system

Abstract

We provide the system. [Solution] A means for the user to enter a company number or company name, A means of sending the entered company number or company name to the server, A means for obtaining company information from a database based on the company number or company name received by the server, A means of analyzing acquired company information and generating proposals, A means of displaying the generated suggestions to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] It is difficult for corporate salespersons or business consultants to quickly and accurately grasp the current situation of customer companies and obtain information for making optimal proposals based on the medium-term business plans of those companies in a unified manner. In conventional systems, information collection and analysis from multiple data sources are performed manually, which requires time and effort. Also, since the generation of proposals depends on the experience and skills of each person in charge, there are variations in the quality and consistency of the proposals. It is necessary to solve these problems.

Means for Solving the Problems

[0005] The present invention is a system that includes means for a user to input a company number or company name, means for transmitting the input company number or company name to a server, means for the server to retrieve company information from a database based on the received company number or company name, means for analyzing the retrieved company information and generating a proposal, and means for displaying the generated proposal to the user. This makes it possible to quickly grasp the current status of a company and efficiently provide optimal proposals based on that company's medium-term management plan. Furthermore, by adding means for displaying the company's sales and profits based on the retrieved company information, and means for displaying various contract statuses, it becomes possible to provide even more detailed analysis results.

[0006] A "user" refers to a person or entity that enters a company number or company name and performs operations on the system.

[0007] A "company number" refers to a number used to uniquely identify each company.

[0008] "Company name" refers to the name used to identify each company.

[0009] "Input method" refers to the interface for entering a company number or company name into the system.

[0010] "Transmission means" refers to an interface or device that has the function of transmitting the entered company number or company name to the server.

[0011] A "server" refers to a computer system that receives a company number or company name and works with a database to retrieve and analyze company information.

[0012] A "database" refers to a system used to store and manage data such as corporate information and medium-term management plans.

[0013] "Company information" refers to detailed information about a company, such as its contract status, sales, and profits.

[0014] "Analysis means" refers to algorithms and processes for analyzing the acquired corporate information.

[0015] "Proposal generation means" refers to algorithms and processes for generating proposals to be provided to the user based on the analyzed corporate information.

[0016] "Display means" refers to an interface for visually presenting the generated proposals and corporate information to the user.

[0017] "Sales" refers to the total amount of revenue obtained by a company by providing goods or services.

[0018] "Profit" refers to the financial gain remaining after subtracting all expenses from a company's sales.

[0019] "Contract status" refers to the current status of various contracts concluded by a company.

[0020] "Medium-term business plan" refers to a plan document summarizing the goals and strategies that a company aims to achieve in a medium-term period.

Brief Explanation of Drawings

[0021] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0022] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0023] First, the language used in the following description will be explained.

[0024] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0025] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0026] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0027] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0029] [First Embodiment]

[0030] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0031] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0034] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0037] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0041] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0042] This invention is a system that allows users to input a company number or company name to obtain information on various contract statuses, sales, and profits of that company, and further provides suggestions based on the company's medium-term management plan. The following describes the overall overview, operation method, and specific examples of the system.

[0043] System Overview

[0044] The system consists of a terminal where the user enters a company number or company name, and a server that receives, analyzes, and responds to the data. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, generates suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0045] How the system works

[0046] 1. The user enters information.

[0047] The user enters the company number or company name into the input field on the terminal.

[0048] For example, a user enters the company number "12345" and clicks the submit button.

[0049] 2. The device sends the request to the server.

[0050] The terminal has the function of sending input data to the server.

[0051] When the terminal sends the company number "12345" to the server, the server receives it.

[0052] 3. The server retrieves company information.

[0053] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0054] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0055] 4. The server analyzes the data and generates suggestions.

[0056] Based on the acquired data, the server analyzes the company's current situation.

[0057] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0058] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0059] 5. The server sends the results to the terminal.

[0060] The server sends the generated proposals and analysis results to the terminal in JSON format.

[0061] The data includes contract status, sales, profits, and proposals.

[0062] 6. The device receives and displays the results.

[0063] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0064] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", Proposal "Please consider introducing new product A. This could potentially increase profits by 10%."

[0065] Specific example

[0066] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. This proposal states, "Please consider introducing new product A. This could potentially increase profits by 10%." This information is then sent back to the terminal and displayed to the user.

[0067] The following describes the processing flow.

[0068] Step 1:

[0069] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0070] Step 2:

[0071] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0072] Step 3:

[0073] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0074] Step 4:

[0075] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0076] Step 5:

[0077] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0078] Step 6:

[0079] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0080] Step 7:

[0081] The server sends the generated proposals and analysis results back to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and proposals in JSON format and sends it to the terminal as an HTTP response.

[0082] Step 8:

[0083] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0084] Step 9:

[0085] The terminal displays the extracted information to the user. Specifically, the screen displays contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Please consider introducing new product A. This could increase profits by 10%."

[0086] Step 10:

[0087] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0088] (Example 1)

[0089] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] Conventional corporate information acquisition systems struggled to quickly and accurately retrieve necessary information and provide useful suggestions based on analysis results, even when users entered a company number or company name. In particular, they lacked a means to generate concrete suggestions based on a company's medium-term management plan, preventing users from making effective decisions.

[0091] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0092] In this invention, the server includes means for the user to input an identification number or identification name, means for transmitting the input identification number or identification name to a central processing unit, means for the central processing unit to retrieve information from a data storage device based on the received identification number or identification name, means for analyzing the retrieved information and generating recommendations, and means for displaying the generated recommendations to the user. This enables the user to quickly and accurately obtain company information and receive useful suggestions based on the analysis results.

[0093] An "identification number" is a numerical or string of characters used to uniquely identify a specific individual or organization.

[0094] An "identification name" is a name or label used to uniquely identify a particular individual or organization.

[0095] A "central processing unit" is a computer system used for processing and managing data.

[0096] A "data storage device" is a database or other storage system used to store and manage information.

[0097] A "recommendation" is a suggestion or instruction generated based on specific data and analysis results.

[0098] "Financial indicators" are metrics used to evaluate a company's financial condition, and include sales, profits, and other metrics.

[0099] "Contract status" refers to information about the current status of contracts a company is undertaking.

[0100] "Information" refers to data obtained from data storage devices, including a company's financial indicators, contract status, and medium-term management plans.

[0101] This invention is a system that allows users to input a company number or company name to obtain various information about that company, and then generates proposals based on that information and its medium-term management plan. The specific form of this system is described below.

[0102] System Configuration

[0103] This system primarily consists of user-operated terminals and servers that process data. The system transmits and receives data between the terminals and servers via a communication network.

[0104] Hardware and software to be used

[0105] Devices: PC (Windows 10), smartphones (iOS / ANDROID®), etc.

[0106] Server: Linux (registered trademark) server (Ubuntu)

[0107] Databases: MySQL (registered trademark), PostgreSQL

[0108] Analysis software: Python, R

[0109] Proposal generation: Generative AI model (OpenAI® GPT)

[0110] Specific examples of the system

[0111] The user enters the company number "12345" into the input field on the terminal and clicks the submit button. This action causes the terminal to send the company number "12345" to the server. The server uses this company number to retrieve information about the corresponding company from its database.

[0112] The information obtained may include, for example:

[0113] Contract status: "Currently under contract"

[0114] Sales: "50 million yen"

[0115] Profit: "5 million yen"

[0116] Information on the medium-term management plan

[0117] The server analyzes this information and assesses the company's current situation. Next, it uses a generative AI model to generate suggestions by prompting the following sentences:

[0118] "Please generate a proposal based on the contract status, sales, profits, and medium-term business plan for company number 12345."

[0119] The proposals generated by the generative AI model include, for example, the following:

[0120] "Please consider introducing new product A. This could potentially increase profits by 10%."

[0121] The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal. The terminal parses the received JSON data and displays it in the user interface. HTML and CSS are used for the display format. Finally, the user sees the following information on the terminal screen:

[0122] Contract status: "Currently under contract"

[0123] Sales: "50 million yen"

[0124] Profit: "5 million yen"

[0125] Proposal: "Please consider introducing new product A. This could potentially increase profits by 10%."

[0126] In this way, users can quickly and accurately obtain the necessary company information and receive useful suggestions.

[0127] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0128] Step 1: The user enters the company number or company name into the terminal.

[0129] Input: Company number or company name (e.g., "12345")

[0130] Output: Input data stored within the terminal

[0131] Specific action: The user enters the company number "12345" into the terminal's input field and clicks the submit button. This action stores the data from the input field into a variable within the terminal.

[0132] Step 2: The terminal sends the input data to the server.

[0133] Input: Company number or company name stored on the terminal

[0134] Output: Request data sent to the server

[0135] Specific operation: The terminal sends the entered company number "12345" to the server in the form of an HTTP request. For example, a request in the format POST / api / getCompanyInfo { "company_id": "12345"} is issued. The server receives this request.

[0136] Step 3: The server retrieves company information from the database.

[0137] Input: Company number "12345" included in the HTTP request

[0138] Output: Information on the company's contract status, sales, profits, and medium-term management plan.

[0139] Specific operation: The server issues a query to the database based on the received company number "12345". For example, it executes an SQL query such as SELECT FROM companies WHERE company_id='12345' to retrieve relevant company information from the database.

[0140] Step 4: The server analyzes the acquired company information and generates proposals.

[0141] Input: Company information obtained from a database (contract status, sales, profits, medium-term business plan)

[0142] Output: Generated proposals and analysis results

[0143] Specific operation: The server analyzes data such as a company's sales and profits to evaluate the company's current situation. Based on the analysis results, it uses a generating AI model and, upon receiving the prompt message "Generate proposals based on the contract status, sales, profits, and medium-term management plan for company number 12345," the AI ​​generates specific recommendations.

[0144] Step 5: The server sends the generated results to the terminal.

[0145] Input: Generated proposals and analysis results

[0146] Output: Data in JSON format

[0147] Specific operation: The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal as an HTTP response. For example, { "contract_status": "Contract in progress", "sales": "50 million yen", "profit": "5 million yen", "suggestion": "Consider introducing new product A. This could increase profits by 10%."}.

[0148] Step 6: The device receives the results and displays them to the user.

[0149] Input: JSON format data received from the server

[0150] Output: Information displayed to the user (contract status, sales, profit, proposal)

[0151] Specific operation: The terminal parses the received JSON data and formats it using HTML and CSS to display it in the user interface. The user checks the parsing results and suggestions displayed on the terminal screen. For example, the screen might show contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Consider introducing new product A. This could increase profits by 10%."

[0152] (Application Example 1)

[0153] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0154] Conventional organizational information acquisition systems only retrieve and display information based on entered company numbers and names, lacking the functionality to automatically generate specific transaction proposals for companies. Therefore, users must analyze and make decisions based on the information they receive, which is inefficient. Furthermore, the process of analyzing company information is burdensome for users, resulting in insufficient support for accurate decision-making. Thus, a system is needed that can solve these problems and generate proposals quickly and accurately.

[0155] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0156] In this invention, the server includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. This makes it possible to provide users with more effective and efficient proposals and automate the process of analyzing corporate information.

[0157] An "identification number" is a number used to uniquely identify a particular organization.

[0158] "Organization name" refers to the name of a specific organization.

[0159] A "computer" refers to an electronic device used for processing and analyzing data, and usually includes a server.

[0160] A "storage medium" is a physical or electronic device used to store data, including hard disks and cloud storage.

[0161] "Organizational information" refers to data relating to a specific organization, including financial information such as contract status, sales, and profits.

[0162] "Data analysis" is a technique for extracting meaningful information based on acquired data and for understanding and evaluating the current situation.

[0163] A "deal proposal" is the process of providing specific actions and recommendations for a particular organization based on the results of data analysis.

[0164] A "generative AI model" is a model trained to perform data analysis and generate suggestions using artificial intelligence technology.

[0165] "Revenue" refers to the total income an organization earns through the provision of goods and services.

[0166] "Profit" refers to the net profit remaining after deducting all expenses from revenue.

[0167] A description in detail will be given of embodiments for carrying out this invention.

[0168] This system includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. The system is executed through user operations.

[0169] First, the user enters an identification number or organization name into the input field on the terminal. The terminal then sends the entered data to a server, which is a computer. Based on the received identification number or organization name, the server retrieves the corresponding organization information from a storage medium. This storage medium contains financial information such as the organization's contract status, sales, and profits.

[0170] The server performs data analysis based on the acquired organizational information. This analysis includes, for example, evaluating sales performance and calculating profit margins. Next, the server uses a generative AI model to generate specific deal proposals from the analysis results. These proposals include specific actions and recommendations that the organization should take.

[0171] The generated suggestions and analysis results are sent to the terminal and displayed to the user. For example, along with information such as contract status "In Contract," sales "50 million yen," and profit "5 million yen," a suggestion such as "Consider introducing new product A. This could increase profits by 10%" might be displayed.

[0172] As a concrete example, when a user enters and submits the identification number "12345," the server retrieves information about the corresponding organization from the storage medium and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and based on the generated AI model, a suggestion is created: "Consider introducing new product A. This could potentially increase profits by 10%." This suggestion and the analysis results are sent back to the terminal and displayed to the user.

[0173] Examples of prompt statements for a generative AI model are as follows:

[0174] "Retrieve company information for company number "12345," and analyze its sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on its medium-term business plan."

[0175] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0176] Step 1:

[0177] The user enters an identification number or organization name into the input field on the terminal. Let's say the user enters the organization name "ABC Company". The input is performed via the terminal's GUI, and after completion, the input data is confirmed by pressing the submit button. The input data is string data based on the identification number or organization name.

[0178] Step 2:

[0179] The terminal sends the entered identification number or organization name to the server. For example, it sends the data "ABC Company" to the server as an HTTP request. This request is formatted in JSON format so that the server can correctly receive and parse the data. Here, the input data is converted to a transmission format.

[0180] Step 3:

[0181] The server retrieves organizational information from the storage medium based on the identification number or organization name received. For example, it might query the database for "ABC Company" to retrieve information such as contract status, sales, and profits. This query extracts the organizational information from the database and returns it to the server. The output is organizational information data structured in JSON format.

[0182] Step 4:

[0183] The server performs data analysis based on the acquired organizational information. For example, it evaluates sales performance and calculates profit margins. This analysis may utilize statistical analysis and data mining techniques. This process generates indicators and numerical values ​​for evaluating the current state of the organization. The input is organizational information data, and the output is the analysis results.

[0184] Step 5:

[0185] The server uses a generation AI model to generate transaction proposals from data analysis results. For example, the prompt "Retrieve company information for company number 'ABC Corporation', analyze sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on the medium-term management plan." is input to the generation AI model, which then generates proposals such as new product introductions. This process utilizes machine learning models to perform advanced predictions and suggestions. The input is the analysis results, and the output is the transaction proposals.

[0186] Step 6:

[0187] The generated suggestions and analysis results are sent from the server to the terminal. The terminal receives this data and displays it to the user in a visually easy-to-understand format. For example, using a dashboard or graph, it might display information such as contract status ("In Contract"), sales ("50 million yen"), and profit ("5 million yen"), along with a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." The input is the generated suggestions and analysis results, and the output is the display on the user interface.

[0188] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0189] This invention is a system that, upon user input of a company number or company name, retrieves information on various contract statuses, sales, and profits for that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview, operation method, and specific examples of the system are described below.

[0190] System Overview

[0191] The system consists of a terminal where the user enters a company number or company name, a server that receives, analyzes, and responds to the input data, and an emotion engine that recognizes the user's emotions. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, adjusts the generated suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0192] How the system works

[0193] 1. The user enters information.

