system

Abstract

A system is provided.SOLUTION: The system includes a means for transmitting an inputted company name to a server, a means for the server collating a database based on the company name and acquiring information, a means for complementing deficient information from an external API, and a means for analyzing / arranging the acquired information and displaying it on a user interface.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Corporate research requires a lot of resources and time, which reduces efficiency. Furthermore, the collection of necessary information can be incomplete, making it difficult to make decisions based on reliable data. For this reason, there is a need for a method to quickly and accurately obtain information on market size, competitors, service models, go-to-market (GTM) strategies, and conduct research efficiently. [Means for solving the problem]

[0005] This invention provides a system that includes a means for sending input company names to a server, a means for the server to retrieve information by checking a database based on the company name, a means for supplementing missing information from an external API, and a means for analyzing and organizing the retrieved information and displaying it in a user interface. This allows users to quickly obtain the necessary company information, enabling efficient research. Furthermore, by comprehensively collecting and displaying information including market size, competitors, service models, and go-to-market strategies, users can make decisions based on reliable data.

[0006] The "means for transmitting the input company name to the server" is a mechanism for transmitting the company name input by the user to the terminal to the server via the Internet.

[0007] "Means for the server to check the database based on the company name and obtain information" is a function that searches for and obtains related information stored in the database based on the company name received by the server.

[0008] "Means of supplementing missing information from external APIs" refers to a mechanism for obtaining data using external API services in order to supplement information that does not exist in the database.

[0009] "Means of analyzing and organizing acquired information and displaying it on the user interface" refers to a function that appropriately classifies and analyzes information acquired from databases and external APIs, and displays it in a form that is easy for users to understand.

[0010] "Market size" is data that indicates the overall economic size of a particular market, i.e., the total sales or value of companies within that market.

[0011] "Competitors" refers to other companies offering similar products or services in the same market.

[0012] A "delivery model" refers to the sales format or strategy a company uses to provide its products or services to customers.

[0013] A "Go-To-Market (GTM) strategy" refers to the strategy and process for introducing a new product or service to the market, including market analysis, marketing plan, and sales strategy. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] To implement this invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then checks the database based on the received company name to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. This allows users to quickly and efficiently obtain the company information they need.

[0036] Detailed explanation of the program's operation:

[0037] User input

[0038] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0039] Starting Data Collection

[0040] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server.

[0041] Database Matching

[0042] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it executes an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0043] Using external APIs

[0044] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0045] Data analysis and organization

[0046] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0047] Displaying the results

[0048] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0049] Market size: $5 billion

[0050] Major competitors: Company B, Company C

[0051] Delivery model: Subscription-based

[0052] GTM Strategy: Digital Marketing, Customer Journey Map

[0053] A system with such a mechanism allows users to efficiently gain deep insight into companies and significantly reduce the amount of research work required.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user enters the name of the company to be surveyed in the input field on the terminal. For example, the user enters "Company A." The user clicks the "Submit" button to proceed to the next step.

[0057] Step 2:

[0058] The terminal sends the company name "Company A" entered by the user to the server. At this time, the terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0059] Step 3:

[0060] The server receives the received company name "Company A" and executes a query against the database. For example, the server sends an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve related information.

[0061] Step 4:

[0062] The server stores the information obtained as a result of the SQL query in temporary storage (e.g., memory), which prepares the data for use in the next process.

[0063] Step 5:

[0064] If the information retrieved from the database is insufficient, the server uses an external API to supplement the information. For example, the server sends an HTTP request to the "Market Information API" including the company name "Company A" as a parameter to retrieve the latest market size data.

[0065] Step 6:

[0066] The server receives the response data from the external API and stores it in temporary storage. Based on the retrieved data, it complements the existing data set to create a complete company information set.

[0067] Step 7:

[0068] The server analyzes the organized data, which includes categorizing the data (market size, competition, delivery model, GTM strategy, etc.) and providing detailed analysis for each category.

[0069] Step 8:

[0070] The server converts the analyzed and organized data into a format that is easy for users to use, such as HTML or JSON, and generates the final dataset.

[0071] Step 9:

[0072] The server sends the final dataset to the device as an HTTP response, which includes detailed information about market size, competition, offering model, and GTM strategy.

[0073] Step 10:

[0074] The device analyzes the data received from the server and displays it on a user interface, which visually displays the following information:

[0075] Market size: $5 billion

[0076] Major competitors: Company B, Company C

[0077] Delivery model: Subscription-based

[0078] GTM Strategy: Digital Marketing, Customer Journey Map

[0079] Example 1

[0080] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0081] In today's business environment, there is a need to quickly and accurately collect and analyze corporate information. However, traditional systems make it difficult to properly supplement missing information in databases, requiring manual work and additional research to obtain complete information. As a result, information collection and analysis require a great deal of time and effort.

[0082] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0083] In this invention, the server includes: a means for a user to input a company name into an input field; a means for a terminal to transmit the input company name to the server; a means for the server to query a database based on the company name and obtain information; a means for the server to call an external API to supplement the missing information if the information obtained from the database is incomplete; a means for the server to analyze the obtained information and classify and organize it by item; and a means for transmitting the organized information from the server to the terminal and for the terminal to display it on a user interface. This makes it possible to quickly and efficiently collect company information and provide the information required by the user in an organized manner.

[0084] A "user" is a person or operator who interacts with the system to enter a business name and receive the results.

[0085] A "terminal" is a device operated by a user, and is a device for inputting a company name and performing data communication with a server.

[0086] "Server" is a central computer system that queries the database based on the company name received from the user, retrieves and completes the required information, and sends the final results to the terminal.

[0087] "Company name" is the name of the corporation that the user designates as the target of the survey or information gathering.

[0088] A "database" is a collection of information managed by a server, including various data related to a company.

[0089] An "external API" is an external application programming interface used by the server to supplement information missing from the database.

[0090] A "query" is a command or question executed by a server to obtain specific information from a database.

[0091] "Analysis" refers to the act of breaking down and processing the data acquired by the server, and processing it to understand its meaning and intent.

[0092] "Classification and organization" is the act of dividing analyzed data into categories based on specific criteria and arranging them in an orderly manner.

[0093] "User interface" refers to the display screen and input means that allow a user to check and operate information on a terminal.

[0094] To implement this invention, a user first uses a terminal to input the name of a company to be investigated. The terminal then sends the input company name to a server as an HTTP request. The server then queries an internal database based on the received company name to retrieve relevant information. This query is performed, for example, using SQL.

[0095] If the information the server retrieves from the database is incomplete, it uses an external API to fill in the missing information. For example, it may call a "Market Information API" to obtain the latest market information. The server sends this request as an HTTP request to the external API to obtain the required data.

[0096] The server then analyzes the acquired data and classifies and organizes it into the necessary items, dividing the information into multiple categories such as market size, competitors, offering models, and go-to-market strategies. This analysis and organization process is carried out using specific algorithms and data mining techniques.

[0097] Once the analysis and organization is complete, the server sends the information to the device, which then displays the received data on a user interface. This allows users to easily understand the desired company information, such as market size, major competitors, the company's service model, and GTM strategy.

[0098] For example, if a user wants to find information about "Company A," they enter "Company A" into their device. The device sends this company name to the server, which then performs the following process:

[0099] 1. Obtain information about "Company A" from the database.

[0100] 2. Obtain missing market information from an external API.

[0101] 3. Analyze and organize the information obtained.

[0102] 4. Present organized information in a user interface.

[0103] The generative AI model can also be used to respond to specific questions from users. For example, by entering a prompt such as, "Please tell me the latest information on Company A's market size, competitors, delivery model, and go-to-market strategy," detailed company information can be provided. This system allows users to efficiently obtain detailed company information and use it for analysis.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] The user uses the terminal to enter the company name into the input field. The company name is received as input and is ready to be sent to the server at this point. For example, the user enters "Company A." Based on this input, the name of the company to be investigated is determined.

[0107] Step 2:

[0108] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server. Specifically, the following HTTP request is generated:

[0109] POST / query HTTP / 1.1

[0110] Host: example.com

[0111] Content-Type: application / json

[0112] {

[0113] "company_name": "Company A"

[0114] }

[0115] The input is the company name "Company A" entered by the user, and the output is an HTTP request containing this company name.

[0116] Step 3:

[0117] The server queries its internal database based on the received company name "Company A" to retrieve relevant information. Specifically, it executes the following SQL query:

[0118] SELECT FROM company_info WHERE name = 'Company A'

[0119] The input is the company name "Company A," and the output is related data such as market size and competitive information obtained from the database.

[0120] Step 4:

[0121] If the information retrieved from the database is incomplete, the server calls an external API to fill in the missing information. For example, if the latest market information is not in the database, the server sends the following HTTP request to the "Market Information API":

[0122] GET / market_info?company_name=Company A HTTP / 1.1

[0123] Host: externalapi.com

[0124] The input is the company name "Company A" and the category of missing information, and the output is the latest market information obtained from an external API.

[0125] Step 5:

[0126] The server analyzes the acquired data and classifies and organizes it according to the required items. For example, as a result of the analysis, information may be divided into categories such as market size, competition, delivery model, and go-to-market strategy. Data mining algorithms and statistical analysis methods are used in the analysis and organization process. The input is raw data acquired from a database or external API, and the output is analyzed and organized information.

[0127] Step 6:

[0128] The server sends the organized and analyzed data to the device. Specifically, the data is sent in JSON format as shown below:

[0129] {

[0130] "market_size": "$5 billion",

[0131] "competitors": ["Company B", "Company C"],

[0132] "business_model": "subscription-based",

[0133] "gtm_strategy": ["Digital Marketing", "Customer Journey Map"]

[0134] }

[0135] The input is parsed and organized information, and the output is JSON data containing this information.

[0136] Step 7:

[0137] The device displays the received data in its user interface. Specifically, the device screen displays the following information:

[0138] Market size: $5 billion

[0139] Major competitors: Company B, Company C

[0140] Delivery model: Subscription-based

[0141] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0142] The input is JSON data received from the server, and the output is organized information displayed on a user interface.

[0143] This will enable users to efficiently obtain detailed information about companies, significantly reducing the amount of work required for corporate analysis.

[0144] (Application example 1)

[0145] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0146] Conventional corporate information acquisition systems have the problem that the necessary information must be acquired manually, which is time-consuming and inefficient. Furthermore, if the information is incomplete, the latest data must be manually supplemented, and organizing and analyzing the information also places a burden on the user. Furthermore, there is a lack of means to quickly acquire corporate security risk information and visually display it. There is a need for a system that can solve these issues and acquire and display corporate information more efficiently and quickly.

[0147] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0148] In this invention, the server includes means for transmitting an input company name to the server, means for the server to retrieve information by checking a database based on the company name, means for supplementing missing information from an external API, means for analyzing and organizing the retrieved information and displaying it on a user interface, means for visually displaying the information on a smart device display, and means for inputting the company name via voice input. This makes it possible to efficiently retrieve company information and quickly provide users with company information, including security risk information, particularly through visual display on a smart device.

[0149] "Company name" refers to the name of a corporation or organization, and is information used to identify a specific company.

[0150] "Server" refers to a computer system that collects and processes data over a network and provides it to other devices.

[0151] A "database" refers to a collection of organized data and a system that allows efficient access and management of that data.

[0152] An "external API" is an application program interface provided by an external system or service, and refers to a means for other programs to use data or functions.

[0153] "User interface" refers to the screens and operating means by which a user interacts with a system.

[0154] "Smart device" refers to a device that is connected to the Internet and has the ability to aggregate, display, and operate information. Examples include smartphones, smart glasses, and tablets.

[0155] "Voice input" refers to the technology of recognizing human voice as an input signal using a microphone or other device.

[0156] "Market size" refers to the size of sales and growth across a particular market.

[0157] "Competitors" refers to other companies or organizations that offer similar products or services in the same market.

[0158] A "delivery model" refers to the strategy or method by which a company delivers its products or services to consumers.

[0159] A "Go-To-Market Strategy" (GTM Strategy) refers to the plan and methodology for bringing a new product or service to market.

[0160] "Security risk information" refers to information about security threats and risks that companies and systems may face.

[0161] "Visual display" refers to a method of visually expressing information and presenting it to a user through a display or the like.

[0162] To implement this invention, a user first uses a smart device to voice-input a company name into a terminal. The smart device uses a voice input system to allow the user to quickly and efficiently obtain information about a specific company.

[0163] The company name entered by the user is sent from the smart device to the server. The server queries the database based on the received company name to retrieve related information. For example, an HTTP request using Python is used to retrieve data matching the company name using an SQL query such as "SELECT FROM company_info WHERE name = 'Company X'".

[0164] Next, if the information retrieved from the database is incomplete, the server uses external APIs to supplement the missing information. External APIs include market information APIs and security risk information APIs, which are used to obtain additional information on the latest market size and security risks. For example, a request is sent to an endpoint such as "http: / / externalapi.com / api / market_info?name=Company X" to supplement the required information.

