the pdflatex command.

[1238] Input: Generated text, user-specified format and page count

[1239] Output: Report in PDF format

[1240] Step 6:

[1241] Report Output

[1242] The server exports the generated report in web or PDF format, saves the exported report as a file, and generates a link to provide to the user, who can click this link to download the report from their device and obtain the required information.

[1243] Input: Generated report

[1244] Output: User accessible links

[1245] The above are the specific processing steps and flow of this system. This system realizes more personalized report generation by providing information according to the user's attributes, interests, and emotions.

[1246] (Application example 2)

[1247] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1248] In modern society, consumers are surrounded by a wide variety of information every day. Particularly when shopping online, choosing the most suitable product from the vast amount of product information can be a challenge. Furthermore, there is a demand for personalized information and guidance that reflects each individual consumer's attributes, interests, and even their emotional state at any given time. However, conventional systems are unable to fully meet these needs, limiting the extent to which they can improve consumer satisfaction. Therefore, there is a need for a system that can simultaneously provide personalized information that takes into account the user's attributes, interests, and emotional state, while optimizing the shopping experience.

[1249] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own attributes, interests, desired number of pages, etc., means for collecting related information from the Internet based on the input data, means for analyzing the collected information and converting it into language expressions corresponding to the user's attributes and interests, means for recognizing the user's emotional state and reflecting it in the analysis results, means for automatically generating a report based on the converted information, means for outputting the generated report in Web format or PDF format, and means for providing a shopping guide and product recommendations based on the user's emotional state. This enables personalized shopping guides and product recommendations according to the user's attributes, interests, and emotional state, thereby improving consumer satisfaction and enabling efficient product selection.

[1250] "User attributes" refers to individual information about an individual, such as age, occupation, gender, and place of residence.

[1251] "Interests" refers to areas or themes that a user is interested in, favorite activities, etc.

[1252] "Desired number of pages" refers to the number of pages of the report desired by the user.

[1253] "Means of collecting relevant information from the Internet" refers to methods for obtaining necessary information from the Internet using web crawlers or APIs.

[1254] "Means for converting into linguistic expression" refers to a method for expressing analyzed data as text in a form suitable for the user.

[1255] "Emotional state" refers to the user's state of mind, and includes emotions such as anxiety, excitement, and satisfaction.

[1256] "Analysis results" refers to the output generated based on collected information and the user's attributes, interests, and emotional state.

[1257] "Means for automatically generating reports" refers to a system or method for compiling collected and analyzed information into a report format.

[1258] "Means for web or PDF output" refers to a method for exporting the generated report as an HTML or PDF file.

[1259] "Shopping Guide" refers to guidelines that provide users with advice and information regarding product selection and purchase.

[1260] "Product recommendation" refers to the process of suggesting appropriate products based on a user's attributes, interests, and emotions.

[1261] This invention is a system that automatically generates customized information based on a user's attributes and interests, and combines it with an emotion engine to provide the generated information in a more personalized format. This system is particularly intended for use in shopping guides and product recommendations within virtual stores.

[1262] Overview of the entire system

[1263] First, the user uses a device (such as a smartphone or head-mounted display) to input their attributes (age, occupation, areas of interest, desired page number, etc.). The device collects this data and sends it to the server.

[1264] The server uses web crawlers and APIs (Application Programming Interfaces) to retrieve data from sources on the Internet to collect related information based on the input data, and the collected data is stored in a database.

[1265] The server then uses an emotion engine to recognize the user's emotional state from the input data. For example, emotional states such as "anxious" or "excited" are analyzed. This emotion data is inferred based on the text entered by the user and other input data.

[1266] After obtaining the emotion data, the server uses Natural Language Processing (NLP) technology to analyze the collected data and emotion data, and generate text according to the user's attributes, interests, and emotions. In particular, a report is generated that incorporates linguistic expressions that match the user's emotional state.