[0194] The user enters the company number or company name into the input field on the terminal.

[0195] For example, a user enters the company number "12345" and clicks the submit button.

[0196] 2. The device sends the request to the server.

[0197] The terminal has the function of sending input data to the server.

[0198] When the terminal sends the company number "12345" to the server, the server receives it.

[0199] 3. The server retrieves company information.

[0200] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0201] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0202] 4. The server analyzes the data and generates suggestions.

[0203] Based on the acquired data, the server analyzes the company's current situation.

[0204] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0205] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0206] 5. The emotion engine recognizes the user's emotions.

[0207] The server is equipped with an emotion engine that recognizes emotions from user input and responses.

[0208] The emotion engine analyzes the user's voice, facial expressions, text input, etc., to detect the user's emotional state.

[0209] 6. Adjust suggestions based on user sentiment.

[0210] Based on the recognized emotional state of the user, the generated suggestions are adjusted.

[0211] For example, if a user looks dissatisfied, the proposal can be flexibly modified to make it more acceptable to the user.

[0212] 7. The server sends the results to the terminal.

[0213] The server returns the generated proposal and analysis results to the terminal in JSON format.

[0214] The data includes recommendations tailored based on contract status, sales, profits, and user sentiment.

[0215] 8. The device receives and displays the results.

[0216] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0217] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", and Adjusted proposal "Please consider introducing new product A. This could increase profits by 10%."

[0218] Specific example

[0219] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0220] The following describes the processing flow.

[0221] Step 1:

[0222] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0223] Step 2:

[0224] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0225] Step 3:

[0226] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0227] Step 4:

[0228] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0229] Step 5:

[0230] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0231] Step 6:

[0232] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0233] Step 7:

[0234] The emotion engine recognizes the user's emotions. The emotion engine installed on the server analyzes the user's input and responses to detect the user's emotional state.

[0235] Step 8:

[0236] The system adjusts suggestions based on the user's emotions. The generated suggestions are adjusted based on the recognized emotional state of the user. For example, if the user appears dissatisfied, the suggestions are flexibly modified to make them more acceptable to the user.

[0237] Step 9:

[0238] The server returns the generated and adjusted proposals and analysis results to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and adjusted proposals in JSON format and sends it to the terminal as an HTTP response.

[0239] Step 10:

[0240] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0241] Step 11:

[0242] The terminal displays the extracted information to the user. Specifically, the screen displays the contract status as "In Contract," sales as "50 million yen," profit as "5 million yen," and the adjusted suggestion as "Please consider introducing new product A. This could increase profits by 10%."

[0243] Step 12:

[0244] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0245] (Example 2)

[0246] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0247] The present invention aims to provide optimal suggestions that take into account the user's emotions when the user acquires company information and receives suggestions based on the company's current situation. Conventional systems have a problem of low user satisfaction because suggestions are made unilaterally without considering the user's emotions.

[0248] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a company number or company name, means for transmitting the input company number or company name to the server, means for obtaining company information from a database based on the company number or company name received by the server, means for analyzing the obtained company information and generating a proposal, means for adjusting the generated proposal based on emotion recognition means, and means for displaying the adjusted proposal to the user. This makes it possible to make more appropriate and satisfying proposals that take the user's emotions into consideration.

[0249] A "company number" is a number assigned to uniquely identify a company.

[0250] A "company name" is a name used to identify a specific company.

[0251] A "user" refers to an individual or organization that attempts to obtain corporate information using the system.

[0252] A "terminal" is an electronic device used by a user to input information and communicate with a system, and includes personal computers and smartphones.

[0253] A "server" is a computer system that processes data received from users, accesses databases, performs data analysis, and transmits results.

[0254] A "database" is a data storage system used to systematically accumulate and manage various types of information within a company.

[0255] "Company information" refers to information that includes data such as contract status, sales, profits, and medium-term management plans related to a company.

[0256] A "proposal" is advice or recommendations generated based on company information, aimed at improving a company's profits or solving problems.

[0257] "Emotion recognition technology" refers to a technology that analyzes and recognizes emotions from a user's facial expressions, voice, and text.

[0258] "Adjustment" refers to changing the content or tone of a suggestion based on the user's emotions.

[0259] "Display" refers to visually showing the analysis results and suggestions on the device screen.

[0260] This invention is a system that, when a user enters a company number or company name, retrieves information on various contract statuses, sales, and profits of that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings.

[0261] First, the user enters a company number or company name into the terminal. The terminal sends the entered data to the server. Based on the received company number or company name, the server retrieves various information about the relevant company from its database. This information includes contract status, sales, profits, and medium-term business plans.

[0262] Next, the server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. Based on the analysis results, a generative AI model is used to generate optimal suggestions that take into account the company's medium-term management plan. For example, a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%," might be generated.

[0263] The server is equipped with an emotion engine to recognize user emotions. The emotion engine analyzes the user's voice, facial expressions, text input, etc., to identify the user's emotional state. Based on the recognized emotional state, the generated suggestions are adjusted. For example, if the user has a dissatisfied expression, the suggestions are flexibly modified to make them more acceptable to the user.

[0264] Finally, the server returns the generated suggestions and analysis results to the terminal in JSON format. The terminal analyzes the received response and displays the results to the user. These results include contract status, sales, profits, and suggestions tailored to specific situations. This allows the user to understand the company's current situation and make optimal business decisions.

[0265] As a concrete example, when a user enters and submits company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0266] An example of a prompt message would be something simple like, "Please enter company number '12345' and submit."

[0267] In this way, this system allows users to easily obtain detailed information about companies and optimal suggestions that address their emotions.

[0268] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0269] Step 1:

[0270] The user enters the company number or company name.

[0271] The user enters the company number or company name into the input field on the terminal. For example, the user enters the company number "12345" or the company name "ABC Corporation" into the terminal field and clicks the submit button. The information entered by the user at this point becomes the input data.

[0272] Step 2:

[0273] The device sends the request to the server.

[0274] The terminal sends the company number or company name entered by the user to the server. At this time, the terminal constructs the input data as JSON-formatted request data and sends an HTTP POST request to the server. The request data includes the company number "12345" or the company name "ABC Corporation".

[0275] Step 3:

[0276] The server retrieves company information.

[0277] The server accesses the database based on the received company number or company name and retrieves information about the corresponding company. Specifically, the server executes SQL queries to retrieve necessary data such as the company's contract status, sales, profits, and medium-term business plan. At this point, company information is output from the database based on the input data.

[0278] Step 4:

[0279] The server analyzes the data and generates suggestions.

[0280] The server conducts analysis based on the acquired corporate information. This analysis includes statistical data analysis considering the company's past performance and industry trends. The server uses a generative AI model to generate optimal proposals based on the analysis results and the medium-term business plan. For example, a proposal such as "Please consider introducing new product A. This may improve profits by 10%." is generated. Here, corporate information is input, and a proposal is output.

[0281] Step 5:

[0282] The emotion engine recognizes the user's emotion

[0283] The emotion engine installed on the server analyzes the user's voice, expression, and text input to recognize the emotion. Specifically, emotion analysis of the text input by the user and expression recognition using a webcam are performed. Here, the user's reaction data is input, and the emotional state is output.

[0284] Step 6:

[0285] Adjust the proposal based on the user's emotion

[0286] The server adjusts the proposal generated based on the recognized emotional state. If the emotion is positive, the proposal remains as it is; if it is negative, the tone and content of the proposal are flexibly changed. For example, the proposal content is adjusted to "Please consider introducing new product A. However, methods to suppress the initial cost are also proposed together." Here, the emotional state is input, and the adjusted proposal is output.

[0287] Step 7:

[0288] The server sends the result to the terminal

[0289] The server returns the adjusted proposal and analysis results to the terminal in JSON format. The response data includes the company's contract status, sales, profits, and adjusted proposal. For example, it might include data such as "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Proposal: Please consider introducing new product A. This could increase profits by 10%." Here, information including the adjusted proposal is output.

[0290] Step 8:

[0291] The device receives and displays the results.

[0292] The terminal receives a response from the server and displays the analyzed data and tailored suggestions to the user. The terminal has the function of displaying the received data on its screen. For example, the terminal's display might show "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Suggestion: Please consider introducing new product A. This could increase profits by 10%." At this point, the tailored suggestions and company information are output to the user.

[0293] Through the above processing steps, users can easily obtain optimal suggestions based on detailed company information and their own sentiments.

[0294] (Application Example 2)

[0295] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0296] Conventional systems can retrieve company information by having users enter an organization number or name, and generate proposals based on that information. However, they cannot provide flexible proposals that take into account the user's emotional state. Furthermore, if a proposal does not match the user's emotions, user satisfaction decreases, leading to a lower acceptance rate of the proposal. Therefore, there is a need for a system that adjusts proposals based on the user's emotions and provides more effective proposals.

[0297] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 2 is realized by the following means.

[0298] In this invention, the server

[0299] means for a user to input an organization number or organization name;

[0300] means for transmitting the input organization number or organization name to the server;

[0301] means for the server to obtain organization information from the database based on the received organization number or organization name;

[0302] means for analyzing the obtained organization information and generating a proposal;

[0303] means for displaying the generated proposal to the user;

[0304] means for recognizing the user's emotion;

[0305] means for adjusting the proposal based on the recognized emotion;

[0306] are included. Thereby, it becomes possible to provide a flexible and effective proposal considering the user's emotional state.

[0307] The "user" is a person or group who operates the system, inputs an organization number or organization name, and obtains organization information.

[0308] The "organization number" is an identification number unique to each organization and is a key for obtaining specific organization information from the database.

[0309] The "organization name" is the official name of the organization and is a key for obtaining specific organization information from the database.

[0310] A "server" is a device or system that processes data received from users and works in conjunction with a database to acquire and analyze information.

[0311] A "database" is an information management system that stores various types of information about an organization (such as contract status, sales, and profits).

[0312] A "proposal" is business advice or recommendations generated based on an analysis of organizational information and the medium-term management plan.

[0313] An "emotion engine" is an artificial intelligence or machine learning model that recognizes a user's emotional state and adjusts its behavior accordingly.

[0314] "Organizational information" refers to data that includes information on the organization's contract status, sales, profits, and medium-term management plan.

[0315] "Analysis" refers to a series of calculations and processes that take acquired data, interpret it, and derive meaning from it.

[0316] "Display" refers to a means of visually conveying information obtained from the server or generated suggestions to the user.

[0317] "Adjustment" is the process of modifying generated suggestions to the most optimal content based on the recognized emotional state of the user.

[0318] This invention is a system that, by allowing users to input an organization number or organization name, retrieves information on various contract statuses, revenues, and profits of an organization, and further provides proposals based on its medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview of the system and specific embodiments are described below.

[0319] System Overview

[0320] The system consists of a smartphone application as the front-end, a back-end server, an organizational information database, and an emotion engine. Users enter an organizational number or name through the smartphone application and send this data to the server. The server receives the input data and retrieves the relevant organizational information from the database. Next, it analyzes the retrieved data and generates suggestions based on the information from the medium-term management plan. The emotion engine then recognizes the user's emotions and adjusts the suggestions accordingly. Finally, the adjusted suggestions are displayed on the smartphone.

[0321] System configuration and operation method

[0322] Hardware and software to be used

[0323] hardware

[0324] Smartphone: A device that allows users to access a system, input data, and view results.

[0325] software

[0326] Frontend: React Native (for mobile application development)

[0327] Backend: Node.js, Express.js (server-side)

[0328] Database: MongoDB (stores organizational information)

[0329] Emotion Engine: TENSORFLOW® (Registered Trademark) (User emotion analysis)

[0330] External API: AI model API (for organizational data analysis)

[0331] Server operation

[0332] The server receives an organization number or organization name sent by the user and uses that information to retrieve various information about the corresponding organization from the database. Specifically, it processes requests using Node.js and Express.js and retrieves organization information from MongoDB. It analyzes the retrieved data and uses an AI model to generate proposals based on the medium-term management plan. The AI ​​model's API is used for this proposal generation.

[0333] The emotion engine analyzes the user's emotions from voice and text input, and adjusts suggestions as needed. TensorFlow is used in the emotion engine, enabling real-time emotion recognition. Finally, the adjusted suggestions are sent to the frontend in JSON format and displayed on the smartphone screen.

[0334] Frontend behavior

[0335] A smartphone application developed using React Native provides a UI where the user enters an organization number or organization name and sends it to a backend server. The application receives the results returned from the server and displays them to the user in an appropriate format.

[0336] Examples of specific cases and prompt statements

[0337] As a concrete example, a user enters the organization number "12345" into a smartphone application and submits it. The server retrieves information from the database based on "12345" and analyzes the company's revenue, profits, and contract status. The AI ​​model generates a suggestion, "Consider introducing new product A," but if the user's emotions are perceived as dissatisfied, the suggestion is adjusted and displayed as "Consider introducing new product B."

[0338] Examples of prompt messages are as follows:

[0339] "Based on the organization number or name entered by the user, retrieve the organization's contract status, revenue, profits, etc., and generate a business proposal based on the medium-term management plan. Also, adjust the proposal considering the user's sentiment."

[0340] The above describes the specific forms for carrying out the invention.

[0341] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0342] Step 1:

[0343] The user enters the organization number or organization name into the smartphone application.

[0344] Input data: Organization number "12345"

[0345] Output data: The input data is stored within the application and ready to be sent to the server in the next step.

[0346] Specific action: The user enters the organization number into the application's input field and clicks the submit button.

[0347] Step 2:

[0348] The terminal sends the input data to the server.

[0349] Input data: User-entered organization number "12345"

[0350] Output data: The server receives the organization number.

[0351] Specific operation: An application created using React Native will send API requests to the server based on user input.

[0352] Step 3:

[0353] Based on the organization number received by the server, the corresponding organization information is retrieved from the database.

[0354] Input data: Organization number "12345" received by the server

[0355] Output data: Organizational information obtained from the database (contract status, sales, profit, medium-term management plan)

[0356] Specific operation: Using Node.js and MongoDB, the server executes database queries to retrieve the necessary organizational information.

[0357] Step 4:

[0358] The server analyzes the organizational information it has acquired and generates proposals based on the medium-term management plan.

[0359] Input data: Acquired organizational information

[0360] Output data: Generated proposal (Example: "Please consider introducing new product A.")

[0361] Specific operation: Call the AI ​​model's API, analyze organizational information as input data, and generate suggestions.

[0362] Step 5:

[0363] The emotion engine recognizes the user's emotions.

[0364] Input data: User's voice, facial expressions, text, etc.

[0365] Output data: Recognized user emotional state

[0366] Specific operation: Use TensorFlow to analyze user emotions in real time.

[0367] Step 6:

[0368] Based on the perceived emotions, the generated suggestions are adjusted.

[0369] Input data: Recognized user's emotional state, generated suggestions

[0370] Output data: Adjusted proposal (e.g., "Please consider introducing new product B.")

[0371] Specific actions: Re-evaluate the proposed content based on the user's emotional state and adjust it to make it more acceptable to the user.

[0372] Step 7:

[0373] The server sends the adjusted suggestions and analysis results to the terminal.

[0374] Input data: Adjusted proposal, analysis results

[0375] Output data: JSON format data for display on the terminal.

[0376] Specific operation: Using Node.js, the adjusted suggestions and analysis results are converted to JSON format and sent to the terminal.

[0377] Step 8:

[0378] The terminal receives a response from the server and displays the suggested content to the user.