[0165] The server analyzes and organizes data obtained from databases and external APIs, converting it into a format suitable for the smart device's user interface. During this analysis and organization process, the data is categorized using Python libraries and presented in a format that can be displayed visually. For example, information can be organized by market size, competitors, delivery model, go-to-market strategy, and security risks.

[0166] The organized information is sent from the server to the smart device and displayed on the device's screen in a format that is easy for users to understand visually. This allows users to efficiently check detailed company information on their devices, such as:

[0167] Market size: $5 billion

[0168] Major competitors: Company Y, Company Z

[0169] Delivery model: Subscription-based

[0170] GTM Strategy: Digital Marketing, Customer Journey Map

[0171] Security Risk: Data leakage risk, medium vulnerability

[0172] As a concrete example, to check security risk information for "Company X," use the following prompt:

[0173] "Please provide detailed information about Company X's market size, key competitors, delivery model, go-to-market strategy, and security risks."

[0174] The system allows for fast and efficient acquisition of corporate information and visualization of security risks, significantly improving business intelligence and security assessment.

[0175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0176] Step 1:

[0177] A user inputs a company name using the voice input system of a smart device.

[0178] Input: Company name via voice input (e.g. "Company X")

[0179] Data processing and output: Convert the voice input data into text format and obtain the company name.

[0180] Step 2:

[0181] The terminal transmits the acquired company name to the server.

[0182] Input: Company name in text format

[0183] Data processing and output: An HTTP request is generated and data including the company name is sent to the server.

[0184] Step 3:

[0185] The server queries a database based on the received business name to retrieve relevant information.

[0186] Enter: Company Name (e.g. "Company X")

[0187] Data processing and output: Execute an SQL query to retrieve company information from the database (e.g., "SELECT FROM company_info WHERE name = 'Company X'"). Retrieved information includes market size, competitors, delivery model, go-to-market strategy, and security risk information.

[0188] Step 4:

[0189] The server uses an external API to supplement information that could not be obtained from the database.

[0190] Input: Incomplete Company Information

[0191] Data processing and output: To obtain the necessary information, HTTP requests are sent to external APIs to obtain complementary information. Specifically, market information APIs and security risk information APIs are used.

[0192] Step 5:

[0193] The server analyzes and organizes the information obtained from the database and external APIs, and converts it into a format suitable for the user interface.

[0194] Input: Acquired company information (market size, competitors, service model, go-to-market strategy, security risk information)

[0195] Data processing and output: Categorize the data and format it in a way that can be displayed visually, for example, by converting it to JSON using a Python library.

[0196] Step 6:

[0197] The server then sends the analyzed and organized information to the smart device.

[0198] Input: Formatted company information

[0199] Data processing and output: Generates an HTTP response and sends it to the smart device.

[0200] Step 7:

[0201] The terminal visually displays the received information on the display of the smart device.

[0202] Input: Formatted company information

[0203] Data processing and output: The received data is analyzed and displayed in a format suitable for a graphical user interface, allowing users to visually check company information.

[0204] This process flow allows users to efficiently and quickly obtain company information and provides the information in a visually understandable format.

[0205] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0206] To implement the present invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then compares the received company name with a database to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the display of the results accordingly. This allows the user to quickly and efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[0207] Detailed explanation of the program's operation:

[0208] User input

[0209] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0210] Starting Data Collection

[0211] The terminal sends the entered company name "Company A" to the server. The terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0212] Database Matching

[0213] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0214] Using external APIs

[0215] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0216] Data analysis and organization

[0217] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0218] Emotion recognition by emotion engine

[0219] The device has an emotion engine that recognizes emotions from the user's face, voice, etc. For example, it analyzes the user's facial expressions and tone of voice through a camera and microphone to detect whether the user is happy, surprised, or anxious.

[0220] Adjusting outcomes according to emotions

[0221] The server adjusts the displayed information and interface based on the emotional data obtained from the emotion engine. For example, if the user is feeling anxious, the server may adjust the information display to be more friendly or add guides or hints.

[0222] Displaying the results

[0223] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0224] Market size: $5 billion

[0225] Major competitors: Company B, Company C

[0226] Delivery model: Subscription-based

[0227] GTM Strategy: Digital Marketing, Customer Journey Map

[0228] Additionally, if the user's emotions are recognized, the display can be customized accordingly, for example by using relaxing language and color schemes to alleviate anxiety.

[0229] This system allows users to efficiently gain deep insights into companies, significantly reducing research efforts, and providing an optimal user experience based on emotions.

[0230] The processing flow will be explained below.

[0231] Step 1:

[0232] The user enters the name of the company to be surveyed in the input field of the terminal. For example, the user enters "Company A" and clicks the "Submit" button.

[0233] Step 2:

[0234] The terminal generates an HTTP request to send the company name "Company A" entered by the user to the server. The request sends JSON-formatted data including the company name as a payload to the server.

[0235] Step 3:

[0236] The server analyzes the received company name "Company A" and generates an SQL statement to query the database. The server sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS).

[0237] Step 4:

[0238] The server receives the query results returned from the database and stores them in temporary storage (such as memory). This information includes market size, competition, delivery model, GTM strategy, etc.

[0239] Step 5:

[0240] If the information obtained from the database is insufficient, the server uses an external API to obtain additional information. For example, it sends an HTTP request to the "Market Information API" including the company name "Company A" to obtain the latest market size information.

[0241] Step 6:

[0242] The server receives additional information from external APIs, stores it in temporary storage, and complements the existing data set with the acquired data to create a complete company profile.

[0243] Step 7:

[0244] The server analyzes the data set and classifies and organizes it by information category (market size, competitors, service model, GTM strategy). The organized data is converted into a user-friendly format (HTML or JSON).

[0245] Step 8:

[0246] The device runs an emotion engine that analyzes the user's facial expressions and tone of voice. The device captures the user's facial expressions and tone of voice through a camera and microphone and generates emotion data.

[0247] Step 9:

[0248] The terminal transmits the generated emotion data to the server, for example, emotion data including information on whether the user is in a relaxed state or an anxious state.

[0249] Step 10:

[0250] The server analyzes the emotion data and adjusts the information and interface displayed according to the user's emotion. For example, if the user is in an anxious state, the server will simplify the information presentation and provide easy-to-understand guidance.

[0251] Step 11:

[0252] The server sends the final dataset, which reflects the analyzed and organized data and adjustments made by the emotion engine, to the terminal and returns the data as an HTTP response.

[0253] Step 12:

[0254] The terminal analyzes the final data set received from the server and displays it in a user interface. The terminal screen displays the following information:

[0255] Market size: $5 billion

[0256] Major competitors: Company B, Company C

[0257] Delivery model: Subscription-based

[0258] GTM Strategy: Digital Marketing, Customer Journey Map

[0259] Additionally, the UI may be adjusted based on the emotional data, such as a relaxing color scheme or additional guidance.

[0260] In this way, the user can efficiently obtain detailed information about the company, and furthermore, an optimal user experience is provided according to the user's feelings.

[0261] Example 2

[0262] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0263] When collecting detailed company information and market data, it is difficult to efficiently obtain information due to the fragmented nature of the information and the incompleteness of the data. Another challenge is providing an appropriate interface that responds to the user's emotions.

[0264] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collating a database based on the company name and acquiring information, a means for supplementing missing information from an external API, a means for analyzing and organizing the acquired information and displaying it on a user interface, and a means for adjusting the display content based on the emotion recognition result. This makes it possible to efficiently collect detailed company information and provide an optimal interface according to the user's emotions.

[0265] "Company name" is a unique name used to identify a company.

[0266] A "server" is a computer system that provides information and services to clients over a network.

[0267] A "database" is a collection of information that is systematically managed so that data can be stored and easily searched and manipulated.

[0268] An "external API" is an interface for communicating with other software or services, providing functions that can be used externally.

[0269] "User interface" refers to the display screen and operating means that allow the user to directly interact with the system.

[0270] An "emotion engine" is an algorithm or system that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[0271] "Market size" is an indicator that shows the total trading volume or total sales of products or services in a particular market.

[0272] "Competitors" refers to multiple companies or businesses that offer similar products or services in the same market.

[0273] A "delivery model" is a business strategy or method for how a company delivers products or services to customers.

[0274] A "go-to-market strategy" is a plan or strategy for bringing a new product or service to market and reaching customers.

[0275] The present invention is a system for efficiently collecting corporate information and providing a user with an appropriate interface according to their emotions. A specific method for carrying out the present invention will be described below.

[0276] First, the user uses the terminal to input the name of the company to be researched. The terminal has an input field where the user can input the name of the company they want to research. For example, if the user inputs "Company A," this company will be the subject of research.

[0277] Next, the device sends the entered company name "Company A" to the server. The device generates an HTTP POST request and sends JSON-formatted data including the company name to the server. At this time, the device communicates with the server via the Internet.

[0278] The server queries its internal database based on the received company name, "Company A," to retrieve relevant information. For example, it executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to collate data with the database management system (DBMS). This database stores company information such as market size, competitors, service model, and go-to-market strategy.

[0279] If the server cannot obtain the necessary information from its internal database, it uses an external API to fill in the missing information. For example, it sends an HTTP request to the "Market Information API" to obtain the latest market size data for "Company A." Data from the external API is also returned in JSON format.

[0280] The server analyzes the information obtained from the database and external APIs, classifying and organizing it according to the required items. For example, it converts the information into a data frame using Python's Pandas library and performs analysis according to each category (market size, competition, delivery model, go-to-market strategy). It then formats the information into a user interface format.

[0281] The device is equipped with an emotion engine that analyzes the user's face and voice to recognize emotions. For example, a facial recognition camera captures the user's facial expressions and inputs the data into an emotion recognition algorithm. A microphone also collects audio and analyzes the tone of voice. This analyzed data is sent to a server.

[0282] The server adjusts the information display and interface based on the emotional data sent from the device. For example, if the user is feeling anxious, the server changes the display to a more friendly format and adds guides and hints, allowing the user to view the necessary information in a relaxed manner.

[0283] Finally, the organized and analyzed data is sent from the server to the device and displayed on the device's user interface. For example, the following information is displayed:

[0284] Market size: $5 billion

[0285] Major competitors: Company B, Company C

[0286] Delivery model: Subscription-based

[0287] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0288] It also customizes the experience based on the user's emotions, adding relaxing color schemes and effective explanatory text to optimize the user experience.

[0289] Example prompt sentence:

[0290] Please explain in detail the processing steps of the program in which the user enters the company name "Company A," the server uses the internal database and external API to collect the necessary information, and displays it to the user.

[0291] In this way, users can quickly and efficiently obtain detailed information about a company, and an optimal interface is provided that responds to the user's emotions.

[0292] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0293] Step 1:

[0294] The user inputs the name of a company into the input field of the terminal. For example, by inputting "Company A," the research target is determined. This input is the input data.

[0295] Step 2:

[0296] The terminal structures the company name "Company A" entered by the user as JSON format data and generates an HTTP POST request. The terminal sends this request to the server. The input is the company name, and the output is the request to the server.

[0297] Step 3:

[0298] The server queries its internal database based on the received company name "Company A". It executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to retrieve relevant information. The input is the company name and the output is information from the database.

[0299] Step 4:

[0300] The server checks the information retrieved from the database and identifies any missing information. For example, if market size or competitive information is missing, it uses an external API to supplement this information. The input is information from the database, and the output is the supplemented information.

[0301] Step 5:

[0302] The server sends an HTTP request to an external API to obtain the missing information. For example, the server obtains market size data for "Company A" from the "Market Information API." The input is the server request, and the output is data from the external API.

[0303] Step 6:

[0304] The server analyzes, classifies, and organizes the acquired information. It uses Python's Pandas library to convert the data into a data frame format and analyzes it by category (market size, competitors, delivery model, go-to-market strategy). The input is information from the database and external API, and the output is the analyzed data.

[0305] Step 7:

[0306] The device uses an emotion engine to recognize the user's emotions. It uses a camera and microphone to collect and analyze the user's facial expressions and voice. For example, if the user is surprised, the emotion engine analyzes their facial expressions and tone of voice. The input is the user's facial expressions and voice, and the output is emotion data.

[0307] Step 8:

[0308] The device sends the recognized emotion data to the server. The input is the emotion data of the device, and the output is the transmission of the emotion data to the server.

[0309] Step 9:

[0310] The server adjusts the displayed information and interface based on the emotional data. For example, if the user feels anxious, it makes the interface more friendly and adds guides and hints. The input is emotional data, and the output is adjusted interface information.

[0311] Step 10:

[0312] The server sends the organized and analyzed data and interface information to the terminal. The input is the organized data and adjusted interface information in the server, and the output is sent to the terminal.

