System

Abstract

To provide a system.SOLUTION: A system contains: means of designating an industry genre; report creation means of creating a report for a plurality of business enterprises in the designated industry genre relating to financial statements, the industry trend, standing positions in the industry, and the relation between stock prices and the plurality of business enterprises; public opinion evaluation means of evaluating public opinions to the plurality of business enterprises based on stock price information; and means of recognizing a user emotion, enhancing positive information containing a new product release or a business performance improvement of the plurality of business enterprises when the emotion is positive, and adjusting the content of the report so as to provide information relating to reliability of the plurality of business enterprises when the emotion is negative.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] In the past, when conducting corporate analysis, it was necessary to collect and analyze information such as financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company separately. In addition, to evaluate public opinion from stock price information, specialized knowledge and time were required. These tasks consumed a large amount of time and effort, and were an obstacle to efficient corporate analysis. [Means for solving the problem]

[0005] This invention automatically creates reports on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company, simply by specifying the company name and industry category. In addition, it can automatically perform public opinion evaluations from stock price information. This makes it possible to streamline the collection and analysis of information required for company analysis, and significantly reduce time and labor. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13]FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

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

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

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

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

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

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. 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.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

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

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

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

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

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

[0027] "Example 1"

[0028] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. It analyzes information such as stock price fluctuations and trading volume to estimate a company's valuation.

[0029] "Example 2"

[0030] As a specific example, if a user specifies the "automobile" industry, the system will create a report on the automobile industry's financial statements, industry trends, position within the industry, and the relationship between stock prices and companies. The report includes each company's financial status, industry trends, each company's position within the market, and the relationship between stock prices and companies. In addition, the system will perform public opinion evaluation from stock price information and add it to the report. This allows users to quickly grasp the overall picture of the automobile industry.

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

[0032] "Example 1"

[0033] Step 1: The user specifies the company name and industry genre through the system interface.

[0034] Step 2: Based on the specified company name and industry category, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[0035] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[0036] Step 4: Further, information such as stock price fluctuations and trading volume is analyzed to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[0037] "Example 2"

[0038] Step 1: The user specifies the "Automotive" industry.

[0039] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the automotive industry.

[0040] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[0041] Step 4: Further, information such as stock price fluctuations and trading volume related to the automotive industry is analyzed to estimate the valuation of the companies. This valuation is added to the report as a public opinion rating.

[0042] Example 1

[0043] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0044] Conventional corporate analysis systems had the problem that even if a user specified a company name or industry, it took a lot of time and effort to collect, process, and analyze the necessary data. In addition, there was a lack of automated means to evaluate public opinion from stock price information, so users had to perform the evaluation manually. This made it difficult to create reports quickly and accurately.

[0045] 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.

[0046] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for processing and analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for providing the created report. This makes it possible for a user to simply designate a company name and an industry category, and quickly and accurately create and provide a report including the company's financial situation, industry trends, the company's position in the market, the relationship between stock price and the company, and evaluation of public opinion.

[0047] The "means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[0048] "Means of collecting data based on a specified company name or industry genre" refers to a function for obtaining data related to a company name or industry genre specified by a user from an external database or API.

[0049] "Means for processing and analyzing collected data" refers to the function of organizing collected data, extracting necessary information, and analyzing it.

[0050] The "means for creating a report based on the analysis results" is a function for automatically generating a report to be provided to a user based on the analyzed data.

[0051] "Means of assessing public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate the market's evaluation and public opinion of a company.

[0052] The "means for providing a generated report" refers to a function for providing a generated report to a user, and includes provision in PDF format or Web page format.

[0053] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. This involves analyzing information such as stock price fluctuations and trading volume, and estimating a company's valuation.

[0054] Hardware and Software Used

[0055] Hardware

[0056] Server: A central processing unit for data collection, processing, analysis, and report generation.

[0057] Terminal: The device through which the user operates the interface (e.g. PC, smartphone)

[0058] software

[0059] Web browser: Provides an interface for users to enter company names and industry categories

[0060] API: Access to external databases and services for data collection (e.g. EDGAR database, Statista, Yahoo Finance API)

[0061] Template engine: a tool for formatting collected and analyzed data into reports

[0062] Data analysis tools: Software for processing and analyzing collected data (e.g. Python, R)

[0063] Data processing and calculation

[0064] The server collects the necessary information from the following data sources based on the company name and industry genre specified by the user.

[0065] Public company financial statements (e.g., EDGAR database)

[0066] Industry statistics (e.g. Statista)

[0067] Stock quotes (e.g. Yahoo Finance API)

[0068] The collected data will be processed and analyzed as follows:

[0069] Analyze financial statement data to evaluate a company's financial position, for example by calculating indicators such as sales, net profit, and debt ratio.

[0070] Use industry statistics to analyze industry trends, for example, to calculate overall industry growth rates and market shares.

[0071] Analyze stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[0072] Analyze stock price fluctuations and trading volume to estimate public opinion. For example, identify the causes of sudden increases or decreases in stock prices.

[0073] Examples

[0074] Example 1: When specifying a company name

[0075] The user specifies "specific company." The server performs the following process:

[0076] 1. The user enters "specific company" into the web form and clicks the submit button.

[0077] 2. The server retrieves the latest financial statements for a particular company from the EDGAR database.

[0078] 3. The server retrieves the latest statistical data for a specific industry from Statista.

[0079] 4. The server retrieves stock price information for a specific company from the Yahoo Finance API.

[0080] 5. The server analyzes the collected data and creates a report that includes the specific company's financial status, industry trends, its position within the industry, the company's relationship with its stock price, and public opinion.

[0081] 6. The server generates the report in PDF format and provides a download link to the user.

[0082] Example 2: When specifying an industry genre

[0083] The user specifies "specific industry." The server performs the following process:

[0084] 1. A user enters "specific industry" into a web form and clicks the submit button.

[0085] 2. The server retrieves the latest statistical data for a specific industry from Statista.

[0086] 3. The server retrieves stock price information for major companies in a specific industry from the Yahoo Finance API.

[0087] 4. The server analyzes the collected data and creates reports that include trends in a particular industry, the position of major companies within the industry, the relationship between stock prices and companies, and public opinion ratings.

[0088] 5. The server generates the report in the form of a web page and displays it to the user.

[0089] Examples of prompt statements

[0090] Example 1: Prompt statement specifying company name

[0091] "Create a report that includes a specific company's latest financials, industry trends, where it stands within the industry, the company's stock price relationship, and public opinion ratings."

[0092] Example 2: Prompt statement specifying industry genre

[0093] "Create a report that includes the latest trends in a particular industry, where major companies stand in the industry, stock price-company relationships, and public opinion ratings."

[0094] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0095] Step 1: User specifies company name and industry category

[0096] A user uses an interface to input a company name and industry category through a web browser or mobile application. For example, the user inputs "specific company" and clicks the submit button. The input data is sent to the server.

[0097] Input: Company name or industry

[0098] Output: The input data sent to the server.

[0099] Step 2: The server collects the data

[0100] The server collects the necessary information from the following data sources based on the company name and industry genre received from the user.

[0101] The server accesses the EDGAR database to retrieve the most recent financial statements for the specified companies.

[0102] The server accesses Statista and retrieves the latest statistical data for the specified industry.

[0103] The server uses the Yahoo Finance API to retrieve stock quotes for the specified companies.

[0104] Input: User-specified company name or industry

[0105] Output: Collected financial statement data, industry statistics, stock price information

[0106] Step 3: The server processes and analyzes the data

[0107] The server processes and analyzes the collected data as follows:

[0108] The server analyzes the financial statement data and evaluates the company's financial condition, for example calculating metrics such as sales, net profit, and debt ratio.

[0109] The server uses industry statistics to analyze industry trends, for example to calculate industry-wide growth rates and market shares.

[0110] The server analyzes stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[0111] The server analyzes stock price fluctuations and trading volume to estimate public opinion, for example by identifying the causes of sudden increases or decreases in stock prices.

[0112] Input: Collected financial statement data, industry statistics, stock price information

[0113] Output: Company financial status, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[0114] Step 4: The server creates the report

[0115] The server automatically generates a report to provide to the user based on the results of the above analysis. The report includes the following:

[0116] Company financial status (e.g. sales, net profit, debt ratio)

[0117] Industry trends (e.g. industry-wide growth rates, market shares)

[0118] Position in the industry (e.g., compared to competitors)

[0119] Relationship between stock prices and companies (e.g. stock price fluctuations, trading volume)

[0120] Public opinion assessment (e.g., reasons for sudden rises and falls in stock prices)

[0121] Input: Company financials, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[0122] Output: Generated report

[0123] Step 5: The server serves the report

[0124] The server then provides the generated report to the user, either in PDF format or as a web page, for example with a link that allows the user to download the report.

[0125] Input: Generated report

[0126] Output: Report provided to user (in PDF or web page format)

[0127] (Application example 1)

[0128] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0129] In conventional corporate analysis systems, even if a user specified a company name or industry, financial statements, industry trends, stock price information, etc. had to be individually collected and analyzed manually. This took time and effort, making it difficult to make quick decisions. In addition, there was a lack of automated means to evaluate public opinion from stock price information, making it impossible to efficiently obtain information that could be used as a reference for investment decisions.

[0130] 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. In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, a position in the industry, and a relationship between stock prices and a company, a means for evaluating public opinion from stock price information, a means for providing a report through an application installed on a smartphone, and a means for automatically generating a report using a generative AI model. This enables a user to quickly and efficiently grasp a company's financial situation, industry trends, a company's position in the market, and a relationship between stock prices and a company, and to obtain information that can be used as a reference for investment decisions.

[0131] "Means for specifying a company name or industry category" refers to a function that provides an interface for a user to input or select a specific company name or industry category.

[0132] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that automatically generates reports by analyzing related financial statements, industry trends, position within the industry, and the relationship between a company and stock prices based on a specified company name and industry genre.

[0133] "Means of evaluating public opinion from stock price information" is a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[0134] "Means for providing a report through an application installed on a smartphone" refers to a function for providing a generated report to a user through a smartphone application.

[0135] "Means for automatically generating reports using a generative AI model" means a function that uses an artificial intelligence model to automatically generate reports based on collected data.

[0136] As an embodiment of the present invention, the following system is constructed.

[0137] System Configuration

[0138] The system consists of a smartphone application that allows users to specify company names and industry genres, a server that collects and analyzes data, and a back-end system that automatically generates reports using generative AI models.

[0139] Hardware and Software Used

[0140] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0141] software:

[0142] Python: Data Processing and Analysis

[0143] Pandas: Dataframe Operations

[0144] BeautifulSoup: Web scraping

[0145] Scikit-learn: Machine learning models

[0146] TENSORFLOW(R): A Generative AI Model

[0147] Flask: Backend API

[0148] Processing flow

[0149] 1. User Interface:

[0150] Users enter company names and industry categories through a smartphone application.

[0151] For example, the user specifies "Automobile Manufacturer A" and the "Automobile Industry."

[0152] 2. Data collection:

[0153] The server uses BeautifulSoup to scrape financial statements, industry statistics, and stock quotes from the web for specified companies.

[0154] Use Pandas to organize and consolidate the collected data.

[0155] 3. Data Analysis:

[0156] The server uses Scikit-learn to build a model for deriving public opinion from stock price information.

[0157] Use TensorFlow to automatically generate reports using generative AI models.

[0158] 4. Report Generation:

[0159] Based on the collected and analyzed data, the server generates reports on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company.

[0160] The generated reports are provided to the user via a smartphone application.

[0161] Examples

[0162] If the user specifies "Automobile manufacturer A" and the "Automobile industry", the server will collect the latest financial statements, industry statistical data, and stock price information of Automobile manufacturer A, and will evaluate public opinion based on Automobile manufacturer A's position in the industry and fluctuations in its stock price. Finally, a report based on this information will be generated and provided to the user.

[0163] Examples of prompt statements

[0164] Company Name: Automobile Manufacturer A

[0165] Industry: Automotive industry

[0166] By entering this prompt, the system will generate a detailed report on car manufacturer A.

[0167] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0168] Step 1:

[0169] The user starts the smartphone application and inputs the company name and industry category. For example, they specify "Automobile Manufacturer A" and "Automobile Industry". The input data is sent to the server.

[0170] Step 2:

[0171] Based on the received company names and industry categories, the server uses BeautifulSoup to scrape relevant financial statements, industry statistics, and stock quotes from the web. The input is the company name and industry category, and the output is the collected raw data.

[0172] Step 3:

[0173] The server uses Pandas to organize and consolidate the collected raw data, creating a data frame, imputing missing values, and normalizing the data. The input is the scraped raw data, and the output is the organized and consolidated data frame.

[0174] Step 4:

[0175] The server uses Scikit-learn to build a machine learning model for public opinion evaluation from stock price information. The input is a cleaned and integrated data frame, and the output is a public opinion evaluation model. Specifically, the server uses stock price fluctuations and trading volume as features to estimate the evaluation of a company.

[0176] Step 5:

[0177] The server uses TensorFlow to automatically generate reports using generative AI models. The input is a data frame organized and integrated with the public opinion evaluation model, and the output is an automatically generated report. Specifically, it generates a report that includes the company's financial status, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[0178] Step 6:

[0179] The server provides the generated report to the user through the smartphone application. The input is the automatically generated report, and the output is the report displayed on the user's smartphone screen. This allows the user to quickly and efficiently obtain detailed information about the company.

[0180] Example 2

[0181] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] In the conventional system, it took a lot of time and effort to create detailed reports on a specific industry. In addition, each step of data collection, analysis, and report generation was often done manually, which was inefficient. In addition, there was a lack of means to evaluate public opinion from stock price information, making it difficult to accurately grasp a company's market position and industry trends.

[0183] 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.

[0184] In this invention, the server includes a means for designating an industry, a means for creating reports on financial data, industry trends, a company's position in the market, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for collecting data, a means for analyzing data, a means for generating reports, and a means for providing reports, thereby making it possible to automatically generate detailed reports on an industry designated by a user and provide them in a short time.

[0185] The "means for specifying an industry" is a function that provides an interface for the user to select or input a specific industry.

[0186] "Financial data" refers to economic indicators such as sales, net profit, and total assets included in a company's financial statements and financial reports.

[0187] "Industry trends" refers to information that indicates the latest developments and market changes within a particular industry.

[0188] "A company's market position" refers to information that indicates the position of a particular company within its industry, including market share and growth rate.

[0189] "The relationship between stock prices and companies" is information that shows how a company's stock price is related to the company's financial situation and market valuation.

[0190] The "means for creating a report" is a function for generating a report to be provided to a user based on collected and analyzed data.

[0191] "Means of evaluating public opinion from stock price information" is a function that analyzes market reactions and public evaluations based on stock price data, and evaluates public opinion.

[0192] "Means of collecting data" means the ability to obtain data related to the specified industry from external data sources, for example, using an API to obtain data.

[0193] "Means of analyzing data" refers to the function of organizing and processing collected data and calculating necessary indicators. Examples include financial data analysis and sentiment analysis.

[0194] "Means for generating reports" refers to a function for creating visually easy-to-understand reports based on analysis results, for example using graphs and charts.

[0195] The "means for providing a report" is a function for providing a generated report to a user, for example, by making the report downloadable in PDF format.

[0196] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0197] The present invention is a system for automatically generating and providing a detailed report on a particular industry when the user designates the industry. A specific embodiment of this system will be described below.

[0198] 1. System Configuration

[0199] The system consists of the following main components:

[0200] User terminal: A device that provides an interface for a user to specify an industry. For example, a PC or smartphone.

[0201] Server: The central component responsible for data collection, analysis, and report generation. Developed using Python.

[0202] External Data Sources: APIs and databases for collecting data. Examples include Yahoo Finance API, GOOGLE Finance API, NewsAPI, etc.

[0203] 2. Hardware and Software Used

[0204] Hardware: The server is a computer equipped with a powerful processor and sufficient memory. The user terminal is a general-purpose PC or smartphone.

[0205] Software: The server is developed using Python and uses the following libraries and tools:

[0206] Pandas: Used to organize and process data.

[0207] NumPy: Used for numerical calculations.

[0208] TextBlob: Used for sentiment analysis.

[0209] Matplotlib and Seaborn for data visualization.

[0210] API Client: Used to retrieve data from external data sources such as Yahoo Finance API, Google® Finance API, NewsAPI, etc.

[0211] 3. Data collection and analysis

[0212] The server collects data related to the industry specified by the user from external data sources. For example, if the user specifies "automotive industry," the server collects the following data:

[0213] Financial Statement Data: Use the Yahoo Finance API to obtain financial statement data for major companies in the automotive industry.

[0214] Stock quotes: Uses the Google Finance API to get the latest stock quotes for each company.

[0215] Industry Trends: Use NewsAPI to gather the latest news articles related to the automotive industry.

[0216] The collected data is organized and processed using Pandas and NumPy. For example, metrics such as sales, net profit, and total assets for each company are calculated and stored in a data frame. TextBlob is also used to perform sentiment analysis on news articles and calculate positive, negative, and neutral sentiment scores.

[0217] 4. Generate and provide reports

[0218] The server generates a report based on the analysis results. The report includes the financial status of each company, industry trends, each company's position in the market, and the relationship between stock prices and companies. Matplotlib and Seaborn are used to visualize the data and create graphs and charts. The generated report is saved in PDF format and made available for users to download.

[0219] 5. Examples and prompts

[0220] As a specific example, the prompt sentence when the user specifies "automobile industry" is shown below.

[0221] "Please prepare reports on financial statements of the automotive industry, industry trends, standing within the industry, and the relationship between stock prices and companies."

[0222] By using this prompt, the user can quickly get an overview of the automotive industry.

[0223] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0224] Program processing flow

[0225] Step 1: User specifies industry

[0226] The user specifies the industry he or she is interested in through the terminal interface, for example, by inputting "automotive industry." The input industry information is sent to the server.

[0227] Input: User-specified industry (e.g. "Automotive Industry")

[0228] Output: Industry information sent to the server

[0229] Step 2: The server collects the data

[0230] The server collects data related to the specified industry from external data sources.

[0231] 1. Collection of financial statements:

[0232] The server uses the Yahoo Finance API to retrieve financial statement data for major companies.

[0233] Input: Industry information, company list

[0234] Output: Acquired financial statement data (e.g. sales, net profit, total assets)

[0235] 2. Collecting stock quotes:

[0236] The server uses the Google Finance API to obtain the latest stock quotes for each company.

[0237] Input: Industry information, company list

[0238] Output: Retrieved stock price data

[0239] 3. Collect industry trends:

[0240] The server uses the NewsAPI to collect the latest news articles related to the industry.

[0241] Input: Industry information, keywords

[0242] Output: Retrieved news article data

[0243] Step 3: The server analyzes the data

[0244] The server analyzes the collected data.

[0245] 1. Financial Analysis:

[0246] The server uses the Pandas library to organize and process each company's financial statement data.

[0247] Input: Retrieved financial statement data

[0248] Output: Organized financial data (e.g. dataframes of sales, net profit, total assets)

[0249] 2. Evaluate your position in the industry:

[0250] The server uses the NumPy library to calculate each company's market share and growth rate.

[0251] Input: Organized financial data

[0252] Output: Market share and growth rate of each company

[0253] 3. Analysis of the relationship between stock prices and public opinion:

[0254] The server uses the TextBlob library to perform sentiment analysis on the collected news articles.

[0255] Input: Retrieved news article data

[0256] Output: Sentiment score (positive, negative, neutral)

[0257] Step 4: The server generates the report

[0258] The server generates a report based on the analysis results.

[0259] 1. Report Structure:

[0260] The server compiles reports on each company's financial situation, industry trends, each company's position in the market, and the relationship between stock prices and the companies.