[0379] Input data: JSON data received from the server

[0380] Output data: Suggestions displayed in a format that users can visually confirm.

[0381] Specific operation: Using React Native, the received data is reflected in the UI and the results are displayed to the user.

[0382] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0383] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0384] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0385] [Second Embodiment]

[0386] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0387] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0388] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0389] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0390] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0391] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0392] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0393] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0394] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0395] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0396] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0397] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0398] This invention is a system that allows users to input a company number or company name to obtain information on various contract statuses, sales, and profits of that company, and further provides suggestions based on the company's medium-term management plan. The following describes the overall overview, operation method, and specific examples of the system.

[0399] System Overview

[0400] The system consists of a terminal where the user enters a company number or company name, and a server that receives, analyzes, and responds to the data. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, generates suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0401] How the system works

[0402] 1. The user enters information.

[0403] The user enters the company number or company name into the input field on the terminal.

[0404] For example, a user enters the company number "12345" and clicks the submit button.

[0405] 2. The device sends the request to the server.

[0406] The terminal has the function of sending input data to the server.

[0407] When the terminal sends the company number "12345" to the server, the server receives it.

[0408] 3. The server retrieves company information.

[0409] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0410] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0411] 4. The server analyzes the data and generates suggestions.

[0412] Based on the acquired data, the server analyzes the company's current situation.

[0413] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0414] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0415] 5. The server sends the results to the terminal.

[0416] The server sends the generated proposals and analysis results to the terminal in JSON format.

[0417] The data includes contract status, sales, profits, and proposals.

[0418] 6. The device receives and displays the results.

[0419] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0420] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", Proposal "Please consider introducing new product A. This could potentially increase profits by 10%."

[0421] Specific example

[0422] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. This proposal states, "Please consider introducing new product A. This could potentially increase profits by 10%." This information is then sent back to the terminal and displayed to the user.

[0423] The following describes the processing flow.

[0424] Step 1:

[0425] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0426] Step 2:

[0427] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0428] Step 3:

[0429] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0430] Step 4:

[0431] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0432] Step 5:

[0433] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0434] Step 6:

[0435] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0436] Step 7:

[0437] The server sends the generated proposals and analysis results back to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and proposals in JSON format and sends it to the terminal as an HTTP response.

[0438] Step 8:

[0439] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0440] Step 9:

[0441] The terminal displays the extracted information to the user. Specifically, the screen displays contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Please consider introducing new product A. This could increase profits by 10%."

[0442] Step 10:

[0443] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0444] (Example 1)

[0445] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0446] Conventional corporate information acquisition systems struggled to quickly and accurately retrieve necessary information and provide useful suggestions based on analysis results, even when users entered a company number or company name. In particular, they lacked a means to generate concrete suggestions based on a company's medium-term management plan, preventing users from making effective decisions.

[0447] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0448] In this invention, the server includes means for the user to input an identification number or identification name, means for transmitting the input identification number or identification name to a central processing unit, means for the central processing unit to retrieve information from a data storage device based on the received identification number or identification name, means for analyzing the retrieved information and generating recommendations, and means for displaying the generated recommendations to the user. This enables the user to quickly and accurately obtain company information and receive useful suggestions based on the analysis results.

[0449] An "identification number" is a numerical or string of characters used to uniquely identify a specific individual or organization.

[0450] An "identification name" is a name or label used to uniquely identify a particular individual or organization.

[0451] A "central processing unit" is a computer system used for processing and managing data.

[0452] A "data storage device" is a database or other storage system used to store and manage information.

[0453] A "recommendation" is a suggestion or instruction generated based on specific data and analysis results.

[0454] "Financial indicators" are metrics used to evaluate a company's financial condition, and include sales, profits, and other metrics.

[0455] "Contract status" refers to information about the current status of contracts a company is undertaking.

[0456] "Information" refers to data obtained from data storage devices, including a company's financial indicators, contract status, and medium-term management plans.

[0457] This invention is a system that allows users to input a company number or company name to obtain various information about that company, and then generates proposals based on that information and its medium-term management plan. The specific form of this system is described below.

[0458] System Configuration

[0459] This system primarily consists of user-operated terminals and servers that process data. The system transmits and receives data between the terminals and servers via a communication network.

[0460] Hardware and software to be used

[0461] Devices: PC (Windows 10), smartphones (iOS / Android), etc.

[0462] Server: Linux server (Ubuntu)

[0463] Database: MySQL, PostgreSQL

[0464] Analysis software: Python, R

[0465] Proposal generation: Generative AI model (OpenAI GPT)

[0466] Specific examples of the system

[0467] The user enters the company number "12345" into the input field on the terminal and clicks the submit button. This action causes the terminal to send the company number "12345" to the server. The server uses this company number to retrieve information about the corresponding company from its database.

[0468] The information obtained may include, for example:

[0469] Contract status: "Currently under contract"

[0470] Sales: "50 million yen"

[0471] Profit: "5 million yen"

[0472] Information on the medium-term management plan

[0473] The server analyzes this information and assesses the company's current situation. Next, it uses a generative AI model to generate suggestions by prompting the following sentences:

[0474] "Please generate a proposal based on the contract status, sales, profits, and medium-term business plan for company number 12345."

[0475] The proposals generated by the generative AI model include, for example, the following:

[0476] "Please consider introducing new product A. This could potentially increase profits by 10%."

[0477] The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal. The terminal parses the received JSON data and displays it in the user interface. HTML and CSS are used for the display format. Finally, the user sees the following information on the terminal screen:

[0478] Contract status: "Currently under contract"

[0479] Sales: "50 million yen"

[0480] Profit: "5 million yen"

[0481] Proposal: "Please consider introducing new product A. This could potentially increase profits by 10%."

[0482] In this way, users can quickly and accurately obtain the necessary company information and receive useful suggestions.

[0483] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0484] Step 1: The user enters the company number or company name into the terminal.

[0485] Input: Company number or company name (e.g., "12345")

[0486] Output: Input data stored within the terminal

[0487] Specific action: The user enters the company number "12345" into the terminal's input field and clicks the submit button. This action stores the data from the input field into a variable within the terminal.

[0488] Step 2: The terminal sends the input data to the server.

[0489] Input: Company number or company name stored on the terminal

[0490] Output: Request data sent to the server

[0491] Specific operation: The terminal sends the entered company number "12345" to the server in the form of an HTTP request. For example, a request in the format POST / api / getCompanyInfo { "company_id": "12345"} is issued. The server receives this request.

[0492] Step 3: The server retrieves company information from the database.

[0493] Input: Company number "12345" included in the HTTP request

[0494] Output: Information on the company's contract status, sales, profits, and medium-term management plan.

[0495] Specific operation: The server issues a query to the database based on the received company number "12345". For example, it executes an SQL query such as SELECT FROM companies WHERE company_id='12345' to retrieve relevant company information from the database.

[0496] Step 4: The server analyzes the acquired company information and generates proposals.

[0497] Input: Company information obtained from a database (contract status, sales, profits, medium-term business plan)

[0498] Output: Generated proposals and analysis results

[0499] Specific operation: The server analyzes data such as a company's sales and profits to evaluate the company's current situation. Based on the analysis results, it uses a generating AI model and, upon receiving the prompt message "Generate proposals based on the contract status, sales, profits, and medium-term management plan for company number 12345," the AI ​​generates specific recommendations.

[0500] Step 5: The server sends the generated results to the terminal.

[0501] Input: Generated proposals and analysis results

[0502] Output: Data in JSON format

[0503] Specific operation: The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal as an HTTP response. For example, { "contract_status": "Contract in progress", "sales": "50 million yen", "profit": "5 million yen", "suggestion": "Consider introducing new product A. This could increase profits by 10%."}.

[0504] Step 6: The device receives the results and displays them to the user.

[0505] Input: JSON format data received from the server

[0506] Output: Information displayed to the user (contract status, sales, profit, proposal)

[0507] Specific operation: The terminal parses the received JSON data and formats it using HTML and CSS to display it in the user interface. The user checks the parsing results and suggestions displayed on the terminal screen. For example, the screen might show contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Consider introducing new product A. This could increase profits by 10%."

[0508] (Application Example 1)

[0509] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0510] Conventional organizational information acquisition systems only retrieve and display information based on entered company numbers and names, lacking the functionality to automatically generate specific transaction proposals for companies. Therefore, users must analyze and make decisions based on the information they receive, which is inefficient. Furthermore, the process of analyzing company information is burdensome for users, resulting in insufficient support for accurate decision-making. Thus, a system is needed that can solve these problems and generate proposals quickly and accurately.

[0511] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0512] In this invention, the server includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. This makes it possible to provide users with more effective and efficient proposals and automate the process of analyzing corporate information.

[0513] An "identification number" is a number used to uniquely identify a particular organization.

[0514] "Organization name" refers to the name of a specific organization.

[0515] A "computer" refers to an electronic device used for processing and analyzing data, and usually includes a server.

[0516] A "storage medium" is a physical or electronic device used to store data, including hard disks and cloud storage.

[0517] "Organizational information" refers to data relating to a specific organization, including financial information such as contract status, sales, and profits.

[0518] "Data analysis" is a technique for extracting meaningful information based on acquired data and for understanding and evaluating the current situation.

[0519] A "deal proposal" is the process of providing specific actions and recommendations for a particular organization based on the results of data analysis.

[0520] A "generative AI model" is a model trained to perform data analysis and generate suggestions using artificial intelligence technology.

[0521] "Revenue" refers to the total income an organization earns through the provision of goods and services.

[0522] "Profit" refers to the net profit remaining after deducting all expenses from revenue.

[0523] A description in detail will be given of embodiments for carrying out this invention.

[0524] This system includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. The system is executed through user operations.

[0525] First, the user enters an identification number or organization name into the input field on the terminal. The terminal then sends the entered data to a server, which is a computer. Based on the received identification number or organization name, the server retrieves the corresponding organization information from a storage medium. This storage medium contains financial information such as the organization's contract status, sales, and profits.

[0526] The server performs data analysis based on the acquired organizational information. This analysis includes, for example, evaluating sales performance and calculating profit margins. Next, the server uses a generative AI model to generate specific deal proposals from the analysis results. These proposals include specific actions and recommendations that the organization should take.

[0527] The generated suggestions and analysis results are sent to the terminal and displayed to the user. For example, along with information such as contract status "In Contract," sales "50 million yen," and profit "5 million yen," a suggestion such as "Consider introducing new product A. This could increase profits by 10%" might be displayed.

[0528] As a concrete example, when a user enters and submits the identification number "12345," the server retrieves information about the corresponding organization from the storage medium and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and based on the generated AI model, a suggestion is created: "Consider introducing new product A. This could potentially increase profits by 10%." This suggestion and the analysis results are sent back to the terminal and displayed to the user.

[0529] Examples of prompt statements for a generative AI model are as follows:

[0530] "Retrieve company information for company number "12345," and analyze its sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on its medium-term business plan."

[0531] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0532] Step 1:

[0533] The user enters an identification number or organization name into the input field on the terminal. Let's say the user enters the organization name "ABC Company". The input is performed via the terminal's GUI, and after completion, the input data is confirmed by pressing the submit button. The input data is string data based on the identification number or organization name.

[0534] Step 2:

[0535] The terminal sends the entered identification number or organization name to the server. For example, it sends the data "ABC Company" to the server as an HTTP request. This request is formatted in JSON format so that the server can correctly receive and parse the data. Here, the input data is converted to a transmission format.

[0536] Step 3:

[0537] The server retrieves organizational information from the storage medium based on the identification number or organization name received. For example, it might query the database for "ABC Company" to retrieve information such as contract status, sales, and profits. This query extracts the organizational information from the database and returns it to the server. The output is organizational information data structured in JSON format.

[0538] Step 4:

[0539] The server performs data analysis based on the acquired organizational information. For example, it evaluates sales performance and calculates profit margins. This analysis may utilize statistical analysis and data mining techniques. This process generates indicators and numerical values ​​for evaluating the current state of the organization. The input is organizational information data, and the output is the analysis results.

[0540] Step 5:

[0541] The server uses a generation AI model to generate transaction proposals from data analysis results. For example, the prompt "Retrieve company information for company number 'ABC Corporation', analyze sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on the medium-term management plan." is input to the generation AI model, which then generates proposals such as new product introductions. This process utilizes machine learning models to perform advanced predictions and suggestions. The input is the analysis results, and the output is the transaction proposals.

[0542] Step 6:

[0543] The generated suggestions and analysis results are sent from the server to the terminal. The terminal receives this data and displays it to the user in a visually easy-to-understand format. For example, using a dashboard or graph, it might display information such as contract status ("In Contract"), sales ("50 million yen"), and profit ("5 million yen"), along with a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." The input is the generated suggestions and analysis results, and the output is the display on the user interface.

[0544] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0545] This invention is a system that, upon user input of a company number or company name, retrieves information on various contract statuses, sales, and profits for that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview, operation method, and specific examples of the system are described below.

[0546] System Overview

[0547] The system consists of a terminal where the user enters a company number or company name, a server that receives, analyzes, and responds to the input data, and an emotion engine that recognizes the user's emotions. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, adjusts the generated suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0548] How the system works

[0549] 1. The user enters information.

[0550] The user enters the company number or company name into the input field on the terminal.

[0551] For example, a user enters the company number "12345" and clicks the submit button.

[0552] 2. The device sends the request to the server.

[0553] The terminal has the function of sending input data to the server.

[0554] When the terminal sends the company number "12345" to the server, the server receives it.

[0555] 3. The server retrieves company information.

[0556] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0557] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0558] 4. The server analyzes the data and generates suggestions.

[0559] Based on the acquired data, the server analyzes the company's current situation.

[0560] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0561] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0562] 5. The emotion engine recognizes the user's emotions.

[0563] The server is equipped with an emotion engine that recognizes emotions from user input and responses.

[0564] The emotion engine analyzes the user's voice, facial expressions, text input, etc., to detect the user's emotional state.

[0565] 6. Adjust suggestions based on user sentiment.

[0566] Based on the recognized emotional state of the user, the generated suggestions are adjusted.

[0567] For example, if a user looks dissatisfied, the proposal can be flexibly modified to make it more acceptable to the user.

[0568] 7. The server sends the results to the terminal.

[0569] The server returns the generated proposal and analysis results to the terminal in JSON format.

[0570] The data includes recommendations tailored based on contract status, sales, profits, and user sentiment.

[0571] 8. The device receives and displays the results.

[0572] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0573] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", and Adjusted proposal "Please consider introducing new product A. This could increase profits by 10%."

[0574] Specific example

[0575] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0579] Step 2:

[0580] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0581] Step 3:

[0582] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0583] Step 4:

[0584] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0585] Step 5:

[0586] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0587] Step 6:

[0588] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0589] Step 7:

[0590] The emotion engine recognizes the user's emotions. The emotion engine installed on the server analyzes the user's input and responses to detect the user's emotional state.

[0591] Step 8:

[0592] The system adjusts suggestions based on the user's emotions. The generated suggestions are adjusted based on the recognized emotional state of the user. For example, if the user appears dissatisfied, the suggestions are flexibly modified to make them more acceptable to the user.

[0593] Step 9:

[0594] The server returns the generated and adjusted proposals and analysis results to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and adjusted proposals in JSON format and sends it to the terminal as an HTTP response.

[0595] Step 10:

[0596] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0597] Step 11:

[0598] The terminal displays the extracted information to the user. Specifically, the screen displays the contract status as "In Contract," sales as "50 million yen," profit as "5 million yen," and the adjusted suggestion as "Please consider introducing new product A. This could increase profits by 10%."