[0313] Step 11:

[0314] The device displays the received data in a user interface. The user can see the following information on the device screen:

[0315] Market size: $5 billion

[0316] Main competitors: Other company B, other company C

[0317] Delivery model: Subscription

[0318] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0319] Furthermore, it provides an interface that is customized according to the user's emotions. The input is data from the server, and the output is a display on the user interface.

[0320] (Application example 2)

[0321] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0322] Collecting and analyzing corporate information requires a lot of time and effort due to the wide range of information involved. Furthermore, the user experience is not sufficiently improved because the information is not displayed optimally according to the user's emotional state. Therefore, there is a need for the development of a system that efficiently acquires necessary information and displays it appropriately according to the user's emotional state.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0324] In this invention, the server includes means for transmitting the input company name, means for collating the company name with a database to obtain information, means for supplementing missing information from an external API, means for analyzing and organizing the obtained information and displaying it on a user interface, and means for recognizing the user's emotions and adjusting the display results. This enables the user to efficiently obtain the company information they need and provides an optimal interface according to their emotions.

[0325] A "company name" is a name used to identify a specific business entity.

[0326] A "server" is a computer system that processes and stores data and provides information in response to user requests.

[0327] A "database" is a collection of data that can be efficiently stored, managed, and searched.

[0328] An "external API" is an external programming interface provided in a form that can be accessed by other systems or applications.

[0329] A "user interface" is the part where information is exchanged between the user and the system, and provides operation and display functions.

[0330] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's response based on that information.

[0331] "Analysis" is the process of examining collected data in detail and extracting the necessary information.

[0332] "Organizing" is the process of classifying acquired data into categories and converting them into an easy-to-read format.

[0333] "Market size" is information about the total sales or total volume of transactions of a product in a particular market.

[0334] "Competitors" are other entities in the same market that offer similar products or services and compete for customers.

[0335] A "delivery model" is a specific method or business model for providing products or services to customers.

[0336] A "Go-To-Market Strategy" is a sales strategy or marketing plan for introducing new products or services to the market.

[0337] "Store information" refers to detailed information about a specific commercial facility or retail store, including its location, opening hours, and the products and services it offers.

[0338] To implement this invention, the user must first operate the terminal to input the name of the company to be surveyed. For example, the user inputs the company name into an input field of the smartphone app "Brick Store Analyzer."

[0339] The device then sends the entered company name to the server. The device generates an HTTP request and sends JSON-formatted data containing the company name as a payload to the server. At this point, a database match is performed on the server side. The server issues a query to its internal database to retrieve information about the company. For example, the SQL query "SELECT FROM store_info WHERE name = 'Company A'" is used. MySQL (registered trademark) is a commonly used database management system (DBMS).

[0340] If the information the server retrieves from the database is incomplete, the server uses external APIs. The missing information is retrieved from external market information APIs or competitive information APIs. The server sends HTTP requests to these external APIs to complete the missing information.

[0341] The server then analyzes and organizes all the information it has acquired. This analysis is performed using data analysis tools such as Python and R, as well as ML libraries (e.g., scikit-learn). The information is categorized into categories such as market size, competitors, service model, GTM strategy, and store information. The analysis results are then converted into a format suitable for the user interface.

[0342] The device is equipped with an emotion recognition function that recognizes the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice through the smartphone's camera and microphone to understand the user's emotional state. Technologies such as TENSORFLOW (registered trademark) and OpenCV are used for this emotion recognition.

[0343] The server adjusts the displayed information and interface based on the emotional data. For example, if the user has an anxious expression, the information display will be more friendly and additional guidance and hints will be provided.

[0344] Finally, the analyzed and organized data is sent from the server to the terminal, which displays it on the user interface. For example, the following information is displayed on the terminal screen:

[0345] Market size: $5 billion

[0346] Main competitors: Store B, Store C

[0347] Delivery model: Subscription-based

[0348] GTM Strategy: Digital Marketing, Customer Journey Map

[0349] This series of processes enables users to efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[0350] An example prompt is:

[0351] "Get Company A's market size, key competitors, delivery model, and GTM strategy, and present it in a format that's easy for users to use. If users are unsure, provide the information in a way that puts them at ease."

[0352] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0353] Step 1:

[0354] The user operates the terminal and inputs the name of the company to be investigated. In the input field, the name of the company to be investigated (e.g., "Company A") is entered. The input company name then becomes the input data for the next processing step.

[0355] Step 2:

[0356] The terminal sends the entered company name to the server. Specifically, it generates an HTTP request and sends JSON-formatted data including the company name as a payload to the server. At this point, the input data is the company name, and the output data is the HTTP request sent to the server.

[0357] Step 3:

[0358] The server issues a query to its internal database based on the received company name. For example, it executes the SQL query "SELECT FROM store_info WHERE name = 'Company A'" to retrieve related information. The input data for this step is the company name, and the output data is the information retrieved from the database.

[0359] Step 4:

[0360] If the information obtained by the server is incomplete, it supplements the missing information from an external API. Specifically, it sends an HTTP request to an external market information API or competitive information API to obtain the necessary information. In this process, the input data is incomplete company information, and the output data is the supplemented, complete information.

[0361] Step 5:

[0362] The server analyzes and organizes all the acquired information. Using data analysis tools such as Python and R, the information is categorized into market size, competitors, service models, GTM strategies, and store information. The input data for this step is the completed company information, and the output data is the analyzed and classified information.

[0363] Step 6:

[0364] The device recognizes the user's emotional state by using an emotion engine to analyze the user's facial expressions and tone of voice via the smartphone's camera and microphone. The input data for this process is the user's real-time facial expressions and voice data, and the output data is the analyzed emotional information.

[0365] Step 7:

[0366] The server adjusts the display content and interface based on the emotion data. For example, if the user is anxious, the information display will be made more friendly and guides and hints will be added. The input data for this step are emotion data and analyzed and classified company information, and the output data is the adjusted display content.

[0367] Step 8:

[0368] The server sends the organized information to the terminal, which then displays the received information on the user interface. For example, information such as market size, major competitors, offering model, and GTM strategy is displayed appropriately on the screen. In this final step, the input data is the adjusted company information, and the output data is the information displayed on the user interface.

[0369] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0370] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search<url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0371] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0372] [Second embodiment]

[0373] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0374] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0375] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0376] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0377] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0378] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0379] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0380] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0381] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0382] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0383] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0384] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0385] To implement this invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then checks the database based on the received company name to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. This allows users to quickly and efficiently obtain the company information they need.

[0386] Detailed explanation of the program's operation:

[0387] User input

[0388] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0389] Starting Data Collection

[0390] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server.

[0391] Database Matching

[0392] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it executes an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0393] Using external APIs

[0394] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0395] Data analysis and organization

[0396] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0397] Displaying the results

[0398] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0399] Market size: $5 billion

[0400] Major competitors: Company B, Company C

[0401] Delivery model: Subscription-based

[0402] GTM Strategy: Digital Marketing, Customer Journey Map

[0403] A system with such a mechanism allows users to efficiently gain deep insight into companies and significantly reduce the amount of research work required.

[0404] The processing flow will be explained below.

[0405] Step 1:

[0406] The user enters the name of the company to be surveyed in the input field on the terminal. For example, the user enters "Company A." The user clicks the "Submit" button to proceed to the next step.

[0407] Step 2:

[0408] The terminal sends the company name "Company A" entered by the user to the server. At this time, the terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0409] Step 3:

[0410] The server receives the received company name "Company A" and executes a query against the database. For example, the server sends an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve related information.

[0411] Step 4:

[0412] The server stores the information obtained as a result of the SQL query in temporary storage (e.g., memory), which prepares the data for use in the next process.

[0413] Step 5:

[0414] If the information retrieved from the database is insufficient, the server uses an external API to supplement the information. For example, the server sends an HTTP request to the "Market Information API" including the company name "Company A" as a parameter to retrieve the latest market size data.

[0415] Step 6:

[0416] The server receives the response data from the external API and stores it in temporary storage. Based on the retrieved data, it complements the existing data set to create a complete company information set.

[0417] Step 7:

[0418] The server analyzes the organized data, which includes categorizing the data (market size, competition, delivery model, GTM strategy, etc.) and providing detailed analysis for each category.

[0419] Step 8:

[0420] The server converts the analyzed and organized data into a format that is easy for users to use, such as HTML or JSON, and generates the final dataset.

[0421] Step 9:

[0422] The server sends the final dataset to the device as an HTTP response, which includes detailed information about market size, competition, offering model, and GTM strategy.

[0423] Step 10:

[0424] The device analyzes the data received from the server and displays it on a user interface, which visually displays the following information:

[0425] Market size: $5 billion

[0426] Major competitors: Company B, Company C

[0427] Delivery model: Subscription-based

[0428] GTM Strategy: Digital Marketing, Customer Journey Map

[0429] Example 1

[0430] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0431] In today's business environment, there is a need to quickly and accurately collect and analyze corporate information. However, traditional systems make it difficult to properly supplement missing information in databases, requiring manual work and additional research to obtain complete information. As a result, information collection and analysis require a great deal of time and effort.

[0432] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0433] In this invention, the server includes: a means for a user to input a company name into an input field; a means for a terminal to transmit the input company name to the server; a means for the server to query a database based on the company name and obtain information; a means for the server to call an external API to supplement the missing information if the information obtained from the database is incomplete; a means for the server to analyze the obtained information and classify and organize it by item; and a means for transmitting the organized information from the server to the terminal and for the terminal to display it on a user interface. This makes it possible to quickly and efficiently collect company information and provide the information required by the user in an organized manner.

[0434] A "user" is a person or operator who interacts with the system to enter a business name and receive the results.

[0435] A "terminal" is a device operated by a user, and is a device for inputting a company name and performing data communication with a server.

[0436] "Server" is a central computer system that queries the database based on the company name received from the user, retrieves and completes the required information, and sends the final results to the terminal.

[0437] "Company name" is the name of the corporation that the user designates as the target of the survey or information gathering.

[0438] A "database" is a collection of information managed by a server, including various data related to a company.

[0439] An "external API" is an external application programming interface used by the server to supplement information missing from the database.

[0440] A "query" is a command or question executed by a server to obtain specific information from a database.

[0441] "Analysis" refers to the act of breaking down and processing the data acquired by the server, and processing it to understand its meaning and intent.

[0442] "Classification and organization" is the act of dividing analyzed data into categories based on specific criteria and arranging them in an orderly manner.

[0443] "User interface" refers to the display screen and input means that allow a user to check and operate information on a terminal.

[0444] To implement this invention, a user first uses a terminal to input the name of a company to be investigated. The terminal then sends the input company name to a server as an HTTP request. The server then queries an internal database based on the received company name to retrieve relevant information. This query is performed, for example, using SQL.

[0445] If the information the server retrieves from the database is incomplete, it uses an external API to fill in the missing information. For example, it may call a "Market Information API" to obtain the latest market information. The server sends this request as an HTTP request to the external API to obtain the required data.

[0446] The server then analyzes the acquired data and classifies and organizes it into the necessary items, dividing the information into multiple categories such as market size, competitors, offering models, and go-to-market strategies. This analysis and organization process is carried out using specific algorithms and data mining techniques.

[0447] Once the analysis and organization is complete, the server sends the information to the device, which then displays the received data on a user interface. This allows users to easily understand the desired company information, such as market size, major competitors, the company's service model, and GTM strategy.

[0448] For example, if a user wants to find information about "Company A," they enter "Company A" into their device. The device sends this company name to the server, which then performs the following process:

[0449] 1. Obtain information about "Company A" from the database.

[0450] 2. Obtain missing market information from an external API.

[0451] 3. Analyze and organize the information obtained.

[0452] 4. Present organized information in a user interface.

[0453] The generative AI model can also be used to respond to specific questions from users. For example, by entering a prompt such as, "Please tell me the latest information on Company A's market size, competitors, delivery model, and go-to-market strategy," detailed company information can be provided. This system allows users to efficiently obtain detailed company information and use it for analysis.

[0454] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0455] Step 1:

[0456] The user uses the terminal to enter the company name into the input field. The company name is received as input and is ready to be sent to the server at this point. For example, the user enters "Company A." Based on this input, the name of the company to be investigated is determined.

[0457] Step 2:

[0458] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server. Specifically, the following HTTP request is generated:

[0459] POST / query HTTP / 1.1

[0460] Host: example.com

[0461] Content-Type: application / json

[0462] {

[0463] "company_name": "Company A"

[0464] }

[0465] The input is the company name "Company A" entered by the user, and the output is an HTTP request containing this company name.

[0466] Step 3:

[0467] The server queries its internal database based on the received company name "Company A" to retrieve relevant information. Specifically, it executes the following SQL query:

[0468] SELECT FROM company_info WHERE name = 'Company A'

[0469] The input is the company name "Company A," and the output is related data such as market size and competitive information obtained from the database.