[0261] Inputs: Analysis results (financial data, market share, sentiment scores)

[0262] Output: Draft report

[0263] 2. Visualization:

[0264] The server uses the Matplotlib and Seaborn libraries to visualize the data.

[0265] Input: Report Draft

[0266] Output: Final report including graphs and charts

[0267] Step 5: The server serves the report to the user

[0268] The server provides the generated report to the user.

[0269] 1. Report Format:

[0270] The server generates the report in PDF format and makes it available for user download.

[0271] Input: Final Report

[0272] Output: Report in PDF format

[0273] 2. Notice:

[0274] The server notifies the user when the report is complete.

[0275] Input: Report in PDF format

[0276] Output: Notification to user (e.g. email)

[0277] In this way, a user can quickly obtain detailed reports on a specific industry.

[0278] (Application example 2)

[0279] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0280] Conventional systems have difficulty generating detailed reports on specific industries in a short time, and lack comprehensive analysis, especially including public opinion evaluations from stock price information. In addition, automation of report creation using generative AI models has not progressed, making it difficult for users to quickly grasp the overall picture of the industry.

[0281] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0282] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for making a public opinion assessment from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies related to a specific industry and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model. This allows a user to obtain a detailed report on a specific industry in a short time and perform a comprehensive analysis including public opinion assessment from stock price information.

[0283] "Means for specifying a company name or industry category" refers to an interface or function that allows a user to input or select a specific company name or industry category.

[0284] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that collects financial data on a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and its stock price, and generates reports based on this information.

[0285] "Means of evaluating public opinion from stock price information" refers to the function of analyzing stock price data and extracting and analyzing market reactions and public evaluations from that data.

[0286] "A means of analyzing financial statements, industry trends, a company's position within the industry, and the relationship between stock prices and companies in a specific industry, and generating reports" refers to the function of collecting and analyzing detailed data on a specific industry, and creating comprehensive reports based on the results.

[0287] "Means for generating prompt sentences for creating a report using a generative AI model" refers to a function for automatically generating appropriate prompt sentences to input into a generative AI model and creating a report using the prompt sentences.

[0288] A system for carrying out this invention has the following configuration: The server includes a means for designating a company name or industry genre, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies for a specific industry, and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model.

[0289] Program processing overview

[0290] 1. A way to specify a company name or industry

[0291] Users input or select a specific company name or industry category using a device such as a smartphone or PC. This information is sent to the server.

[0292] 2. Report Creation Method

[0293] The server collects financial statements, industry trends, industry standing, and the relationship between stock prices and companies for specified companies and industries. This is done using public databases and APIs on the Internet. The collected data is analyzed using data analysis tools such as Python and pandas.

[0294] 3. A means of assessing public opinion from stock price information

[0295] The server parses the stock price data and extracts market reactions and public valuations from it using a natural language processing model that uses Hugging Face's transformers library.

[0296] 4. Report Generation Methods

[0297] The server uses the collected and analyzed data to generate comprehensive reports about a particular industry, including company financials, industry trends, company positioning in the market, and company relationships with stock prices.

[0298] 5. Prompt Generation Method

[0299] The server automatically generates prompt sentences for creating a report using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report.

[0300] Examples

[0301] For example, if the user specifies the fashion industry, the following prompt sentence is generated:

[0302] Create a report on the financial statements of the fashion industry, industry trends, the position of each company in the industry, and the relationship between stock prices and companies. The report will include the financial status of each company, industry trends, the position of each company in the market, and the relationship between stock prices and companies. In addition, create a public opinion assessment from stock price information and add it to the report.

[0303] Based on this prompt, a generative AI model will create a report, allowing users to quickly get an overall picture of the fashion industry.

[0304] Hardware and Software Used

[0305] Hardware: Computer or smartphone with internet connection

[0306] Software: Python, requests, BeautifulSoup, pandas, transformers (Hugging Face)

[0307] In this way, users can quickly obtain detailed reports on specific industries and perform comprehensive analysis including public opinion assessments from stock price information.

[0308] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0309] Step 1:

[0310] The user uses the terminal to input or select a specific company name or industry category. The input information is sent to the server. The input data, which is the company name or industry category, is used for the next step of processing.

[0311] Step 2:

[0312] Based on the received company name and industry genre, the server collects data on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies from public databases and APIs on the Internet. The collected data is saved in JSON and CSV formats.

[0313] Step 3:

[0314] The server analyzes the collected data using data analysis tools such as Python and pandas. Specifically, it aggregates financial statement data, analyzes industry trends, evaluates the position of companies in the market, and analyzes the relationship between stock prices and companies. The input data is the collected raw data, and the output data is the analysis results.

[0315] Step 4:

[0316] The server analyzes the stock price data and extracts market reactions and public evaluations from the data using a natural language processing model using the Hugging Face transformers library. The input data is the stock price information and the output data is the result of the public evaluation.

[0317] Step 5:

[0318] The server generates a comprehensive report on a particular industry based on the analysis results and the opinion rating. The report includes the company's financial status, the industry trend, the company's position in the market, and the relationship between stock price and the company. The input data are the analysis results and the opinion rating, and the output data is the generated report.

[0319] Step 6:

[0320] The server automatically generates prompt sentences for creating reports using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report. The input data are the requirements for report generation, and the output data are the prompt sentences.

[0321] Step 7:

[0322] The server inputs the generated prompt sentences into the AI ​​model and creates a final report. The user can view this report through the terminal. The input data is the prompt sentences, and the output data is the final report.

[0323] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0324] "Example 1"

[0325] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the emotions of a user. When a user specifies a company name or industry genre through the system interface, this system collects data from publicly available company financial statements, industry statistical data, stock price information, etc., and analyzes the data. Then, a report is created on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Furthermore, information such as stock price fluctuations and trading volume is analyzed to estimate the company's evaluation. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the user's emotions and adjusts the display method and content of the report based on the emotion. For example, if the user shows an emotion of joy, the system displays positive information with emphasis. Conversely, if the user shows an emotion of anxiety or sadness, the system provides information that alleviates the emotion.

[0326] "Example 2"

[0327] Another embodiment of the present invention is a system in which an emotion engine adjusts the contents of a report based on the emotion of a user. When a user specifies the "automobile" industry, the system collects data from financial statements, industry statistics, stock price information, and other information related to the automobile industry, and analyzes the data. Then, a report is created on the financial statements, industry trends, the position in the industry, and the relationship between stock prices and companies in the automobile industry. Furthermore, information such as fluctuations in stock prices and trading volume related to the automobile industry is analyzed to estimate the evaluation of the companies. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the emotion of the user and adjusts the content of the report based on the emotion. For example, if the user shows excitement, the system highlights and displays positive information such as the launch of a new product or improved performance. Conversely, if the user shows anxiety, the system provides information on the stability of the industry and the reliability of the companies.

[0328] The process flow of each embodiment will be described below.

[0329] "Example 1"

[0330] Step 1: The user specifies the company name and industry genre through the system interface.

[0331] Step 2: Based on the specified company name and industry genre, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[0332] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[0333] Step 4: Analyze information such as stock price fluctuations and trading volume to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[0334] Step 5: The emotion engine recognizes the user's emotion and adjusts the presentation and content of the report based on that emotion.

[0335] "Example 2"

[0336] Step 1: The user specifies the "Automotive" industry.

[0337] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the specified "automotive" industry.

[0338] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[0339] Step 4: Analyze information such as stock price fluctuations and trading volume related to the automotive industry to estimate the valuation of the companies. This valuation is added to the report as a public opinion rating.

[0340] Step 5: The sentiment engine recognises the user's sentiment and adapts the report content based on that sentiment.

[0341] Example 1

[0342] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0343] In conventional corporate analysis systems, even if users specify a company name or industry, data collection and analysis are done manually, which is time-consuming and labor-intensive. In addition, reports are not adjusted based on public opinion from stock price information or user sentiment, making it difficult to provide useful information to users.

[0344] 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.

[0345] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for recognizing user emotions and adjusting the display method and contents of the report. This enables automatic collection and analysis of data, and makes it possible to provide useful information to users quickly and efficiently.

[0346] A "means for specifying a company name or industry category" is a device or software that provides an interface for a user to input or select a particular company name or industry category.

[0347] "Means for collecting data based on a specified company name or industry category" refers to a device or software that automatically obtains data related to a company name or industry category specified by a user from the Internet or a database.

[0348] "Means for analyzing collected data" refers to devices or software that organize the collected data and analyze it using statistical or machine learning methods.

[0349] A "means for creating a report based on the analysis results" is a device or software that automatically generates a report to be provided to a user based on the results of data analysis.

[0350] A "means for assessing public opinion from stock price information" is a device or software that analyzes information such as stock price fluctuations and trading volume, and estimates a company's evaluation and the market's reaction.

[0351] The "means for recognizing a user's emotions and adjusting the display method and contents of a report" refers to a device or software that analyzes a user's emotions and dynamically changes the display method and contents of a report in accordance with those emotions.

[0352] This invention is a system in which the server automatically collects data, analyzes it, and creates a report when the user selects a company name and industry category. It also has a function to evaluate public opinion from stock price information and adjust the display method and content of the report based on the user's feelings.

[0353] Hardware and Software Used

[0354] Hardware

[0355] Server: A central processing unit for data collection, analysis, reporting, and emotion recognition.

[0356] Terminal: The device (PC, smartphone, tablet, etc.) through which the user enters the company name and industry genre.

[0357] software

[0358] Interface: A GUI (Graphical User Interface) that allows users to specify company names and industry genres.

[0359] Data collection: Web scraping using Python's BeautifulSoup and Selenium, and stock quotes using the Yahoo Finance API.

[0360] Data Analysis: Use Python's Pandas and NumPy to organize the data and Scikit-learn to apply machine learning models.

[0361] Reporting: Generate reports using Python ReportLab or Jinja2.

[0362] Public opinion assessment: We use natural language processing techniques and machine learning algorithms to assess public opinion. Specifically, we use libraries such as NLTK, TensorFlow, and PyTorch.

[0363] Emotion Recognition: Analyze user emotions using Microsoft® Azure® Emotion API and Google Cloud's Natural Language API.

[0364] Examples

[0365] Example 1: User specifies "ABC Corporation" and "IT industry"

[0366] A user opens the system interface using a terminal and selects "ABC Corporation" and the "IT industry." The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements for "ABC Corporation" and statistical data for the "IT industry," and obtains stock price information using the Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, and estimates public opinion for "ABC Corporation" using NLTK and TensorFlow, which it adds to the report.

[0367] Example 2: User specifies "XYZ Corporation" and "manufacturing industry" and emotion engine recognizes anxiety

[0368] The user opens the system interface using a terminal and selects "XYZ Corporation" and "Manufacturing". The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements of "XYZ Corporation" and statistical data of "Manufacturing", and obtains stock price information using Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, estimates public opinion evaluation of "XYZ Corporation" using NLTK and TensorFlow, and adds it to the report. As the emotion engine recognizes the user's anxiety, the server uses Microsoft Azure's Emotion API and Google Cloud's Natural Language API to analyze the user's emotions and provide information that will ease their anxiety.

[0369] Examples of prompt statements

[0370] "Collect ABC Corporation's financial statements, IT industry statistics, and stock price information, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, analyze stock price fluctuations and trading volume, estimate public opinion, and add it to the report."

[0371] "Please collect financial statements, manufacturing industry statistics, and stock price information for XYZ Corporation, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, please analyze stock price fluctuations and trading volume, estimate public opinion, and add this to the report. Users are feeling anxious, so please provide information that will ease their anxiety."

[0372] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0373] Step 1:

[0374] The user opens the system interface using a terminal and inputs the company name and industry category. The input information is sent to the server as text data of the company name and industry category.

[0375] Step 2:

[0376] The server collects data based on the company name and industry category specified by the user. Specifically, it uses Python's BeautifulSoup and Selenium to perform web scraping to obtain company financial statements and industry statistical data. It also obtains stock price information using the Yahoo Finance API. The input is text data of company names and industry categories, and the output is a dataset of financial statement data, industry statistical data, and stock price information.

[0377] Step 3:

[0378] The server analyzes the collected data. Specifically, it organizes the data using Python's Pandas and NumPy, and applies machine learning models using Scikit-learn. The input is a dataset of financial statement data, industry statistical data, and stock price information, and the output is a dataset of the analysis results. For example, the server performs specific operations such as "analyzing financial statement data to evaluate the financial situation of ABC Corporation" or "analyzing statistical data to understand trends in the IT industry."

[0379] Step 4:

[0380] The server creates reports based on the analysis results. Specifically, it generates reports using Python's ReportLab or Jinja2. The input is a dataset of the analysis results, and the output is a report to be provided to the user. For example, the server performs a specific operation such as "create a report summarizing the financial situation of ABC Corporation, trends in the IT industry, ABC Corporation's position within the industry, and the relationship between stock prices and companies."

[0381] Step 5:

[0382] The server analyzes information such as stock price fluctuations and trading volume to estimate the evaluation of the company. Specifically, it uses natural language processing technology and machine learning algorithms to perform public opinion evaluation. The input is a dataset of stock price information, and the output is a dataset of public opinion evaluation. For example, the server performs a specific operation such as "analyzing stock price fluctuation data and estimating public opinion evaluation of ABC Co., Ltd."

[0383] Step 6:

[0384] The server recognizes the user's emotions. Specifically, it analyzes the user's emotions using Microsoft Azure's Emotion API and Google Cloud's Natural Language API. The input is data such as the user's input, facial expressions, and tone of voice, and the output is the user's emotional data. For example, the server performs specific operations such as "recognizing emotions from the user's input, facial expressions, and tone of voice."

[0385] Step 7:

[0386] The server adjusts the display method and content of the report based on the user's emotions recognized by the emotion engine. The input is the user's emotion data and the report, and the output is the adjusted report. For example, if the user expresses emotions of joy, the server takes specific actions such as "displaying the report with positive information emphasized." Conversely, if the user expresses emotions of anxiety or sadness, the server takes specific actions such as "providing information that will ease anxiety."

[0387] (Application example 1)

[0388] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0389] In conventional corporate information analysis systems, even if the user specified a company name or industry, the system would only collect and analyze data such as financial statements, industry trends, and stock price information, and could not provide information based on the user's emotions. As a result, the system was unable to provide appropriate information based on the user's emotions, which led to an issue of poor user experience.

[0390] 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.

[0391] In this invention, the server includes a means for designating a company name and industry category, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and content of the report based on the user emotions, thereby making it possible to provide appropriate information according to the user's emotions.

[0392] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[0393] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that collects publicly available financial statements, industry trends, position within the industry, stock price information, etc. based on a specified company name or industry genre, analyzes them, and automatically generates reports.

[0394] "Means of evaluating public opinion from stock price information" is a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[0395] "Means of recognizing user emotions" refers to a function that analyzes emotions from text, voice, facial expressions, etc. entered by the user and recognizes those emotions.

[0396] The "means for adjusting the display method and contents of a report based on the user's emotions" is a function for dynamically changing the display method and contents of a report in response to the recognized emotions of a user.

[0397] As an embodiment of the present invention, the following system can be constructed.

[0398] The server includes a means for specifying a company name and industry category, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and contents of the report based on the user emotions.

[0399] Specifically, the server uses the following hardware and software.

[0400] Hardware: Servers, smartphones

[0401] Software: Python, requests, pandas, TextBlob, scikit-learn

[0402] The server first receives the company name and industry category entered by the user via smartphone. The server then collects publicly available company financial statements, industry statistics, stock price information, etc., and converts them into a data frame using pandas. This allows the server to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[0403] Additionally, the server uses TextBlob to analyze user sentiment and adjust the presentation and content of reports based on that sentiment. For example, if a user types, "I'm worried about the recent stock market movements," TextBlob can be used to analyze sentiment and, if negative sentiment is detected, the server will highlight information that requires attention.

[0404] As a concrete example, the following prompt sentence can be used:

[0405] Company Name: General company name

[0406] Emotional text: "I'm worried about the recent stock market movements."

[0407] When this prompt is entered into the server, the server collects financial data from companies and generates a report based on the user's emotions, allowing the user to obtain appropriate information according to their own emotions.

[0408] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0409] Step 1:

[0410] A user inputs a company name and an industry category using a terminal. The input company name and industry category are sent to a server. The input data is text information about the company name and industry category.

[0411] Step 2:

[0412] The server collects publicly available company financial statements, industry statistical data, stock price information, etc. based on the received company name and industry category. Specifically, the server obtains data using an API (e.g., Yahoo Finance API). The input data is the company name and industry category, and the output data is a data set including financial statements, industry statistical data, and stock price information.

[0413] Step 3:

[0414] The server converts the collected data into a data frame using pandas. The data converted into a data frame is used to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and companies. The input data is the collected raw data, and the output data is analyzable data in the data frame format.

[0415] Step 4:

[0416] The server uses TextBlob to analyze the sentiment from the user-entered text. Specifically, it passes the user-entered text to TextBlob and gets the sentiment score (positive or negative). The input data is the user's text and the output data is the sentiment score.

[0417] Step 5:

[0418] The server adjusts the presentation and content of the report based on the sentiment score, for example highlighting information that requires attention if negative sentiment is detected. The input data are sentiment scores and a data frame, and the output data is the adjusted report.

[0419] Step 6:

[0420] The server generates the reconciled report and sends it to the terminal, which displays the received report to the user, the input data being the reconciled report and the output data being the report displayed to the user.

[0421] Step 7:

[0422] The user can check the displayed report through the terminal and retrieve the information again by inputting additional company names and industry categories as necessary. The input data is the user's feedback and new company names and industry categories, and the output data is the updated report.

[0423] Example 2

[0424] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0425] Conventional industry analysis systems had the problem that it took a lot of time and effort for users to understand the overall picture of the industry. In addition, they could not fully meet the needs of users because they did not provide information according to their emotions. Furthermore, public opinion evaluation from stock price information was insufficient, and the evaluation of companies was not accurately reflected.

[0426] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for designating an industry, a means for collecting data, a means for analyzing data, a means for generating a report, a means for public opinion evaluation, a means for recognizing emotions and adjusting the report, and a means for providing the report. This allows the user to grasp the overall picture of the industry in a short time, and information is provided according to the user's emotions, so that the user's needs can be met. In addition, an accurate public opinion evaluation is performed based on stock price information, and the evaluation of the company is accurately reflected.

[0427] The "means for specifying an industry" is an interface that allows the user to select or input the industry in which he or she is interested.

[0428] "Means of collecting data" refers to the function of obtaining information related to the specified industry from the Internet or databases.

[0429] "Means for analyzing data" refers to a function for organizing collected data and analyzing it using statistical or machine learning methods.

[0430] The "means for generating a report" is a function for creating a report to be provided to a user based on the analysis results.

[0431] "Means of evaluating public opinion" refers to a function that analyzes stock price information and market reactions to estimate a company's valuation.

[0432] The "means for recognizing emotions and adjusting reports" is a function for detecting the emotions of a user and adjusting the contents of a report in accordance with the emotions.

[0433] The "means for providing a report" is a function for displaying or transmitting a generated report to a user.

[0434] The present invention is a system in which a user specifies an industry, and a server collects data, analyzes data, generates reports, evaluates public opinion, recognizes emotions, and provides reports. A specific embodiment of this system is described below.

[0435] 1. Means of specifying industry

[0436] A user uses a terminal to access the system and specify the industry he or she is interested in. For example, the user opens a browser, accesses the system's web page, enters "automotive" in the search box, and clicks the search button. This action sends the user's specification to the server.

[0437] 2. How we collect data

[0438] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[0439] Use the Yahoo Finance API to collect company financial statements.