[0599] Step 12:

[0600] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0601] (Example 2)

[0602] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0603] The present invention aims to provide optimal suggestions that take into account the user's emotions when the user acquires company information and receives suggestions based on the company's current situation. Conventional systems have a problem of low user satisfaction because suggestions are made unilaterally without considering the user's emotions.

[0604] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a company number or company name, means for transmitting the input company number or company name to the server, means for obtaining company information from a database based on the company number or company name received by the server, means for analyzing the obtained company information and generating a proposal, means for adjusting the generated proposal based on emotion recognition means, and means for displaying the adjusted proposal to the user. This makes it possible to make more appropriate and satisfying proposals that take the user's emotions into consideration.

[0605] A "company number" is a number assigned to uniquely identify a company.

[0606] A "company name" is a name used to identify a specific company.

[0607] A "user" refers to an individual or organization that attempts to obtain corporate information using the system.

[0608] A "terminal" is an electronic device used by a user to input information and communicate with a system, and includes personal computers and smartphones.

[0609] A "server" is a computer system that processes data received from users, accesses databases, performs data analysis, and transmits results.

[0610] A "database" is a data storage system used to systematically accumulate and manage various types of information within a company.

[0611] "Company information" refers to information that includes data such as contract status, sales, profits, and medium-term management plans related to a company.

[0612] A "proposal" is advice or recommendations generated based on company information, aimed at improving a company's profits or solving problems.

[0613] "Emotion recognition technology" refers to a technology that analyzes and recognizes emotions from a user's facial expressions, voice, and text.

[0614] "Adjustment" refers to changing the content or tone of a suggestion based on the user's emotions.

[0615] "Display" refers to visually showing the analysis results and suggestions on the device screen.

[0616] This invention is a system that, when a user enters a company number or company name, retrieves information on various contract statuses, sales, and profits of that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings.

[0617] First, the user enters a company number or company name into the terminal. The terminal sends the entered data to the server. Based on the received company number or company name, the server retrieves various information about the relevant company from its database. This information includes contract status, sales, profits, and medium-term business plans.

[0618] Next, the server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. Based on the analysis results, a generative AI model is used to generate optimal suggestions that take into account the company's medium-term management plan. For example, a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%," might be generated.

[0619] The server is equipped with an emotion engine to recognize user emotions. The emotion engine analyzes the user's voice, facial expressions, text input, etc., to identify the user's emotional state. Based on the recognized emotional state, the generated suggestions are adjusted. For example, if the user has a dissatisfied expression, the suggestions are flexibly modified to make them more acceptable to the user.

[0620] Finally, the server returns the generated suggestions and analysis results to the terminal in JSON format. The terminal analyzes the received response and displays the results to the user. These results include contract status, sales, profits, and suggestions tailored to specific situations. This allows the user to understand the company's current situation and make optimal business decisions.

[0621] As a concrete example, when a user enters and submits company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0622] An example of a prompt message would be something simple like, "Please enter company number '12345' and submit."

[0623] In this way, this system allows users to easily obtain detailed information about companies and optimal suggestions that address their emotions.

[0624] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0625] Step 1:

[0626] The user enters the company number or company name.

[0627] The user enters the company number or company name into the input field on the terminal. For example, the user enters the company number "12345" or the company name "ABC Corporation" into the terminal field and clicks the submit button. The information entered by the user at this point becomes the input data.

[0628] Step 2:

[0629] The device sends the request to the server.

[0630] The terminal sends the company number or company name entered by the user to the server. At this time, the terminal constructs the input data as JSON-formatted request data and sends an HTTP POST request to the server. The request data includes the company number "12345" or the company name "ABC Corporation".

[0631] Step 3:

[0632] The server retrieves company information.

[0633] The server accesses the database based on the received company number or company name and retrieves information about the corresponding company. Specifically, the server executes SQL queries to retrieve necessary data such as the company's contract status, sales, profits, and medium-term business plan. At this point, company information is output from the database based on the input data.

[0634] Step 4:

[0635] The server analyzes the data and generates suggestions.

[0636] The server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. The server uses a generative AI model to generate optimal suggestions based on the analysis results and the medium-term management plan. For example, it might generate a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." Here, company information is taken as input, and suggestions are output.

[0637] Step 5:

[0638] The emotion engine recognizes the user's emotions.

[0639] The emotion engine installed on the server analyzes the user's voice, facial expressions, and text input to recognize emotions. Specifically, it performs sentiment analysis on the text entered by the user and facial recognition using a webcam. Here, the emotional state is output based on the user's response data.

[0640] Step 6:

[0641] Adjust suggestions based on user sentiment.

[0642] The server adjusts the suggestions generated based on the recognized emotional state. If the emotion is positive, the suggestion remains unchanged; if it is negative, the tone and content of the suggestion are flexibly modified. For example, the suggestion might be adjusted to "Please consider introducing new product A. However, we will also suggest ways to reduce initial costs." Here, the emotional state is taken as input, and the adjusted suggestion is output.

[0643] Step 7:

[0644] The server sends the results to the terminal.

[0645] The server returns the adjusted proposal and analysis results to the terminal in JSON format. The response data includes the company's contract status, sales, profits, and adjusted proposal. For example, it might include data such as "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Proposal: Please consider introducing new product A. This could increase profits by 10%." Here, information including the adjusted proposal is output.

[0646] Step 8:

[0647] The device receives and displays the results.

[0648] The terminal receives a response from the server and displays the analyzed data and tailored suggestions to the user. The terminal has the function of displaying the received data on its screen. For example, the terminal's display might show "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Suggestion: Please consider introducing new product A. This could increase profits by 10%." At this point, the tailored suggestions and company information are output to the user.

[0649] Through the above processing steps, users can easily obtain optimal suggestions based on detailed company information and their own sentiments.

[0650] (Application Example 2)

[0651] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0652] Conventional systems can retrieve company information by having users enter an organization number or name, and generate proposals based on that information. However, they cannot provide flexible proposals that take into account the user's emotional state. Furthermore, if a proposal does not match the user's emotions, user satisfaction decreases, leading to a lower acceptance rate of the proposal. Therefore, there is a need for a system that adjusts proposals based on the user's emotions and provides more effective proposals.

[0653] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0654] In this invention, the server is

[0655] A means for the user to enter an organization number or organization name,

[0656] A means of sending the entered organization number or organization name to the server,

[0657] A means for obtaining organizational information from a database based on the organizational number or organizational name received by the server,

[0658] A means for analyzing acquired organizational information and generating proposals,

[0659] A means of displaying the generated suggestions to the user,

[0660] Means of recognizing user emotions,

[0661] Means of adjusting proposals based on perceived emotions,

[0662] This includes providing flexible and effective suggestions that take into account the user's emotional state.

[0663] A "user" is a person or organization that operates the system and obtains organizational information by entering an organizational number or organizational name.

[0664] An "organizational number" is a unique identification number for each organization and serves as a key for retrieving specific organizational information from the database.

[0665] The "organization name" is the official name of the organization and serves as a key for retrieving specific organizational information from the database.

[0666] A "server" is a device or system that processes data received from users and works in conjunction with a database to acquire and analyze information.

[0667] A "database" is an information management system that stores various types of information about an organization (such as contract status, sales, and profits).

[0668] A "proposal" is business advice or recommendations generated based on an analysis of organizational information and the medium-term management plan.

[0669] An "emotion engine" is an artificial intelligence or machine learning model that recognizes a user's emotional state and adjusts its behavior accordingly.

[0670] "Organizational information" refers to data that includes information on the organization's contract status, sales, profits, and medium-term management plan.

[0671] "Analysis" refers to a series of calculations and processes that take acquired data, interpret it, and derive meaning from it.

[0672] "Display" refers to a means of visually conveying information obtained from the server or generated suggestions to the user.

[0673] "Adjustment" is the process of modifying generated suggestions to the most optimal content based on the recognized emotional state of the user.

[0674] This invention is a system that, by allowing users to input an organization number or organization name, retrieves information on various contract statuses, revenues, and profits of an organization, and further provides proposals based on its medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview of the system and specific embodiments are described below.

[0675] System Overview

[0676] The system consists of a smartphone application as the front-end, a back-end server, an organizational information database, and an emotion engine. Users enter an organizational number or name through the smartphone application and send this data to the server. The server receives the input data and retrieves the relevant organizational information from the database. Next, it analyzes the retrieved data and generates suggestions based on the information from the medium-term management plan. The emotion engine then recognizes the user's emotions and adjusts the suggestions accordingly. Finally, the adjusted suggestions are displayed on the smartphone.

[0677] System configuration and operation method

[0678] Hardware and software to be used

[0679] hardware

[0680] Smartphone: A device that allows users to access a system, input data, and view results.

[0681] software

[0682] Frontend: React Native (for mobile application development)

[0683] Backend: Node.js, Express.js (server-side)

[0684] Database: MongoDB (stores organizational information)

[0685] Emotion engine: TensorFlow (user emotion analysis)

[0686] External API: AI model API (for organizational data analysis)

[0687] Server operation

[0688] The server receives an organization number or organization name sent by the user and uses that information to retrieve various information about the corresponding organization from the database. Specifically, it processes requests using Node.js and Express.js and retrieves organization information from MongoDB. It analyzes the retrieved data and uses an AI model to generate proposals based on the medium-term management plan. The AI ​​model's API is used for this proposal generation.

[0689] The emotion engine analyzes the user's emotions from voice and text input, and adjusts suggestions as needed. TensorFlow is used in the emotion engine, enabling real-time emotion recognition. Finally, the adjusted suggestions are sent to the frontend in JSON format and displayed on the smartphone screen.

[0690] Frontend behavior

[0691] A smartphone application developed using React Native provides a UI where the user enters an organization number or organization name and sends it to a backend server. The application receives the results returned from the server and displays them to the user in an appropriate format.

[0692] Examples of specific cases and prompt statements

[0693] As a concrete example, a user enters the organization number "12345" into a smartphone application and submits it. The server retrieves information from the database based on "12345" and analyzes the company's revenue, profits, and contract status. The AI ​​model generates a suggestion, "Consider introducing new product A," but if the user's emotions are perceived as dissatisfied, the suggestion is adjusted and displayed as "Consider introducing new product B."

[0694] Examples of prompt messages are as follows:

[0695] "Based on the organization number or name entered by the user, retrieve the organization's contract status, revenue, profits, etc., and generate a business proposal based on the medium-term management plan. Also, adjust the proposal considering the user's sentiment."

[0696] The above describes the specific forms for carrying out the invention.

[0697] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0698] Step 1:

[0699] The user enters the organization number or organization name into the smartphone application.

[0700] Input data: Organization number "12345"

[0701] Output data: The input data is stored within the application and ready to be sent to the server in the next step.

[0702] Specific action: The user enters the organization number into the application's input field and clicks the submit button.

[0703] Step 2:

[0704] The terminal sends the input data to the server.

[0705] Input data: User-entered organization number "12345"

[0706] Output data: The server receives the organization number.

[0707] Specific operation: An application created using React Native will send API requests to the server based on user input.

[0708] Step 3:

[0709] Based on the organization number received by the server, the corresponding organization information is retrieved from the database.

[0710] Input data: Organization number "12345" received by the server

[0711] Output data: Organizational information obtained from the database (contract status, sales, profit, medium-term management plan)

[0712] Specific operation: Using Node.js and MongoDB, the server executes database queries to retrieve the necessary organizational information.

[0713] Step 4:

[0714] The server analyzes the organizational information it has acquired and generates proposals based on the medium-term management plan.

[0715] Input data: Acquired organizational information

[0716] Output data: Generated proposal (Example: "Please consider introducing new product A.")

[0717] Specific operation: Call the AI ​​model's API, analyze organizational information as input data, and generate suggestions.

[0718] Step 5:

[0719] The emotion engine recognizes the user's emotions.

[0720] Input data: User's voice, facial expressions, text, etc.

[0721] Output data: Recognized user emotional state

[0722] Specific operation: Use TensorFlow to analyze user emotions in real time.

[0723] Step 6:

[0724] Based on the perceived emotions, the generated suggestions are adjusted.

[0725] Input data: Recognized user's emotional state, generated suggestions

[0726] Output data: Adjusted proposal (e.g., "Please consider introducing new product B.")

[0727] Specific actions: Re-evaluate the proposed content based on the user's emotional state and adjust it to make it more acceptable to the user.

[0728] Step 7:

[0729] The server sends the adjusted suggestions and analysis results to the terminal.

[0730] Input data: Adjusted proposal, analysis results

[0731] Output data: JSON format data for display on the terminal.

[0732] Specific operation: Using Node.js, the adjusted suggestions and analysis results are converted to JSON format and sent to the terminal.

[0733] Step 8:

[0734] The terminal receives a response from the server and displays the suggested content to the user.

[0735] Input data: JSON data received from the server

[0736] Output data: Suggestions displayed in a format that users can visually confirm.

[0737] Specific operation: Using React Native, the received data is reflected in the UI and the results are displayed to the user.

[0738] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0739] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0740] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0741] [Third Embodiment]

[0742] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0743] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0744] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0745] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0746] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0747] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0748] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0749] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0750] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0751] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0752] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0753] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0754] This invention is a system that allows users to input a company number or company name to obtain information on various contract statuses, sales, and profits of that company, and further provides suggestions based on the company's medium-term management plan. The following describes the overall overview, operation method, and specific examples of the system.

[0755] System Overview

[0756] The system consists of a terminal where the user enters a company number or company name, and a server that receives, analyzes, and responds to the data. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, generates suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0757] How the system works

[0758] 1. The user enters information.

[0759] The user enters the company number or company name into the input field on the terminal.

[0760] For example, a user enters the company number "12345" and clicks the submit button.

[0761] 2. The device sends the request to the server.

[0762] The terminal has the function of sending input data to the server.

[0763] When the terminal sends the company number "12345" to the server, the server receives it.

[0764] 3. The server retrieves company information.

[0765] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0766] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0767] 4. The server analyzes the data and generates suggestions.

[0768] Based on the acquired data, the server analyzes the company's current situation.

[0769] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0770] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0771] 5. The server sends the results to the terminal.

[0772] The server sends the generated proposals and analysis results to the terminal in JSON format.

[0773] The data includes contract status, sales, profits, and proposals.

[0774] 6. The device receives and displays the results.

[0775] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0776] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", Proposal "Please consider introducing new product A. This could potentially increase profits by 10%."

[0777] Specific example

[0778] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. This proposal states, "Please consider introducing new product A. This could potentially increase profits by 10%." This information is then sent back to the terminal and displayed to the user.

[0779] The following describes the processing flow.

[0780] Step 1:

[0781] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0782] Step 2:

[0783] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0784] Step 3:

[0785] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0786] Step 4:

[0787] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0788] Step 5:

[0789] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0790] Step 6:

[0791] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0792] Step 7:

[0793] The server sends the generated proposals and analysis results back to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and proposals in JSON format and sends it to the terminal as an HTTP response.

[0794] Step 8:

[0795] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0796] Step 9:

[0797] The terminal displays the extracted information to the user. Specifically, the screen displays contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Please consider introducing new product A. This could increase profits by 10%."

[0798] Step 10:

[0799] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0800] (Example 1)

[0801] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0802] Conventional corporate information acquisition systems struggled to quickly and accurately retrieve necessary information and provide useful suggestions based on analysis results, even when users entered a company number or company name. In particular, they lacked a means to generate concrete suggestions based on a company's medium-term management plan, preventing users from making effective decisions.