[1267] The server generates reports to provide users with optimal shopping guides and product recommendations, and exports the information in the format of the user's choice (web or PDF), generating links for easy access.

[1268] Hardware and software used

[1269] Hardware: Smartphone, Head-Mounted Display (HMD)

[1270] Software: Python, requests (for data collection), NLPProcessor (for natural language generation), EmotionEngine (for emotion engine), pdf_generator (for PDF generation)

[1271] Specific examples

[1272] For example, consumer User B inputs "Age: 35, Occupation: Designer, Interests: Latest Gadgets, Desired Page Count: 3 pages." If the emotion engine recognizes "excitement" from User B's input, the server collects information using keywords such as "latest gadget reviews" and "innovative technology." It then generates a report that incorporates the emotion data and includes expressions that amplify excitement and information on the latest trends. Finally, the report is exported in PDF format and made available for User B to download and use.

[1273] Prompt Sentence Examples

[1274] User Attributes:

[1275] Age: 35

[1276] Occupation: Designer

[1277] Interests: Latest gadgets

[1278] Desired number of pages: 3 pages

[1279] Emotion: Excitement

[1280] In this way, the system provides personalized shopping guides and product recommendations that are tailored to the user's individual needs and emotions.

[1281] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1282] Step 1:

[1283] The user uses a device (smartphone, head-mounted display, etc.) to input their attributes (age, occupation, areas of interest, desired number of pages, etc.). The input data includes age, occupation, areas of interest, and desired number of pages. When the user completes the input and clicks the "Submit" button, this data is sent to the server.

[1284] Input: User attribute data (age, occupation, areas of interest, desired number of pages)

[1285] Output: User attribute data sent to the server

[1286] Step 2:

[1287] The server analyzes the data received from the user, generates appropriate search keywords, and determines the scope and type of data to collect. Specifically, it selects the most appropriate information source based on the user's area of ​​interest and the number of pages required.

[1288] Input: User attribute data

[1289] Output: Search keywords, type and range of collected data

[1290] Step 3:

[1291] The server uses the generated search keywords to collect relevant information from sources on the Internet via web crawlers and APIs, and the collected data is stored in a database.

[1292] Input: Search keywords, type and range of collected data

[1293] Output: Relevant information collected

[1294] Step 4:

[1295] The server uses an emotion engine to analyze the user's input data and recognize the user's emotional state, inferring emotions such as "anxiety," "excitement," and "satisfaction" from context and word choice.

[1296] Input: User attribute data

[1297] Output: User emotion data

[1298] Step 5:

[1299] The server uses NLP (Natural Language Processing) technology to generate text based on the collected information and emotional data. This text is personalized according to the user's attributes, interests, and emotions. For example, if the emotional state is "excited," expressions that enhance excitement are used.

[1300] Input: Collected relevant information, user emotion data

[1301] Output: Generated personalized text

[1302] Step 6:

[1303] The server then uses the generated text to create a report in the format desired by the user (Web or PDF), based on the number of pages and format desired by the user.

[1304] Input: Generated personalized text, user-preferred page count and format

[1305] Output: The constructed report

[1306] Step 7:

[1307] The server exports the constructed report in the specified format (Web format or PDF format) and generates a link to provide it to the user. The user can click this link to download the report from their terminal and easily obtain the information they need.

[1308] Input: Constructed report

[1309] Output: Web or PDF report, download link

[1310] The above steps realize a system that efficiently and effectively provides information according to the user's attributes, interests, and emotional state.

[1311] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1312] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1313] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1314] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1315] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1316] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1317] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1318] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1319] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1320] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1321] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1322] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1323] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1324] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1325] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1326] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1327] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1328] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1329] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1330] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1331] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1332] The following is further disclosed regarding the above embodiment.