[0470] Step 4:

[0471] If the information retrieved from the database is incomplete, the server calls an external API to fill in the missing information. For example, if the latest market information is not in the database, the server sends the following HTTP request to the "Market Information API":

[0472] GET / market_info?company_name=Company A HTTP / 1.1

[0473] Host: externalapi.com

[0474] The input is the company name "Company A" and the category of missing information, and the output is the latest market information obtained from an external API.

[0475] Step 5:

[0476] The server analyzes the acquired data and classifies and organizes it according to the required items. For example, as a result of the analysis, information may be divided into categories such as market size, competition, delivery model, and go-to-market strategy. Data mining algorithms and statistical analysis methods are used in the analysis and organization process. The input is raw data acquired from a database or external API, and the output is analyzed and organized information.

[0477] Step 6:

[0478] The server sends the organized and analyzed data to the device. Specifically, the data is sent in JSON format as shown below:

[0479] {

[0480] "market_size": "$5 billion",

[0481] "competitors": ["Company B", "Company C"],

[0482] "business_model": "subscription-based",

[0483] "gtm_strategy": ["Digital Marketing", "Customer Journey Map"]

[0484] }

[0485] The input is parsed and organized information, and the output is JSON data containing this information.

[0486] Step 7:

[0487] The device displays the received data in its user interface. Specifically, the device screen displays the following information:

[0488] Market size: $5 billion

[0489] Major competitors: Company B, Company C

[0490] Delivery model: Subscription-based

[0491] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0492] The input is JSON data received from the server, and the output is organized information displayed on a user interface.

[0493] This will enable users to efficiently obtain detailed information about companies, significantly reducing the amount of work required for corporate analysis.

[0494] (Application example 1)

[0495] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0496] Conventional corporate information acquisition systems have the problem that the necessary information must be acquired manually, which is time-consuming and inefficient. Furthermore, if the information is incomplete, the latest data must be manually supplemented, and organizing and analyzing the information also places a burden on the user. Furthermore, there is a lack of means to quickly acquire corporate security risk information and visually display it. There is a need for a system that can solve these issues and acquire and display corporate information more efficiently and quickly.

[0497] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0498] In this invention, the server includes means for transmitting an input company name to the server, means for the server to retrieve information by checking a database based on the company name, means for supplementing missing information from an external API, means for analyzing and organizing the retrieved information and displaying it on a user interface, means for visually displaying the information on a smart device display, and means for inputting the company name via voice input. This makes it possible to efficiently retrieve company information and quickly provide users with company information, including security risk information, particularly through visual display on a smart device.

[0499] "Company name" refers to the name of a corporation or organization, and is information used to identify a specific company.

[0500] "Server" refers to a computer system that collects and processes data over a network and provides it to other devices.

[0501] A "database" refers to a collection of organized data and a system that allows efficient access and management of that data.

[0502] An "external API" is an application program interface provided by an external system or service, and refers to a means for other programs to use data or functions.

[0503] "User interface" refers to the screens and operating means by which a user interacts with a system.

[0504] "Smart device" refers to a device that is connected to the Internet and has the ability to aggregate, display, and operate information. Examples include smartphones, smart glasses, and tablets.

[0505] "Voice input" refers to the technology of recognizing human voice as an input signal using a microphone or other device.

[0506] "Market size" refers to the size of sales and growth across a particular market.

[0507] "Competitors" refers to other companies or organizations that offer similar products or services in the same market.

[0508] A "delivery model" refers to the strategy or method by which a company delivers its products or services to consumers.

[0509] A "Go-To-Market Strategy" (GTM Strategy) refers to the plan and methodology for bringing a new product or service to market.

[0510] "Security risk information" refers to information about security threats and risks that companies and systems may face.

[0511] "Visual display" refers to a method of visually expressing information and presenting it to a user through a display or the like.

[0512] To implement this invention, a user first uses a smart device to voice-input a company name into a terminal. The smart device uses a voice input system to allow the user to quickly and efficiently obtain information about a specific company.

[0513] The company name entered by the user is sent from the smart device to the server. The server queries the database based on the received company name to retrieve related information. For example, an HTTP request using Python is used to retrieve data matching the company name using an SQL query such as "SELECT FROM company_info WHERE name = 'Company X'".

[0514] Next, if the information retrieved from the database is incomplete, the server uses external APIs to supplement the missing information. External APIs include market information APIs and security risk information APIs, which are used to obtain additional information on the latest market size and security risks. For example, a request is sent to an endpoint such as "http: / / externalapi.com / api / market_info?name=Company X" to supplement the required information.

[0515] The server analyzes and organizes data obtained from databases and external APIs, converting it into a format suitable for the smart device's user interface. During this analysis and organization process, the data is categorized using Python libraries and presented in a format that can be displayed visually. For example, information can be organized by market size, competitors, delivery model, go-to-market strategy, and security risks.

[0516] The organized information is sent from the server to the smart device and displayed on the device's screen in a format that is easy for users to understand visually. This allows users to efficiently check detailed company information on their devices, such as:

[0517] Market size: $5 billion

[0518] Major competitors: Company Y, Company Z

[0519] Delivery model: Subscription-based

[0520] GTM Strategy: Digital Marketing, Customer Journey Map

[0521] Security Risk: Data leakage risk, medium vulnerability

[0522] As a concrete example, to check security risk information for "Company X," use the following prompt:

[0523] "Please provide detailed information about Company X's market size, key competitors, delivery model, go-to-market strategy, and security risks."

[0524] The system allows for fast and efficient acquisition of corporate information and visualization of security risks, significantly improving business intelligence and security assessment.

[0525] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0526] Step 1:

[0527] A user inputs a company name using the voice input system of a smart device.

[0528] Input: Company name via voice input (e.g. "Company X")

[0529] Data processing and output: Convert the voice input data into text format and obtain the company name.

[0530] Step 2:

[0531] The terminal transmits the acquired company name to the server.

[0532] Input: Company name in text format

[0533] Data processing and output: An HTTP request is generated and data including the company name is sent to the server.

[0534] Step 3:

[0535] The server queries a database based on the received business name to retrieve relevant information.

[0536] Enter: Company Name (e.g. "Company X")

[0537] Data processing and output: Execute an SQL query to retrieve company information from the database (e.g., "SELECT FROM company_info WHERE name = 'Company X'"). Retrieved information includes market size, competitors, delivery model, go-to-market strategy, and security risk information.

[0538] Step 4:

[0539] The server uses an external API to supplement information that could not be obtained from the database.

[0540] Input: Incomplete Company Information

[0541] Data processing and output: To obtain the necessary information, HTTP requests are sent to external APIs to obtain complementary information. Specifically, market information APIs and security risk information APIs are used.

[0542] Step 5:

[0543] The server analyzes and organizes the information obtained from the database and external APIs, and converts it into a format suitable for the user interface.

[0544] Input: Acquired company information (market size, competitors, service model, go-to-market strategy, security risk information)

[0545] Data processing and output: Categorize the data and format it in a way that can be displayed visually, for example, by converting it to JSON using a Python library.

[0546] Step 6:

[0547] The server then sends the analyzed and organized information to the smart device.

[0548] Input: Formatted company information

[0549] Data processing and output: Generates an HTTP response and sends it to the smart device.

[0550] Step 7:

[0551] The terminal visually displays the received information on the display of the smart device.

[0552] Input: Formatted company information

[0553] Data processing and output: The received data is analyzed and displayed in a format suitable for a graphical user interface, allowing users to visually check company information.

[0554] This process flow allows users to efficiently and quickly obtain company information and provides the information in a visually understandable format.

[0555] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0556] To implement the present invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then compares the received company name with a database to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the display of the results accordingly. This allows the user to quickly and efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[0557] Detailed explanation of the program's operation:

[0558] User input

[0559] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0560] Starting Data Collection

[0561] The terminal sends the entered company name "Company A" to the server. The terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0562] Database Matching

[0563] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0564] Using external APIs

[0565] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0566] Data analysis and organization

[0567] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0568] Emotion recognition by emotion engine

[0569] The device has an emotion engine that recognizes emotions from the user's face, voice, etc. For example, it analyzes the user's facial expressions and tone of voice through a camera and microphone to detect whether the user is happy, surprised, or anxious.

[0570] Adjusting outcomes according to emotions

[0571] The server adjusts the displayed information and interface based on the emotional data obtained from the emotion engine. For example, if the user is feeling anxious, the server may adjust the information display to be more friendly or add guides or hints.

[0572] Displaying the results

[0573] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0574] Market size: $5 billion

[0575] Major competitors: Company B, Company C

[0576] Delivery model: Subscription-based

[0577] GTM Strategy: Digital Marketing, Customer Journey Map

[0578] Additionally, if the user's emotions are recognized, the display can be customized accordingly, for example by using relaxing language and color schemes to alleviate anxiety.

[0579] This system allows users to efficiently gain deep insights into companies, significantly reducing research efforts, and providing an optimal user experience based on emotions.

[0580] The processing flow will be explained below.

[0581] Step 1:

[0582] The user enters the name of the company to be surveyed in the input field of the terminal. For example, the user enters "Company A" and clicks the "Submit" button.

[0583] Step 2:

[0584] The terminal generates an HTTP request to send the company name "Company A" entered by the user to the server. The request sends JSON-formatted data including the company name as a payload to the server.

[0585] Step 3:

[0586] The server analyzes the received company name "Company A" and generates an SQL statement to query the database. The server sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS).

[0587] Step 4:

[0588] The server receives the query results returned from the database and stores them in temporary storage (such as memory). This information includes market size, competition, delivery model, GTM strategy, etc.

[0589] Step 5:

[0590] If the information obtained from the database is insufficient, the server uses an external API to obtain additional information. For example, it sends an HTTP request to the "Market Information API" including the company name "Company A" to obtain the latest market size information.

[0591] Step 6:

[0592] The server receives additional information from external APIs, stores it in temporary storage, and complements the existing data set with the acquired data to create a complete company profile.

[0593] Step 7:

[0594] The server analyzes the data set and classifies and organizes it by information category (market size, competitors, service model, GTM strategy). The organized data is converted into a user-friendly format (HTML or JSON).

[0595] Step 8:

[0596] The device runs an emotion engine that analyzes the user's facial expressions and tone of voice. The device captures the user's facial expressions and tone of voice through a camera and microphone and generates emotion data.

[0597] Step 9:

[0598] The terminal transmits the generated emotion data to the server, for example, emotion data including information on whether the user is in a relaxed state or an anxious state.

[0599] Step 10:

[0600] The server analyzes the emotion data and adjusts the information and interface displayed according to the user's emotion. For example, if the user is in an anxious state, the server will simplify the information presentation and provide easy-to-understand guidance.

[0601] Step 11:

[0602] The server sends the final dataset, which reflects the analyzed and organized data and adjustments made by the emotion engine, to the terminal and returns the data as an HTTP response.

[0603] Step 12:

[0604] The terminal analyzes the final data set received from the server and displays it in a user interface. The terminal screen displays the following information:

[0605] Market size: $5 billion

[0606] Major competitors: Company B, Company C

[0607] Delivery model: Subscription-based

[0608] GTM Strategy: Digital Marketing, Customer Journey Map

[0609] Additionally, the UI may be adjusted based on the emotional data, such as a relaxing color scheme or additional guidance.

[0610] In this way, the user can efficiently obtain detailed information about the company, and furthermore, an optimal user experience is provided according to the user's feelings.

[0611] Example 2

[0612] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0613] When collecting detailed company information and market data, it is difficult to efficiently obtain information due to the fragmented nature of the information and the incompleteness of the data. Another challenge is providing an appropriate interface that responds to the user's emotions.

[0614] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collating a database based on the company name and acquiring information, a means for supplementing missing information from an external API, a means for analyzing and organizing the acquired information and displaying it on a user interface, and a means for adjusting the display content based on the emotion recognition result. This makes it possible to efficiently collect detailed company information and provide an optimal interface according to the user's emotions.

[0615] "Company name" is a unique name used to identify a company.

[0616] A "server" is a computer system that provides information and services to clients over a network.

[0617] A "database" is a collection of information that is systematically managed so that data can be stored and easily searched and manipulated.

[0618] An "external API" is an interface for communicating with other software or services, providing functions that can be used externally.

[0619] "User interface" refers to the display screen and operating means that allow the user to directly interact with the system.

[0620] An "emotion engine" is an algorithm or system that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[0621] "Market size" is an indicator that shows the total trading volume or total sales of products or services in a particular market.

[0622] "Competitors" refers to multiple companies or businesses that offer similar products or services in the same market.

[0623] A "delivery model" is a business strategy or method for how a company delivers products or services to customers.

[0624] A "go-to-market strategy" is a plan or strategy for bringing a new product or service to market and reaching customers.