[0803] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0804] In this invention, the server includes means for the user to input an identification number or identification name, means for transmitting the input identification number or identification name to a central processing unit, means for the central processing unit to retrieve information from a data storage device based on the received identification number or identification name, means for analyzing the retrieved information and generating recommendations, and means for displaying the generated recommendations to the user. This enables the user to quickly and accurately obtain company information and receive useful suggestions based on the analysis results.

[0805] An "identification number" is a numerical or string of characters used to uniquely identify a specific individual or organization.

[0806] An "identification name" is a name or label used to uniquely identify a particular individual or organization.

[0807] A "central processing unit" is a computer system used for processing and managing data.

[0808] A "data storage device" is a database or other storage system used to store and manage information.

[0809] A "recommendation" is a suggestion or instruction generated based on specific data and analysis results.

[0810] "Financial indicators" are metrics used to evaluate a company's financial condition, and include sales, profits, and other metrics.

[0811] "Contract status" refers to information about the current status of contracts a company is undertaking.

[0812] "Information" refers to data obtained from data storage devices, including a company's financial indicators, contract status, and medium-term management plans.

[0813] This invention is a system that allows users to input a company number or company name to obtain various information about that company, and then generates proposals based on that information and its medium-term management plan. The specific form of this system is described below.

[0814] System Configuration

[0815] This system primarily consists of user-operated terminals and servers that process data. The system transmits and receives data between the terminals and servers via a communication network.

[0816] Hardware and software to be used

[0817] Devices: PC (Windows 10), smartphones (iOS / Android), etc.

[0818] Server: Linux server (Ubuntu)

[0819] Database: MySQL, PostgreSQL

[0820] Analysis software: Python, R

[0821] Proposal generation: Generative AI model (OpenAI GPT)

[0822] Specific examples of the system

[0823] The user enters the company number "12345" into the input field on the terminal and clicks the submit button. This action causes the terminal to send the company number "12345" to the server. The server uses this company number to retrieve information about the corresponding company from its database.

[0824] The information obtained may include, for example:

[0825] Contract status: "Currently under contract"

[0826] Sales: "50 million yen"

[0827] Profit: "5 million yen"

[0828] Information on the medium-term management plan

[0829] The server analyzes this information and assesses the company's current situation. Next, it uses a generative AI model to generate suggestions by prompting the following sentences:

[0830] "Please generate a proposal based on the contract status, sales, profits, and medium-term business plan for company number 12345."

[0831] The proposals generated by the generative AI model include, for example, the following:

[0832] "Please consider introducing new product A. This could potentially increase profits by 10%."

[0833] The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal. The terminal parses the received JSON data and displays it in the user interface. HTML and CSS are used for the display format. Finally, the user sees the following information on the terminal screen:

[0834] Contract status: "Currently under contract"

[0835] Sales: "50 million yen"

[0836] Profit: "5 million yen"

[0837] Proposal: "Please consider introducing new product A. This could potentially increase profits by 10%."

[0838] In this way, users can quickly and accurately obtain the necessary company information and receive useful suggestions.

[0839] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0840] Step 1: The user enters the company number or company name into the terminal.

[0841] Input: Company number or company name (e.g., "12345")

[0842] Output: Input data stored within the terminal

[0843] Specific action: The user enters the company number "12345" into the terminal's input field and clicks the submit button. This action stores the data from the input field into a variable within the terminal.

[0844] Step 2: The terminal sends the input data to the server.

[0845] Input: Company number or company name stored on the terminal

[0846] Output: Request data sent to the server

[0847] Specific operation: The terminal sends the entered company number "12345" to the server in the form of an HTTP request. For example, a request in the format POST / api / getCompanyInfo { "company_id": "12345"} is issued. The server receives this request.

[0848] Step 3: The server retrieves company information from the database.

[0849] Input: Company number "12345" included in the HTTP request

[0850] Output: Information on the company's contract status, sales, profits, and medium-term management plan.

[0851] Specific operation: The server issues a query to the database based on the received company number "12345". For example, it executes an SQL query such as SELECT FROM companies WHERE company_id='12345' to retrieve relevant company information from the database.

[0852] Step 4: The server analyzes the acquired company information and generates proposals.

[0853] Input: Company information obtained from a database (contract status, sales, profits, medium-term business plan)

[0854] Output: Generated proposals and analysis results

[0855] Specific operation: The server analyzes data such as a company's sales and profits to evaluate the company's current situation. Based on the analysis results, it uses a generating AI model and, upon receiving the prompt message "Generate proposals based on the contract status, sales, profits, and medium-term management plan for company number 12345," the AI ​​generates specific recommendations.

[0856] Step 5: The server sends the generated results to the terminal.

[0857] Input: Generated proposals and analysis results

[0858] Output: Data in JSON format

[0859] Specific operation: The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal as an HTTP response. For example, { "contract_status": "Contract in progress", "sales": "50 million yen", "profit": "5 million yen", "suggestion": "Consider introducing new product A. This could increase profits by 10%."}.

[0860] Step 6: The device receives the results and displays them to the user.

[0861] Input: JSON format data received from the server

[0862] Output: Information displayed to the user (contract status, sales, profit, proposal)

[0863] Specific operation: The terminal parses the received JSON data and formats it using HTML and CSS to display it in the user interface. The user checks the parsing results and suggestions displayed on the terminal screen. For example, the screen might show contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Consider introducing new product A. This could increase profits by 10%."

[0864] (Application Example 1)

[0865] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0866] Conventional organizational information acquisition systems only retrieve and display information based on entered company numbers and names, lacking the functionality to automatically generate specific transaction proposals for companies. Therefore, users must analyze and make decisions based on the information they receive, which is inefficient. Furthermore, the process of analyzing company information is burdensome for users, resulting in insufficient support for accurate decision-making. Thus, a system is needed that can solve these problems and generate proposals quickly and accurately.

[0867] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0868] In this invention, the server includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. This makes it possible to provide users with more effective and efficient proposals and automate the process of analyzing corporate information.

[0869] An "identification number" is a number used to uniquely identify a particular organization.

[0870] "Organization name" refers to the name of a specific organization.

[0871] A "computer" refers to an electronic device used for processing and analyzing data, and usually includes a server.

[0872] A "storage medium" is a physical or electronic device used to store data, including hard disks and cloud storage.

[0873] "Organizational information" refers to data relating to a specific organization, including financial information such as contract status, sales, and profits.

[0874] "Data analysis" is a technique for extracting meaningful information based on acquired data and for understanding and evaluating the current situation.

[0875] A "deal proposal" is the process of providing specific actions and recommendations for a particular organization based on the results of data analysis.

[0876] A "generative AI model" is a model trained to perform data analysis and generate suggestions using artificial intelligence technology.

[0877] "Revenue" refers to the total income an organization earns through the provision of goods and services.

[0878] "Profit" refers to the net profit remaining after deducting all expenses from revenue.

[0879] A description in detail will be given of embodiments for carrying out this invention.

[0880] This system includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. The system is executed through user operations.

[0881] First, the user enters an identification number or organization name into the input field on the terminal. The terminal then sends the entered data to a server, which is a computer. Based on the received identification number or organization name, the server retrieves the corresponding organization information from a storage medium. This storage medium contains financial information such as the organization's contract status, sales, and profits.

[0882] The server performs data analysis based on the acquired organizational information. This analysis includes, for example, evaluating sales performance and calculating profit margins. Next, the server uses a generative AI model to generate specific deal proposals from the analysis results. These proposals include specific actions and recommendations that the organization should take.

[0883] The generated suggestions and analysis results are sent to the terminal and displayed to the user. For example, along with information such as contract status "In Contract," sales "50 million yen," and profit "5 million yen," a suggestion such as "Consider introducing new product A. This could increase profits by 10%" might be displayed.

[0884] As a concrete example, when a user enters and submits the identification number "12345," the server retrieves information about the corresponding organization from the storage medium and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and based on the generated AI model, a suggestion is created: "Consider introducing new product A. This could potentially increase profits by 10%." This suggestion and the analysis results are sent back to the terminal and displayed to the user.

[0885] Examples of prompt statements for a generative AI model are as follows:

[0886] "Retrieve company information for company number "12345," and analyze its sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on its medium-term business plan."

[0887] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0888] Step 1:

[0889] The user enters an identification number or organization name into the input field on the terminal. Let's say the user enters the organization name "ABC Company". The input is performed via the terminal's GUI, and after completion, the input data is confirmed by pressing the submit button. The input data is string data based on the identification number or organization name.

[0890] Step 2:

[0891] The terminal sends the entered identification number or organization name to the server. For example, it sends the data "ABC Company" to the server as an HTTP request. This request is formatted in JSON format so that the server can correctly receive and parse the data. Here, the input data is converted to a transmission format.

[0892] Step 3:

[0893] The server retrieves organizational information from the storage medium based on the identification number or organization name received. For example, it might query the database for "ABC Company" to retrieve information such as contract status, sales, and profits. This query extracts the organizational information from the database and returns it to the server. The output is organizational information data structured in JSON format.

[0894] Step 4:

[0895] The server performs data analysis based on the acquired organizational information. For example, it evaluates sales performance and calculates profit margins. This analysis may utilize statistical analysis and data mining techniques. This process generates indicators and numerical values ​​for evaluating the current state of the organization. The input is organizational information data, and the output is the analysis results.

[0896] Step 5:

[0897] The server uses a generation AI model to generate transaction proposals from data analysis results. For example, the prompt "Retrieve company information for company number 'ABC Corporation', analyze sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on the medium-term management plan." is input to the generation AI model, which then generates proposals such as new product introductions. This process utilizes machine learning models to perform advanced predictions and suggestions. The input is the analysis results, and the output is the transaction proposals.

[0898] Step 6:

[0899] The generated suggestions and analysis results are sent from the server to the terminal. The terminal receives this data and displays it to the user in a visually easy-to-understand format. For example, using a dashboard or graph, it might display information such as contract status ("In Contract"), sales ("50 million yen"), and profit ("5 million yen"), along with a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." The input is the generated suggestions and analysis results, and the output is the display on the user interface.

[0900] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0901] This invention is a system that, upon user input of a company number or company name, retrieves information on various contract statuses, sales, and profits for that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview, operation method, and specific examples of the system are described below.

[0902] System Overview

[0903] The system consists of a terminal where the user enters a company number or company name, a server that receives, analyzes, and responds to the input data, and an emotion engine that recognizes the user's emotions. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, adjusts the generated suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[0904] How the system works

[0905] 1. The user enters information.

[0906] The user enters the company number or company name into the input field on the terminal.

[0907] For example, a user enters the company number "12345" and clicks the submit button.

[0908] 2. The device sends the request to the server.

[0909] The terminal has the function of sending input data to the server.

[0910] When the terminal sends the company number "12345" to the server, the server receives it.

[0911] 3. The server retrieves company information.

[0912] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[0913] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[0914] 4. The server analyzes the data and generates suggestions.

[0915] Based on the acquired data, the server analyzes the company's current situation.

[0916] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[0917] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[0918] 5. The emotion engine recognizes the user's emotions.

[0919] The server is equipped with an emotion engine that recognizes emotions from user input and responses.

[0920] The emotion engine analyzes the user's voice, facial expressions, text input, etc., to detect the user's emotional state.

[0921] 6. Adjust suggestions based on user sentiment.

[0922] Based on the recognized emotional state of the user, the generated suggestions are adjusted.

[0923] For example, if a user looks dissatisfied, the proposal can be flexibly modified to make it more acceptable to the user.

[0924] 7. The server sends the results to the terminal.

[0925] The server returns the generated proposal and analysis results to the terminal in JSON format.

[0926] The data includes recommendations tailored based on contract status, sales, profits, and user sentiment.

[0927] 8. The device receives and displays the results.

[0928] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[0929] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", and Adjusted proposal "Please consider introducing new product A. This could increase profits by 10%."

[0930] Specific example

[0931] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0932] The following describes the processing flow.

[0933] Step 1:

[0934] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[0935] Step 2:

[0936] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[0937] Step 3:

[0938] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[0939] Step 4:

[0940] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[0941] Step 5:

[0942] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[0943] Step 6:

[0944] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[0945] Step 7:

[0946] The emotion engine recognizes the user's emotions. The emotion engine installed on the server analyzes the user's input and responses to detect the user's emotional state.

[0947] Step 8:

[0948] The system adjusts suggestions based on the user's emotions. The generated suggestions are adjusted based on the recognized emotional state of the user. For example, if the user appears dissatisfied, the suggestions are flexibly modified to make them more acceptable to the user.

[0949] Step 9:

[0950] The server returns the generated and adjusted proposals and analysis results to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and adjusted proposals in JSON format and sends it to the terminal as an HTTP response.

[0951] Step 10:

[0952] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[0953] Step 11:

[0954] The terminal displays the extracted information to the user. Specifically, the screen displays the contract status as "In Contract," sales as "50 million yen," profit as "5 million yen," and the adjusted suggestion as "Please consider introducing new product A. This could increase profits by 10%."

[0955] Step 12:

[0956] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[0957] (Example 2)

[0958] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0959] The present invention aims to provide optimal suggestions that take into account the user's emotions when the user acquires company information and receives suggestions based on the company's current situation. Conventional systems have a problem of low user satisfaction because suggestions are made unilaterally without considering the user's emotions.

[0960] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a company number or company name, means for transmitting the input company number or company name to the server, means for obtaining company information from a database based on the company number or company name received by the server, means for analyzing the obtained company information and generating a proposal, means for adjusting the generated proposal based on emotion recognition means, and means for displaying the adjusted proposal to the user. This makes it possible to make more appropriate and satisfying proposals that take the user's emotions into consideration.

[0961] A "company number" is a number assigned to uniquely identify a company.

[0962] A "company name" is a name used to identify a specific company.

[0963] A "user" refers to an individual or organization that attempts to obtain corporate information using the system.

[0964] A "terminal" is an electronic device used by a user to input information and communicate with a system, and includes personal computers and smartphones.

[0965] A "server" is a computer system that processes data received from users, accesses databases, performs data analysis, and transmits results.

[0966] A "database" is a data storage system used to systematically accumulate and manage various types of information within a company.

[0967] "Company information" refers to information that includes data such as contract status, sales, profits, and medium-term management plans related to a company.

[0968] A "proposal" is advice or recommendations generated based on company information, aimed at improving a company's profits or solving problems.

[0969] "Emotion recognition technology" refers to a technology that analyzes and recognizes emotions from a user's facial expressions, voice, and text.

[0970] "Adjustment" refers to changing the content or tone of a suggestion based on the user's emotions.

[0971] "Display" refers to visually showing the analysis results and suggestions on the device screen.

[0972] This invention is a system that, when a user enters a company number or company name, retrieves information on various contract statuses, sales, and profits of that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings.

[0973] First, the user enters a company number or company name into the terminal. The terminal sends the entered data to the server. Based on the received company number or company name, the server retrieves various information about the relevant company from its database. This information includes contract status, sales, profits, and medium-term business plans.

[0974] Next, the server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. Based on the analysis results, a generative AI model is used to generate optimal suggestions that take into account the company's medium-term management plan. For example, a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%," might be generated.

[0975] The server is equipped with an emotion engine to recognize user emotions. The emotion engine analyzes the user's voice, facial expressions, text input, etc., to identify the user's emotional state. Based on the recognized emotional state, the generated suggestions are adjusted. For example, if the user has a dissatisfied expression, the suggestions are flexibly modified to make them more acceptable to the user.