[0440] Use the Google Finance API to get stock price data for the past year.

[0441] 3. How to analyze the data

[0442] The server analyzes the collected data. Specifically, it uses the following libraries:

[0443] Use Pandas to organize financial data for each company.

[0444] Analyzing industry trends using NumPy.

[0445] 4. How to generate reports

[0446] The server generates a report based on the analysis results. It uses a generative AI model (e.g., GPT-4 (registered trademark) from OpenAI (registered trademark)) to create a report like the one below.

[0447] Automotive Industry Report:

[0448] Company A's financial situation is good, with sales increasing 10% year-on-year.

[0449] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[0450] Company A has a strong position in the market and its stock price is stable.

[0451] 5. Means of assessing public opinion

[0452] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[0453] Analyze stock price fluctuations and rate Company A as "high."

[0454] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[0455] 6. How to recognize emotions and adjust reports

[0456] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[0457] If users are excited, highlight information about a new product launch or business improvement.

[0458] If users express concern, provide information about industry stability and company trustworthiness.

[0459] 7. Means of Providing Reports

[0460] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[0461] Examples of concrete examples and prompts

[0462] As a specific example, the process when the user specifies the "automobile" industry is shown below.

[0463] Data collection:

[0464] The server collects financial statements of Company A, Company B, and Company C using the Yahoo Finance API.

[0465] Use the Google Finance API to get stock price data for the past year.

[0466] Data Analysis:

[0467] The server uses Pandas to organize each company's financial data and NumPy to analyze industry trends.

[0468] Report Generation:

[0469] The server uses GPT-4 to generate a report like this:

[0470] Automotive Industry Report:

[0471] Company A's financial situation is good, with sales increasing 10% year-on-year.

[0472] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[0473] Company A has a strong position in the market and its stock price is stable.

[0474] Adding public opinion ratings:

[0475] The server analyzes the fluctuations in stock prices and rates Company A as "high."

[0476] Emotion Recognition and Report Adjustment:

[0477] The server highlights information about new product launches or business improvements if the user is excited about them.

[0478] Conversely, if users express concern, provide information about industry stability and company trustworthiness.

[0479] Example prompt:

[0480] Please create a report on the "Automobile" industry. Please include the financial statements of Company A, Company B, and Company C, industry trends, the market position of each company, and the relationship between stock prices and the companies. Also, please make a public opinion assessment based on stock price information and add it to the report.

[0481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0482] Step 1:

[0483] The user specifies the industry.

[0484] The user opens a browser on the terminal and accesses the system's web page. The user enters "car" in the search box and clicks the search button. This operation sends the user's specification to the server.

[0485] Input: A user-specified industry (e.g. "Automotive")

[0486] Output: Industry-specific information sent to the server

[0487] Step 2:

[0488] The server collects the data.

[0489] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[0490] Use the Yahoo Finance API to collect company financial statements.

[0491] Use the Google Finance API to get stock price data for the past year.

[0492] Input: Industry-specific information

[0493] Output: Collected company financial statements and stock price data

[0494] Step 3:

[0495] The server analyzes the data.

[0496] The server analyzes the collected data. Specifically, it uses the following libraries:

[0497] Use Pandas to organize financial data for each company.

[0498] Analyzing industry trends using NumPy.

[0499] Input: Collected company financial statements and stock price data

[0500] Output: Organized financial data and industry trend analysis

[0501] Step 4:

[0502] The server generates the report.

[0503] The server generates a report based on the analysis results. It uses a generative AI model (e.g., OpenAI's GPT-4) to create a report like the one below.

[0504] Automotive Industry Report:

[0505] Company A's financial situation is good, with sales increasing 10% year-on-year.

[0506] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[0507] Company A has a strong position in the market and its stock price is stable.

[0508] Input: Organized financial data and industry trend analysis results

[0509] Output: Generated report

[0510] Step 5:

[0511] The server adds a public opinion rating.

[0512] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[0513] Analyze stock price fluctuations and rate Company A as "high."

[0514] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[0515] Input: Stock price data

[0516] Output: Report with opinion ratings added

[0517] Step 6:

[0518] The server performs emotion recognition and adjusts the reports.

[0519] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[0520] If users are excited, highlight information about a new product launch or business improvement.

[0521] If users express concern, provide information about industry stability and company trustworthiness.

[0522] Input: User emotion data

[0523] Output: Reconciled report

[0524] Step 7:

[0525] The server provides the report to the user.

[0526] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[0527] Input: Reconciled report

[0528] Output: Report provided to the user

[0529] (Application example 2)

[0530] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0531] Conventional industry report creation systems lacked the ability to adjust report content based on user sentiment, making it difficult to provide information that meets user needs. In addition, report generation and prompt sentence generation were not performed using generative AI models, which led to problems with the quality of reports and user experience not improving.

[0532] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0533] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the content of the report based on the emotions, a means for generating a report using a generative AI model, and a means for generating a prompt sentence. This makes it possible to provide a report customized according to the user's emotions, and realizes high-quality report generation and prompt sentence generation using a generative AI model.

[0534] "Means for specifying a company name or industry category" refers to a function that provides an interface for a user to input or select a specific company name or industry category.

[0535] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that analyzes financial data for a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and information, and synthesizes this information to generate a report.

[0536] "Means of evaluating public opinion from stock price information" refers to a function that analyzes stock price data, extracts market reactions and public evaluations, and evaluates public opinion toward companies and industries.

[0537] "Means for recognizing a user's emotions and adjusting the contents of the report based on those emotions" is a function for analyzing a user's emotions and dynamically changing the contents of the report in accordance with those emotions.

[0538] A "means for generating reports using a generative AI model" is a function that uses an artificial intelligence model to automatically generate detailed reports on specified industries or companies.

[0539] A "means for generating a prompt sentence" is a function for automatically creating an appropriate prompt sentence to input to a generative AI model.

[0540] A system for carrying out the present invention includes a server, a user terminal, and a generative AI model. The server includes a means for specifying a company name and industry genre, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the contents of the report based on the emotions, a means for generating a report using the generative AI model, and a means for generating prompt sentences.

[0541] Hardware and Software Configuration

[0542] Hardware: Server, user terminal (smartphone, head-mounted display)

[0543] Software: Python, Requests library, Pandas library, TextBlob library

[0544] Data processing and calculation

[0545] 1. Specify your company name and industry:

[0546] The user terminal provides an interface for the user to input or select a particular company name or industry category. The information input by the user is transmitted to the server.

[0547] 2. Data Collection and Reporting:

[0548] The server collects financial data on specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The collected data is organized and analyzed using the Pandas library, and a report is generated.

[0549] 3. Public opinion assessment:

[0550] The server analyzes the stock price data and extracts market reactions and public evaluations. Using the TextBlob library, we perform sentiment analysis of the text data obtained from stock price information and perform public opinion evaluation.

[0551] 4. Emotion recognition and report adjustment:

[0552] The user terminal provides an interface for recognizing the user's emotions, and the user's emotion data is transmitted to the server, which dynamically adjusts the report content based on the emotions.

[0553] 5. Report generation using generative AI models:

[0554] The server uses the generative AI model to automatically generate detailed reports on the specified industry or company by generating prompt sentences and inputting them into the generative AI model.

[0555] 6. Prompt generation:

[0556] The server automatically creates appropriate prompt sentences to input to the generative AI model. For example, create a report on financial statements, industry trends, corporate positions, and the relationship between stock prices and companies in the "automotive" industry. If the user's sentiment is positive, highlight positive information such as new product launches and improved performance, and if it is negative, provide information on industry stability and company reliability.

[0557] Examples

[0558] If the user specifies the “Automotive” industry and the sentiment engine determines the user’s sentiment to be positive, a report like the one below will be generated.

[0559] Industry: Automotive

[0560] Financial Statement: Financial Statement for Q1 2023

[0561] Industry Trend: Electric vehicles are on the rise

[0562] Company position: Major automakers hold top market share

[0563] Stock prices and companies: Major automakers' stock prices are rising

[0564] Positive news: new product launches and improving performance

[0565] In this way, it becomes possible to provide customized reports based on the user's emotions, and high-quality report generation and prompt generation can be achieved by utilizing generative AI models.

[0566] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0567] Step 1:

[0568] The user terminal provides an interface for the user to input or select a particular company name or industry category. The company name or industry category input by the user is sent to the server. The input data is the text information of the company name or industry category. The output is the text information of the company name or industry category sent to the server.

[0569] Step 2:

[0570] The server collects financial data for specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The input data is text information on company names and industry genres. The server uses the Requests library to obtain data from the API, and organizes and analyzes the data using the Pandas library. The output is organized and analyzed financial data, industry trends, the company's position in the market, and the relationship between stock prices and companies.

[0571] Step 3:

[0572] The server analyzes stock price data and extracts market reactions and public evaluations. The input data is stock price information obtained from the API. The server uses the TextBlob library to perform sentiment analysis of the text data obtained from the stock price information and perform public opinion evaluation. The output is public opinion evaluation data including the sentiment analysis results.

[0573] Step 4:

[0574] The user terminal provides an interface for recognizing the user's emotions. The user's emotion data is transmitted to the server. The input data is text information or sensor data indicating the user's emotions. The output is the user's emotion data transmitted to the server.

[0575] Step 5:

[0576] The server dynamically adjusts the report content based on the user's emotion data. The input data are the user's emotion data and the data obtained in steps 2 and 3. If the user's emotion is positive, the server emphasizes positive information, and if the user's emotion is negative, it emphasizes information about stability and reliability. The output is report data adjusted according to the user's emotion.

[0577] Step 6:

[0578] The server uses the generative AI model to automatically generate a detailed report on the specified industry or company. The input data are the data obtained in step 2 and step 3 and the prompt sentence. The server inputs the prompt sentence into the generative AI model and generates a report. The output is the generated report.

[0579] Step 7:

[0580] The server automatically creates appropriate prompt sentences to input to the generative AI model. The input data is text information on the company name and industry genre specified by the user. The server generates the prompt sentences and inputs them into the generative AI model. The output is the generated prompt sentence.

[0581] As a specific example, if a user specifies the "automobile" industry and the emotion engine determines that the user's emotion is positive, the following prompt sentence is generated:

[0582] Create a report on financial statements, industry trends, company positions, and company relationships for the "Automotive" industry. If user sentiment is positive, highlight positive information such as new product launches and improving performance. If sentiment is negative, provide information about industry stability and company reliability.

[0583] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0584] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0585] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0586] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0587] [Second embodiment]

[0588] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0589] 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.

[0590] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0591] 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.

[0592] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0593] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0594] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0595] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0600] "Example 1"

[0601] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. It analyzes information such as stock price fluctuations and trading volume to estimate a company's valuation.

[0602] "Example 2"

[0603] As a specific example, if a user specifies the "automobile" industry, the system will create a report on the automobile industry's financial statements, industry trends, position within the industry, and the relationship between stock prices and companies. The report includes each company's financial status, industry trends, each company's position within the market, and the relationship between stock prices and companies. In addition, the system will perform public opinion evaluation from stock price information and add it to the report. This allows users to quickly grasp the overall picture of the automobile industry.

[0604] The process flow of each embodiment will be described below.

[0605] "Example 1"

[0606] Step 1: The user specifies the company name and industry genre through the system interface.

[0607] Step 2: Based on the specified company name and industry category, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[0608] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[0609] Step 4: Further, information such as stock price fluctuations and trading volume is analyzed to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[0610] "Example 2"

[0611] Step 1: The user specifies the "Automotive" industry.

[0612] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the automotive industry.

[0613] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[0614] Step 4: Further, information such as stock price fluctuations and trading volume related to the automotive industry is analyzed to estimate the valuation of the companies. This valuation is added to the report as a public opinion rating.

[0615] Example 1

[0616] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0617] Conventional corporate analysis systems had the problem that even if a user specified a company name or industry, it took a lot of time and effort to collect, process, and analyze the necessary data. In addition, there was a lack of automated means to evaluate public opinion from stock price information, so users had to perform the evaluation manually. This made it difficult to create reports quickly and accurately.

[0618] 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.

[0619] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for processing and analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for providing the created report. This makes it possible for a user to simply designate a company name and an industry category, and quickly and accurately create and provide a report including the company's financial situation, industry trends, the company's position in the market, the relationship between stock price and the company, and evaluation of public opinion.

[0620] The "means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[0621] "Means of collecting data based on a specified company name or industry genre" refers to a function for obtaining data related to a company name or industry genre specified by a user from an external database or API.

[0622] "Means for processing and analyzing collected data" refers to the function of organizing collected data, extracting necessary information, and analyzing it.

[0623] The "means for creating a report based on the analysis results" is a function for automatically generating a report to be provided to a user based on the analyzed data.

[0624] "Means of assessing public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate the market's evaluation and public opinion of a company.

[0625] The "means for providing a generated report" refers to a function for providing a generated report to a user, and includes provision in PDF format or Web page format.

[0626] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. This involves analyzing information such as stock price fluctuations and trading volume, and estimating a company's valuation.

[0627] Hardware and Software Used

[0628] Hardware

[0629] Server: A central processing unit for data collection, processing, analysis, and report generation.

[0630] Terminal: The device through which the user operates the interface (e.g. PC, smartphone)

[0631] software

[0632] Web browser: Provides an interface for users to enter company names and industry categories

[0633] API: Access to external databases and services for data collection (e.g. EDGAR database, Statista, Yahoo Finance API)

[0634] Template engine: a tool for formatting collected and analyzed data into reports

[0635] Data analysis tools: Software for processing and analyzing collected data (e.g. Python, R)

[0636] Data processing and calculation

[0637] The server collects the necessary information from the following data sources based on the company name and industry genre specified by the user.

[0638] Public company financial statements (e.g., EDGAR database)

[0639] Industry statistics (e.g. Statista)

[0640] Stock quotes (e.g. Yahoo Finance API)

[0641] The collected data will be processed and analyzed as follows:

[0642] Analyze financial statement data to evaluate a company's financial position, for example by calculating indicators such as sales, net profit, and debt ratio.

[0643] Use industry statistics to analyze industry trends, for example, to calculate overall industry growth rates and market shares.

[0644] Analyze stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[0645] Analyze stock price fluctuations and trading volume to estimate public opinion. For example, identify the causes of sudden increases or decreases in stock prices.

[0646] Examples

[0647] Example 1: When specifying a company name

[0648] The user specifies "specific company." The server performs the following process:

[0649] 1. The user enters "specific company" into the web form and clicks the submit button.

[0650] 2. The server retrieves the latest financial statements for a particular company from the EDGAR database.

[0651] 3. The server retrieves the latest statistical data for a specific industry from Statista.

[0652] 4. The server retrieves stock price information for a specific company from the Yahoo Finance API.

[0653] 5. The server analyzes the collected data and creates a report that includes the specific company's financial status, industry trends, its position within the industry, the company's relationship with stock prices, and public opinion ratings.

[0654] 6. The server generates the report in PDF format and provides a download link to the user.

[0655] Example 2: When specifying an industry genre

[0656] The user specifies "specific industry." The server performs the following process:

[0657] 1. A user enters "specific industry" into a web form and clicks the submit button.

[0658] 2. The server retrieves the latest statistical data for a specific industry from Statista.

[0659] 3. The server retrieves stock price information for major companies in a specific industry from the Yahoo Finance API.

[0660] 4. The server analyzes the collected data and creates reports that include trends in a particular industry, the position of major companies within the industry, the relationship between stock prices and companies, and public opinion ratings.

[0661] 5. The server generates the report in the form of a web page and displays it to the user.

[0662] Examples of prompt statements

[0663] Example 1: Prompt statement specifying company name

[0664] "Create a report that includes a specific company's latest financials, industry trends, where it stands within the industry, the company's stock price relationship, and public opinion ratings."

[0665] Example 2: Prompt statement specifying industry genre

[0666] "Create a report that includes the latest trends in a particular industry, where major companies stand in the industry, stock price-company relationships, and public opinion ratings."

[0667] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0668] Step 1: User specifies company name and industry category

[0669] A user uses an interface to input a company name and industry category through a web browser or mobile application. For example, the user inputs "specific company" and clicks the submit button. The input data is sent to the server.

[0670] Input: Company name or industry

[0671] Output: The input data sent to the server.

[0672] Step 2: The server collects the data

[0673] The server collects the necessary information from the following data sources based on the company name and industry genre received from the user.

[0674] The server accesses the EDGAR database to retrieve the most recent financial statements for the specified companies.

[0675] The server accesses Statista and retrieves the latest statistical data for the specified industry.

[0676] The server uses the Yahoo Finance API to retrieve stock quotes for the specified companies.

[0677] Input: User-specified company name or industry

[0678] Output: Collected financial statement data, industry statistics, stock price information

[0679] Step 3: The server processes and analyzes the data

[0680] The server processes and analyzes the collected data as follows:

[0681] The server analyzes the financial statement data and evaluates the company's financial condition, for example calculating metrics such as sales, net profit, and debt ratio.

[0682] The server uses industry statistics to analyze industry trends, for example to calculate industry-wide growth rates and market shares.

[0683] The server analyzes stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[0684] The server analyzes stock price fluctuations and trading volume to estimate public opinion, for example by identifying the causes of sudden increases or decreases in stock prices.

[0685] Input: Collected financial statement data, industry statistics, stock price information

[0686] Output: Company financial status, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[0687] Step 4: The server creates the report

[0688] The server automatically generates a report to provide to the user based on the results of the above analysis. The report includes the following:

[0689] Company financial status (e.g. sales, net profit, debt ratio)

[0690] Industry trends (e.g. industry-wide growth rates, market shares)

[0691] Position in the industry (e.g., compared to competitors)

[0692] Relationship between stock prices and companies (e.g. stock price fluctuations, trading volume)

[0693] Public opinion assessment (e.g., reasons for sudden rises and falls in stock prices)

[0694] Input: Company financials, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[0695] Output: Generated report

[0696] Step 5: The server serves the report

[0697] The server then provides the generated report to the user, either in PDF format or as a web page, for example with a link that allows the user to download the report.

[0698] Input: Generated report

[0699] Output: Report provided to user (in PDF or web page format)

[0700] (Application example 1)

[0701] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0702] In conventional corporate analysis systems, even if a user specified a company name or industry, financial statements, industry trends, stock price information, etc. had to be individually collected and analyzed manually. This took time and effort, making it difficult to make quick decisions. In addition, there was a lack of automated means to evaluate public opinion from stock price information, making it impossible to efficiently obtain information that could be used as a reference for investment decisions.

[0703] 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. In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, a position in the industry, and a relationship between stock prices and a company, a means for evaluating public opinion from stock price information, a means for providing a report through an application installed on a smartphone, and a means for automatically generating a report using a generative AI model. This enables a user to quickly and efficiently grasp a company's financial situation, industry trends, a company's position in the market, and a relationship between stock prices and a company, and to obtain information that can be used as a reference for investment decisions.

[0704] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[0705] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that automatically generates reports by analyzing related financial statements, industry trends, position within the industry, and the relationship between a company and stock prices based on a specified company name and industry genre.

[0706] "Means of evaluating public opinion from stock price information" is a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[0707] "Means for providing a report through an application installed on a smartphone" refers to a function for providing a generated report to a user through a smartphone application.

[0708] "Means for automatically generating reports using a generative AI model" means a function that uses an artificial intelligence model to automatically generate reports based on collected data.

[0709] As an embodiment of the present invention, the following system is constructed.

[0710] System Configuration

[0711] The system consists of a smartphone application that allows users to specify company names and industry genres, a server that collects and analyzes data, and a back-end system that automatically generates reports using generative AI models.