[0625] The present invention is a system for efficiently collecting corporate information and providing a user with an appropriate interface according to their emotions. A specific method for carrying out the present invention will be described below.

[0626] First, the user uses the terminal to input the name of the company to be researched. The terminal has an input field where the user can input the name of the company they want to research. For example, if the user inputs "Company A," this company will be the subject of research.

[0627] Next, the device sends the entered company name "Company A" to the server. The device generates an HTTP POST request and sends JSON-formatted data including the company name to the server. At this time, the device communicates with the server via the Internet.

[0628] The server queries its internal database based on the received company name, "Company A," to retrieve relevant information. For example, it executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to collate data with the database management system (DBMS). This database stores company information such as market size, competitors, service model, and go-to-market strategy.

[0629] If the server cannot obtain the necessary information from its internal database, it uses an external API to fill in the missing information. For example, it sends an HTTP request to the "Market Information API" to obtain the latest market size data for "Company A." Data from the external API is also returned in JSON format.

[0630] The server analyzes the information obtained from the database and external APIs, classifying and organizing it according to the required items. For example, it converts the information into a data frame using Python's Pandas library and performs analysis according to each category (market size, competition, delivery model, go-to-market strategy). It then formats the information into a user interface format.

[0631] The device is equipped with an emotion engine that analyzes the user's face and voice to recognize emotions. For example, a facial recognition camera captures the user's facial expressions and inputs the data into an emotion recognition algorithm. A microphone also collects audio and analyzes the tone of voice. This analyzed data is sent to a server.

[0632] The server adjusts the information display and interface based on the emotional data sent from the device. For example, if the user is feeling anxious, the server changes the display to a more friendly format and adds guides and hints, allowing the user to view the necessary information in a relaxed manner.

[0633] Finally, the organized and analyzed data is sent from the server to the device and displayed on the device's user interface. For example, the following information is displayed:

[0634] Market size: $5 billion

[0635] Major competitors: Company B, Company C

[0636] Delivery model: Subscription-based

[0637] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0638] It also customizes the experience based on the user's emotions, adding relaxing color schemes and effective explanatory text to optimize the user experience.

[0639] Example prompt sentence:

[0640] Please explain in detail the processing steps of the program in which the user enters the company name "Company A," the server uses the internal database and external API to collect the necessary information, and displays it to the user.

[0641] In this way, users can quickly and efficiently obtain detailed information about a company, and an optimal interface is provided that responds to the user's emotions.

[0642] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0643] Step 1:

[0644] The user inputs the name of a company into the input field of the terminal. For example, by inputting "Company A," the research target is determined. This input is the input data.

[0645] Step 2:

[0646] The terminal structures the company name "Company A" entered by the user as JSON format data and generates an HTTP POST request. The terminal sends this request to the server. The input is the company name, and the output is the request to the server.

[0647] Step 3:

[0648] The server queries its internal database based on the received company name "Company A". It executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to retrieve relevant information. The input is the company name and the output is information from the database.

[0649] Step 4:

[0650] The server checks the information retrieved from the database and identifies any missing information. For example, if market size or competitive information is missing, it uses an external API to supplement this information. The input is information from the database, and the output is the supplemented information.

[0651] Step 5:

[0652] The server sends an HTTP request to an external API to obtain the missing information. For example, the server obtains market size data for "Company A" from the "Market Information API." The input is the server request, and the output is data from the external API.

[0653] Step 6:

[0654] The server analyzes, classifies, and organizes the acquired information. It uses Python's Pandas library to convert the data into a data frame format and analyzes it by category (market size, competitors, delivery model, go-to-market strategy). The input is information from the database and external API, and the output is the analyzed data.

[0655] Step 7:

[0656] The device uses an emotion engine to recognize the user's emotions. It uses a camera and microphone to collect and analyze the user's facial expressions and voice. For example, if the user is surprised, the emotion engine analyzes their facial expressions and tone of voice. The input is the user's facial expressions and voice, and the output is emotion data.

[0657] Step 8:

[0658] The device sends the recognized emotion data to the server. The input is the emotion data of the device, and the output is the transmission of the emotion data to the server.

[0659] Step 9:

[0660] The server adjusts the displayed information and interface based on the emotional data. For example, if the user feels anxious, it makes the interface more friendly and adds guides and hints. The input is emotional data, and the output is adjusted interface information.

[0661] Step 10:

[0662] The server sends the organized and analyzed data and interface information to the terminal. The input is the organized data and adjusted interface information in the server, and the output is sent to the terminal.

[0663] Step 11:

[0664] The device displays the received data in a user interface. The user can see the following information on the device screen:

[0665] Market size: $5 billion

[0666] Main competitors: Other company B, other company C

[0667] Delivery model: Subscription

[0668] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0669] Furthermore, it provides an interface that is customized according to the user's emotions. The input is data from the server, and the output is a display on the user interface.

[0670] (Application example 2)

[0671] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0672] Collecting and analyzing corporate information requires a lot of time and effort due to the wide range of information involved. Furthermore, the user experience is not sufficiently improved because the information is not displayed optimally according to the user's emotional state. Therefore, there is a need for the development of a system that efficiently acquires necessary information and displays it appropriately according to the user's emotional state.

[0673] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0674] In this invention, the server includes means for transmitting the input company name, means for collating the company name with a database to obtain information, means for supplementing missing information from an external API, means for analyzing and organizing the obtained information and displaying it on a user interface, and means for recognizing the user's emotions and adjusting the display results. This enables the user to efficiently obtain the company information they need and provides an optimal interface according to their emotions.

[0675] A "company name" is a name used to identify a specific business entity.

[0676] A "server" is a computer system that processes and stores data and provides information in response to user requests.

[0677] A "database" is a collection of data that can be efficiently stored, managed, and searched.

[0678] An "external API" is an external programming interface provided in a form that can be accessed by other systems or applications.

[0679] A "user interface" is the part where information is exchanged between the user and the system, and provides operation and display functions.

[0680] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's response based on that information.

[0681] "Analysis" is the process of examining collected data in detail and extracting the necessary information.

[0682] "Organizing" is the process of classifying acquired data into categories and converting them into an easy-to-read format.

[0683] "Market size" is information about the total sales or total volume of transactions of a product in a particular market.

[0684] "Competitors" are other entities in the same market that offer similar products or services and compete for customers.

[0685] A "delivery model" is a specific method or business model for providing products or services to customers.

[0686] A "Go-To-Market Strategy" is a sales strategy or marketing plan for introducing new products or services to the market.

[0687] "Store information" refers to detailed information about a specific commercial facility or retail store, including its location, opening hours, and the products and services it offers.

[0688] To implement this invention, the user must first operate the terminal to input the name of the company to be surveyed. For example, the user inputs the company name into an input field of the smartphone app "Brick Store Analyzer."

[0689] The device then sends the entered company name to the server. The device generates an HTTP request and sends JSON-formatted data containing the company name as a payload to the server. At this point, a database match is performed on the server side. The server issues a query to its internal database to retrieve information about the company. For example, the SQL query "SELECT FROM store_info WHERE name = 'Company A'" is used. MySQL is a commonly used database management system (DBMS).

[0690] If the information the server retrieves from the database is incomplete, the server uses external APIs. The missing information is retrieved from external market information APIs or competitive information APIs. The server sends HTTP requests to these external APIs to complete the missing information.

[0691] The server then analyzes and organizes all the information it has acquired. This analysis is performed using data analysis tools such as Python and R, as well as ML libraries (e.g., scikit-learn). The information is categorized into categories such as market size, competitors, service model, GTM strategy, and store information. The analysis results are then converted into a format suitable for the user interface.

[0692] The device is equipped with an emotion recognition function that recognizes the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice through the smartphone's camera and microphone to understand the user's emotional state. This emotion recognition uses technologies such as TensorFlow and OpenCV.

[0693] The server adjusts the displayed information and interface based on the emotional data. For example, if the user has an anxious expression, the information display will be more friendly and additional guidance and hints will be provided.

[0694] Finally, the analyzed and organized data is sent from the server to the terminal, which displays it on the user interface. For example, the following information is displayed on the terminal screen:

[0695] Market size: $5 billion

[0696] Main competitors: Store B, Store C

[0697] Delivery model: Subscription-based

[0698] GTM Strategy: Digital Marketing, Customer Journey Map

[0699] This series of processes enables users to efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[0700] An example prompt is:

[0701] "Get Company A's market size, key competitors, delivery model, and GTM strategy, and present it in a format that's easy for users to use. If users are unsure, provide the information in a way that puts them at ease."

[0702] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0703] Step 1:

[0704] The user operates the terminal and inputs the name of the company to be investigated. In the input field, the name of the company to be investigated (e.g., "Company A") is entered. The input company name then becomes the input data for the next processing step.

[0705] Step 2:

[0706] The terminal sends the entered company name to the server. Specifically, it generates an HTTP request and sends JSON-formatted data including the company name as a payload to the server. At this point, the input data is the company name, and the output data is the HTTP request sent to the server.

[0707] Step 3:

[0708] The server issues a query to its internal database based on the received company name. For example, it executes the SQL query "SELECT FROM store_info WHERE name = 'Company A'" to retrieve related information. The input data for this step is the company name, and the output data is the information retrieved from the database.

[0709] Step 4:

[0710] If the information obtained by the server is incomplete, it supplements the missing information from an external API. Specifically, it sends an HTTP request to an external market information API or competitive information API to obtain the necessary information. In this process, the input data is incomplete company information, and the output data is the supplemented, complete information.

[0711] Step 5:

[0712] The server analyzes and organizes all the acquired information. Using data analysis tools such as Python and R, the information is categorized into market size, competitors, service models, GTM strategies, and store information. The input data for this step is the completed company information, and the output data is the analyzed and classified information.

[0713] Step 6:

[0714] The device recognizes the user's emotional state by using an emotion engine to analyze the user's facial expressions and tone of voice via the smartphone's camera and microphone. The input data for this process is the user's real-time facial expressions and voice data, and the output data is the analyzed emotional information.

[0715] Step 7:

[0716] The server adjusts the display content and interface based on the emotion data. For example, if the user is anxious, the information display will be made more friendly and guides and hints will be added. The input data for this step are emotion data and analyzed and classified company information, and the output data is the adjusted display content.

[0717] Step 8:

[0718] The server sends the organized information to the terminal, which then displays the received information on the user interface. For example, information such as market size, major competitors, offering model, and GTM strategy is displayed appropriately on the screen. In this final step, the input data is the adjusted company information, and the output data is the information displayed on the user interface.

[0719] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0720] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0721] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0722] [Third embodiment]

[0723] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0724] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0725] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0726] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0727] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0728] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0729] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0730] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0731] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0732] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0733] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0734] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0735] To implement this invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then checks the database based on the received company name to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. This allows users to quickly and efficiently obtain the company information they need.

[0736] Detailed explanation of the program's operation:

[0737] User input

[0738] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0739] Starting Data Collection

[0740] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server.

[0741] Database Matching

[0742] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it executes an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0743] Using external APIs

[0744] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0745] Data analysis and organization

[0746] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0747] Displaying the results

[0748] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0749] Market size: $5 billion

[0750] Major competitors: Company B, Company C

[0751] Delivery model: Subscription-based

[0752] GTM Strategy: Digital Marketing, Customer Journey Map

[0753] A system with such a mechanism allows users to efficiently gain deep insight into companies and significantly reduce the amount of research work required.

[0754] The processing flow will be explained below.

[0755] Step 1:

[0756] The user enters the name of the company to be surveyed in the input field on the terminal. For example, the user enters "Company A." The user clicks the "Submit" button to proceed to the next step.

[0757] Step 2:

[0758] The terminal sends the company name "Company A" entered by the user to the server. At this time, the terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0759] Step 3:

[0760] The server receives the received company name "Company A" and executes a query against the database. For example, the server sends an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve related information.

[0761] Step 4:

[0762] The server stores the information obtained as a result of the SQL query in temporary storage (e.g., memory), which prepares the data for use in the next process.

[0763] Step 5:

[0764] If the information retrieved from the database is insufficient, the server uses an external API to supplement the information. For example, the server sends an HTTP request to the "Market Information API" including the company name "Company A" as a parameter to retrieve the latest market size data.

[0765] Step 6:

[0766] The server receives the response data from the external API and stores it in temporary storage. Based on the retrieved data, it complements the existing data set to create a complete company information set.

[0767] Step 7:

[0768] The server analyzes the organized data, which includes categorizing the data (market size, competition, delivery model, GTM strategy, etc.) and providing detailed analysis for each category.

[0769] Step 8:

[0770] The server converts the analyzed and organized data into a format that is easy for users to use, such as HTML or JSON, and generates the final dataset.