[0976] Finally, the server returns the generated suggestions and analysis results to the terminal in JSON format. The terminal analyzes the received response and displays the results to the user. These results include contract status, sales, profits, and suggestions tailored to specific situations. This allows the user to understand the company's current situation and make optimal business decisions.

[0977] As a concrete example, when a user enters and submits company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[0978] An example of a prompt message would be something simple like, "Please enter company number '12345' and submit."

[0979] In this way, this system allows users to easily obtain detailed information about companies and optimal suggestions that address their emotions.

[0980] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0981] Step 1:

[0982] The user enters the company number or company name.

[0983] The user enters the company number or company name into the input field on the terminal. For example, the user enters the company number "12345" or the company name "ABC Corporation" into the terminal field and clicks the submit button. The information entered by the user at this point becomes the input data.

[0984] Step 2:

[0985] The device sends the request to the server.

[0986] The terminal sends the company number or company name entered by the user to the server. At this time, the terminal constructs the input data as JSON-formatted request data and sends an HTTP POST request to the server. The request data includes the company number "12345" or the company name "ABC Corporation".

[0987] Step 3:

[0988] The server retrieves company information.

[0989] The server accesses the database based on the received company number or company name and retrieves information about the corresponding company. Specifically, the server executes SQL queries to retrieve necessary data such as the company's contract status, sales, profits, and medium-term business plan. At this point, company information is output from the database based on the input data.

[0990] Step 4:

[0991] The server analyzes the data and generates suggestions.

[0992] The server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. The server uses a generative AI model to generate optimal suggestions based on the analysis results and the medium-term management plan. For example, it might generate a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." Here, company information is taken as input, and suggestions are output.

[0993] Step 5:

[0994] The emotion engine recognizes the user's emotions.

[0995] The emotion engine installed on the server analyzes the user's voice, facial expressions, and text input to recognize emotions. Specifically, it performs sentiment analysis on the text entered by the user and facial recognition using a webcam. Here, the emotional state is output based on the user's response data.

[0996] Step 6:

[0997] Adjust suggestions based on user sentiment.

[0998] The server adjusts the suggestions generated based on the recognized emotional state. If the emotion is positive, the suggestion remains unchanged; if it is negative, the tone and content of the suggestion are flexibly modified. For example, the suggestion might be adjusted to "Please consider introducing new product A. However, we will also suggest ways to reduce initial costs." Here, the emotional state is taken as input, and the adjusted suggestion is output.

[0999] Step 7:

[1000] The server sends the results to the terminal.

[1001] The server returns the adjusted proposal and analysis results to the terminal in JSON format. The response data includes the company's contract status, sales, profits, and adjusted proposal. For example, it might include data such as "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Proposal: Please consider introducing new product A. This could increase profits by 10%." Here, information including the adjusted proposal is output.

[1002] Step 8:

[1003] The device receives and displays the results.

[1004] The terminal receives a response from the server and displays the analyzed data and tailored suggestions to the user. The terminal has the function of displaying the received data on its screen. For example, the terminal's display might show "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Suggestion: Please consider introducing new product A. This could increase profits by 10%." At this point, the tailored suggestions and company information are output to the user.

[1005] Through the above processing steps, users can easily obtain optimal suggestions based on detailed company information and their own sentiments.

[1006] (Application Example 2)

[1007] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1008] Conventional systems can retrieve company information by having users enter an organization number or name, and generate proposals based on that information. However, they cannot provide flexible proposals that take into account the user's emotional state. Furthermore, if a proposal does not match the user's emotions, user satisfaction decreases, leading to a lower acceptance rate of the proposal. Therefore, there is a need for a system that adjusts proposals based on the user's emotions and provides more effective proposals.

[1009] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1010] In this invention, the server is

[1011] A means for the user to enter an organization number or organization name,

[1012] A means of sending the entered organization number or organization name to the server,

[1013] A means for obtaining organizational information from a database based on the organizational number or organizational name received by the server,

[1014] A means for analyzing acquired organizational information and generating proposals,

[1015] A means of displaying the generated suggestions to the user,

[1016] Means of recognizing user emotions,

[1017] Means of adjusting proposals based on perceived emotions,

[1018] This includes providing flexible and effective suggestions that take into account the user's emotional state.

[1019] A "user" is a person or organization that operates the system and obtains organizational information by entering an organizational number or organizational name.

[1020] An "organizational number" is a unique identification number for each organization and serves as a key for retrieving specific organizational information from the database.

[1021] The "organization name" is the official name of the organization and serves as a key for retrieving specific organizational information from the database.

[1022] A "server" is a device or system that processes data received from users and works in conjunction with a database to acquire and analyze information.

[1023] A "database" is an information management system that stores various types of information about an organization (such as contract status, sales, and profits).

[1024] A "proposal" is business advice or recommendations generated based on an analysis of organizational information and the medium-term management plan.

[1025] An "emotion engine" is an artificial intelligence or machine learning model that recognizes a user's emotional state and adjusts its behavior accordingly.

[1026] "Organizational information" refers to data that includes information on the organization's contract status, sales, profits, and medium-term management plan.

[1027] "Analysis" refers to a series of calculations and processes that take acquired data, interpret it, and derive meaning from it.

[1028] "Display" refers to a means of visually conveying information obtained from the server or generated suggestions to the user.

[1029] "Adjustment" is the process of modifying generated suggestions to the most optimal content based on the recognized emotional state of the user.

[1030] This invention is a system that, by allowing users to input an organization number or organization name, retrieves information on various contract statuses, revenues, and profits of an organization, and further provides proposals based on its medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview of the system and specific embodiments are described below.

[1031] System Overview

[1032] The system consists of a smartphone application as the front-end, a back-end server, an organizational information database, and an emotion engine. Users enter an organizational number or name through the smartphone application and send this data to the server. The server receives the input data and retrieves the relevant organizational information from the database. Next, it analyzes the retrieved data and generates suggestions based on the information from the medium-term management plan. The emotion engine then recognizes the user's emotions and adjusts the suggestions accordingly. Finally, the adjusted suggestions are displayed on the smartphone.

[1033] System configuration and operation method

[1034] Hardware and software to be used

[1035] hardware

[1036] Smartphone: A device that allows users to access a system, input data, and view results.

[1037] software

[1038] Frontend: React Native (for mobile application development)

[1039] Backend: Node.js, Express.js (server-side)

[1040] Database: MongoDB (stores organizational information)

[1041] Emotion engine: TensorFlow (user emotion analysis)

[1042] External API: AI model API (for organizational data analysis)

[1043] Server operation

[1044] The server receives an organization number or organization name sent by the user and uses that information to retrieve various information about the corresponding organization from the database. Specifically, it processes requests using Node.js and Express.js and retrieves organization information from MongoDB. It analyzes the retrieved data and uses an AI model to generate proposals based on the medium-term management plan. The AI ​​model's API is used for this proposal generation.

[1045] The emotion engine analyzes the user's emotions from voice and text input, and adjusts suggestions as needed. TensorFlow is used in the emotion engine, enabling real-time emotion recognition. Finally, the adjusted suggestions are sent to the frontend in JSON format and displayed on the smartphone screen.

[1046] Frontend behavior

[1047] A smartphone application developed using React Native provides a UI where the user enters an organization number or organization name and sends it to a backend server. The application receives the results returned from the server and displays them to the user in an appropriate format.

[1048] Examples of specific cases and prompt statements

[1049] As a concrete example, a user enters the organization number "12345" into a smartphone application and submits it. The server retrieves information from the database based on "12345" and analyzes the company's revenue, profits, and contract status. The AI ​​model generates a suggestion, "Consider introducing new product A," but if the user's emotions are perceived as dissatisfied, the suggestion is adjusted and displayed as "Consider introducing new product B."

[1050] Examples of prompt messages are as follows:

[1051] "Based on the organization number or name entered by the user, retrieve the organization's contract status, revenue, profits, etc., and generate a business proposal based on the medium-term management plan. Also, adjust the proposal considering the user's sentiment."

[1052] The above describes the specific forms for carrying out the invention.

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

[1054] Step 1:

[1055] The user enters the organization number or organization name into the smartphone application.

[1056] Input data: Organization number "12345"

[1057] Output data: The input data is stored within the application and ready to be sent to the server in the next step.

[1058] Specific action: The user enters the organization number into the application's input field and clicks the submit button.

[1059] Step 2:

[1060] The terminal sends the input data to the server.

[1061] Input data: User-entered organization number "12345"

[1062] Output data: The server receives the organization number.

[1063] Specific operation: An application created using React Native will send API requests to the server based on user input.

[1064] Step 3:

[1065] Based on the organization number received by the server, the corresponding organization information is retrieved from the database.

[1066] Input data: Organization number "12345" received by the server

[1067] Output data: Organizational information obtained from the database (contract status, sales, profit, medium-term management plan)

[1068] Specific operation: Using Node.js and MongoDB, the server executes database queries to retrieve the necessary organizational information.

[1069] Step 4:

[1070] The server analyzes the organizational information it has acquired and generates proposals based on the medium-term management plan.

[1071] Input data: Acquired organizational information

[1072] Output data: Generated proposal (Example: "Please consider introducing new product A.")

[1073] Specific operation: Call the AI ​​model's API, analyze organizational information as input data, and generate suggestions.

[1074] Step 5:

[1075] The emotion engine recognizes the user's emotions.

[1076] Input data: User's voice, facial expressions, text, etc.

[1077] Output data: Recognized user emotional state

[1078] Specific operation: Use TensorFlow to analyze user emotions in real time.

[1079] Step 6:

[1080] Based on the perceived emotions, the generated suggestions are adjusted.

[1081] Input data: Recognized user's emotional state, generated suggestions

[1082] Output data: Adjusted proposal (e.g., "Please consider introducing new product B.")

[1083] Specific actions: Re-evaluate the proposed content based on the user's emotional state and adjust it to make it more acceptable to the user.

[1084] Step 7:

[1085] The server sends the adjusted suggestions and analysis results to the terminal.

[1086] Input data: Adjusted proposal, analysis results

[1087] Output data: JSON format data for display on the terminal.

[1088] Specific operation: Using Node.js, the adjusted suggestions and analysis results are converted to JSON format and sent to the terminal.

[1089] Step 8:

[1090] The terminal receives a response from the server and displays the suggested content to the user.

[1091] Input data: JSON data received from the server

[1092] Output data: Suggestions displayed in a format that users can visually confirm.

[1093] Specific operation: Using React Native, the received data is reflected in the UI and the results are displayed to the user.

[1094] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1095] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1096] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1097] [Fourth Embodiment]

[1098] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1099] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1100] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1101] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1102] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1103] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1104] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1105] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1106] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1107] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1108] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1109] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1110] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1111] This invention is a system that allows users to input a company number or company name to obtain information on various contract statuses, sales, and profits of that company, and further provides suggestions based on the company's medium-term management plan. The following describes the overall overview, operation method, and specific examples of the system.

[1112] System Overview

[1113] The system consists of a terminal where the user enters a company number or company name, and a server that receives, analyzes, and responds to the data. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, generates suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[1114] How the system works

[1115] 1. The user enters information.

[1116] The user enters the company number or company name into the input field on the terminal.

[1117] For example, a user enters the company number "12345" and clicks the submit button.

[1118] 2. The device sends the request to the server.

[1119] The terminal has the function of sending input data to the server.

[1120] When the terminal sends the company number "12345" to the server, the server receives it.

[1121] 3. The server retrieves company information.

[1122] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[1123] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[1124] 4. The server analyzes the data and generates suggestions.

[1125] Based on the acquired data, the server analyzes the company's current situation.

[1126] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[1127] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[1128] 5. The server sends the results to the terminal.

[1129] The server sends the generated proposals and analysis results to the terminal in JSON format.

[1130] The data includes contract status, sales, profits, and proposals.

[1131] 6. The device receives and displays the results.

[1132] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[1133] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", Proposal "Please consider introducing new product A. This could potentially increase profits by 10%."

[1134] Specific example

[1135] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. This proposal states, "Please consider introducing new product A. This could potentially increase profits by 10%." This information is then sent back to the terminal and displayed to the user.

[1136] The following describes the processing flow.

[1137] Step 1:

[1138] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[1139] Step 2:

[1140] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[1141] Step 3:

[1142] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[1143] Step 4:

[1144] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[1145] Step 5:

[1146] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[1147] Step 6:

[1148] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[1149] Step 7:

[1150] The server sends the generated proposals and analysis results back to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and proposals in JSON format and sends it to the terminal as an HTTP response.

[1151] Step 8:

[1152] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[1153] Step 9:

[1154] The terminal displays the extracted information to the user. Specifically, the screen displays contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Please consider introducing new product A. This could increase profits by 10%."

[1155] Step 10:

[1156] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[1157] (Example 1)

[1158] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1159] Conventional corporate information acquisition systems struggled to quickly and accurately retrieve necessary information and provide useful suggestions based on analysis results, even when users entered a company number or company name. In particular, they lacked a means to generate concrete suggestions based on a company's medium-term management plan, preventing users from making effective decisions.

[1160] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1161] In this invention, the server includes means for the user to input an identification number or identification name, means for transmitting the input identification number or identification name to a central processing unit, means for the central processing unit to retrieve information from a data storage device based on the received identification number or identification name, means for analyzing the retrieved information and generating recommendations, and means for displaying the generated recommendations to the user. This enables the user to quickly and accurately obtain company information and receive useful suggestions based on the analysis results.

[1162] An "identification number" is a numerical or string of characters used to uniquely identify a specific individual or organization.

[1163] An "identification name" is a name or label used to uniquely identify a particular individual or organization.

[1164] A "central processing unit" is a computer system used for processing and managing data.

[1165] A "data storage device" is a database or other storage system used to store and manage information.

[1166] A "recommendation" is a suggestion or instruction generated based on specific data and analysis results.

[1167] "Financial indicators" are metrics used to evaluate a company's financial condition, and include sales, profits, and other metrics.

[1168] "Contract status" refers to information about the current status of contracts a company is undertaking.

[1169] "Information" refers to data obtained from data storage devices, including a company's financial indicators, contract status, and medium-term management plans.

[1170] This invention is a system that allows users to input a company number or company name to obtain various information about that company, and then generates proposals based on that information and its medium-term management plan. The specific form of this system is described below.

[1171] System Configuration

[1172] This system primarily consists of user-operated terminals and servers that process data. The system transmits and receives data between the terminals and servers via a communication network.

[1173] Hardware and software to be used

[1174] Devices: PC (Windows 10), smartphones (iOS / Android), etc.

[1175] Server: Linux server (Ubuntu)

[1176] Database: MySQL, PostgreSQL

[1177] Analysis software: Python, R

[1178] Proposal generation: Generative AI model (OpenAI GPT)

[1179] Specific examples of the system

[1180] The user enters the company number "12345" into the input field on the terminal and clicks the submit button. This action causes the terminal to send the company number "12345" to the server. The server uses this company number to retrieve information about the corresponding company from its database.

[1181] The information obtained may include, for example:

[1182] Contract status: "Currently under contract"

[1183] Sales: "50 million yen"

[1184] Profit: "5 million yen"

[1185] Information on the medium-term management plan

[1186] The server analyzes this information and assesses the company's current situation. Next, it uses a generative AI model to generate suggestions by prompting the following sentences:

[1187] "Please generate a proposal based on the contract status, sales, profits, and medium-term business plan for company number 12345."