[0712] Hardware and Software Used

[0713] Hardware: Smartphone (iOS or Android)

[0714] software:

[0715] Python: Data Processing and Analysis

[0716] Pandas: Dataframe Operations

[0717] BeautifulSoup: Web scraping

[0718] Scikit-learn: Machine learning models

[0719] TensorFlow: Generative AI Models

[0720] Flask: Backend API

[0721] Processing flow

[0722] 1. User Interface:

[0723] Users enter company names and industry categories through a smartphone application.

[0724] For example, the user specifies "Automobile Manufacturer A" and the "Automobile Industry."

[0725] 2. Data collection:

[0726] The server uses BeautifulSoup to scrape financial statements, industry statistics, and stock quotes from the web for specified companies.

[0727] Use Pandas to organize and consolidate the collected data.

[0728] 3. Data Analysis:

[0729] The server uses Scikit-learn to build a model for deriving public opinion from stock price information.

[0730] Use TensorFlow to automatically generate reports using generative AI models.

[0731] 4. Report Generation:

[0732] Based on the collected and analyzed data, the server generates reports on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company.

[0733] The generated reports are provided to the user via a smartphone application.

[0734] Examples

[0735] If the user specifies "Automobile manufacturer A" and the "Automobile industry", the server will collect the latest financial statements, industry statistical data, and stock price information of Automobile manufacturer A, and will evaluate public opinion based on Automobile manufacturer A's position in the industry and fluctuations in its stock price. Finally, a report based on this information will be generated and provided to the user.

[0736] Examples of prompt statements

[0737] Company Name: Automobile Manufacturer A

[0738] Industry: Automotive industry

[0739] By entering this prompt, the system will generate a detailed report on car manufacturer A.

[0740] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0741] Step 1:

[0742] The user starts the smartphone application and inputs the company name and industry category. For example, they specify "Automobile Manufacturer A" and "Automobile Industry". The input data is sent to the server.

[0743] Step 2:

[0744] Based on the received company names and industry categories, the server uses BeautifulSoup to scrape relevant financial statements, industry statistics, and stock quotes from the web. The input is the company name and industry category, and the output is the collected raw data.

[0745] Step 3:

[0746] The server uses Pandas to organize and consolidate the collected raw data, creating a data frame, imputing missing values, and normalizing the data. The input is the scraped raw data, and the output is the organized and consolidated data frame.

[0747] Step 4:

[0748] The server uses Scikit-learn to build a machine learning model for public opinion evaluation from stock price information. The input is a cleaned and integrated data frame, and the output is a public opinion evaluation model. Specifically, the server uses stock price fluctuations and trading volume as features to estimate the evaluation of a company.

[0749] Step 5:

[0750] The server uses TensorFlow to automatically generate reports using generative AI models. The input is a data frame organized and integrated with the public opinion evaluation model, and the output is an automatically generated report. Specifically, it generates a report that includes the company's financial status, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[0751] Step 6:

[0752] The server provides the generated report to the user through the smartphone application. The input is the automatically generated report, and the output is the report displayed on the user's smartphone screen. This allows the user to quickly and efficiently obtain detailed information about the company.

[0753] Example 2

[0754] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0755] In the conventional system, it took a lot of time and effort to create detailed reports on a specific industry. In addition, each step of data collection, analysis, and report generation was often done manually, which was inefficient. In addition, there was a lack of means to evaluate public opinion from stock price information, making it difficult to accurately grasp a company's market position and industry trends.

[0756] 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.

[0757] In this invention, the server includes a means for designating an industry, a means for creating reports on financial data, industry trends, a company's position in the market, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for collecting data, a means for analyzing data, a means for generating reports, and a means for providing reports, thereby making it possible to automatically generate detailed reports on an industry designated by a user and provide them in a short time.

[0758] The "means for specifying an industry" is a function that provides an interface for the user to select or input a specific industry.

[0759] "Financial data" refers to economic indicators such as sales, net profit, and total assets included in a company's financial statements and financial reports.

[0760] "Industry trends" refers to information that indicates the latest developments and market changes within a particular industry.

[0761] "A company's market position" refers to information that indicates the position of a particular company within its industry, including market share and growth rate.

[0762] "The relationship between stock prices and companies" is information that shows how a company's stock price is related to the company's financial situation and market valuation.

[0763] The "means for creating a report" is a function for generating a report to be provided to a user based on collected and analyzed data.

[0764] "Means of evaluating public opinion from stock price information" is a function that analyzes market reactions and public evaluations based on stock price data, and evaluates public opinion.

[0765] "Means of collecting data" means the ability to obtain data related to the specified industry from external data sources, for example, using an API to obtain data.

[0766] "Means of analyzing data" refers to the function of organizing and processing collected data and calculating necessary indicators. Examples include financial data analysis and sentiment analysis.

[0767] "Means for generating reports" refers to a function for creating visually easy-to-understand reports based on analysis results, for example using graphs and charts.

[0768] The "means for providing a report" is a function for providing a generated report to a user, for example, by making the report downloadable in PDF format.

[0769] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0770] The present invention is a system for automatically generating and providing a detailed report on a particular industry when the user designates the industry. A specific embodiment of this system will be described below.

[0771] 1. System Configuration

[0772] The system consists of the following main components:

[0773] User terminal: A device that provides an interface for a user to specify an industry. For example, a PC or smartphone.

[0774] Server: The central component responsible for data collection, analysis, and report generation. Developed using Python.

[0775] External Data Sources: APIs and databases used to collect data. Examples include Yahoo Finance API, Google Finance API, NewsAPI, etc.

[0776] 2. Hardware and Software Used

[0777] Hardware: The server is a computer equipped with a powerful processor and sufficient memory. The user terminal is a general-purpose PC or smartphone.

[0778] Software: The server is developed using Python and uses the following libraries and tools:

[0779] Pandas: Used to organize and process data.

[0780] NumPy: Used for numerical calculations.

[0781] TextBlob: Used for sentiment analysis.

[0782] Matplotlib and Seaborn for data visualization.

[0783] API Client: Used to retrieve data from external data sources such as Yahoo Finance API, Google Finance API, NewsAPI, etc.

[0784] 3. Data collection and analysis

[0785] The server collects data related to the industry specified by the user from external data sources. For example, if the user specifies "automotive industry," the server collects the following data:

[0786] Financial Statement Data: Use the Yahoo Finance API to obtain financial statement data for major companies in the automotive industry.

[0787] Stock quotes: Uses the Google Finance API to get the latest stock quotes for each company.

[0788] Industry Trends: Use NewsAPI to gather the latest news articles related to the automotive industry.

[0789] The collected data is organized and processed using Pandas and NumPy. For example, metrics such as sales, net profit, and total assets for each company are calculated and stored in a data frame. TextBlob is also used to perform sentiment analysis on news articles and calculate positive, negative, and neutral sentiment scores.

[0790] 4. Generate and provide reports

[0791] The server generates a report based on the analysis results. The report includes the financial status of each company, industry trends, each company's position in the market, and the relationship between stock prices and companies. Matplotlib and Seaborn are used to visualize the data and create graphs and charts. The generated report is saved in PDF format and made available for users to download.

[0792] 5. Examples and prompts

[0793] As a specific example, the prompt sentence when the user specifies "automobile industry" is shown below.

[0794] "Please prepare reports on financial statements of the automotive industry, industry trends, standing within the industry, and the relationship between stock prices and companies."

[0795] By using this prompt, the user can quickly get an overview of the automotive industry.

[0796] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0797] Program processing flow

[0798] Step 1: User specifies industry

[0799] The user specifies the industry he or she is interested in through the terminal interface, for example, by inputting "automotive industry." The input industry information is sent to the server.

[0800] Input: User-specified industry (e.g. "Automotive Industry")

[0801] Output: Industry information sent to the server

[0802] Step 2: The server collects the data

[0803] The server collects data related to the specified industry from external data sources.

[0804] 1. Collection of financial statements:

[0805] The server uses the Yahoo Finance API to retrieve financial statement data for major companies.

[0806] Input: Industry information, company list

[0807] Output: Acquired financial statement data (e.g. sales, net profit, total assets)

[0808] 2. Collecting stock quotes:

[0809] The server uses the Google Finance API to obtain the latest stock quotes for each company.

[0810] Input: Industry information, company list

[0811] Output: Retrieved stock price data

[0812] 3. Collect industry trends:

[0813] The server uses the NewsAPI to collect the latest news articles related to the industry.

[0814] Input: Industry information, keywords

[0815] Output: Retrieved news article data

[0816] Step 3: The server analyzes the data

[0817] The server analyzes the collected data.

[0818] 1. Financial Analysis:

[0819] The server uses the Pandas library to organize and process each company's financial statement data.

[0820] Input: Retrieved financial statement data

[0821] Output: Organized financial data (e.g. dataframes of sales, net profit, total assets)

[0822] 2. Evaluate your position in the industry:

[0823] The server uses the NumPy library to calculate each company's market share and growth rate.

[0824] Input: Organized financial data

[0825] Output: Market share and growth rate of each company

[0826] 3. Analysis of the relationship between stock prices and public opinion:

[0827] The server uses the TextBlob library to perform sentiment analysis on the collected news articles.

[0828] Input: Retrieved news article data

[0829] Output: Sentiment score (positive, negative, neutral)

[0830] Step 4: The server generates the report

[0831] The server generates a report based on the analysis results.

[0832] 1. Report Structure:

[0833] The server compiles reports on each company's financial situation, industry trends, each company's position in the market, and the relationship between stock prices and the companies.

[0834] Inputs: Analysis results (financial data, market share, sentiment scores)

[0835] Output: Draft report

[0836] 2. Visualization:

[0837] The server uses the Matplotlib and Seaborn libraries to visualize the data.

[0838] Input: Report Draft

[0839] Output: Final report including graphs and charts

[0840] Step 5: The server serves the report to the user

[0841] The server provides the generated report to the user.

[0842] 1. Report Format:

[0843] The server generates the report in PDF format and makes it available for user download.

[0844] Input: Final Report

[0845] Output: Report in PDF format

[0846] 2. Notice:

[0847] The server notifies the user when the report is complete.

[0848] Input: Report in PDF format

[0849] Output: Notification to user (e.g. email)

[0850] In this way, a user can quickly obtain detailed reports on a specific industry.

[0851] (Application example 2)

[0852] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[0853] Conventional systems have difficulty generating detailed reports on specific industries in a short time, and lack comprehensive analysis, especially including public opinion evaluations from stock price information. In addition, automation of report creation using generative AI models has not progressed, making it difficult for users to quickly grasp the overall picture of the industry.

[0854] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0855] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for making a public opinion assessment from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies related to a specific industry and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model. This allows a user to obtain a detailed report on a specific industry in a short time and perform a comprehensive analysis including public opinion assessment from stock price information.

[0856] "Means for specifying a company name or industry category" refers to an interface or function that allows a user to input or select a specific company name or industry category.

[0857] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that collects financial data on a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and its stock price, and generates reports based on this information.

[0858] "Means of evaluating public opinion from stock price information" refers to the function of analyzing stock price data and extracting and analyzing market reactions and public evaluations from that data.

[0859] "A means of analyzing financial statements, industry trends, a company's position within the industry, and the relationship between stock prices and companies in a specific industry, and generating reports" refers to the function of collecting and analyzing detailed data on a specific industry, and creating comprehensive reports based on the results.

[0860] "Means for generating prompt sentences for creating a report using a generative AI model" refers to a function for automatically generating appropriate prompt sentences to input into a generative AI model and creating a report using the prompt sentences.

[0861] A system for carrying out this invention has the following configuration: The server includes a means for designating a company name or industry genre, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies for a specific industry, and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model.

[0862] Program processing overview

[0863] 1. A way to specify a company name or industry

[0864] Users input or select a specific company name or industry category using a device such as a smartphone or PC. This information is sent to the server.

[0865] 2. Report Creation Method

[0866] The server collects financial statements, industry trends, industry standing, and the relationship between stock prices and companies for specified companies and industries. This is done using public databases and APIs on the Internet. The collected data is analyzed using data analysis tools such as Python and pandas.

[0867] 3. A means of assessing public opinion from stock price information

[0868] The server parses the stock price data and extracts market reactions and public valuations from it using a natural language processing model that uses Hugging Face's transformers library.

[0869] 4. Report Generation Methods

[0870] The server uses the collected and analyzed data to generate comprehensive reports about a particular industry, including company financials, industry trends, company positioning in the market, and company relationships with stock prices.

[0871] 5. Prompt Generation Method

[0872] The server automatically generates prompt sentences for creating a report using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report.

[0873] Examples

[0874] For example, if the user specifies the fashion industry, the following prompt sentence is generated:

[0875] Create a report on the financial statements of the fashion industry, industry trends, the position of each company in the industry, and the relationship between stock prices and companies. The report will include the financial status of each company, industry trends, the position of each company in the market, and the relationship between stock prices and companies. In addition, create a public opinion assessment from stock price information and add it to the report.

[0876] Based on this prompt, a generative AI model will create a report, allowing users to quickly get an overall picture of the fashion industry.

[0877] Hardware and Software Used

[0878] Hardware: Computer or smartphone with internet connection

[0879] Software: Python, requests, BeautifulSoup, pandas, transformers (Hugging Face)

[0880] In this way, users can quickly obtain detailed reports on specific industries and perform comprehensive analysis including public opinion assessments from stock price information.

[0881] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0882] Step 1:

[0883] The user uses the terminal to input or select a specific company name or industry category. The input information is sent to the server. The input data, which is the company name or industry category, is used for the next step of processing.

[0884] Step 2:

[0885] Based on the received company name and industry genre, the server collects data on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies from public databases and APIs on the Internet. The collected data is saved in JSON and CSV formats.

[0886] Step 3:

[0887] The server analyzes the collected data using data analysis tools such as Python and pandas. Specifically, it aggregates financial statement data, analyzes industry trends, evaluates the position of companies in the market, and analyzes the relationship between stock prices and companies. The input data is the collected raw data, and the output data is the analysis results.

[0888] Step 4:

[0889] The server analyzes the stock price data and extracts market reactions and public evaluations from the data using a natural language processing model using the Hugging Face transformers library. The input data is the stock price information and the output data is the result of the public evaluation.

[0890] Step 5:

[0891] The server generates a comprehensive report on a particular industry based on the analysis results and the opinion rating. The report includes the company's financial status, the industry trend, the company's position in the market, and the relationship between stock price and the company. The input data are the analysis results and the opinion rating, and the output data is the generated report.

[0892] Step 6:

[0893] The server automatically generates prompt sentences for creating reports using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report. The input data are the requirements for report generation, and the output data are the prompt sentences.

[0894] Step 7:

[0895] The server inputs the generated prompt sentences into the AI ​​model and creates a final report. The user can view this report through the terminal. The input data is the prompt sentences, and the output data is the final report.

[0896] In addition, 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.

[0897] "Example 1"

[0898] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the emotions of a user. When a user specifies a company name or industry genre through the system interface, this system collects data from publicly available company financial statements, industry statistical data, stock price information, etc., and analyzes the data. Then, a report is created on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Furthermore, information such as stock price fluctuations and trading volume is analyzed to estimate the company's evaluation. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the user's emotions and adjusts the display method and content of the report based on the emotion. For example, if the user shows an emotion of joy, the system displays positive information with emphasis. Conversely, if the user shows an emotion of anxiety or sadness, the system provides information that alleviates the emotion.

[0899] "Example 2"

[0900] Another embodiment of the present invention is a system in which an emotion engine adjusts the contents of a report based on the emotion of a user. When a user specifies the "automobile" industry, the system collects data from financial statements, industry statistics, stock price information, and other information related to the automobile industry, and analyzes the data. Then, a report is created on the financial statements, industry trends, the position in the industry, and the relationship between stock prices and companies in the automobile industry. Furthermore, information such as fluctuations in stock prices and trading volume related to the automobile industry is analyzed to estimate the evaluation of the companies. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the emotion of the user and adjusts the content of the report based on the emotion. For example, if the user shows excitement, the system highlights and displays positive information such as the launch of a new product or improved performance. Conversely, if the user shows anxiety, the system provides information on the stability of the industry and the reliability of the companies.

[0901] The process flow of each embodiment will be described below.

[0902] "Example 1"

[0903] Step 1: The user specifies the company name and industry genre through the system interface.

[0904] Step 2: Based on the specified company name and industry genre, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[0905] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[0906] Step 4: Analyze information such as stock price fluctuations and trading volume to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[0907] Step 5: The emotion engine recognizes the user's emotion and adjusts the presentation and content of the report based on that emotion.

[0908] "Example 2"

[0909] Step 1: The user specifies the "Automotive" industry.

[0910] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the specified "automotive" industry.

[0911] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[0912] Step 4: Analyze information such as stock price fluctuations and trading volume related to the automotive industry to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[0913] Step 5: The sentiment engine recognises the user's sentiment and adapts the report content based on that sentiment.

[0914] Example 1

[0915] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0916] In conventional corporate analysis systems, even if users specify a company name or industry, data collection and analysis are done manually, which is time-consuming and labor-intensive. In addition, reports are not adjusted based on public opinion from stock price information or user sentiment, making it difficult to provide useful information to users.

[0917] 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.

[0918] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for recognizing user emotions and adjusting the display method and contents of the report. This enables automatic collection and analysis of data, and makes it possible to provide useful information to users quickly and efficiently.

[0919] A "means for specifying a company name or industry category" is a device or software that provides an interface for a user to input or select a particular company name or industry category.

[0920] "Means for collecting data based on a specified company name or industry category" refers to a device or software that automatically obtains data related to a company name or industry category specified by a user from the Internet or a database.

[0921] "Means for analyzing collected data" refers to devices or software that organize the collected data and analyze it using statistical or machine learning methods.

[0922] A "means for creating a report based on the analysis results" is a device or software that automatically generates a report to be provided to a user based on the results of data analysis.

[0923] A "means for assessing public opinion from stock price information" is a device or software that analyzes information such as stock price fluctuations and trading volume, and estimates a company's evaluation and the market's reaction.

[0924] The "means for recognizing a user's emotions and adjusting the display method and contents of a report" refers to a device or software that analyzes a user's emotions and dynamically changes the display method and contents of a report in accordance with those emotions.

[0925] This invention is a system in which the server automatically collects data, analyzes it, and creates a report when the user selects a company name and industry category. It also has a function to evaluate public opinion from stock price information and adjust the display method and content of the report based on the user's feelings.

[0926] Hardware and Software Used

[0927] Hardware

[0928] Server: A central processing unit for data collection, analysis, reporting, and emotion recognition.

[0929] Terminal: The device (PC, smartphone, tablet, etc.) through which the user enters the company name and industry genre.

[0930] software

[0931] Interface: A GUI (Graphical User Interface) that allows users to specify company names and industry genres.

[0932] Data collection: Web scraping using Python's BeautifulSoup and Selenium, and stock quotes using the Yahoo Finance API.

[0933] Data Analysis: Use Python's Pandas and NumPy to organize the data and Scikit-learn to apply machine learning models.

[0934] Reporting: Generate reports using Python ReportLab or Jinja2.

[0935] Public opinion assessment: We use natural language processing techniques and machine learning algorithms to assess public opinion. Specifically, we use libraries such as NLTK, TensorFlow, and PyTorch.

[0936] Emotion Recognition: Analyze user emotions using Microsoft Azure's Emotion API and Google Cloud's Natural Language API.

[0937] Examples

[0938] Example 1: User specifies "ABC Corporation" and "IT industry"

[0939] A user opens the system interface using a terminal and selects "ABC Corporation" and the "IT industry." The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements for "ABC Corporation" and statistical data for the "IT industry," and obtains stock price information using the Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, and estimates public opinion for "ABC Corporation" using NLTK and TensorFlow, which it adds to the report.