[1333] (Claim 1)

[1334] A means for users to input their attributes, interests, desired number of pages, etc.;

[1335] A means for collecting related information from the Internet based on the input data;

[1336] A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests;

[1337] A means for automatically generating reports based on the converted information;

[1338] A means to output the generated report in web or PDF format;

[1339] A system including:

[1340] (Claim 2)

[1341] 10. The system of claim 1, further comprising means for converting the information in a language style appropriate for a target audience.

[1342] (Claim 3)

[1343] 10. The system of claim 1, further comprising means for storing the collected information in a database.

[1344] "Example 1"

[1345] (Claim 1)

[1346] A means for users to input their attributes, interests, desired number of pages, etc.;

[1347] A means for collecting related information from the Internet based on the input data;

[1348] A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests;

[1349] a means of analyzing the transformed data using Natural Language Processing (NLP) techniques;

[1350] A means for automatically generating a report based on the generated information and determining the chapter structure and paragraphs of the report;

[1351] A means to add images and graphs to the generated reports,

[1352] A means to output the generated report in web or PDF format;

[1353] a means for providing a user with an access link to the generated report;

[1354] A system including:

[1355] (Claim 2)

[1356] 10. The system of claim 1, further comprising means for converting the information in a language style appropriate for a target audience.

[1357] (Claim 3)

[1358] 10. The system of claim 1, further comprising means for storing the collected information in a database.

[1359] "Application Example 1"

[1360] (Claim 1)

[1361] A means for users to input their attributes, interests, desired number of pages, etc.;

[1362] A means for collecting related information from the Internet based on the input data;

[1363] A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests;

[1364] A means for automatically generating reports based on the converted information;

[1365] A means to output the generated report in web or PDF format;

[1366] A means for collecting appropriate product information based on customer information;

[1367] A means for automatically generating a customized product description using the collected product information;

[1368] a means for providing an automatically generated product description in visual or audio output;

[1369] A system including:

[1370] (Claim 2)

[1371] 10. The system of claim 1, further comprising means for converting the information in a language style appropriate for a target audience.

[1372] (Claim 3)

[1373] 10. The system of claim 1, further comprising means for storing the collected information in a database.

[1374] "Example 2: Combining Emotion Engines"

[1375] (Claim 1)

[1376] A means for users to input their attributes, interests, desired number of pages, etc.;

[1377] A means for collecting related information from the Internet based on the input data;

[1378] A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests;

[1379] means for automatically generating a report based on the converted information and the user's emotional state;

[1380] A means to output the generated report in web or PDF format;

[1381] A system including:

[1382] (Claim 2)

[1383] 10. The system of claim 1, further comprising means for selecting a language style appropriate for a target audience and for transforming information taking into account the emotional state of the user.

[1384] (Claim 3)

[1385] 10. The system of claim 1, further comprising means for storing the collected information in a data store.

[1386] "Application example 2 when combining emotion engines"

[1387] (Claim 1)

[1388] A means for users to input their attributes, interests, desired number of pages, etc.;

[1389] A means for collecting related information from the Internet based on the input data;

[1390] A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests;

[1391] A means for recognizing the emotional state of the user and reflecting it in the analysis results;

[1392] A means for automatically generating reports based on the converted information;

[1393] A means to output the generated report in web or PDF format;

[1394] means for providing shopping guides and product recommendations based on the user's emotional state;

[1395] A system including:

[1396] (Claim 2)

[1397] 10. The system of claim 1, further comprising means for converting the information in a language style appropriate for a target audience.

[1398] (Claim 3)

[1399] 10. The system of claim 1, further comprising means for storing the collected information in a database. [Explanation of symbols]

[1400] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input their attributes, interests, desired number of pages, etc.; A means for collecting related information from the Internet based on the input data; A means of analyzing the collected information and converting it into language expressions that correspond to the user's attributes and interests; A means for automatically generating reports based on the converted information; A means to output the generated report in web or PDF format; A system including:

2. 10. The system of claim 1, further comprising means for converting information in a language style appropriate for a target audience.

3. 10. The system of claim 1, further comprising means for storing the collected information in a database.

Images