[1188] The proposals generated by the generative AI model include, for example, the following:

[1189] "Please consider introducing new product A. This could potentially increase profits by 10%."

[1190] The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal. The terminal parses the received JSON data and displays it in the user interface. HTML and CSS are used for the display format. Finally, the user sees the following information on the terminal screen:

[1191] Contract status: "Currently under contract"

[1192] Sales: "50 million yen"

[1193] Profit: "5 million yen"

[1194] Proposal: "Please consider introducing new product A. This could potentially increase profits by 10%."

[1195] In this way, users can quickly and accurately obtain the necessary company information and receive useful suggestions.

[1196] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1197] Step 1: The user enters the company number or company name into the terminal.

[1198] Input: Company number or company name (e.g., "12345")

[1199] Output: Input data stored within the terminal

[1200] Specific action: The user enters the company number "12345" into the terminal's input field and clicks the submit button. This action stores the data from the input field into a variable within the terminal.

[1201] Step 2: The terminal sends the input data to the server.

[1202] Input: Company number or company name stored on the terminal

[1203] Output: Request data sent to the server

[1204] Specific operation: The terminal sends the entered company number "12345" to the server in the form of an HTTP request. For example, a request in the format POST / api / getCompanyInfo { "company_id": "12345"} is issued. The server receives this request.

[1205] Step 3: The server retrieves company information from the database.

[1206] Input: Company number "12345" included in the HTTP request

[1207] Output: Information on the company's contract status, sales, profits, and medium-term management plan.

[1208] Specific operation: The server issues a query to the database based on the received company number "12345". For example, it executes an SQL query such as SELECT FROM companies WHERE company_id='12345' to retrieve relevant company information from the database.

[1209] Step 4: The server analyzes the acquired company information and generates proposals.

[1210] Input: Company information obtained from a database (contract status, sales, profits, medium-term business plan)

[1211] Output: Generated proposals and analysis results

[1212] Specific operation: The server analyzes data such as a company's sales and profits to evaluate the company's current situation. Based on the analysis results, it uses a generating AI model and, upon receiving the prompt message "Generate proposals based on the contract status, sales, profits, and medium-term management plan for company number 12345," the AI ​​generates specific recommendations.

[1213] Step 5: The server sends the generated results to the terminal.

[1214] Input: Generated proposals and analysis results

[1215] Output: Data in JSON format

[1216] Specific operation: The server formats the generated suggestions and analysis results as a JSON response and sends it to the terminal as an HTTP response. For example, { "contract_status": "Contract in progress", "sales": "50 million yen", "profit": "5 million yen", "suggestion": "Consider introducing new product A. This could increase profits by 10%."}.

[1217] Step 6: The device receives the results and displays them to the user.

[1218] Input: JSON format data received from the server

[1219] Output: Information displayed to the user (contract status, sales, profit, proposal)

[1220] Specific operation: The terminal parses the received JSON data and formats it using HTML and CSS to display it in the user interface. The user checks the parsing results and suggestions displayed on the terminal screen. For example, the screen might show contract status "In Contract", sales "50 million yen", profit "5 million yen", and suggestion "Consider introducing new product A. This could increase profits by 10%."

[1221] (Application Example 1)

[1222] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1223] Conventional organizational information acquisition systems only retrieve and display information based on entered company numbers and names, lacking the functionality to automatically generate specific transaction proposals for companies. Therefore, users must analyze and make decisions based on the information they receive, which is inefficient. Furthermore, the process of analyzing company information is burdensome for users, resulting in insufficient support for accurate decision-making. Thus, a system is needed that can solve these problems and generate proposals quickly and accurately.

[1224] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1225] In this invention, the server includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. This makes it possible to provide users with more effective and efficient proposals and automate the process of analyzing corporate information.

[1226] An "identification number" is a number used to uniquely identify a particular organization.

[1227] "Organization name" refers to the name of a specific organization.

[1228] A "computer" refers to an electronic device used for processing and analyzing data, and usually includes a server.

[1229] A "storage medium" is a physical or electronic device used to store data, including hard disks and cloud storage.

[1230] "Organizational information" refers to data relating to a specific organization, including financial information such as contract status, sales, and profits.

[1231] "Data analysis" is a technique for extracting meaningful information based on acquired data and for understanding and evaluating the current situation.

[1232] A "deal proposal" is the process of providing specific actions and recommendations for a particular organization based on the results of data analysis.

[1233] A "generative AI model" is a model trained to perform data analysis and generate suggestions using artificial intelligence technology.

[1234] "Revenue" refers to the total income an organization earns through the provision of goods and services.

[1235] "Profit" refers to the net profit remaining after deducting all expenses from revenue.

[1236] A description in detail will be given of embodiments for carrying out this invention.

[1237] This system includes means for inputting an identification number or organization name, means for transmitting the inputted identification number or organization name to a computer, means for the computer to retrieve organization information from a storage medium based on the received identification number or organization name, means for analyzing the retrieved organization information and generating a transaction proposal using a generation AI model, means for displaying the generated proposal to the user, and means for displaying the organization's revenue and profit. The system is executed through user operations.

[1238] First, the user enters an identification number or organization name into the input field on the terminal. The terminal then sends the entered data to a server, which is a computer. Based on the received identification number or organization name, the server retrieves the corresponding organization information from a storage medium. This storage medium contains financial information such as the organization's contract status, sales, and profits.

[1239] The server performs data analysis based on the acquired organizational information. This analysis includes, for example, evaluating sales performance and calculating profit margins. Next, the server uses a generative AI model to generate specific deal proposals from the analysis results. These proposals include specific actions and recommendations that the organization should take.

[1240] The generated suggestions and analysis results are sent to the terminal and displayed to the user. For example, along with information such as contract status "In Contract," sales "50 million yen," and profit "5 million yen," a suggestion such as "Consider introducing new product A. This could increase profits by 10%" might be displayed.

[1241] As a concrete example, when a user enters and submits the identification number "12345," the server retrieves information about the corresponding organization from the storage medium and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and based on the generated AI model, a suggestion is created: "Consider introducing new product A. This could potentially increase profits by 10%." This suggestion and the analysis results are sent back to the terminal and displayed to the user.

[1242] Examples of prompt statements for a generative AI model are as follows:

[1243] "Retrieve company information for company number "12345," and analyze its sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on its medium-term business plan."

[1244] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1245] Step 1:

[1246] The user enters an identification number or organization name into the input field on the terminal. Let's say the user enters the organization name "ABC Company". The input is performed via the terminal's GUI, and after completion, the input data is confirmed by pressing the submit button. The input data is string data based on the identification number or organization name.

[1247] Step 2:

[1248] The terminal sends the entered identification number or organization name to the server. For example, it sends the data "ABC Company" to the server as an HTTP request. This request is formatted in JSON format so that the server can correctly receive and parse the data. Here, the input data is converted to a transmission format.

[1249] Step 3:

[1250] The server retrieves organizational information from the storage medium based on the identification number or organization name received. For example, it might query the database for "ABC Company" to retrieve information such as contract status, sales, and profits. This query extracts the organizational information from the database and returns it to the server. The output is organizational information data structured in JSON format.

[1251] Step 4:

[1252] The server performs data analysis based on the acquired organizational information. For example, it evaluates sales performance and calculates profit margins. This analysis may utilize statistical analysis and data mining techniques. This process generates indicators and numerical values ​​for evaluating the current state of the organization. The input is organizational information data, and the output is the analysis results.

[1253] Step 5:

[1254] The server uses a generation AI model to generate transaction proposals from data analysis results. For example, the prompt "Retrieve company information for company number 'ABC Corporation', analyze sales, profits, and contract status. Furthermore, generate optimal transaction proposals based on the medium-term management plan." is input to the generation AI model, which then generates proposals such as new product introductions. This process utilizes machine learning models to perform advanced predictions and suggestions. The input is the analysis results, and the output is the transaction proposals.

[1255] Step 6:

[1256] The generated suggestions and analysis results are sent from the server to the terminal. The terminal receives this data and displays it to the user in a visually easy-to-understand format. For example, using a dashboard or graph, it might display information such as contract status ("In Contract"), sales ("50 million yen"), and profit ("5 million yen"), along with a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." The input is the generated suggestions and analysis results, and the output is the display on the user interface.

[1257] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1258] This invention is a system that, upon user input of a company number or company name, retrieves information on various contract statuses, sales, and profits for that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview, operation method, and specific examples of the system are described below.

[1259] System Overview

[1260] The system consists of a terminal where the user enters a company number or company name, a server that receives, analyzes, and responds to the input data, and an emotion engine that recognizes the user's emotions. The terminal sends the entered data to the server, which retrieves company information from a database, analyzes it, adjusts the generated suggestions, and sends the results back to the terminal. The terminal then displays these results to the user.

[1261] How the system works

[1262] 1. The user enters information.

[1263] The user enters the company number or company name into the input field on the terminal.

[1264] For example, a user enters the company number "12345" and clicks the submit button.

[1265] 2. The device sends the request to the server.

[1266] The terminal has the function of sending input data to the server.

[1267] When the terminal sends the company number "12345" to the server, the server receives it.

[1268] 3. The server retrieves company information.

[1269] Based on the company number "12345" received by the server, various information about the corresponding company is retrieved from the database.

[1270] For example, obtain information on the contract status, sales, profits, and medium-term management plan of company "12345".

[1271] 4. The server analyzes the data and generates suggestions.

[1272] Based on the acquired data, the server analyzes the company's current situation.

[1273] Based on the analyzed information, the system generates optimal proposals that take into account the company's medium-term management plan.

[1274] For example, a proposal might be generated stating, "Please consider introducing new product A. This could potentially increase profits by 10%."

[1275] 5. The emotion engine recognizes the user's emotions.

[1276] The server is equipped with an emotion engine that recognizes emotions from user input and responses.

[1277] The emotion engine analyzes the user's voice, facial expressions, text input, etc., to detect the user's emotional state.

[1278] 6. Adjust suggestions based on user sentiment.

[1279] Based on the recognized emotional state of the user, the generated suggestions are adjusted.

[1280] For example, if a user looks dissatisfied, the proposal can be flexibly modified to make it more acceptable to the user.

[1281] 7. The server sends the results to the terminal.

[1282] The server returns the generated proposal and analysis results to the terminal in JSON format.

[1283] The data includes recommendations tailored based on contract status, sales, profits, and user sentiment.

[1284] 8. The device receives and displays the results.

[1285] The terminal receives a response from the server and displays the analysis data and suggestions to the user.

[1286] Specifically, the following information is displayed: Contract status "In Contract", Sales "50 million yen", Profit "5 million yen", and Adjusted proposal "Please consider introducing new product A. This could increase profits by 10%."

[1287] Specific example

[1288] When a user enters and submits the company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[1289] The following describes the processing flow.

[1290] Step 1:

[1291] The user enters the company number or company name on their device. Specifically, the user enters the company number "12345" into the input field on a web page or application and clicks the submit button.

[1292] Step 2:

[1293] The terminal sends the input data to the server. The terminal issues an HTTP POST request to send a request containing the entered company number "12345" to the server.

[1294] Step 3:

[1295] The server parses the received request and extracts the company number or company name. Specifically, the server extracts the company number "12345" from the request body.

[1296] Step 4:

[1297] The server connects to the database and queries for company information based on the extracted company number "12345". It retrieves information from the database such as the company's contract status, sales, profits, and medium-term business plan.

[1298] Step 5:

[1299] The server analyzes the company information it has acquired. It reviews the acquired company data (contract status, sales, profits, etc.) and performs analytical processing to understand the current state of the company.

[1300] Step 6:

[1301] The server generates proposals based on the medium-term management plan. It generates appropriate action plans and improvement measures as proposals, in accordance with the company's goals and strategies. For example, it might generate a proposal such as, "Consider introducing new product A. This could potentially increase profits by 10%."

[1302] Step 7:

[1303] The emotion engine recognizes the user's emotions. The emotion engine installed on the server analyzes the user's input and responses to detect the user's emotional state.

[1304] Step 8:

[1305] The system adjusts suggestions based on the user's emotions. The generated suggestions are adjusted based on the recognized emotional state of the user. For example, if the user appears dissatisfied, the suggestions are flexibly modified to make them more acceptable to the user.

[1306] Step 9:

[1307] The server returns the generated and adjusted proposals and analysis results to the terminal in JSON format. Specifically, it packages data including contract status, sales, profits, and adjusted proposals in JSON format and sends it to the terminal as an HTTP response.

[1308] Step 10:

[1309] The terminal receives a response from the server. The terminal parses the JSON data and extracts the information sent from the server (contract status, sales, profit, proposal).

[1310] Step 11:

[1311] The terminal displays the extracted information to the user. Specifically, the screen displays the contract status as "In Contract," sales as "50 million yen," profit as "5 million yen," and the adjusted suggestion as "Please consider introducing new product A. This could increase profits by 10%."

[1312] Step 12:

[1313] The user reviews the displayed information and decides on their next course of action. The user makes decisions based on the suggestions and company information provided.

[1314] (Example 2)

[1315] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1316] The present invention aims to provide optimal suggestions that take into account the user's emotions when the user acquires company information and receives suggestions based on the company's current situation. Conventional systems have a problem of low user satisfaction because suggestions are made unilaterally without considering the user's emotions.

[1317] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a company number or company name, means for transmitting the input company number or company name to the server, means for obtaining company information from a database based on the company number or company name received by the server, means for analyzing the obtained company information and generating a proposal, means for adjusting the generated proposal based on emotion recognition means, and means for displaying the adjusted proposal to the user. This makes it possible to make more appropriate and satisfying proposals that take the user's emotions into consideration.

[1318] A "company number" is a number assigned to uniquely identify a company.

[1319] A "company name" is a name used to identify a specific company.

[1320] A "user" refers to an individual or organization that attempts to obtain corporate information using the system.

[1321] A "terminal" is an electronic device used by a user to input information and communicate with a system, and includes personal computers and smartphones.

[1322] A "server" is a computer system that processes data received from users, accesses databases, performs data analysis, and transmits results.

[1323] A "database" is a data storage system used to systematically accumulate and manage various types of information within a company.

[1324] "Company information" refers to information that includes data such as contract status, sales, profits, and medium-term management plans related to a company.

[1325] A "proposal" is advice or recommendations generated based on company information, aimed at improving a company's profits or solving problems.

[1326] "Emotion recognition technology" refers to a technology that analyzes and recognizes emotions from a user's facial expressions, voice, and text.

[1327] "Adjustment" refers to changing the content or tone of a suggestion based on the user's emotions.

[1328] "Display" refers to visually showing the analysis results and suggestions on the device screen.

[1329] This invention is a system that, when a user enters a company number or company name, retrieves information on various contract statuses, sales, and profits of that company, and further provides proposals based on the company's medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings.

[1330] First, the user enters a company number or company name into the terminal. The terminal sends the entered data to the server. Based on the received company number or company name, the server retrieves various information about the relevant company from its database. This information includes contract status, sales, profits, and medium-term business plans.

[1331] Next, the server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. Based on the analysis results, a generative AI model is used to generate optimal suggestions that take into account the company's medium-term management plan. For example, a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%," might be generated.

[1332] The server is equipped with an emotion engine to recognize user emotions. The emotion engine analyzes the user's voice, facial expressions, text input, etc., to identify the user's emotional state. Based on the recognized emotional state, the generated suggestions are adjusted. For example, if the user has a dissatisfied expression, the suggestions are flexibly modified to make them more acceptable to the user.