[0940] Example 2: User specifies "XYZ Corporation" and "manufacturing industry" and emotion engine recognizes anxiety

[0941] The user opens the system interface using a terminal and selects "XYZ Corporation" and "Manufacturing". The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements of "XYZ Corporation" and statistical data of "Manufacturing", and obtains stock price information using Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, estimates public opinion evaluation of "XYZ Corporation" using NLTK and TensorFlow, and adds it to the report. As the emotion engine recognizes the user's anxiety, the server uses Microsoft Azure's Emotion API and Google Cloud's Natural Language API to analyze the user's emotions and provide information that will ease their anxiety.

[0942] Examples of prompt statements

[0943] "Collect ABC Corporation's financial statements, IT industry statistics, and stock price information, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, analyze stock price fluctuations and trading volume, estimate public opinion, and add it to the report."

[0944] "Please collect financial statements, manufacturing industry statistics, and stock price information for XYZ Corporation, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, please analyze stock price fluctuations and trading volume, estimate public opinion, and add this to the report. Users are feeling anxious, so please provide information that will ease their anxiety."

[0945] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0946] Step 1:

[0947] The user opens the system interface using a terminal and inputs the company name and industry category. The input information is sent to the server as text data of the company name and industry category.

[0948] Step 2:

[0949] The server collects data based on the company name and industry category specified by the user. Specifically, it uses Python's BeautifulSoup and Selenium to perform web scraping to obtain company financial statements and industry statistical data. It also obtains stock price information using the Yahoo Finance API. The input is text data of company names and industry categories, and the output is a dataset of financial statement data, industry statistical data, and stock price information.

[0950] Step 3:

[0951] The server analyzes the collected data. Specifically, it organizes the data using Python's Pandas and NumPy, and applies machine learning models using Scikit-learn. The input is a dataset of financial statement data, industry statistical data, and stock price information, and the output is a dataset of the analysis results. For example, the server performs specific operations such as "analyzing financial statement data to evaluate the financial situation of ABC Corporation" or "analyzing statistical data to understand trends in the IT industry."

[0952] Step 4:

[0953] The server creates reports based on the analysis results. Specifically, it generates reports using Python's ReportLab or Jinja2. The input is a dataset of the analysis results, and the output is a report to be provided to the user. For example, the server performs a specific operation such as "create a report summarizing the financial situation of ABC Corporation, trends in the IT industry, ABC Corporation's position within the industry, and the relationship between stock prices and companies."

[0954] Step 5:

[0955] The server analyzes information such as stock price fluctuations and trading volume to estimate the evaluation of the company. Specifically, it uses natural language processing technology and machine learning algorithms to perform public opinion evaluation. The input is a dataset of stock price information, and the output is a dataset of public opinion evaluation. For example, the server performs a specific operation such as "analyzing stock price fluctuation data and estimating public opinion evaluation of ABC Co., Ltd."

[0956] Step 6:

[0957] The server recognizes the user's emotions. Specifically, it analyzes the user's emotions using Microsoft Azure's Emotion API and Google Cloud's Natural Language API. The input is data such as the user's input, facial expressions, and tone of voice, and the output is the user's emotional data. For example, the server performs specific operations such as "recognizing emotions from the user's input, facial expressions, and tone of voice."

[0958] Step 7:

[0959] The server adjusts the display method and content of the report based on the user's emotions recognized by the emotion engine. The input is the user's emotion data and the report, and the output is the adjusted report. For example, if the user expresses emotions of joy, the server takes specific actions such as "displaying the report with positive information emphasized." Conversely, if the user expresses emotions of anxiety or sadness, the server takes specific actions such as "providing information that will ease anxiety."

[0960] (Application example 1)

[0961] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0962] In conventional corporate information analysis systems, even if the user specified a company name or industry, the system would only collect and analyze data such as financial statements, industry trends, and stock price information, and could not provide information based on the user's emotions. As a result, the system was unable to provide appropriate information based on the user's emotions, which led to an issue of poor user experience.

[0963] 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.

[0964] In this invention, the server includes a means for designating a company name and industry category, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and content of the report based on the user emotions, thereby making it possible to provide appropriate information according to the user's emotions.

[0965] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[0966] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that collects publicly available financial statements, industry trends, position within the industry, stock price information, etc. based on a specified company name or industry genre, analyzes them, and automatically generates reports.

[0967] "Means of evaluating public opinion from stock price information" is a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[0968] "Means of recognizing user emotions" refers to a function that analyzes emotions from text, voice, facial expressions, etc. entered by the user and recognizes those emotions.

[0969] The "means for adjusting the display method and contents of a report based on the user's emotions" is a function for dynamically changing the display method and contents of a report in response to the recognized emotions of a user.

[0970] As an embodiment of the present invention, the following system can be constructed.

[0971] The server includes a means for specifying a company name and industry category, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and contents of the report based on the user emotions.

[0972] Specifically, the server uses the following hardware and software.

[0973] Hardware: Servers, smartphones

[0974] Software: Python, requests, pandas, TextBlob, scikit-learn

[0975] The server first receives the company name and industry category entered by the user via smartphone. The server then collects publicly available company financial statements, industry statistics, stock price information, etc., and converts them into a data frame using pandas. This allows the server to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[0976] Additionally, the server uses TextBlob to analyze user sentiment and adjust the presentation and content of reports based on that sentiment. For example, if a user types, "I'm worried about the recent stock market movements," TextBlob can be used to analyze sentiment and, if negative sentiment is detected, the server will highlight information that requires attention.

[0977] As a concrete example, the following prompt sentence can be used:

[0978] Company Name: General company name

[0979] Emotional text: "I'm worried about the recent stock market movements."

[0980] When this prompt is entered into the server, the server collects financial data from companies and generates a report based on the user's emotions, allowing the user to obtain appropriate information according to their own emotions.

[0981] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0982] Step 1:

[0983] A user inputs a company name and an industry category using a terminal. The input company name and industry category are sent to a server. The input data is text information about the company name and industry category.

[0984] Step 2:

[0985] The server collects publicly available company financial statements, industry statistical data, stock price information, etc. based on the received company name and industry category. Specifically, the server obtains data using an API (e.g., Yahoo Finance API). The input data is the company name and industry category, and the output data is a data set including financial statements, industry statistical data, and stock price information.

[0986] Step 3:

[0987] The server converts the collected data into a data frame using pandas. The data converted into a data frame is used to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and companies. The input data is the collected raw data, and the output data is analyzable data in the data frame format.

[0988] Step 4:

[0989] The server uses TextBlob to analyze the sentiment from the user-entered text. Specifically, it passes the user-entered text to TextBlob and gets the sentiment score (positive or negative). The input data is the user's text and the output data is the sentiment score.

[0990] Step 5:

[0991] The server adjusts the presentation and content of the report based on the sentiment score, for example highlighting information that requires attention if negative sentiment is detected. The input data are sentiment scores and a data frame, and the output data is the adjusted report.

[0992] Step 6:

[0993] The server generates the reconciled report and sends it to the terminal, which displays the received report to the user, the input data being the reconciled report and the output data being the report displayed to the user.

[0994] Step 7:

[0995] The user can check the displayed report through the terminal and retrieve the information again by inputting additional company names and industry categories as necessary. The input data is the user's feedback and new company names and industry categories, and the output data is the updated report.

[0996] Example 2

[0997] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0998] Conventional industry analysis systems had the problem that it took a lot of time and effort for users to understand the overall picture of the industry. In addition, they could not fully meet the needs of users because they did not provide information according to their emotions. Furthermore, public opinion evaluation from stock price information was insufficient, and the evaluation of companies was not accurately reflected.

[0999] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for designating an industry, a means for collecting data, a means for analyzing data, a means for generating a report, a means for public opinion evaluation, a means for recognizing emotions and adjusting the report, and a means for providing the report. This allows the user to grasp the overall picture of the industry in a short time, and information is provided according to the user's emotions, so that the user's needs can be met. In addition, an accurate public opinion evaluation is performed based on stock price information, and the evaluation of the company is accurately reflected.

[1000] The "means for specifying an industry" is an interface that allows the user to select or input the industry in which he or she is interested.

[1001] "Means of collecting data" refers to the function of obtaining information related to the specified industry from the Internet or databases.

[1002] "Means for analyzing data" refers to a function for organizing collected data and analyzing it using statistical or machine learning methods.

[1003] The "means for generating a report" is a function for creating a report to be provided to a user based on the analysis results.

[1004] "Means of evaluating public opinion" refers to a function that analyzes stock price information and market reactions to estimate a company's valuation.

[1005] The "means for recognizing emotions and adjusting reports" is a function for detecting the emotions of a user and adjusting the contents of a report in accordance with the emotions.

[1006] The "means for providing a report" is a function for displaying or transmitting a generated report to a user.

[1007] The present invention is a system in which a user specifies an industry, and a server collects data, analyzes data, generates reports, evaluates public opinion, recognizes emotions, and provides reports. A specific embodiment of this system is described below.

[1008] 1. Means of specifying industry

[1009] A user uses a terminal to access the system and specify the industry he or she is interested in. For example, the user opens a browser, accesses the system's web page, enters "automotive" in the search box, and clicks the search button. This action sends the user's specification to the server.

[1010] 2. How we collect data

[1011] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[1012] Use the Yahoo Finance API to collect company financial statements.

[1013] Use the Google Finance API to get stock price data for the past year.

[1014] 3. How to analyze the data

[1015] The server analyzes the collected data. Specifically, it uses the following libraries:

[1016] Use Pandas to organize financial data for each company.

[1017] Analyzing industry trends using NumPy.

[1018] 4. How to generate reports

[1019] The server generates a report based on the analysis results. It uses a generative AI model (e.g., OpenAI's GPT-4) to create a report like the one below.

[1020] Automotive Industry Report:

[1021] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1022] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1023] Company A has a strong position in the market and its stock price is stable.

[1024] 5. Means of assessing public opinion

[1025] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[1026] Analyze stock price fluctuations and rate Company A as "high."

[1027] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[1028] 6. How to recognize emotions and adjust reports

[1029] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[1030] If users are excited, highlight information about a new product launch or business improvement.

[1031] If users express concern, provide information about industry stability and company trustworthiness.

[1032] 7. Means of Providing Reports

[1033] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[1034] Examples of concrete examples and prompts

[1035] As a specific example, the process when the user specifies the "automobile" industry is shown below.

[1036] Data collection:

[1037] The server collects financial statements of Company A, Company B, and Company C using the Yahoo Finance API.

[1038] Use the Google Finance API to get stock price data for the past year.

[1039] Data Analysis:

[1040] The server uses Pandas to organize each company's financial data and NumPy to analyze industry trends.

[1041] Report Generation:

[1042] The server uses GPT-4 to generate a report like this:

[1043] Automotive Industry Report:

[1044] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1045] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1046] Company A has a strong position in the market and its stock price is stable.

[1047] Adding public opinion ratings:

[1048] The server analyzes the fluctuations in stock prices and rates Company A as "high."

[1049] Emotion Recognition and Report Adjustment:

[1050] The server highlights information about new product launches or business improvements if the user is excited about them.

[1051] Conversely, if users express concern, provide information about industry stability and company trustworthiness.

[1052] Example prompt:

[1053] Please create a report on the "Automobile" industry. Please include the financial statements of Company A, Company B, and Company C, industry trends, the market position of each company, and the relationship between stock prices and the companies. Also, please make a public opinion assessment from stock price information and add it to the report.

[1054] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1055] Step 1:

[1056] The user specifies the industry.

[1057] The user opens a browser on the terminal and accesses the system's web page. The user enters "car" in the search box and clicks the search button. This operation sends the user's specification to the server.

[1058] Input: A user-specified industry (e.g. "Automotive")

[1059] Output: Industry-specific information sent to the server

[1060] Step 2:

[1061] The server collects the data.

[1062] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[1063] Use the Yahoo Finance API to collect company financial statements.

[1064] Use the Google Finance API to get stock price data for the past year.

[1065] Input: Industry-specific information

[1066] Output: Collected company financial statements and stock price data

[1067] Step 3:

[1068] The server analyzes the data.

[1069] The server analyzes the collected data. Specifically, it uses the following libraries:

[1070] Use Pandas to organize financial data for each company.

[1071] Analyzing industry trends using NumPy.

[1072] Input: Collected company financial statements and stock price data

[1073] Output: Organized financial data and industry trend analysis

[1074] Step 4:

[1075] The server generates the report.

[1076] The server generates a report based on the analysis results. It uses a generative AI model (e.g., OpenAI's GPT-4) to create a report like the one below.

[1077] Automotive Industry Report:

[1078] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1079] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1080] Company A has a strong position in the market and its stock price is stable.

[1081] Input: Organized financial data and industry trend analysis results

[1082] Output: Generated report

[1083] Step 5:

[1084] The server adds a public opinion rating.

[1085] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[1086] Analyze stock price fluctuations and rate Company A as "high."

[1087] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[1088] Input: Stock price data

[1089] Output: Report with opinion ratings added

[1090] Step 6:

[1091] The server performs emotion recognition and adjusts the reports.

[1092] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[1093] If users are excited, highlight information about a new product launch or business improvement.

[1094] If users express concern, provide information about industry stability and company trustworthiness.

[1095] Input: User emotion data

[1096] Output: Reconciled report

[1097] Step 7:

[1098] The server provides the report to the user.

[1099] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[1100] Input: Reconciled report

[1101] Output: Report provided to the user

[1102] (Application example 2)

[1103] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1104] Conventional industry report creation systems lacked the ability to adjust report content based on user sentiment, making it difficult to provide information that meets user needs. In addition, report generation and prompt sentence generation were not performed using generative AI models, which led to problems with the quality of reports and user experience not improving.

[1105] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1106] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the content of the report based on the emotions, a means for generating a report using a generative AI model, and a means for generating a prompt sentence. This makes it possible to provide a report customized according to the user's emotions, and realizes high-quality report generation and prompt sentence generation using a generative AI model.

[1107] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[1108] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that analyzes financial data for a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and information, and synthesizes this information to generate a report.

[1109] "Means of evaluating public opinion from stock price information" refers to a function that analyzes stock price data, extracts market reactions and public evaluations, and evaluates public opinion toward companies and industries.

[1110] "Means for recognizing a user's emotions and adjusting the contents of the report based on those emotions" is a function for analyzing a user's emotions and dynamically changing the contents of the report in accordance with those emotions.

[1111] A "means for generating reports using a generative AI model" is a function that uses an artificial intelligence model to automatically generate detailed reports on specified industries or companies.

[1112] A "means for generating a prompt sentence" is a function for automatically creating an appropriate prompt sentence to input to a generative AI model.

[1113] A system for carrying out the present invention includes a server, a user terminal, and a generative AI model. The server includes a means for specifying a company name and industry genre, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the contents of the report based on the emotions, a means for generating a report using the generative AI model, and a means for generating prompt sentences.

[1114] Hardware and Software Configuration

[1115] Hardware: Server, user terminal (smartphone, head-mounted display)

[1116] Software: Python, Requests library, Pandas library, TextBlob library

[1117] Data processing and calculation

[1118] 1. Specify your company name and industry:

[1119] The user terminal provides an interface for the user to input or select a particular company name or industry category. The information input by the user is transmitted to the server.

[1120] 2. Data Collection and Reporting:

[1121] The server collects financial data on specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The collected data is organized and analyzed using the Pandas library, and a report is generated.

[1122] 3. Public opinion assessment:

[1123] The server analyzes the stock price data and extracts market reactions and public evaluations. Using the TextBlob library, we perform sentiment analysis of the text data obtained from stock price information and perform public opinion evaluation.

[1124] 4. Emotion recognition and report adjustment:

[1125] The user terminal provides an interface for recognizing the user's emotions, and the user's emotion data is transmitted to the server, which dynamically adjusts the report content based on the emotions.

[1126] 5. Report generation using generative AI models:

[1127] The server uses the generative AI model to automatically generate detailed reports on the specified industry or company by generating prompt sentences and inputting them into the generative AI model.

[1128] 6. Prompt generation:

[1129] The server automatically creates appropriate prompt sentences to input to the generative AI model. For example, create a report on financial statements, industry trends, corporate positions, and the relationship between stock prices and companies in the "automotive" industry. If the user's sentiment is positive, highlight positive information such as new product launches and improved performance, and if it is negative, provide information on industry stability and company reliability.

[1130] Examples

[1131] If the user specifies the “Automotive” industry and the sentiment engine determines the user’s sentiment to be positive, a report like the one below will be generated.

[1132] Industry: Automotive

[1133] Financial Statement: Financial Statement for Q1 2023

[1134] Industry Trend: Electric vehicles are on the rise

[1135] Company position: Major automakers hold top market share

[1136] Stock prices and companies: Major automakers' stock prices are rising

[1137] Positive news: new product launches and improving performance

[1138] In this way, it becomes possible to provide customized reports based on the user's emotions, and high-quality report generation and prompt generation can be achieved by utilizing generative AI models.

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

[1140] Step 1:

[1141] The user terminal provides an interface for the user to input or select a particular company name or industry category. The company name or industry category input by the user is sent to the server. The input data is the text information of the company name or industry category. The output is the text information of the company name or industry category sent to the server.

[1142] Step 2:

[1143] The server collects financial data for specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The input data is text information on company names and industry genres. The server uses the Requests library to obtain data from the API, and organizes and analyzes the data using the Pandas library. The output is organized and analyzed financial data, industry trends, the company's position in the market, and the relationship between stock prices and companies.

[1144] Step 3:

[1145] The server analyzes stock price data and extracts market reactions and public evaluations. The input data is stock price information obtained from the API. The server uses the TextBlob library to perform sentiment analysis of the text data obtained from the stock price information and perform public opinion evaluation. The output is public opinion evaluation data including the sentiment analysis results.

[1146] Step 4:

[1147] The user terminal provides an interface for recognizing the user's emotions. The user's emotion data is transmitted to the server. The input data is text information or sensor data indicating the user's emotions. The output is the user's emotion data transmitted to the server.

[1148] Step 5:

[1149] The server dynamically adjusts the report content based on the user's emotion data. The input data are the user's emotion data and the data obtained in steps 2 and 3. If the user's emotion is positive, the server emphasizes positive information, and if the user's emotion is negative, it emphasizes information about stability and reliability. The output is report data adjusted according to the user's emotion.

[1150] Step 6:

[1151] The server uses the generative AI model to automatically generate a detailed report on the specified industry or company. The input data are the data obtained in step 2 and step 3 and the prompt sentence. The server inputs the prompt sentence into the generative AI model and generates a report. The output is the generated report.

[1152] Step 7:

[1153] The server automatically creates appropriate prompt sentences to input to the generative AI model. The input data is text information on the company name and industry genre specified by the user. The server generates the prompt sentences and inputs them into the generative AI model. The output is the generated prompt sentence.

[1154] As a specific example, if a user specifies the "automobile" industry and the emotion engine determines that the user's emotion is positive, the following prompt sentence is generated:

[1155] Create a report on financial statements, industry trends, company positions, and company relationships for the "Automotive" industry. If user sentiment is positive, highlight positive information such as new product launches and improving performance. If sentiment is negative, provide information about industry stability and company reliability.

[1156] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1157] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1158] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1159] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1160] [Third embodiment]

[1161] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1162] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1163] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1164] 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.

[1165] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1166] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[1167] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1168] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1169] 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.

[1170] 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.

[1171] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1172] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1173] "Example 1"

[1174] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. It analyzes information such as stock price fluctuations and trading volume to estimate a company's valuation.