[0771] Step 9:

[0772] The server sends the final dataset to the device as an HTTP response, which includes detailed information about market size, competition, offering model, and GTM strategy.

[0773] Step 10:

[0774] The device analyzes the data received from the server and displays it on a user interface, which visually displays the following information:

[0775] Market size: $5 billion

[0776] Major competitors: Company B, Company C

[0777] Delivery model: Subscription-based

[0778] GTM Strategy: Digital Marketing, Customer Journey Map

[0779] Example 1

[0780] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0781] In today's business environment, there is a need to quickly and accurately collect and analyze corporate information. However, traditional systems make it difficult to properly supplement missing information in databases, requiring manual work and additional research to obtain complete information. As a result, information collection and analysis require a great deal of time and effort.

[0782] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0783] In this invention, the server includes: a means for a user to input a company name into an input field; a means for a terminal to transmit the input company name to the server; a means for the server to query a database based on the company name and obtain information; a means for the server to call an external API to supplement the missing information if the information obtained from the database is incomplete; a means for the server to analyze the obtained information and classify and organize it by item; and a means for transmitting the organized information from the server to the terminal and for the terminal to display it on a user interface. This makes it possible to quickly and efficiently collect company information and provide the information required by the user in an organized manner.

[0784] A "user" is a person or operator who interacts with the system to enter a business name and receive the results.

[0785] A "terminal" is a device operated by a user, and is a device for inputting a company name and performing data communication with a server.

[0786] "Server" is a central computer system that queries the database based on the company name received from the user, retrieves and completes the required information, and sends the final results to the terminal.

[0787] "Company name" is the name of the corporation that the user designates as the target of the survey or information gathering.

[0788] A "database" is a collection of information managed by a server, including various data related to a company.

[0789] An "external API" is an external application programming interface used by the server to supplement information missing from the database.

[0790] A "query" is a command or question executed by a server to obtain specific information from a database.

[0791] "Analysis" refers to the act of breaking down and processing the data acquired by the server, and processing it to understand its meaning and intent.

[0792] "Classification and organization" is the act of dividing analyzed data into categories based on specific criteria and arranging them in an orderly manner.

[0793] "User interface" refers to the display screen and input means that allow a user to check and operate information on a terminal.

[0794] To implement this invention, a user first uses a terminal to input the name of a company to be investigated. The terminal then sends the input company name to a server as an HTTP request. The server then queries an internal database based on the received company name to retrieve relevant information. This query is performed, for example, using SQL.

[0795] If the information the server retrieves from the database is incomplete, it uses an external API to fill in the missing information. For example, it may call a "Market Information API" to obtain the latest market information. The server sends this request as an HTTP request to the external API to obtain the required data.

[0796] The server then analyzes the acquired data and classifies and organizes it into the necessary items, dividing the information into multiple categories such as market size, competitors, offering models, and go-to-market strategies. This analysis and organization process is carried out using specific algorithms and data mining techniques.

[0797] Once the analysis and organization is complete, the server sends the information to the device, which then displays the received data on a user interface. This allows users to easily understand the desired company information, such as market size, major competitors, the company's service model, and GTM strategy.

[0798] For example, if a user wants to find information about "Company A," they enter "Company A" into their device. The device sends this company name to the server, which then performs the following process:

[0799] 1. Obtain information about "Company A" from the database.

[0800] 2. Obtain missing market information from an external API.

[0801] 3. Analyze and organize the information obtained.

[0802] 4. Present organized information in a user interface.

[0803] The generative AI model can also be used to respond to specific questions from users. For example, by entering a prompt such as, "Please tell me the latest information on Company A's market size, competitors, delivery model, and go-to-market strategy," detailed company information can be provided. This system allows users to efficiently obtain detailed company information and use it for analysis.

[0804] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0805] Step 1:

[0806] The user uses the terminal to enter the company name into the input field. The company name is received as input and is ready to be sent to the server at this point. For example, the user enters "Company A." Based on this input, the name of the company to be investigated is determined.

[0807] Step 2:

[0808] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server. Specifically, the following HTTP request is generated:

[0809] POST / query HTTP / 1.1

[0810] Host: example.com

[0811] Content-Type: application / json

[0812] {

[0813] "company_name": "Company A"

[0814] }

[0815] The input is the company name "Company A" entered by the user, and the output is an HTTP request containing this company name.

[0816] Step 3:

[0817] The server queries its internal database based on the received company name "Company A" to retrieve relevant information. Specifically, it executes the following SQL query:

[0818] SELECT FROM company_info WHERE name = 'Company A'

[0819] The input is the company name "Company A," and the output is related data such as market size and competitive information obtained from the database.

[0820] Step 4:

[0821] If the information retrieved from the database is incomplete, the server calls an external API to fill in the missing information. For example, if the latest market information is not in the database, the server sends the following HTTP request to the "Market Information API":

[0822] GET / market_info?company_name=Company A HTTP / 1.1

[0823] Host: externalapi.com

[0824] The input is the company name "Company A" and the category of missing information, and the output is the latest market information obtained from an external API.

[0825] Step 5:

[0826] The server analyzes the acquired data and classifies and organizes it according to the required items. For example, as a result of the analysis, information may be divided into categories such as market size, competition, delivery model, and go-to-market strategy. Data mining algorithms and statistical analysis methods are used in the analysis and organization process. The input is raw data acquired from a database or external API, and the output is analyzed and organized information.

[0827] Step 6:

[0828] The server sends the organized and analyzed data to the device. Specifically, the data is sent in JSON format as shown below:

[0829] {

[0830] "market_size": "$5 billion",

[0831] "competitors": ["Company B", "Company C"],

[0832] "business_model": "subscription-based",

[0833] "gtm_strategy": ["Digital Marketing", "Customer Journey Map"]

[0834] }

[0835] The input is parsed and organized information, and the output is JSON data containing this information.

[0836] Step 7:

[0837] The device displays the received data in its user interface. Specifically, the device screen displays the following information:

[0838] Market size: $5 billion

[0839] Major competitors: Company B, Company C

[0840] Delivery model: Subscription-based

[0841] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0842] The input is JSON data received from the server, and the output is organized information displayed on a user interface.

[0843] This will enable users to efficiently obtain detailed information about companies, significantly reducing the amount of work required for corporate analysis.

[0844] (Application example 1)

[0845] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0846] Conventional corporate information acquisition systems have the problem that the necessary information must be acquired manually, which is time-consuming and inefficient. Furthermore, if the information is incomplete, the latest data must be manually supplemented, and organizing and analyzing the information also places a burden on the user. Furthermore, there is a lack of means to quickly acquire corporate security risk information and visually display it. There is a need for a system that can solve these issues and acquire and display corporate information more efficiently and quickly.

[0847] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0848] In this invention, the server includes means for transmitting an input company name to the server, means for the server to retrieve information by checking a database based on the company name, means for supplementing missing information from an external API, means for analyzing and organizing the retrieved information and displaying it on a user interface, means for visually displaying the information on a smart device display, and means for inputting the company name via voice input. This makes it possible to efficiently retrieve company information and quickly provide users with company information, including security risk information, particularly through visual display on a smart device.

[0849] "Company name" refers to the name of a corporation or organization, and is information used to identify a specific company.

[0850] "Server" refers to a computer system that collects and processes data over a network and provides it to other devices.

[0851] A "database" refers to a collection of organized data and a system that allows efficient access and management of that data.

[0852] An "external API" is an application program interface provided by an external system or service, and refers to a means for other programs to use data or functions.

[0853] "User interface" refers to the screens and operating means by which a user interacts with a system.

[0854] "Smart device" refers to a device that is connected to the Internet and has the ability to aggregate, display, and operate information. Examples include smartphones, smart glasses, and tablets.

[0855] "Voice input" refers to the technology of recognizing human voice as an input signal using a microphone or other device.

[0856] "Market size" refers to the size of sales and growth across a particular market.

[0857] "Competitors" refers to other companies or organizations that offer similar products or services in the same market.

[0858] A "delivery model" refers to the strategy or method by which a company delivers its products or services to consumers.

[0859] A "Go-To-Market Strategy" (GTM Strategy) refers to the plan and methodology for bringing a new product or service to market.

[0860] "Security risk information" refers to information about security threats and risks that companies and systems may face.

[0861] "Visual display" refers to a method of visually expressing information and presenting it to a user through a display or the like.

[0862] To implement this invention, a user first uses a smart device to voice-input a company name into a terminal. The smart device uses a voice input system to allow the user to quickly and efficiently obtain information about a specific company.

[0863] The company name entered by the user is sent from the smart device to the server. The server queries the database based on the received company name to retrieve related information. For example, an HTTP request using Python is used to retrieve data matching the company name using an SQL query such as "SELECT FROM company_info WHERE name = 'Company X'".

[0864] Next, if the information retrieved from the database is incomplete, the server uses external APIs to supplement the missing information. External APIs include market information APIs and security risk information APIs, which are used to obtain additional information on the latest market size and security risks. For example, a request is sent to an endpoint such as "http: / / externalapi.com / api / market_info?name=Company X" to supplement the required information.

[0865] The server analyzes and organizes data obtained from databases and external APIs, converting it into a format suitable for the smart device's user interface. During this analysis and organization process, the data is categorized using Python libraries and presented in a format that can be displayed visually. For example, information can be organized by market size, competitors, delivery model, go-to-market strategy, and security risks.

[0866] The organized information is sent from the server to the smart device and displayed on the device's screen in a format that is easy for users to understand visually. This allows users to efficiently check detailed company information on their devices, such as:

[0867] Market size: $5 billion

[0868] Major competitors: Company Y, Company Z

[0869] Delivery model: Subscription-based

[0870] GTM Strategy: Digital Marketing, Customer Journey Map

[0871] Security Risk: Data leakage risk, medium vulnerability

[0872] As a concrete example, to check security risk information for "Company X," use the following prompt:

[0873] "Please provide detailed information about Company X's market size, key competitors, delivery model, go-to-market strategy, and security risks."

[0874] The system allows for fast and efficient acquisition of corporate information and visualization of security risks, significantly improving business intelligence and security assessment.

[0875] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0876] Step 1:

[0877] A user inputs a company name using the voice input system of a smart device.

[0878] Input: Company name via voice input (e.g. "Company X")

[0879] Data processing and output: Convert the voice input data into text format and obtain the company name.

[0880] Step 2:

[0881] The terminal transmits the acquired company name to the server.

[0882] Input: Company name in text format

[0883] Data processing and output: An HTTP request is generated and data including the company name is sent to the server.

[0884] Step 3:

[0885] The server queries a database based on the received business name to retrieve relevant information.

[0886] Enter: Company Name (e.g. "Company X")

[0887] Data processing and output: Execute an SQL query to retrieve company information from the database (e.g., "SELECT FROM company_info WHERE name = 'Company X'"). Retrieved information includes market size, competitors, delivery model, go-to-market strategy, and security risk information.

[0888] Step 4:

[0889] The server uses an external API to supplement information that could not be obtained from the database.

[0890] Input: Incomplete Company Information

[0891] Data processing and output: To obtain the necessary information, HTTP requests are sent to external APIs to obtain complementary information. Specifically, market information APIs and security risk information APIs are used.

[0892] Step 5:

[0893] The server analyzes and organizes the information obtained from the database and external APIs, and converts it into a format suitable for the user interface.

[0894] Input: Acquired company information (market size, competitors, service model, go-to-market strategy, security risk information)

[0895] Data processing and output: Categorize the data and format it in a way that can be displayed visually, for example, by converting it to JSON using a Python library.

[0896] Step 6:

[0897] The server then sends the analyzed and organized information to the smart device.

[0898] Input: Formatted company information

[0899] Data processing and output: Generates an HTTP response and sends it to the smart device.

[0900] Step 7:

[0901] The terminal visually displays the received information on the display of the smart device.

[0902] Input: Formatted company information

[0903] Data processing and output: The received data is analyzed and displayed in a format suitable for a graphical user interface, allowing users to visually check company information.

[0904] This process flow allows users to efficiently and quickly obtain company information and provides the information in a visually understandable format.

[0905] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0906] To implement the present invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then compares the received company name with a database to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the display of the results accordingly. This allows the user to quickly and efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[0907] Detailed explanation of the program's operation:

[0908] User input

[0909] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[0910] Starting Data Collection

[0911] The terminal sends the entered company name "Company A" to the server. The terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[0912] Database Matching

[0913] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[0914] Using external APIs

[0915] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[0916] Data analysis and organization

[0917] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[0918] Emotion recognition by emotion engine

[0919] The device has an emotion engine that recognizes emotions from the user's face, voice, etc. For example, it analyzes the user's facial expressions and tone of voice through a camera and microphone to detect whether the user is happy, surprised, or anxious.

[0920] Adjusting outcomes according to emotions

[0921] The server adjusts the displayed information and interface based on the emotional data obtained from the emotion engine. For example, if the user is feeling anxious, the server may adjust the information display to be more friendly or add guides or hints.