[1333] Finally, the server returns the generated suggestions and analysis results to the terminal in JSON format. The terminal analyzes the received response and displays the results to the user. These results include contract status, sales, profits, and suggestions tailored to specific situations. This allows the user to understand the company's current situation and make optimal business decisions.

[1334] As a concrete example, when a user enters and submits company number "12345," the server retrieves the company's information from the database and analyzes it. The analysis results show the contract status as "in contract," sales of "50 million yen," and profit of "5 million yen," and a proposal is generated based on the medium-term management plan. Subsequently, the emotion engine recognizes the user's emotions and adjusts the proposal as needed. Finally, the adjusted proposal is sent back to the terminal and displayed to the user.

[1335] An example of a prompt message would be something simple like, "Please enter company number '12345' and submit."

[1336] In this way, this system allows users to easily obtain detailed information about companies and optimal suggestions that address their emotions.

[1337] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1338] Step 1:

[1339] The user enters the company number or company name.

[1340] The user enters the company number or company name into the input field on the terminal. For example, the user enters the company number "12345" or the company name "ABC Corporation" into the terminal field and clicks the submit button. The information entered by the user at this point becomes the input data.

[1341] Step 2:

[1342] The device sends the request to the server.

[1343] The terminal sends the company number or company name entered by the user to the server. At this time, the terminal constructs the input data as JSON-formatted request data and sends an HTTP POST request to the server. The request data includes the company number "12345" or the company name "ABC Corporation".

[1344] Step 3:

[1345] The server retrieves company information.

[1346] The server accesses the database based on the received company number or company name and retrieves information about the corresponding company. Specifically, the server executes SQL queries to retrieve necessary data such as the company's contract status, sales, profits, and medium-term business plan. At this point, company information is output from the database based on the input data.

[1347] Step 4:

[1348] The server analyzes the data and generates suggestions.

[1349] The server performs analysis based on the acquired company information. This analysis includes statistical data analysis that takes into account the company's past performance and industry trends. The server uses a generative AI model to generate optimal suggestions based on the analysis results and the medium-term management plan. For example, it might generate a suggestion such as, "Consider introducing new product A. This could potentially increase profits by 10%." Here, company information is taken as input, and suggestions are output.

[1350] Step 5:

[1351] The emotion engine recognizes the user's emotions.

[1352] The emotion engine installed on the server analyzes the user's voice, facial expressions, and text input to recognize emotions. Specifically, it performs sentiment analysis on the text entered by the user and facial recognition using a webcam. Here, the emotional state is output based on the user's response data.

[1353] Step 6:

[1354] Adjust suggestions based on user sentiment.

[1355] The server adjusts the suggestions generated based on the recognized emotional state. If the emotion is positive, the suggestion remains unchanged; if it is negative, the tone and content of the suggestion are flexibly modified. For example, the suggestion might be adjusted to "Please consider introducing new product A. However, we will also suggest ways to reduce initial costs." Here, the emotional state is taken as input, and the adjusted suggestion is output.

[1356] Step 7:

[1357] The server sends the results to the terminal.

[1358] The server returns the adjusted proposal and analysis results to the terminal in JSON format. The response data includes the company's contract status, sales, profits, and adjusted proposal. For example, it might include data such as "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Proposal: Please consider introducing new product A. This could increase profits by 10%." Here, information including the adjusted proposal is output.

[1359] Step 8:

[1360] The device receives and displays the results.

[1361] The terminal receives a response from the server and displays the analyzed data and tailored suggestions to the user. The terminal has the function of displaying the received data on its screen. For example, the terminal's display might show "Contract Status: In Contract," "Sales: 50 million yen," "Profit: 5 million yen," and "Suggestion: Please consider introducing new product A. This could increase profits by 10%." At this point, the tailored suggestions and company information are output to the user.

[1362] Through the above processing steps, users can easily obtain optimal suggestions based on detailed company information and their own sentiments.

[1363] (Application Example 2)

[1364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1365] Conventional systems can retrieve company information by having users enter an organization number or name, and generate proposals based on that information. However, they cannot provide flexible proposals that take into account the user's emotional state. Furthermore, if a proposal does not match the user's emotions, user satisfaction decreases, leading to a lower acceptance rate of the proposal. Therefore, there is a need for a system that adjusts proposals based on the user's emotions and provides more effective proposals.

[1366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1367] In this invention, the server is

[1368] A means for the user to enter an organization number or organization name,

[1369] A means of sending the entered organization number or organization name to the server,

[1370] A means for obtaining organizational information from a database based on the organizational number or organizational name received by the server,

[1371] A means for analyzing acquired organizational information and generating proposals,

[1372] A means of displaying the generated suggestions to the user,

[1373] Means of recognizing user emotions,

[1374] Means of adjusting proposals based on perceived emotions,

[1375] This includes providing flexible and effective suggestions that take into account the user's emotional state.

[1376] A "user" is a person or organization that operates the system and obtains organizational information by entering an organizational number or organizational name.

[1377] An "organizational number" is a unique identification number for each organization and serves as a key for retrieving specific organizational information from the database.

[1378] The "organization name" is the official name of the organization and serves as a key for retrieving specific organizational information from the database.

[1379] A "server" is a device or system that processes data received from users and works in conjunction with a database to acquire and analyze information.

[1380] A "database" is an information management system that stores various types of information about an organization (such as contract status, sales, and profits).

[1381] A "proposal" is business advice or recommendations generated based on an analysis of organizational information and the medium-term management plan.

[1382] An "emotion engine" is an artificial intelligence or machine learning model that recognizes a user's emotional state and adjusts its behavior accordingly.

[1383] "Organizational information" refers to data that includes information on the organization's contract status, sales, profits, and medium-term management plan.

[1384] "Analysis" refers to a series of calculations and processes that take acquired data, interpret it, and derive meaning from it.

[1385] "Display" refers to a means of visually conveying information obtained from the server or generated suggestions to the user.

[1386] "Adjustment" is the process of modifying generated suggestions to the most optimal content based on the recognized emotional state of the user.

[1387] This invention is a system that, by allowing users to input an organization number or organization name, retrieves information on various contract statuses, revenues, and profits of an organization, and further provides proposals based on its medium-term management plan. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the proposals based on the user's feelings. The overall overview of the system and specific embodiments are described below.

[1388] System Overview

[1389] The system consists of a smartphone application as the front-end, a back-end server, an organizational information database, and an emotion engine. Users enter an organizational number or name through the smartphone application and send this data to the server. The server receives the input data and retrieves the relevant organizational information from the database. Next, it analyzes the retrieved data and generates suggestions based on the information from the medium-term management plan. The emotion engine then recognizes the user's emotions and adjusts the suggestions accordingly. Finally, the adjusted suggestions are displayed on the smartphone.

[1390] System configuration and operation method

[1391] Hardware and software to be used

[1392] hardware

[1393] Smartphone: A device that allows users to access a system, input data, and view results.

[1394] software

[1395] Frontend: React Native (for mobile application development)

[1396] Backend: Node.js, Express.js (server-side)

[1397] Database: MongoDB (stores organizational information)

[1398] Emotion engine: TensorFlow (user emotion analysis)

[1399] External API: AI model API (for organizational data analysis)

[1400] Server operation

[1401] The server receives an organization number or organization name sent by the user and uses that information to retrieve various information about the corresponding organization from the database. Specifically, it processes requests using Node.js and Express.js and retrieves organization information from MongoDB. It analyzes the retrieved data and uses an AI model to generate proposals based on the medium-term management plan. The AI ​​model's API is used for this proposal generation.

[1402] The emotion engine analyzes the user's emotions from voice and text input, and adjusts suggestions as needed. TensorFlow is used in the emotion engine, enabling real-time emotion recognition. Finally, the adjusted suggestions are sent to the frontend in JSON format and displayed on the smartphone screen.

[1403] Frontend behavior

[1404] A smartphone application developed using React Native provides a UI where the user enters an organization number or organization name and sends it to a backend server. The application receives the results returned from the server and displays them to the user in an appropriate format.

[1405] Examples of specific cases and prompt statements

[1406] As a concrete example, a user enters the organization number "12345" into a smartphone application and submits it. The server retrieves information from the database based on "12345" and analyzes the company's revenue, profits, and contract status. The AI ​​model generates a suggestion, "Consider introducing new product A," but if the user's emotions are perceived as dissatisfied, the suggestion is adjusted and displayed as "Consider introducing new product B."

[1407] Examples of prompt messages are as follows:

[1408] "Based on the organization number or name entered by the user, retrieve the organization's contract status, revenue, profits, etc., and generate a business proposal based on the medium-term management plan. Also, adjust the proposal considering the user's sentiment."

[1409] The above describes the specific forms for carrying out the invention.

[1410] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1411] Step 1:

[1412] The user enters the organization number or organization name into the smartphone application.

[1413] Input data: Organization number "12345"

[1414] Output data: The input data is stored within the application and ready to be sent to the server in the next step.

[1415] Specific action: The user enters the organization number into the application's input field and clicks the submit button.

[1416] Step 2:

[1417] The terminal sends the input data to the server.

[1418] Input data: User-entered organization number "12345"

[1419] Output data: The server receives the organization number.

[1420] Specific operation: An application created using React Native will send API requests to the server based on user input.

[1421] Step 3:

[1422] Based on the organization number received by the server, the corresponding organization information is retrieved from the database.

[1423] Input data: Organization number "12345" received by the server

[1424] Output data: Organizational information obtained from the database (contract status, sales, profit, medium-term management plan)

[1425] Specific operation: Using Node.js and MongoDB, the server executes database queries to retrieve the necessary organizational information.

[1426] Step 4:

[1427] The server analyzes the organizational information it has acquired and generates proposals based on the medium-term management plan.

[1428] Input data: Acquired organizational information

[1429] Output data: Generated proposal (Example: "Please consider introducing new product A.")

[1430] Specific operation: Call the AI ​​model's API, analyze organizational information as input data, and generate suggestions.

[1431] Step 5:

[1432] The emotion engine recognizes the user's emotions.

[1433] Input data: User's voice, facial expressions, text, etc.

[1434] Output data: Recognized user emotional state

[1435] Specific operation: Use TensorFlow to analyze user emotions in real time.

[1436] Step 6:

[1437] Based on the perceived emotions, the generated suggestions are adjusted.

[1438] Input data: Recognized user's emotional state, generated suggestions

[1439] Output data: Adjusted proposal (e.g., "Please consider introducing new product B.")

[1440] Specific actions: Re-evaluate the proposed content based on the user's emotional state and adjust it to make it more acceptable to the user.

[1441] Step 7:

[1442] The server sends the adjusted suggestions and analysis results to the terminal.

[1443] Input data: Adjusted proposal, analysis results

[1444] Output data: JSON format data for display on the terminal.

[1445] Specific operation: Using Node.js, the adjusted suggestions and analysis results are converted to JSON format and sent to the terminal.

[1446] Step 8:

[1447] The terminal receives a response from the server and displays the suggested content to the user.

[1448] Input data: JSON data received from the server

[1449] Output data: Suggestions displayed in a format that users can visually confirm.

[1450] Specific operation: Using React Native, the received data is reflected in the UI and the results are displayed to the user.

[1451] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1452] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1453] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1454] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1455] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1456] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1457] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1458] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1459] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1460] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1461] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1462] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1463] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1464] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1465] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1466] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1467] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1468] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1469] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1470] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1471] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1472] The following is further disclosed regarding the embodiments described above.

[1473] (Claim 1)

[1474] A means for the user to enter a company number or company name,

[1475] A means of sending the entered company number or company name to the server,

[1476] A means for obtaining company information from a database based on the company number or company name received by the server,

[1477] A means of analyzing acquired company information and generating proposals,

[1478] A means of displaying the generated suggestions to the user,

[1479] A system that includes this.

[1480] (Claim 2)

[1481] A means of displaying a company's sales and profits based on acquired company information,

[1482] The system according to claim 1, further comprising:

[1483] (Claim 3)

[1484] A means of displaying various contract statuses of a company based on acquired company information,

[1485] The system according to claim 1, further comprising:

[1486] "Example 1"

[1487] (Claim 1)

[1488] A means by which the user enters an identification number or identification name,

[1489] Means for transmitting the input identification number or identification name to a central processing unit,

[1490] Means for obtaining information from a data storage device based on an identification number or identification name received by the central processing unit,

[1491] A means of analyzing acquired information and generating recommendations,

[1492] A means of displaying the generated recommendations to the user,

[1493] A system that includes this.

[1494] (Claim 2)

[1495] A means of displaying financial indicators based on acquired information,

[1496] The system according to claim 1, further comprising:

[1497] (Claim 3)

[1498] A means of displaying the contract status based on the acquired information,

[1499] The system according to claim 1, further comprising:

[1500] "Application Example 1"

[1501] (Claim 1)

[1502] A means for the user to enter an identification number or organization name,

[1503] Means for transmitting the entered identification number or organization name to a computer,

[1504] A means for obtaining organizational information from a storage medium based on an identification number or organization name received by a computer,

[1505] A means for analyzing acquired organizational information and generating proposals,

[1506] A means of displaying the generated suggestions to the user,

[1507] A system that includes this.

[1508] (Claim 2)

[1509] A means of displaying the organization's revenue and profit based on acquired organizational information,

[1510] A means of generating transaction proposals based on data acquired by a computer,

[1511] The system according to claim 1, further comprising:

[1512] (Claim 3)

[1513] A means of displaying the status of various contracts of an organization based on acquired organizational information,

[1514] A means of generating proposals using a generative AI model,

[1515] The system according to claim 1, further comprising:

[1516] "Example 2 of combining an emotion engine"

[1517] (Claim 1)

[1518] A means for the user to enter a company number or company name,

[1519] A means of sending the entered company number or company name to the server,

[1520] A means for obtaining company information from a database based on the company number or company name received by the server,

[1521] A means of analyzing acquired company information and generating proposals,

[1522] A means for adjusting the generated proposals based on emotion recognition means,

[1523] A means of displaying the adjusted suggestions to the user,

[1524] A system that includes this.

[1525] (Claim 2)

[1526] The system according to claim 1, further comprising means for displaying a company's sales and profits based on acquired company information.

[1527] (Claim 3)

[1528] The system according to claim 1, further comprising means for displaying various contract statuses of a company based on acquired company information.

[1529] "Application example 2 when combining with an emotional engine"

[1530] (Claim 1)

[1531] A means for the user to enter an organization number or organization name,

[1532] A means of sending the entered organization number or organization name to the server,

[1533] A means for obtaining organizational information from a database based on the organizational number or organizational name received by the server,

[1534] A means for analyzing acquired organizational information and generating proposals,

[1535] A means of displaying the generated suggestions to the user,

[1536] Means of recognizing user emotions,

[1537] Means of adjusting proposals based on perceived emotions,

[1538] A system that includes this.

[1539] (Claim 2)

[1540] A means of displaying the organization's revenue and profits based on the acquired organizational information,

[1541] The system according to claim 1, further comprising:

[1542] (Claim 3)

[1543] A means of displaying the status of various contracts of an organization based on acquired organizational information,

[1544] The system according to claim 1, further comprising: [Explanation of symbols]

[1545] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to enter a company number or company name, A means of sending the entered company number or company name to the server, A means for obtaining company information from a database based on the company number or company name received by the server, A means of analyzing acquired company information and generating proposals, A means of displaying the generated suggestions to the user, A system that includes this.

2. A means of displaying a company's sales and profits based on acquired company information, The system according to claim 1, further comprising:

3. A means of displaying various contract statuses of a company based on acquired company information, The system according to claim 1, further comprising:

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