[1175] "Example 2"

[1176] As a specific example, if a user specifies the "automobile" industry, the system will create a report on the automobile industry's financial statements, industry trends, position within the industry, and the relationship between stock prices and companies. The report includes each company's financial status, industry trends, each company's position within the market, and the relationship between stock prices and companies. In addition, the system will perform public opinion evaluation from stock price information and add it to the report. This allows users to quickly grasp the overall picture of the automobile industry.

[1177] The process flow of each embodiment will be described below.

[1178] "Example 1"

[1179] Step 1: The user specifies the company name and industry genre through the system interface.

[1180] Step 2: Based on the specified company name and industry category, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[1181] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[1182] Step 4: Further, information such as stock price fluctuations and trading volume is analyzed to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[1183] "Example 2"

[1184] Step 1: The user specifies the "Automotive" industry.

[1185] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the automotive industry.

[1186] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[1187] Step 4: Further, information such as stock price fluctuations and trading volume related to the automotive industry is analyzed to estimate the valuation of the companies. This valuation is added to the report as a public opinion rating.

[1188] Example 1

[1189] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1190] Conventional corporate analysis systems had the problem that even if a user specified a company name or industry, it took a lot of time and effort to collect, process, and analyze the necessary data. In addition, there was a lack of automated means to evaluate public opinion from stock price information, so users had to perform the evaluation manually. This made it difficult to create reports quickly and accurately.

[1191] 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.

[1192] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for processing and analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for providing the created report. This makes it possible for a user to simply designate a company name and an industry category, and quickly and accurately create and provide a report including the company's financial situation, industry trends, the company's position in the market, the relationship between stock price and the company, and evaluation of public opinion.

[1193] The "means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[1194] "Means of collecting data based on a specified company name or industry genre" refers to a function for obtaining data related to a company name or industry genre specified by a user from an external database or API.

[1195] "Means for processing and analyzing collected data" refers to the function of organizing collected data, extracting necessary information, and analyzing it.

[1196] The "means for creating a report based on the analysis results" is a function for automatically generating a report to be provided to a user based on the analyzed data.

[1197] "Means of assessing public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate the market's evaluation and public opinion of a company.

[1198] The "means for providing a generated report" refers to a function for providing a generated report to a user, and includes provision in PDF format or Web page format.

[1199] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. This involves analyzing information such as stock price fluctuations and trading volume, and estimating a company's valuation.

[1200] Hardware and Software Used

[1201] Hardware

[1202] Server: A central processing unit for data collection, processing, analysis, and report generation.

[1203] Terminal: The device through which the user operates the interface (e.g. PC, smartphone)

[1204] software

[1205] Web browser: Provides an interface for users to enter company names and industry categories

[1206] API: Access to external databases and services for data collection (e.g. EDGAR database, Statista, Yahoo Finance API)

[1207] Template engine: a tool for formatting collected and analyzed data into reports

[1208] Data analysis tools: Software for processing and analyzing collected data (e.g. Python, R)

[1209] Data processing and calculation

[1210] The server collects the necessary information from the following data sources based on the company name and industry genre specified by the user.

[1211] Public company financial statements (e.g., EDGAR database)

[1212] Industry statistics (e.g. Statista)

[1213] Stock quotes (e.g. Yahoo Finance API)

[1214] The collected data will be processed and analyzed as follows:

[1215] Analyze financial statement data to evaluate a company's financial position, for example by calculating indicators such as sales, net profit, and debt ratio.

[1216] Use industry statistics to analyze industry trends, for example, to calculate overall industry growth rates and market shares.

[1217] Analyze stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[1218] Analyze stock price fluctuations and trading volume to estimate public opinion. For example, identify the causes of sudden increases or decreases in stock prices.

[1219] Examples

[1220] Example 1: When specifying a company name

[1221] The user specifies "specific company." The server performs the following process:

[1222] 1. The user enters "specific company" into the web form and clicks the submit button.

[1223] 2. The server retrieves the latest financial statements for a particular company from the EDGAR database.

[1224] 3. The server retrieves the latest statistical data for a specific industry from Statista.

[1225] 4. The server retrieves stock price information for a specific company from the Yahoo Finance API.

[1226] 5. The server analyzes the collected data and creates a report that includes the specific company's financial status, industry trends, its position within the industry, the company's relationship with its stock price, and public opinion.

[1227] 6. The server generates the report in PDF format and provides a download link to the user.

[1228] Example 2: When specifying an industry genre

[1229] The user specifies "specific industry." The server performs the following process:

[1230] 1. A user enters "specific industry" into a web form and clicks the submit button.

[1231] 2. The server retrieves the latest statistical data for a specific industry from Statista.

[1232] 3. The server retrieves stock price information for major companies in a specific industry from the Yahoo Finance API.

[1233] 4. The server analyzes the collected data and creates reports that include trends in a particular industry, the position of major companies within the industry, the relationship between stock prices and companies, and public opinion ratings.

[1234] 5. The server generates the report in the form of a web page and displays it to the user.

[1235] Examples of prompt statements

[1236] Example 1: Prompt statement specifying company name

[1237] "Create a report that includes a specific company's latest financials, industry trends, where it stands within the industry, the company's stock price relationship, and public opinion ratings."

[1238] Example 2: Prompt statement specifying industry genre

[1239] "Create a report that includes the latest trends in a particular industry, where major companies stand in the industry, stock price-company relationships, and public opinion ratings."

[1240] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1241] Step 1: User specifies company name and industry category

[1242] A user uses an interface to input a company name and industry category through a web browser or mobile application. For example, the user inputs "specific company" and clicks the submit button. The input data is sent to the server.

[1243] Input: Company name or industry

[1244] Output: The input data sent to the server.

[1245] Step 2: The server collects the data

[1246] The server collects the necessary information from the following data sources based on the company name and industry genre received from the user.

[1247] The server accesses the EDGAR database to retrieve the most recent financial statements for the specified companies.

[1248] The server accesses Statista and retrieves the latest statistical data for the specified industry.

[1249] The server uses the Yahoo Finance API to retrieve stock quotes for the specified companies.

[1250] Input: User-specified company name or industry

[1251] Output: Collected financial statement data, industry statistics, stock price information

[1252] Step 3: The server processes and analyzes the data

[1253] The server processes and analyzes the collected data as follows:

[1254] The server analyzes the financial statement data and evaluates the company's financial condition, for example calculating metrics such as sales, net profit, and debt ratio.

[1255] The server uses industry statistics to analyze industry trends, for example to calculate industry-wide growth rates and market shares.

[1256] The server analyzes stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[1257] The server analyzes stock price fluctuations and trading volume to estimate public opinion, for example by identifying the causes of sudden increases or decreases in stock prices.

[1258] Input: Collected financial statement data, industry statistics, stock price information

[1259] Output: Company financial status, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[1260] Step 4: The server creates the report

[1261] The server automatically generates a report to provide to the user based on the results of the above analysis. The report includes the following:

[1262] Company financial status (e.g. sales, net profit, debt ratio)

[1263] Industry trends (e.g. industry-wide growth rates, market shares)

[1264] Position in the industry (e.g., compared to competitors)

[1265] Relationship between stock prices and companies (e.g. stock price fluctuations, trading volume)

[1266] Public opinion assessment (e.g., reasons for sudden rises and falls in stock prices)

[1267] Input: Company financials, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[1268] Output: Generated report

[1269] Step 5: The server serves the report

[1270] The server then provides the generated report to the user, either in PDF format or as a web page, for example with a link that allows the user to download the report.

[1271] Input: Generated report

[1272] Output: Report provided to user (in PDF or web page format)

[1273] (Application example 1)

[1274] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1275] In conventional corporate analysis systems, even if a user specified a company name or industry, financial statements, industry trends, stock price information, etc. had to be individually collected and analyzed manually. This took time and effort, making it difficult to make quick decisions. In addition, there was a lack of automated means to evaluate public opinion from stock price information, making it impossible to efficiently obtain information that could be used as a reference for investment decisions.

[1276] 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. In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, a position in the industry, and a relationship between stock prices and a company, a means for evaluating public opinion from stock price information, a means for providing a report through an application installed on a smartphone, and a means for automatically generating a report using a generative AI model. This enables a user to quickly and efficiently grasp a company's financial situation, industry trends, a company's position in the market, and a relationship between stock prices and a company, and to obtain information that can be used as a reference for investment decisions.

[1277] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[1278] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that automatically generates reports by analyzing related financial statements, industry trends, position within the industry, and the relationship between a company and stock prices based on a specified company name and industry genre.

[1279] "Means of evaluating public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[1280] "Means for providing a report through an application installed on a smartphone" refers to a function for providing a generated report to a user through a smartphone application.

[1281] "Means for automatically generating reports using a generative AI model" means a function that uses an artificial intelligence model to automatically generate reports based on collected data.

[1282] As an embodiment of the present invention, the following system is constructed.

[1283] System Configuration

[1284] The system consists of a smartphone application that allows users to specify company names and industry genres, a server that collects and analyzes data, and a back-end system that automatically generates reports using generative AI models.

[1285] Hardware and Software Used

[1286] Hardware: Smartphone (iOS or Android)

[1287] software:

[1288] Python: Data Processing and Analysis

[1289] Pandas: Dataframe Operations

[1290] BeautifulSoup: Web scraping

[1291] Scikit-learn: Machine learning models

[1292] TensorFlow: Generative AI Models

[1293] Flask: Backend API

[1294] Processing flow

[1295] 1. User Interface:

[1296] Users enter company names and industry categories through a smartphone application.

[1297] For example, the user specifies "Automobile Manufacturer A" and the "Automobile Industry."

[1298] 2. Data collection:

[1299] The server uses BeautifulSoup to scrape financial statements, industry statistics, and stock quotes from the web for specified companies.

[1300] Use Pandas to organize and consolidate the collected data.

[1301] 3. Data Analysis:

[1302] The server uses Scikit-learn to build a model for deriving public opinion from stock price information.

[1303] Use TensorFlow to automatically generate reports using generative AI models.

[1304] 4. Report Generation:

[1305] Based on the collected and analyzed data, the server generates reports on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company.

[1306] The generated reports are provided to the user via a smartphone application.

[1307] Examples

[1308] If the user specifies "Automobile manufacturer A" and the "Automobile industry", the server will collect the latest financial statements, industry statistical data, and stock price information of Automobile manufacturer A, and will evaluate public opinion based on Automobile manufacturer A's position in the industry and fluctuations in its stock price. Finally, a report based on this information will be generated and provided to the user.

[1309] Examples of prompt statements

[1310] Company Name: Automobile Manufacturer A

[1311] Industry: Automotive industry

[1312] By entering this prompt, the system will generate a detailed report on car manufacturer A.

[1313] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1314] Step 1:

[1315] The user starts the smartphone application and inputs the company name and industry category. For example, they specify "Automobile Manufacturer A" and "Automobile Industry". The input data is sent to the server.

[1316] Step 2:

[1317] Based on the received company names and industry categories, the server uses BeautifulSoup to scrape relevant financial statements, industry statistics, and stock quotes from the web. The input is the company name and industry category, and the output is the collected raw data.

[1318] Step 3:

[1319] The server uses Pandas to organize and consolidate the collected raw data, creating a data frame, imputing missing values, and normalizing the data. The input is the scraped raw data, and the output is the organized and consolidated data frame.

[1320] Step 4:

[1321] The server uses Scikit-learn to build a machine learning model for public opinion evaluation from stock price information. The input is a cleaned and integrated data frame, and the output is a public opinion evaluation model. Specifically, the server uses stock price fluctuations and trading volume as features to estimate the evaluation of a company.

[1322] Step 5:

[1323] The server uses TensorFlow to automatically generate reports using generative AI models. The input is a data frame organized and integrated with the public opinion evaluation model, and the output is an automatically generated report. Specifically, it generates a report that includes the company's financial status, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[1324] Step 6:

[1325] The server provides the generated report to the user through the smartphone application. The input is the automatically generated report, and the output is the report displayed on the user's smartphone screen. This allows the user to quickly and efficiently obtain detailed information about the company.

[1326] Example 2

[1327] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1328] In the conventional system, it took a lot of time and effort to create detailed reports on a specific industry. In addition, each step of data collection, analysis, and report generation was often done manually, which was inefficient. In addition, there was a lack of means to evaluate public opinion from stock price information, making it difficult to accurately grasp a company's market position and industry trends.

[1329] 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.

[1330] In this invention, the server includes a means for designating an industry, a means for creating reports on financial data, industry trends, a company's position in the market, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for collecting data, a means for analyzing data, a means for generating reports, and a means for providing reports, thereby making it possible to automatically generate detailed reports on an industry designated by a user and provide them in a short time.

[1331] The "means for specifying an industry" is a function that provides an interface for the user to select or input a specific industry.

[1332] "Financial data" refers to economic indicators such as sales, net profit, and total assets included in a company's financial statements and financial reports.

[1333] "Industry trends" refers to information that indicates the latest developments and market changes within a particular industry.

[1334] "A company's market position" refers to information that indicates the position of a particular company within its industry, including market share and growth rate.

[1335] "The relationship between stock prices and companies" is information that shows how a company's stock price is related to the company's financial situation and market valuation.

[1336] The "means for creating a report" is a function for generating a report to be provided to a user based on collected and analyzed data.

[1337] "Means of evaluating public opinion from stock price information" is a function that analyzes market reactions and public evaluations based on stock price data, and evaluates public opinion.

[1338] "Means of collecting data" means the ability to obtain data related to the specified industry from external data sources, for example, using an API to obtain data.

[1339] "Means of analyzing data" refers to the function of organizing and processing collected data and calculating necessary indicators. Examples include financial data analysis and sentiment analysis.

[1340] "Means for generating reports" refers to a function for creating visually easy-to-understand reports based on analysis results, for example using graphs and charts.

[1341] The "means for providing a report" is a function for providing a generated report to a user, for example, by making the report downloadable in PDF format.

[1342] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1343] The present invention is a system for automatically generating and providing a detailed report on a particular industry when the user designates the industry. A specific embodiment of this system will be described below.

[1344] 1. System Configuration

[1345] The system consists of the following main components:

[1346] User terminal: A device that provides an interface for a user to specify an industry. For example, a PC or smartphone.

[1347] Server: The central component responsible for data collection, analysis, and report generation. Developed using Python.

[1348] External Data Sources: APIs and databases used to collect data. Examples include Yahoo Finance API, Google Finance API, NewsAPI, etc.

[1349] 2. Hardware and Software Used

[1350] Hardware: The server is a computer equipped with a powerful processor and sufficient memory. The user terminal is a general-purpose PC or smartphone.

[1351] Software: The server is developed using Python and uses the following libraries and tools:

[1352] Pandas: Used to organize and process data.

[1353] NumPy: Used for numerical calculations.

[1354] TextBlob: Used for sentiment analysis.

[1355] Matplotlib and Seaborn for data visualization.

[1356] API Client: Used to retrieve data from external data sources such as Yahoo Finance API, Google Finance API, NewsAPI, etc.

[1357] 3. Data collection and analysis

[1358] The server collects data related to the industry specified by the user from external data sources. For example, if the user specifies "automotive industry," the server collects the following data:

[1359] Financial Statement Data: Use the Yahoo Finance API to obtain financial statement data for major companies in the automotive industry.

[1360] Stock quotes: Uses the Google Finance API to get the latest stock quotes for each company.

[1361] Industry Trends: Use NewsAPI to gather the latest news articles related to the automotive industry.

[1362] The collected data is organized and processed using Pandas and NumPy. For example, metrics such as sales, net profit, and total assets for each company are calculated and stored in a data frame. TextBlob is also used to perform sentiment analysis on news articles and calculate positive, negative, and neutral sentiment scores.

[1363] 4. Generate and provide reports

[1364] The server generates a report based on the analysis results. The report includes the financial status of each company, industry trends, each company's position in the market, and the relationship between stock prices and companies. Matplotlib and Seaborn are used to visualize the data and create graphs and charts. The generated report is saved in PDF format and made available for users to download.

[1365] 5. Examples and prompts

[1366] As a specific example, the prompt sentence when the user specifies "automobile industry" is shown below.

[1367] "Please prepare reports on financial statements of the automotive industry, industry trends, standing within the industry, and the relationship between stock prices and companies."

[1368] By using this prompt, the user can quickly get an overview of the automotive industry.

[1369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1370] Program processing flow

[1371] Step 1: User specifies industry

[1372] The user specifies the industry he or she is interested in through the terminal interface, for example, by inputting "automotive industry." The input industry information is sent to the server.

[1373] Input: User-specified industry (e.g. "Automotive Industry")

[1374] Output: Industry information sent to the server

[1375] Step 2: The server collects the data

[1376] The server collects data related to the specified industry from external data sources.

[1377] 1. Collection of financial statements:

[1378] The server uses the Yahoo Finance API to retrieve financial statement data for major companies.

[1379] Input: Industry information, company list

[1380] Output: Acquired financial statement data (e.g. sales, net profit, total assets)

[1381] 2. Collecting stock quotes:

[1382] The server uses the Google Finance API to obtain the latest stock quotes for each company.

[1383] Input: Industry information, company list

[1384] Output: Retrieved stock price data

[1385] 3. Collect industry trends:

[1386] The server uses the NewsAPI to collect the latest news articles related to the industry.

[1387] Input: Industry information, keywords

[1388] Output: Retrieved news article data

[1389] Step 3: The server analyzes the data

[1390] The server analyzes the collected data.

[1391] 1. Financial Analysis:

[1392] The server uses the Pandas library to organize and process each company's financial statement data.

[1393] Input: Retrieved financial statement data

[1394] Output: Organized financial data (e.g. dataframes of sales, net profit, total assets)

[1395] 2. Evaluate your position in the industry:

[1396] The server uses the NumPy library to calculate each company's market share and growth rate.

[1397] Input: Organized financial data

[1398] Output: Market share and growth rate of each company

[1399] 3. Analysis of the relationship between stock prices and public opinion:

[1400] The server uses the TextBlob library to perform sentiment analysis on the collected news articles.

[1401] Input: Retrieved news article data

[1402] Output: Sentiment score (positive, negative, neutral)

[1403] Step 4: The server generates the report

[1404] The server generates a report based on the analysis results.

[1405] 1. Report Structure:

[1406] The server compiles reports on each company's financial situation, industry trends, each company's position in the market, and the relationship between stock prices and the companies.

[1407] Inputs: Analysis results (financial data, market share, sentiment scores)

[1408] Output: Draft report

[1409] 2. Visualization:

[1410] The server uses the Matplotlib and Seaborn libraries to visualize the data.

[1411] Input: Report Draft

[1412] Output: Final report including graphs and charts

[1413] Step 5: The server serves the report to the user

[1414] The server provides the generated report to the user.

[1415] 1. Report Format:

[1416] The server generates the report in PDF format and makes it available for user download.

[1417] Input: Final Report

[1418] Output: Report in PDF format

[1419] 2. Notice:

[1420] The server notifies the user when the report is complete.

[1421] Input: Report in PDF format

[1422] Output: Notification to user (e.g. email)

[1423] In this way, a user can quickly obtain detailed reports on a specific industry.

[1424] (Application example 2)

[1425] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1426] Conventional systems have difficulty generating detailed reports on specific industries in a short time, and lack comprehensive analysis, especially including public opinion evaluations from stock price information. In addition, automation of report creation using generative AI models has not progressed, making it difficult for users to quickly grasp the overall picture of the industry.

[1427] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1428] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for making a public opinion assessment from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies related to a specific industry and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model. This allows a user to obtain a detailed report on a specific industry in a short time and perform a comprehensive analysis including public opinion assessment from stock price information.

[1429] "Means for specifying a company name or industry category" refers to an interface or function that allows a user to input or select a specific company name or industry category.

[1430] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that collects financial data on a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and its stock price, and generates reports based on this information.