[0922] Displaying the results

[0923] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[0924] Market size: $5 billion

[0925] Major competitors: Company B, Company C

[0926] Delivery model: Subscription-based

[0927] GTM Strategy: Digital Marketing, Customer Journey Map

[0928] Additionally, if the user's emotions are recognized, the display can be customized accordingly, for example by using relaxing language and color schemes to alleviate anxiety.

[0929] This system allows users to efficiently gain deep insights into companies, significantly reducing research efforts, and providing an optimal user experience based on emotions.

[0930] The processing flow will be explained below.

[0931] Step 1:

[0932] The user enters the name of the company to be surveyed in the input field of the terminal. For example, the user enters "Company A" and clicks the "Submit" button.

[0933] Step 2:

[0934] The terminal generates an HTTP request to send the company name "Company A" entered by the user to the server. The request sends JSON-formatted data including the company name as a payload to the server.

[0935] Step 3:

[0936] The server analyzes the received company name "Company A" and generates an SQL statement to query the database. The server sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS).

[0937] Step 4:

[0938] The server receives the query results returned from the database and stores them in temporary storage (such as memory). This information includes market size, competition, delivery model, GTM strategy, etc.

[0939] Step 5:

[0940] If the information obtained from the database is insufficient, the server uses an external API to obtain additional information. For example, it sends an HTTP request to the "Market Information API" including the company name "Company A" to obtain the latest market size information.

[0941] Step 6:

[0942] The server receives additional information from external APIs, stores it in temporary storage, and complements the existing data set with the acquired data to create a complete company profile.

[0943] Step 7:

[0944] The server analyzes the data set and classifies and organizes it by information category (market size, competitors, service model, GTM strategy). The organized data is converted into a user-friendly format (HTML or JSON).

[0945] Step 8:

[0946] The device runs an emotion engine that analyzes the user's facial expressions and tone of voice. The device captures the user's facial expressions and tone of voice through a camera and microphone and generates emotion data.

[0947] Step 9:

[0948] The terminal transmits the generated emotion data to the server, for example, emotion data including information on whether the user is in a relaxed state or an anxious state.

[0949] Step 10:

[0950] The server analyzes the emotion data and adjusts the information and interface displayed according to the user's emotion. For example, if the user is in an anxious state, the server will simplify the information presentation and provide easy-to-understand guidance.

[0951] Step 11:

[0952] The server sends the final dataset, which reflects the analyzed and organized data and adjustments made by the emotion engine, to the terminal and returns the data as an HTTP response.

[0953] Step 12:

[0954] The terminal analyzes the final data set received from the server and displays it in a user interface. The terminal screen displays the following information:

[0955] Market size: $5 billion

[0956] Major competitors: Company B, Company C

[0957] Delivery model: Subscription-based

[0958] GTM Strategy: Digital Marketing, Customer Journey Map

[0959] Additionally, the UI may be adjusted based on the emotional data, such as a relaxing color scheme or additional guidance.

[0960] In this way, the user can efficiently obtain detailed information about the company, and furthermore, an optimal user experience is provided according to the user's feelings.

[0961] Example 2

[0962] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0963] When collecting detailed company information and market data, it is difficult to efficiently obtain information due to the fragmented nature of the information and the incompleteness of the data. Another challenge is providing an appropriate interface that responds to the user's emotions.

[0964] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collating a database based on the company name and acquiring information, a means for supplementing missing information from an external API, a means for analyzing and organizing the acquired information and displaying it on a user interface, and a means for adjusting the display content based on the emotion recognition result. This makes it possible to efficiently collect detailed company information and provide an optimal interface according to the user's emotions.

[0965] "Company name" is a unique name used to identify a company.

[0966] A "server" is a computer system that provides information and services to clients over a network.

[0967] A "database" is a collection of information that is systematically managed so that data can be stored and easily searched and manipulated.

[0968] An "external API" is an interface for communicating with other software or services, providing functions that can be used externally.

[0969] "User interface" refers to the display screen and operating means that allow the user to directly interact with the system.

[0970] An "emotion engine" is an algorithm or system that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[0971] "Market size" is an indicator that shows the total trading volume or total sales of products or services in a particular market.

[0972] "Competitors" refers to multiple companies or businesses that offer similar products or services in the same market.

[0973] A "delivery model" is a business strategy or method for how a company delivers products or services to customers.

[0974] A "go-to-market strategy" is a plan or strategy for bringing a new product or service to market and reaching customers.

[0975] The present invention is a system for efficiently collecting corporate information and providing a user with an appropriate interface according to their emotions. A specific method for carrying out the present invention will be described below.

[0976] First, the user uses the terminal to input the name of the company to be researched. The terminal has an input field where the user can input the name of the company they want to research. For example, if the user inputs "Company A," this company will be the subject of research.

[0977] Next, the device sends the entered company name "Company A" to the server. The device generates an HTTP POST request and sends JSON-formatted data including the company name to the server. At this time, the device communicates with the server via the Internet.

[0978] The server queries its internal database based on the received company name, "Company A," to retrieve relevant information. For example, it executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to collate data with the database management system (DBMS). This database stores company information such as market size, competitors, service model, and go-to-market strategy.

[0979] If the server cannot obtain the necessary information from its internal database, it uses an external API to fill in the missing information. For example, it sends an HTTP request to the "Market Information API" to obtain the latest market size data for "Company A." Data from the external API is also returned in JSON format.

[0980] The server analyzes the information obtained from the database and external APIs, classifying and organizing it according to the required items. For example, it converts the information into a data frame using Python's Pandas library and performs analysis according to each category (market size, competition, delivery model, go-to-market strategy). It then formats the information into a user interface format.

[0981] The device is equipped with an emotion engine that analyzes the user's face and voice to recognize emotions. For example, a facial recognition camera captures the user's facial expressions and inputs the data into an emotion recognition algorithm. A microphone also collects audio and analyzes the tone of voice. This analyzed data is sent to a server.

[0982] The server adjusts the information display and interface based on the emotional data sent from the device. For example, if the user is feeling anxious, the server changes the display to a more friendly format and adds guides and hints, allowing the user to view the necessary information in a relaxed manner.

[0983] Finally, the organized and analyzed data is sent from the server to the device and displayed on the device's user interface. For example, the following information is displayed:

[0984] Market size: $5 billion

[0985] Major competitors: Company B, Company C

[0986] Delivery model: Subscription-based

[0987] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[0988] It also customizes the experience based on the user's emotions, adding relaxing color schemes and effective explanatory text to optimize the user experience.

[0989] Example prompt sentence:

[0990] Please explain in detail the processing steps of the program in which the user enters the company name "Company A," the server uses the internal database and external API to collect the necessary information, and displays it to the user.

[0991] In this way, users can quickly and efficiently obtain detailed information about a company, and an optimal interface is provided that responds to the user's emotions.

[0992] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0993] Step 1:

[0994] The user inputs the name of a company into the input field of the terminal. For example, by inputting "Company A," the research target is determined. This input is the input data.

[0995] Step 2:

[0996] The terminal structures the company name "Company A" entered by the user as JSON format data and generates an HTTP POST request. The terminal sends this request to the server. The input is the company name, and the output is the request to the server.

[0997] Step 3:

[0998] The server queries its internal database based on the received company name "Company A". It executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to retrieve relevant information. The input is the company name and the output is information from the database.

[0999] Step 4:

[1000] The server checks the information retrieved from the database and identifies any missing information. For example, if market size or competitive information is missing, it uses an external API to supplement this information. The input is information from the database, and the output is the supplemented information.

[1001] Step 5:

[1002] The server sends an HTTP request to an external API to obtain the missing information. For example, the server obtains market size data for "Company A" from the "Market Information API." The input is the server request, and the output is data from the external API.

[1003] Step 6:

[1004] The server analyzes, classifies, and organizes the acquired information. It uses Python's Pandas library to convert the data into a data frame format and analyzes it by category (market size, competitors, delivery model, go-to-market strategy). The input is information from the database and external API, and the output is the analyzed data.

[1005] Step 7:

[1006] The device uses an emotion engine to recognize the user's emotions. It uses a camera and microphone to collect and analyze the user's facial expressions and voice. For example, if the user is surprised, the emotion engine analyzes their facial expressions and tone of voice. The input is the user's facial expressions and voice, and the output is emotion data.

[1007] Step 8:

[1008] The device sends the recognized emotion data to the server. The input is the emotion data of the device, and the output is the transmission of the emotion data to the server.

[1009] Step 9:

[1010] The server adjusts the displayed information and interface based on the emotional data. For example, if the user feels anxious, it makes the interface more friendly and adds guides and hints. The input is emotional data, and the output is adjusted interface information.

[1011] Step 10:

[1012] The server sends the organized and analyzed data and interface information to the terminal. The input is the organized data and adjusted interface information in the server, and the output is sent to the terminal.

[1013] Step 11:

[1014] The device displays the received data in a user interface. The user can see the following information on the device screen:

[1015] Market size: $5 billion

[1016] Main competitors: Other company B, other company C

[1017] Delivery model: Subscription

[1018] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[1019] Furthermore, it provides an interface that is customized according to the user's emotions. The input is data from the server, and the output is a display on the user interface.

[1020] (Application example 2)

[1021] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1022] Collecting and analyzing corporate information requires a lot of time and effort due to the wide range of information involved. Furthermore, the user experience is not sufficiently improved because the information is not displayed optimally according to the user's emotional state. Therefore, there is a need for the development of a system that efficiently acquires necessary information and displays it appropriately according to the user's emotional state.

[1023] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1024] In this invention, the server includes means for transmitting the input company name, means for collating the company name with a database to obtain information, means for supplementing missing information from an external API, means for analyzing and organizing the obtained information and displaying it on a user interface, and means for recognizing the user's emotions and adjusting the display results. This enables the user to efficiently obtain the company information they need and provides an optimal interface according to their emotions.

[1025] A "company name" is a name used to identify a specific business entity.

[1026] A "server" is a computer system that processes and stores data and provides information in response to user requests.

[1027] A "database" is a collection of data that can be efficiently stored, managed, and searched.

[1028] An "external API" is an external programming interface provided in a form that can be accessed by other systems or applications.

[1029] A "user interface" is the part where information is exchanged between the user and the system, and provides operation and display functions.

[1030] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's response based on that information.

[1031] "Analysis" is the process of examining collected data in detail and extracting the necessary information.

[1032] "Organizing" is the process of classifying acquired data into categories and converting them into an easy-to-read format.

[1033] "Market size" is information about the total sales or total volume of transactions of a product in a particular market.

[1034] "Competitors" are other entities in the same market that offer similar products or services and compete for customers.

[1035] A "delivery model" is a specific method or business model for providing products or services to customers.

[1036] A "Go-To-Market Strategy" is a sales strategy or marketing plan for introducing new products or services to the market.

[1037] "Store information" refers to detailed information about a specific commercial facility or retail store, including its location, opening hours, and the products and services it offers.

[1038] To implement this invention, the user must first operate the terminal to input the name of the company to be surveyed. For example, the user inputs the company name into an input field of the smartphone app "Brick Store Analyzer."

[1039] The device then sends the entered company name to the server. The device generates an HTTP request and sends JSON-formatted data containing the company name as a payload to the server. At this point, a database match is performed on the server side. The server issues a query to its internal database to retrieve information about the company. For example, the SQL query "SELECT FROM store_info WHERE name = 'Company A'" is used. MySQL is a commonly used database management system (DBMS).

[1040] If the information the server retrieves from the database is incomplete, the server uses external APIs. The missing information is retrieved from external market information APIs or competitive information APIs. The server sends HTTP requests to these external APIs to complete the missing information.

[1041] The server then analyzes and organizes all the information it has acquired. This analysis is performed using data analysis tools such as Python and R, as well as ML libraries (e.g., scikit-learn). The information is categorized into categories such as market size, competitors, service model, GTM strategy, and store information. The analysis results are then converted into a format suitable for the user interface.

[1042] The device is equipped with an emotion recognition function that recognizes the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice through the smartphone's camera and microphone to understand the user's emotional state. This emotion recognition uses technologies such as TensorFlow and OpenCV.

[1043] The server adjusts the displayed information and interface based on the emotional data. For example, if the user has an anxious expression, the information display will be more friendly and additional guidance and hints will be provided.

[1044] Finally, the analyzed and organized data is sent from the server to the terminal, which displays it on the user interface. For example, the following information is displayed on the terminal screen:

[1045] Market size: $5 billion

[1046] Main competitors: Store B, Store C

[1047] Delivery model: Subscription-based

[1048] GTM Strategy: Digital Marketing, Customer Journey Map

[1049] This series of processes enables users to efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[1050] An example prompt is:

[1051] "Get Company A's market size, key competitors, delivery model, and GTM strategy, and present it in a format that's easy for users to use. If users are unsure, provide the information in a way that puts them at ease."