[1431] "Means of evaluating public opinion from stock price information" refers to the function of analyzing stock price data and extracting and analyzing market reactions and public evaluations from that data.

[1432] "A means of analyzing financial statements, industry trends, a company's position within the industry, and the relationship between stock prices and companies in a specific industry, and generating reports" refers to the function of collecting and analyzing detailed data on a specific industry, and creating comprehensive reports based on the results.

[1433] "Means for generating prompt sentences for creating a report using a generative AI model" refers to a function for automatically generating appropriate prompt sentences to input into a generative AI model and creating a report using the prompt sentences.

[1434] A system for carrying out this invention has the following configuration: The server includes a means for designating a company name or industry genre, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for analyzing financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies for a specific industry, and generating a report, and a means for generating a prompt sentence for creating a report using a generative AI model.

[1435] Program processing overview

[1436] 1. A way to specify a company name or industry

[1437] Users input or select a specific company name or industry category using a device such as a smartphone or PC. This information is sent to the server.

[1438] 2. Report Creation Method

[1439] The server collects financial statements, industry trends, industry standing, and the relationship between stock prices and companies for specified companies and industries. This is done using public databases and APIs on the Internet. The collected data is analyzed using data analysis tools such as Python and pandas.

[1440] 3. A means of assessing public opinion from stock price information

[1441] The server parses the stock price data and extracts market reactions and public valuations from it using a natural language processing model that uses Hugging Face's transformers library.

[1442] 4. Report Generation Methods

[1443] The server uses the collected and analyzed data to generate comprehensive reports about a particular industry, including company financials, industry trends, company positioning in the market, and company relationships with stock prices.

[1444] 5. Prompt Generation Method

[1445] The server automatically generates prompt sentences for creating a report using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report.

[1446] Examples

[1447] For example, if the user specifies the fashion industry, the following prompt sentence is generated:

[1448] Create a report on the financial statements of the fashion industry, industry trends, the position of each company in the industry, and the relationship between stock prices and companies. The report will include the financial status of each company, industry trends, the position of each company in the market, and the relationship between stock prices and companies. In addition, create a public opinion assessment from stock price information and add it to the report.

[1449] Based on this prompt, a generative AI model will create a report, allowing users to quickly get an overall picture of the fashion industry.

[1450] Hardware and Software Used

[1451] Hardware: Computer or smartphone with internet connection

[1452] Software: Python, requests, BeautifulSoup, pandas, transformers (Hugging Face)

[1453] In this way, users can quickly obtain detailed reports on specific industries and perform comprehensive analysis including public opinion assessments from stock price information.

[1454] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1455] Step 1:

[1456] The user uses the terminal to input or select a specific company name or industry category. The input information is sent to the server. The input data, which is the company name or industry category, is used for the next step of processing.

[1457] Step 2:

[1458] Based on the received company name and industry genre, the server collects data on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies from public databases and APIs on the Internet. The collected data is saved in JSON and CSV formats.

[1459] Step 3:

[1460] The server analyzes the collected data using data analysis tools such as Python and pandas. Specifically, it aggregates financial statement data, analyzes industry trends, evaluates the position of companies in the market, and analyzes the relationship between stock prices and companies. The input data is the collected raw data, and the output data is the analysis results.

[1461] Step 4:

[1462] The server analyzes the stock price data and extracts market reactions and public evaluations from the data using a natural language processing model using the Hugging Face transformers library. The input data is the stock price information and the output data is the result of the public evaluation.

[1463] Step 5:

[1464] The server generates a comprehensive report on a particular industry based on the analysis results and the opinion rating. The report includes the company's financial status, the industry trend, the company's position in the market, and the relationship between stock price and the company. The input data are the analysis results and the opinion rating, and the output data is the generated report.

[1465] Step 6:

[1466] The server automatically generates prompt sentences for creating reports using a generative AI model. The generated prompt sentences are input to the AI ​​model to create the final report. The input data are the requirements for report generation, and the output data are the prompt sentences.

[1467] Step 7:

[1468] The server inputs the generated prompt sentences into the AI ​​model and creates a final report. The user can view this report through the terminal. The input data is the prompt sentences, and the output data is the final report.

[1469] In addition, 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.

[1470] "Example 1"

[1471] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the emotions of a user. When a user specifies a company name or industry genre through the system interface, this system collects data from publicly available company financial statements, industry statistical data, stock price information, etc., and analyzes the data. Then, a report is created on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Furthermore, information such as stock price fluctuations and trading volume is analyzed to estimate the company's evaluation. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the user's emotions and adjusts the display method and content of the report based on the emotion. For example, if the user shows an emotion of joy, the system displays positive information with emphasis. Conversely, if the user shows an emotion of anxiety or sadness, the system provides information that alleviates the emotion.

[1472] "Example 2"

[1473] Another embodiment of the present invention is a system in which an emotion engine adjusts the contents of a report based on the emotion of a user. When a user specifies the "automobile" industry, the system collects data from financial statements, industry statistics, stock price information, and other information related to the automobile industry, and analyzes the data. Then, a report is created on the financial statements, industry trends, the position in the industry, and the relationship between stock prices and companies in the automobile industry. Furthermore, information such as fluctuations in stock prices and trading volume related to the automobile industry is analyzed to estimate the evaluation of the companies. This evaluation is added to the report as a public opinion evaluation. The emotion engine recognizes the emotion of the user and adjusts the content of the report based on the emotion. For example, if the user shows excitement, the system highlights and displays positive information such as the launch of a new product or improved performance. Conversely, if the user shows anxiety, the system provides information on the stability of the industry and the reliability of the companies.

[1474] The process flow of each embodiment will be described below.

[1475] "Example 1"

[1476] Step 1: The user specifies the company name and industry genre through the system interface.

[1477] Step 2: Based on the specified company name and industry genre, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[1478] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[1479] Step 4: Analyze information such as stock price fluctuations and trading volume to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[1480] Step 5: The emotion engine recognizes the user's emotion and adjusts the presentation and content of the report based on that emotion.

[1481] "Example 2"

[1482] Step 1: The user specifies the "Automotive" industry.

[1483] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the specified "automotive" industry.

[1484] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[1485] Step 4: Analyze information such as stock price fluctuations and trading volume related to the automotive industry to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[1486] Step 5: The sentiment engine recognises the user's sentiment and adapts the report content based on that sentiment.

[1487] Example 1

[1488] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1489] In conventional corporate analysis systems, even if users specify a company name or industry, data collection and analysis are done manually, which is time-consuming and labor-intensive. In addition, reports are not adjusted based on public opinion from stock price information or user sentiment, making it difficult to provide useful information to users.

[1490] 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.

[1491] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for recognizing user emotions and adjusting the display method and contents of the report. This enables automatic collection and analysis of data, and makes it possible to provide useful information to users quickly and efficiently.

[1492] A "means for specifying a company name or industry category" is a device or software that provides an interface for a user to input or select a particular company name or industry category.

[1493] "Means for collecting data based on a specified company name or industry category" refers to a device or software that automatically obtains data related to a company name or industry category specified by a user from the Internet or a database.

[1494] "Means for analyzing collected data" refers to devices or software that organize the collected data and analyze it using statistical or machine learning methods.

[1495] A "means for creating a report based on the analysis results" is a device or software that automatically generates a report to be provided to a user based on the results of data analysis.

[1496] A "means for assessing public opinion from stock price information" is a device or software that analyzes information such as stock price fluctuations and trading volume, and estimates a company's evaluation and the market's reaction.

[1497] The "means for recognizing a user's emotions and adjusting the display method and contents of a report" refers to a device or software that analyzes a user's emotions and dynamically changes the display method and contents of a report in accordance with those emotions.

[1498] This invention is a system in which the server automatically collects data, analyzes it, and creates a report when the user selects a company name and industry category. It also has a function to evaluate public opinion from stock price information and adjust the display method and content of the report based on the user's feelings.

[1499] Hardware and Software Used

[1500] Hardware

[1501] Server: A central processing unit for data collection, analysis, reporting, and emotion recognition.

[1502] Terminal: The device (PC, smartphone, tablet, etc.) through which the user enters the company name and industry genre.

[1503] software

[1504] Interface: A GUI (Graphical User Interface) that allows users to specify company names and industry genres.

[1505] Data collection: Web scraping using Python's BeautifulSoup and Selenium, and stock quotes using the Yahoo Finance API.

[1506] Data Analysis: Use Python's Pandas and NumPy to organize the data and Scikit-learn to apply machine learning models.

[1507] Reporting: Generate reports using Python ReportLab or Jinja2.

[1508] Public opinion assessment: We use natural language processing techniques and machine learning algorithms to assess public opinion. Specifically, we use libraries such as NLTK, TensorFlow, and PyTorch.

[1509] Emotion Recognition: Analyze user emotions using Microsoft Azure's Emotion API and Google Cloud's Natural Language API.

[1510] Examples

[1511] Example 1: User specifies "ABC Corporation" and "IT industry"

[1512] A user opens the system interface using a terminal and selects "ABC Corporation" and the "IT industry." The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements for "ABC Corporation" and statistical data for the "IT industry," and obtains stock price information using the Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, and estimates public opinion for "ABC Corporation" using NLTK and TensorFlow, which it adds to the report.

[1513] Example 2: User specifies "XYZ Corporation" and "manufacturing industry" and emotion engine recognizes anxiety

[1514] The user opens the system interface using a terminal and selects "XYZ Corporation" and "Manufacturing". The terminal sends this information to the server. The server uses Python's BeautifulSoup and Selenium to collect financial statements of "XYZ Corporation" and statistical data of "Manufacturing", and obtains stock price information using Yahoo Finance API. The server then organizes the data using Python's Pandas and NumPy, and analyzes the data using Scikit-learn. Based on the analysis results, it creates a report using Python's ReportLab and Jinja2. In addition, the server analyzes stock price fluctuations and trading volume, estimates public opinion evaluation of "XYZ Corporation" using NLTK and TensorFlow, and adds it to the report. As the emotion engine recognizes the user's anxiety, the server uses Microsoft Azure's Emotion API and Google Cloud's Natural Language API to analyze the user's emotions and provide information that will ease their anxiety.

[1515] Examples of prompt statements

[1516] "Collect ABC Corporation's financial statements, IT industry statistics, and stock price information, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, analyze stock price fluctuations and trading volume, estimate public opinion, and add it to the report."

[1517] "Please collect financial statements, manufacturing industry statistics, and stock price information for XYZ Corporation, and create a report on its financial status, industry trends, its position within the industry, and the relationship between stock prices and the company. Also, please analyze stock price fluctuations and trading volume, estimate public opinion, and add this to the report. Users are feeling anxious, so please provide information that will ease their anxiety."

[1518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1519] Step 1:

[1520] The user opens the system interface using a terminal and inputs the company name and industry category. The input information is sent to the server as text data of the company name and industry category.

[1521] Step 2:

[1522] The server collects data based on the company name and industry category specified by the user. Specifically, it uses Python's BeautifulSoup and Selenium to perform web scraping to obtain company financial statements and industry statistical data. It also obtains stock price information using the Yahoo Finance API. The input is text data of company names and industry categories, and the output is a dataset of financial statement data, industry statistical data, and stock price information.

[1523] Step 3:

[1524] The server analyzes the collected data. Specifically, it organizes the data using Python's Pandas and NumPy, and applies machine learning models using Scikit-learn. The input is a dataset of financial statement data, industry statistical data, and stock price information, and the output is a dataset of the analysis results. For example, the server performs specific operations such as "analyzing financial statement data to evaluate the financial situation of ABC Corporation" or "analyzing statistical data to understand trends in the IT industry."

[1525] Step 4:

[1526] The server creates reports based on the analysis results. Specifically, it generates reports using Python's ReportLab or Jinja2. The input is a dataset of the analysis results, and the output is a report to be provided to the user. For example, the server performs a specific operation such as "create a report summarizing the financial situation of ABC Corporation, trends in the IT industry, ABC Corporation's position within the industry, and the relationship between stock prices and companies."

[1527] Step 5:

[1528] The server analyzes information such as stock price fluctuations and trading volume to estimate the evaluation of the company. Specifically, it uses natural language processing technology and machine learning algorithms to perform public opinion evaluation. The input is a dataset of stock price information, and the output is a dataset of public opinion evaluation. For example, the server performs a specific operation such as "analyzing stock price fluctuation data and estimating public opinion evaluation of ABC Co., Ltd."

[1529] Step 6:

[1530] The server recognizes the user's emotions. Specifically, it analyzes the user's emotions using Microsoft Azure's Emotion API and Google Cloud's Natural Language API. The input is data such as the user's input, facial expressions, and tone of voice, and the output is the user's emotional data. For example, the server performs specific operations such as "recognizing emotions from the user's input, facial expressions, and tone of voice."

[1531] Step 7:

[1532] The server adjusts the display method and content of the report based on the user's emotions recognized by the emotion engine. The input is the user's emotion data and the report, and the output is the adjusted report. For example, if the user expresses emotions of joy, the server takes specific actions such as "displaying the report with positive information emphasized." Conversely, if the user expresses emotions of anxiety or sadness, the server takes specific actions such as "providing information that will ease anxiety."

[1533] (Application example 1)

[1534] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1535] In conventional corporate information analysis systems, even if the user specified a company name or industry, the system would only collect and analyze data such as financial statements, industry trends, and stock price information, and could not provide information based on the user's emotions. As a result, the system was unable to provide appropriate information based on the user's emotions, which led to an issue of poor user experience.

[1536] 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.

[1537] In this invention, the server includes a means for designating a company name and industry category, a means for creating reports on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and content of the report based on the user emotions, thereby making it possible to provide appropriate information according to the user's emotions.

[1538] "Means for specifying a company name or industry category" refers to a function that provides an interface for a user to input or select a specific company name or industry category.

[1539] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and stock prices" refers to a function that collects publicly available financial statements, industry trends, position within the industry, stock price information, etc. based on a specified company name or industry genre, analyzes them, and automatically generates reports.

[1540] "Means of evaluating public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate a company's evaluation.

[1541] "Means of recognizing user emotions" refers to a function that analyzes emotions from text, voice, facial expressions, etc. entered by the user and recognizes those emotions.

[1542] The "means for adjusting the display method and contents of a report based on the user's emotions" is a function for dynamically changing the display method and contents of a report in response to the recognized emotions of a user.

[1543] As an embodiment of the present invention, the following system can be constructed.

[1544] The server includes a means for specifying a company name and industry category, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions, and a means for adjusting the display method and contents of the report based on the user emotions.

[1545] Specifically, the server uses the following hardware and software.

[1546] Hardware: Servers, smartphones

[1547] Software: Python, requests, pandas, TextBlob, scikit-learn

[1548] The server first receives the company name and industry category entered by the user via smartphone. The server then collects publicly available company financial statements, industry statistics, stock price information, etc., and converts them into a data frame using pandas. This allows the server to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and the company.

[1549] Additionally, the server uses TextBlob to analyze user sentiment and adjust the presentation and content of reports based on that sentiment. For example, if a user types, "I'm worried about the recent stock market movements," TextBlob can be used to analyze sentiment and, if negative sentiment is detected, the server will highlight information that requires attention.

[1550] As a concrete example, the following prompt sentence can be used:

[1551] Company Name: General company name

[1552] Emotional text: "I'm worried about the recent stock market movements."

[1553] When this prompt is entered into the server, the server collects financial data from companies and generates a report based on the user's emotions, allowing the user to obtain appropriate information according to their own emotions.

[1554] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1555] Step 1:

[1556] A user inputs a company name and an industry category using a terminal. The input company name and industry category are sent to a server. The input data is text information about the company name and industry category.

[1557] Step 2:

[1558] The server collects publicly available company financial statements, industry statistical data, stock price information, etc. based on the received company name and industry category. Specifically, the server obtains data using an API (e.g., Yahoo Finance API). The input data is the company name and industry category, and the output data is a data set including financial statements, industry statistical data, and stock price information.

[1559] Step 3:

[1560] The server converts the collected data into a data frame using pandas. The data converted into a data frame is used to analyze the company's financial situation, industry trends, the company's position in the market, and the relationship between stock prices and companies. The input data is the collected raw data, and the output data is analyzable data in the data frame format.

[1561] Step 4:

[1562] The server uses TextBlob to analyze the sentiment from the user-entered text. Specifically, it passes the user-entered text to TextBlob and gets the sentiment score (positive or negative). The input data is the user's text and the output data is the sentiment score.

[1563] Step 5:

[1564] The server adjusts the presentation and content of the report based on the sentiment score, for example highlighting information that requires attention if negative sentiment is detected. The input data are sentiment scores and a data frame, and the output data is the adjusted report.

[1565] Step 6:

[1566] The server generates the reconciled report and sends it to the terminal, which displays the received report to the user, the input data being the reconciled report and the output data being the report displayed to the user.

[1567] Step 7:

[1568] The user can check the displayed report through the terminal and retrieve the information again by inputting additional company names and industry categories as necessary. The input data is the user's feedback and new company names and industry categories, and the output data is the updated report.

[1569] Example 2

[1570] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1571] Conventional industry analysis systems had the problem that it took a lot of time and effort for users to understand the overall picture of the industry. In addition, they could not fully meet the needs of users because they did not provide information according to their emotions. Furthermore, public opinion evaluation from stock price information was insufficient, and the evaluation of companies was not accurately reflected.

[1572] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for designating an industry, a means for collecting data, a means for analyzing data, a means for generating a report, a means for public opinion evaluation, a means for recognizing emotions and adjusting the report, and a means for providing the report. This allows the user to grasp the overall picture of the industry in a short time, and information is provided according to the user's emotions, so that the user's needs can be met. In addition, an accurate public opinion evaluation is performed based on stock price information, and the evaluation of the company is accurately reflected.

[1573] The "means for specifying an industry" is an interface that allows the user to select or input the industry in which he or she is interested.

[1574] "Means of collecting data" refers to the function of obtaining information related to the specified industry from the Internet or databases.

[1575] "Means for analyzing data" refers to a function for organizing collected data and analyzing it using statistical or machine learning methods.

[1576] The "means for generating a report" is a function for creating a report to be provided to a user based on the analysis results.

[1577] "Means of evaluating public opinion" refers to a function that analyzes stock price information and market reactions to estimate a company's valuation.

[1578] The "means for recognizing emotions and adjusting reports" is a function for detecting the emotions of a user and adjusting the contents of a report in accordance with the emotions.

[1579] The "means for providing a report" is a function for displaying or transmitting a generated report to a user.

[1580] The present invention is a system in which a user specifies an industry, and a server collects data, analyzes data, generates reports, evaluates public opinion, recognizes emotions, and provides reports. A specific embodiment of this system is described below.

[1581] 1. Means of specifying industry

[1582] A user uses a terminal to access the system and specify the industry he or she is interested in. For example, the user opens a browser, accesses the system's web page, enters "automotive" in the search box, and clicks the search button. This action sends the user's specification to the server.

[1583] 2. How we collect data

[1584] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[1585] Use the Yahoo Finance API to collect company financial statements.

[1586] Use the Google Finance API to get stock price data for the past year.

[1587] 3. How to analyze the data

[1588] The server analyzes the collected data. Specifically, it uses the following libraries:

[1589] Use Pandas to organize financial data for each company.

[1590] Analyzing industry trends using NumPy.

[1591] 4. How to generate reports

[1592] The server generates a report based on the analysis results. It uses a generative AI model (e.g., OpenAI's GPT-4) to create a report like the one below.

[1593] Automotive Industry Report:

[1594] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1595] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1596] Company A has a strong position in the market and its stock price is stable.

[1597] 5. Means of assessing public opinion

[1598] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[1599] Analyze stock price fluctuations and rate Company A as "high."

[1600] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[1601] 6. How to recognize emotions and adjust reports

[1602] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[1603] If users are excited, highlight information about a new product launch or business improvement.

[1604] If users express concern, provide information about industry stability and company trustworthiness.

[1605] 7. Means of Providing Reports

[1606] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[1607] Examples of concrete examples and prompts

[1608] As a specific example, the process when the user specifies the "automobile" industry is shown below.

[1609] Data collection:

[1610] The server collects financial statements of Company A, Company B, and Company C using the Yahoo Finance API.

[1611] Use the Google Finance API to get stock price data for the past year.

[1612] Data Analysis:

[1613] The server uses Pandas to organize each company's financial data and NumPy to analyze industry trends.

[1614] Report Generation:

[1615] The server uses GPT-4 to generate a report like this:

[1616] Automotive Industry Report:

[1617] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1618] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1619] Company A has a strong position in the market and its stock price is stable.

[1620] Adding public opinion ratings:

[1621] The server analyzes the fluctuations in stock prices and rates Company A as "high."

[1622] Emotion Recognition and Report Adjustment:

[1623] The server highlights information about new product launches or business improvements if the user is excited about them.

[1624] Conversely, if users express concern, provide information about industry stability and company trustworthiness.

[1625] Example prompt:

[1626] Please create a report on the "Automobile" industry. Please include the financial statements of Company A, Company B, and Company C, industry trends, the market position of each company, and the relationship between stock prices and the companies. Also, please make a public opinion assessment based on stock price information and add it to the report.

[1627] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1628] Step 1:

[1629] The user specifies the industry.

[1630] The user opens a browser on the terminal and accesses the system's web page. The user enters "car" in the search box and clicks the search button. This operation sends the user's specification to the server.

[1631] Input: A user-specified industry (e.g. "Automotive")

[1632] Output: Industry-specific information sent to the server

[1633] Step 2:

[1634] The server collects the data.

[1635] The server collects data related to the industry specified by the user from the Internet. Specifically, it uses the following APIs:

[1636] Use the Yahoo Finance API to collect company financial statements.

[1637] Use the Google Finance API to get stock price data for the past year.

[1638] Input: Industry-specific information

[1639] Output: Collected company financial statements and stock price data

[1640] Step 3:

[1641] The server analyzes the data.

[1642] The server analyzes the collected data. Specifically, it uses the following libraries:

[1643] Use Pandas to organize financial data for each company.

[1644] Analyzing industry trends using NumPy.

[1645] Input: Collected company financial statements and stock price data

[1646] Output: Organized financial data and industry trend analysis

[1647] Step 4:

[1648] The server generates the report.

[1649] The server generates a report based on the analysis results. It uses a generative AI model (e.g., OpenAI's GPT-4) to create a report like the one below.

[1650] Automotive Industry Report:

[1651] Company A's financial situation is good, with sales increasing 10% year-on-year.

[1652] As an industry-wide trend, demand for electric vehicles is rapidly increasing.

[1653] Company A has a strong position in the market and its stock price is stable.

[1654] Input: Organized financial data and industry trend analysis results

[1655] Output: Generated report

[1656] Step 5:

[1657] The server adds a public opinion rating.

[1658] The server evaluates public opinion from stock price information and adds it to the report. Specifically, it does this in the following steps:

[1659] Analyze stock price fluctuations and rate Company A as "high."

[1660] We also estimate the valuations of other companies, taking into account fluctuations in trading volume.

[1661] Input: Stock price data

[1662] Output: Report with opinion ratings added

[1663] Step 6:

[1664] The server performs emotion recognition and adjusts the reports.

[1665] The server uses the emotion engine to recognize the user's emotion. Specifically, it performs the following operations:

[1666] If users are excited, highlight information about a new product launch or business improvement.

[1667] If users express concern, provide information about industry stability and company trustworthiness.

[1668] Input: User emotion data

[1669] Output: Reconciled report

[1670] Step 7:

[1671] The server provides the report to the user.

[1672] The server generates the final report and sends it to the user's device, where the user can view it in their device's browser and download it if desired.

[1673] Input: Reconciled report

[1674] Output: Report provided to the user

[1675] (Application example 2)

[1676] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1677] Conventional industry report creation systems lacked the ability to adjust report content based on user sentiment, making it difficult to provide information that meets user needs. In addition, report generation and prompt sentence generation were not performed using generative AI models, which led to problems with the quality of reports and user experience not improving.

[1678] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1679] In this invention, the server includes a means for specifying a company name and industry genre, a means for creating a report on financial statements, industry trends, standing within the industry, and the relationship between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the content of the report based on the emotions, a means for generating a report using a generative AI model, and a means for generating a prompt sentence. This makes it possible to provide a report customized according to the user's emotions, and realizes high-quality report generation and prompt sentence generation using a generative AI model.

[1680] "Means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[1681] "A means of creating reports on financial statements, industry trends, position within the industry, and the relationship between a company and its stock price" refers to a function that analyzes financial data for a specified company or industry, industry trends, a company's position within the market, and the relationship between a company's stock price and information, and synthesizes this information to generate a report.

[1682] "Means of evaluating public opinion from stock price information" refers to a function that analyzes stock price data, extracts market reactions and public evaluations, and evaluates public opinion toward companies and industries.

[1683] "Means for recognizing a user's emotions and adjusting the contents of the report based on those emotions" is a function for analyzing a user's emotions and dynamically changing the contents of the report in accordance with those emotions.

[1684] A "means for generating reports using a generative AI model" is a function that uses an artificial intelligence model to automatically generate detailed reports on specified industries or companies.

[1685] A "means for generating a prompt sentence" is a function for automatically creating an appropriate prompt sentence to input to a generative AI model.

[1686] A system for carrying out the present invention includes a server, a user terminal, and a generative AI model. The server includes a means for specifying a company name and industry genre, a means for creating reports on financial statements, industry trends, positions within the industry, and relationships between stock prices and companies, a means for evaluating public opinion from stock price information, a means for recognizing user emotions and adjusting the contents of the report based on the emotions, a means for generating a report using the generative AI model, and a means for generating prompt sentences.

[1687] Hardware and Software Configuration

[1688] Hardware: Server, user terminal (smartphone, head-mounted display)

[1689] Software: Python, Requests library, Pandas library, TextBlob library

[1690] Data processing and calculation

[1691] 1. Specify your company name and industry:

[1692] The user terminal provides an interface for the user to input or select a particular company name or industry category. The information input by the user is transmitted to the server.

[1693] 2. Data Collection and Reporting:

[1694] The server collects financial data on specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The collected data is organized and analyzed using the Pandas library, and a report is generated.

[1695] 3. Public opinion assessment:

[1696] The server analyzes the stock price data and extracts market reactions and public evaluations. Using the TextBlob library, we perform sentiment analysis of the text data obtained from stock price information and perform public opinion evaluation.

[1697] 4. Emotion recognition and report adjustment:

[1698] The user terminal provides an interface for recognizing the user's emotions, and the user's emotion data is transmitted to the server, which dynamically adjusts the report content based on the emotions.

[1699] 5. Report generation using generative AI models:

[1700] The server uses the generative AI model to automatically generate detailed reports on the specified industry or company by generating prompt sentences and inputting them into the generative AI model.

[1701] 6. Prompt generation:

[1702] The server automatically creates appropriate prompt sentences to input to the generative AI model. For example, create a report on financial statements, industry trends, corporate positions, and the relationship between stock prices and companies in the "automotive" industry. If the user's sentiment is positive, highlight positive information such as new product launches and improved performance, and if it is negative, provide information on industry stability and company reliability.

[1703] Examples

[1704] If the user specifies the “Automotive” industry and the sentiment engine determines the user’s sentiment to be positive, a report like the one below will be generated.

[1705] Industry: Automotive

[1706] Financial Statement: Financial Statement for Q1 2023

[1707] Industry Trend: Electric vehicles are on the rise

[1708] Company position: Major automakers hold top market share

[1709] Stock prices and companies: Major automakers' stock prices are rising

[1710] Positive news: new product launches and improving performance

[1711] In this way, it becomes possible to provide customized reports based on the user's emotions, and high-quality report generation and prompt generation can be achieved by utilizing generative AI models.

[1712] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1713] Step 1:

[1714] The user terminal provides an interface for the user to input or select a particular company name or industry category. The company name or industry category input by the user is sent to the server. The input data is the text information of the company name or industry category. The output is the text information of the company name or industry category sent to the server.

[1715] Step 2:

[1716] The server collects financial data for specified companies and industries, industry trends, the company's position in the market, and the relationship between stock prices and companies through the API. The input data is text information on company names and industry genres. The server uses the Requests library to obtain data from the API, and organizes and analyzes the data using the Pandas library. The output is organized and analyzed financial data, industry trends, the company's position in the market, and the relationship between stock prices and companies.

[1717] Step 3:

[1718] The server analyzes stock price data and extracts market reactions and public evaluations. The input data is stock price information obtained from the API. The server uses the TextBlob library to perform sentiment analysis of the text data obtained from the stock price information and perform public opinion evaluation. The output is public opinion evaluation data including the sentiment analysis results.

[1719] Step 4:

[1720] The user terminal provides an interface for recognizing the user's emotions. The user's emotion data is transmitted to the server. The input data is text information or sensor data indicating the user's emotions. The output is the user's emotion data transmitted to the server.

[1721] Step 5:

[1722] The server dynamically adjusts the report content based on the user's emotion data. The input data are the user's emotion data and the data obtained in steps 2 and 3. If the user's emotion is positive, the server emphasizes positive information, and if the user's emotion is negative, it emphasizes information about stability and reliability. The output is report data adjusted according to the user's emotion.

[1723] Step 6:

[1724] The server uses the generative AI model to automatically generate a detailed report on the specified industry or company. The input data are the data obtained in step 2 and step 3 and the prompt sentence. The server inputs the prompt sentence into the generative AI model and generates a report. The output is the generated report.

[1725] Step 7:

[1726] The server automatically creates appropriate prompt sentences to input to the generative AI model. The input data is text information on the company name and industry genre specified by the user. The server generates the prompt sentences and inputs them into the generative AI model. The output is the generated prompt sentence.

[1727] As a specific example, if a user specifies the "automobile" industry and the emotion engine determines that the user's emotion is positive, the following prompt sentence is generated:

[1728] Create a report on financial statements, industry trends, company positions, and company relationships for the "Automotive" industry. If user sentiment is positive, highlight positive information such as new product launches and improving performance. If sentiment is negative, provide information about industry stability and company reliability.

[1729] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1730] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1731] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1732] 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.

[1733] [Fourth embodiment]

[1734] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1735] 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.

[1736] 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.

[1737] The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1738] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1739] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1740] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1741] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1742] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1743] Fig. 8 shows an example of main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1744] 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.

[1745] 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.

[1746] In the robot 414, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1747] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1748] "Example 1"

[1749] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. It analyzes information such as stock price fluctuations and trading volume to estimate a company's valuation.

[1750] "Example 2"

[1751] As a specific example, if a user specifies the "automobile" industry, the system will create a report on the automobile industry's financial statements, industry trends, position within the industry, and the relationship between stock prices and companies. The report includes each company's financial status, industry trends, each company's position within the market, and the relationship between stock prices and companies. In addition, the system will perform public opinion evaluation from stock price information and add it to the report. This allows users to quickly grasp the overall picture of the automobile industry.

[1752] The process flow of each embodiment will be described below.

[1753] "Example 1"

[1754] Step 1: The user specifies the company name and industry genre through the system interface.

[1755] Step 2: Based on the specified company name and industry category, the system collects data from publicly available company financial statements, industry statistics, stock price information, etc.

[1756] Step 3: Analyze the collected data and prepare reports on financial statements, industry trends, industry standing, and company relationships with stock prices.

[1757] Step 4: Further, information such as stock price fluctuations and trading volume is analyzed to estimate the company's valuation. This valuation is added to the report as a public opinion rating.

[1758] "Example 2"

[1759] Step 1: The user specifies the "Automotive" industry.

[1760] Step 2: The system collects data from financial statements, industry statistics, stock price information, etc. of companies related to the automotive industry.

[1761] Step 3: Analyze the collected data and prepare reports on the financial statements, industry trends, industry standing, and stock prices of the automotive industry.

[1762] Step 4: Further, information such as stock price fluctuations and trading volume related to the automotive industry is analyzed to estimate the valuation of the companies. This valuation is added to the report as a public opinion rating.

[1763] Example 1

[1764] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1765] Conventional corporate analysis systems had the problem that even if a user specified a company name or industry, it took a lot of time and effort to collect, process, and analyze the necessary data. In addition, there was a lack of automated means to evaluate public opinion from stock price information, so users had to perform the evaluation manually. This made it difficult to create reports quickly and accurately.

[1766] 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.

[1767] In this invention, the server includes a means for designating a company name and an industry category, a means for collecting data based on the designated company name and industry category, a means for processing and analyzing the collected data, a means for creating a report based on the analysis results, a means for evaluating public opinion from stock price information, and a means for providing the created report. This makes it possible for a user to simply designate a company name and an industry category, and quickly and accurately create and provide a report including the company's financial situation, industry trends, the company's position in the market, the relationship between stock price and the company, and evaluation of public opinion.

[1768] The "means for specifying a company name or industry category" is a function that provides an interface for a user to input or select a specific company name or industry category.

[1769] "Means of collecting data based on a specified company name or industry genre" refers to a function for obtaining data related to a company name or industry genre specified by a user from an external database or API.

[1770] "Means for processing and analyzing collected data" refers to the function of organizing collected data, extracting necessary information, and analyzing it.

[1771] The "means for creating a report based on the analysis results" is a function for automatically generating a report to be provided to a user based on the analyzed data.

[1772] "Means of assessing public opinion from stock price information" refers to a function that analyzes information such as stock price fluctuations and trading volume to estimate the market's evaluation and public opinion of a company.

[1773] The "means for providing a generated report" refers to a function for providing a generated report to a user, and includes provision in PDF format or Web page format.

[1774] The system of the present invention is equipped with an interface that allows the user to specify a company name and industry category. When the user specifies a company name and industry category, the system automatically creates a report on financial statements, industry trends, the company's position within the industry, and the relationship between stock prices and the company. Data for creating the report is collected from publicly available company financial statements, industry statistical data, stock price information, etc. The system also automatically performs public opinion evaluation from stock price information. This involves analyzing information such as stock price fluctuations and trading volume, and estimating a company's valuation.

[1775] Hardware and Software Used

[1776] Hardware

[1777] Server: A central processing unit for data collection, processing, analysis, and report generation.

[1778] Terminal: The device through which the user operates the interface (e.g. PC, smartphone)

[1779] software

[1780] Web browser: Provides an interface for users to enter company names and industry categories

[1781] API: Access to external databases and services for data collection (e.g. EDGAR database, Statista, Yahoo Finance API)

[1782] Template engine: a tool for formatting collected and analyzed data into reports

[1783] Data analysis tools: Software for processing and analyzing collected data (e.g. Python, R)

[1784] Data processing and calculation

[1785] The server collects the necessary information from the following data sources based on the company name and industry genre specified by the user.

[1786] Public company financial statements (e.g., EDGAR database)

[1787] Industry statistics (e.g. Statista)

[1788] Stock quotes (e.g. Yahoo Finance API)

[1789] The collected data will be processed and analyzed as follows:

[1790] Analyze financial statement data to evaluate a company's financial position, for example by calculating indicators such as sales, net profit, and debt ratio.

[1791] Use industry statistics to analyze industry trends, for example, to calculate overall industry growth rates and market shares.

[1792] Analyze stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[1793] Analyze stock price fluctuations and trading volume to estimate public opinion. For example, identify the causes of sudden increases or decreases in stock prices.

[1794] Examples

[1795] Example 1: When specifying a company name

[1796] The user specifies "specific company." The server performs the following process:

[1797] 1. The user enters "specific company" into the web form and clicks the submit button.

[1798] 2. The server retrieves the latest financial statements for a particular company from the EDGAR database.

[1799] 3. The server retrieves the latest statistical data for a specific industry from Statista.

[1800] 4. The server retrieves stock price information for a specific company from the Yahoo Finance API.

[1801] 5. The server analyzes the collected data and creates a report that includes the specific company's financial status, industry trends, its position within the industry, the company's relationship with stock prices, and public opinion ratings.

[1802] 6. The server generates the report in PDF format and provides a download link to the user.

[1803] Example 2: When specifying an industry genre

[1804] The user specifies "specific industry." The server performs the following process:

[1805] 1. A user enters "specific industry" into a web form and clicks the submit button.

[1806] 2. The server retrieves the latest statistical data for a specific industry from Statista.

[1807] 3. The server retrieves stock price information for major companies in a specific industry from the Yahoo Finance API.

[1808] 4. The server analyzes the collected data and creates reports that include trends in a particular industry, the position of major companies within the industry, the relationship between stock prices and companies, and public opinion ratings.

[1809] 5. The server generates the report in the form of a web page and displays it to the user.

[1810] Examples of prompt statements

[1811] Example 1: Prompt statement specifying company name

[1812] "Create a report that includes a specific company's latest financials, industry trends, where it stands within the industry, the company's stock price relationship, and public opinion ratings."

[1813] Example 2: Prompt statement specifying industry genre

[1814] "Create a report that includes the latest trends in a particular industry, where major companies stand in the industry, stock price-company relationships, and public opinion ratings."

[1815] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1816] Step 1: User specifies company name and industry category

[1817] A user uses an interface to input a company name and industry category through a web browser or mobile application. For example, the user inputs "specific company" and clicks the submit button. The input data is sent to the server.

[1818] Input: Company name or industry

[1819] Output: The input data sent to the server.

[1820] Step 2: The server collects the data

[1821] The server collects the necessary information from the following data sources based on the company name and industry genre received from the user.

[1822] The server accesses the EDGAR database to retrieve the most recent financial statements for the specified companies.

[1823] The server accesses Statista and retrieves the latest statistical data for the specified industry.

[1824] The server uses the Yahoo Finance API to retrieve stock quotes for the specified companies.

[1825] Input: User-specified company name or industry

[1826] Output: Collected financial statement data, industry statistics, stock price information

[1827] Step 3: The server processes and analyzes the data

[1828] The server processes and analyzes the collected data as follows:

[1829] The server analyzes the financial statement data and evaluates the company's financial condition, for example calculating metrics such as sales, net profit, and debt ratio.

[1830] The server uses industry statistics to analyze industry trends, for example to calculate industry-wide growth rates and market shares.

[1831] The server analyzes stock price information to evaluate a company's stock price and its position in the industry, for example by calculating stock price volatility and trading volume.

[1832] The server analyzes stock price fluctuations and trading volume to estimate public opinion, for example by identifying the causes of sudden increases or decreases in stock prices.

[1833] Input: Collected financial statement data, industry statistics, stock price information

[1834] Output: Company financial status, industry trends, industry standing, stock price and company relationship, public opinion evaluation

[1835] Step...

Claims

1. A means to specify an industry genre; A report creation means for creating a report on financial statements, industry trends, positions within the industry, stock prices, and relationships between the multiple companies in the specified industry genre; a public opinion evaluation means for evaluating public opinion of the plurality of companies based on stock price information; means for recognizing user sentiment, and adjusting the content of the report to emphasize positive information, including new product launches and business performance improvements of the companies, when the sentiment is positive, and to provide information about the reliability of the companies, when the sentiment is negative; A system including:

2. 2. The system according to claim 1, wherein said report generating means includes means for analyzing a company's financial condition, industry trends, a company's position in the market, and a relationship between stock prices and the company.

3. 3. A system according to claim 1, wherein said public opinion assessment means includes means for analysing public opinion and market reaction obtained from stock price information.

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