[1052] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1053] Step 1:

[1054] The user operates the terminal and inputs the name of the company to be investigated. In the input field, the name of the company to be investigated (e.g., "Company A") is entered. The input company name then becomes the input data for the next processing step.

[1055] Step 2:

[1056] The terminal sends the entered company name to the server. Specifically, it generates an HTTP request and sends JSON-formatted data including the company name as a payload to the server. At this point, the input data is the company name, and the output data is the HTTP request sent to the server.

[1057] Step 3:

[1058] The server issues a query to its internal database based on the received company name. For example, it executes the SQL query "SELECT FROM store_info WHERE name = 'Company A'" to retrieve related information. The input data for this step is the company name, and the output data is the information retrieved from the database.

[1059] Step 4:

[1060] If the information obtained by the server is incomplete, it supplements the missing information from an external API. Specifically, it sends an HTTP request to an external market information API or competitive information API to obtain the necessary information. In this process, the input data is incomplete company information, and the output data is the supplemented, complete information.

[1061] Step 5:

[1062] The server analyzes and organizes all the acquired information. Using data analysis tools such as Python and R, the information is categorized into market size, competitors, service models, GTM strategies, and store information. The input data for this step is the completed company information, and the output data is the analyzed and classified information.

[1063] Step 6:

[1064] The device recognizes the user's emotional state by using an emotion engine to analyze the user's facial expressions and tone of voice via the smartphone's camera and microphone. The input data for this process is the user's real-time facial expressions and voice data, and the output data is the analyzed emotional information.

[1065] Step 7:

[1066] The server adjusts the display content and interface based on the emotion data. For example, if the user is anxious, the information display will be made more friendly and guides and hints will be added. The input data for this step are emotion data and analyzed and classified company information, and the output data is the adjusted display content.

[1067] Step 8:

[1068] The server sends the organized information to the terminal, which then displays the received information on the user interface. For example, information such as market size, major competitors, offering model, and GTM strategy is displayed appropriately on the screen. In this final step, the input data is the adjusted company information, and the output data is the information displayed on the user interface.

[1069] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1070] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1071] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1072] [Fourth embodiment]

[1073] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1074] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1075] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1076] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1077] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1078] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1079] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1080] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1081] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1082] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1083] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1084] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1085] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1086] To implement this invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then checks the database based on the received company name to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. This allows users to quickly and efficiently obtain the company information they need.

[1087] Detailed explanation of the program's operation:

[1088] User input

[1089] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[1090] Starting Data Collection

[1091] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server.

[1092] Database Matching

[1093] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it executes an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[1094] Using external APIs

[1095] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[1096] Data analysis and organization

[1097] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[1098] Displaying the results

[1099] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[1100] Market size: $5 billion

[1101] Major competitors: Company B, Company C

[1102] Delivery model: Subscription-based

[1103] GTM Strategy: Digital Marketing, Customer Journey Map

[1104] A system with such a mechanism allows users to efficiently gain deep insight into companies and significantly reduce the amount of research work required.

[1105] The processing flow will be explained below.

[1106] Step 1:

[1107] The user enters the name of the company to be surveyed in the input field on the terminal. For example, the user enters "Company A." The user clicks the "Submit" button to proceed to the next step.

[1108] Step 2:

[1109] The terminal sends the company name "Company A" entered by the user to the server. At this time, the terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[1110] Step 3:

[1111] The server receives the received company name "Company A" and executes a query against the database. For example, the server sends an SQL query such as "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve related information.

[1112] Step 4:

[1113] The server stores the information obtained as a result of the SQL query in temporary storage (e.g., memory), which prepares the data for use in the next process.

[1114] Step 5:

[1115] If the information retrieved from the database is insufficient, the server uses an external API to supplement the information. For example, the server sends an HTTP request to the "Market Information API" including the company name "Company A" as a parameter to retrieve the latest market size data.

[1116] Step 6:

[1117] The server receives the response data from the external API and stores it in temporary storage. Based on the retrieved data, it complements the existing data set to create a complete company information set.

[1118] Step 7:

[1119] The server analyzes the organized data, which includes categorizing the data (market size, competition, delivery model, GTM strategy, etc.) and providing detailed analysis for each category.

[1120] Step 8:

[1121] The server converts the analyzed and organized data into a format that is easy for users to use, such as HTML or JSON, and generates the final dataset.

[1122] Step 9:

[1123] The server sends the final dataset to the device as an HTTP response, which includes detailed information about market size, competition, offering model, and GTM strategy.

[1124] Step 10:

[1125] The device analyzes the data received from the server and displays it on a user interface, which visually displays the following information:

[1126] Market size: $5 billion

[1127] Major competitors: Company B, Company C

[1128] Delivery model: Subscription-based

[1129] GTM Strategy: Digital Marketing, Customer Journey Map

[1130] Example 1

[1131] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1132] In today's business environment, there is a need to quickly and accurately collect and analyze corporate information. However, traditional systems make it difficult to properly supplement missing information in databases, requiring manual work and additional research to obtain complete information. As a result, information collection and analysis require a great deal of time and effort.

[1133] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1134] In this invention, the server includes: a means for a user to input a company name into an input field; a means for a terminal to transmit the input company name to the server; a means for the server to query a database based on the company name and obtain information; a means for the server to call an external API to supplement the missing information if the information obtained from the database is incomplete; a means for the server to analyze the obtained information and classify and organize it by item; and a means for transmitting the organized information from the server to the terminal and for the terminal to display it on a user interface. This makes it possible to quickly and efficiently collect company information and provide the information required by the user in an organized manner.

[1135] A "user" is a person or operator who interacts with the system to enter a business name and receive the results.

[1136] A "terminal" is a device operated by a user, and is a device for inputting a company name and performing data communication with a server.

[1137] "Server" is a central computer system that queries the database based on the company name received from the user, retrieves and completes the required information, and sends the final results to the terminal.

[1138] "Company name" is the name of the corporation that the user designates as the target of the survey or information gathering.

[1139] A "database" is a collection of information managed by a server, including various data related to a company.

[1140] An "external API" is an external application programming interface used by the server to supplement information missing from the database.

[1141] A "query" is a command or question executed by a server to obtain specific information from a database.

[1142] "Analysis" refers to the act of breaking down and processing the data acquired by the server, and processing it to understand its meaning and intent.

[1143] "Classification and organization" is the act of dividing analyzed data into categories based on specific criteria and arranging them in an orderly manner.

[1144] "User interface" refers to the display screen and input means that allow a user to check and operate information on a terminal.

[1145] To implement this invention, a user first uses a terminal to input the name of a company to be investigated. The terminal then sends the input company name to a server as an HTTP request. The server then queries an internal database based on the received company name to retrieve relevant information. This query is performed, for example, using SQL.

[1146] If the information the server retrieves from the database is incomplete, it uses an external API to fill in the missing information. For example, it may call a "Market Information API" to obtain the latest market information. The server sends this request as an HTTP request to the external API to obtain the required data.

[1147] The server then analyzes the acquired data and classifies and organizes it into the necessary items, dividing the information into multiple categories such as market size, competitors, offering models, and go-to-market strategies. This analysis and organization process is carried out using specific algorithms and data mining techniques.

[1148] Once the analysis and organization is complete, the server sends the information to the device, which then displays the received data on a user interface. This allows users to easily understand the desired company information, such as market size, major competitors, the company's service model, and GTM strategy.

[1149] For example, if a user wants to find information about "Company A," they enter "Company A" into their device. The device sends this company name to the server, which then performs the following process:

[1150] 1. Obtain information about "Company A" from the database.

[1151] 2. Obtain missing market information from an external API.

[1152] 3. Analyze and organize the information obtained.

[1153] 4. Present organized information in a user interface.

[1154] The generative AI model can also be used to respond to specific questions from users. For example, by entering a prompt such as, "Please tell me the latest information on Company A's market size, competitors, delivery model, and go-to-market strategy," detailed company information can be provided. This system allows users to efficiently obtain detailed company information and use it for analysis.

[1155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1156] Step 1:

[1157] The user uses the terminal to enter the company name into the input field. The company name is received as input and is ready to be sent to the server at this point. For example, the user enters "Company A." Based on this input, the name of the company to be investigated is determined.

[1158] Step 2:

[1159] The terminal sends the entered company name to the server. The terminal generates an HTTP request and sends data including the company name "Company A" to the server. Specifically, the following HTTP request is generated:

[1160] POST / query HTTP / 1.1

[1161] Host: example.com

[1162] Content-Type: application / json

[1163] {

[1164] "company_name": "Company A"

[1165] }

[1166] The input is the company name "Company A" entered by the user, and the output is an HTTP request containing this company name.

[1167] Step 3:

[1168] The server queries its internal database based on the received company name "Company A" to retrieve relevant information. Specifically, it executes the following SQL query:

[1169] SELECT FROM company_info WHERE name = 'Company A'

[1170] The input is the company name "Company A," and the output is related data such as market size and competitive information obtained from the database.

[1171] Step 4:

[1172] If the information retrieved from the database is incomplete, the server calls an external API to fill in the missing information. For example, if the latest market information is not in the database, the server sends the following HTTP request to the "Market Information API":

[1173] GET / market_info?company_name=Company A HTTP / 1.1

[1174] Host: externalapi.com

[1175] The input is the company name "Company A" and the category of missing information, and the output is the latest market information obtained from an external API.

[1176] Step 5:

[1177] The server analyzes the acquired data and classifies and organizes it according to the required items. For example, as a result of the analysis, information may be divided into categories such as market size, competition, delivery model, and go-to-market strategy. Data mining algorithms and statistical analysis methods are used in the analysis and organization process. The input is raw data acquired from a database or external API, and the output is analyzed and organized information.

[1178] Step 6:

[1179] The server sends the organized and analyzed data to the device. Specifically, the data is sent in JSON format as shown below:

[1180] {

[1181] "market_size": "$5 billion",

[1182] "competitors": ["Company B", "Company C"],

[1183] "business_model": "subscription-based",

[1184] "gtm_strategy": ["Digital Marketing", "Customer Journey Map"]

[1185] }

[1186] The input is parsed and organized information, and the output is JSON data containing this information.

[1187] Step 7:

[1188] The device displays the received data in its user interface. Specifically, the device screen displays the following information:

[1189] Market size: $5 billion

[1190] Major competitors: Company B, Company C

[1191] Delivery model: Subscription-based

[1192] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[1193] The input is JSON data received from the server, and the output is organized information displayed on a user interface.

[1194] This will enable users to efficiently obtain detailed information about companies, significantly reducing the amount of work required for corporate analysis.

[1195] (Application example 1)

[1196] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1197] Conventional corporate information acquisition systems have the problem that the necessary information must be acquired manually, which is time-consuming and inefficient. Furthermore, if the information is incomplete, the latest data must be manually supplemented, and organizing and analyzing the information also places a burden on the user. Furthermore, there is a lack of means to quickly acquire corporate security risk information and visually display it. There is a need for a system that can solve these issues and acquire and display corporate information more efficiently and quickly.

[1198] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1199] In this invention, the server includes means for transmitting an input company name to the server, means for the server to retrieve information by checking a database based on the company name, means for supplementing missing information from an external API, means for analyzing and organizing the retrieved information and displaying it on a user interface, means for visually displaying the information on a smart device display, and means for inputting the company name via voice input. This makes it possible to efficiently retrieve company information and quickly provide users with company information, including security risk information, particularly through visual display on a smart device.

[1200] "Company name" refers to the name of a corporation or organization, and is information used to identify a specific company.

[1201] "Server" refers to a computer system that collects and processes data over a network and provides it to other devices.

[1202] A "database" refers to a collection of organized data and a system that allows efficient access and management of that data.

[1203] An "external API" is an application program interface provided by an external system or service, and refers to a means for other programs to use data or functions.

[1204] "User interface" refers to the screens and operating means by which a user interacts with a system.

[1205] "Smart device" refers to a device that is connected to the Internet and has the ability to aggregate, display, and operate information. Examples include smartphones, smart glasses, and tablets.

[1206] "Voice input" refers to the technology of recognizing human voice as an input signal using a microphone or other device.

[1207] "Market size" refers to the size of sales and growth across a particular market.

[1208] "Competitors" refers to other companies or organizations that offer similar products or services in the same market.

[1209] A "delivery model" refers to the strategy or method by which a company delivers its products or services to consumers.

[1210] A "Go-To-Market Strategy" (GTM Strategy) refers to the plan and methodology for bringing a new product or service to market.

[1211] "Security risk information" refers to information about security threats and risks that companies and systems may face.

[1212] "Visual display" refers to a method of visually expressing information and presenting it to a user through a display or the like.

[1213] To implement this invention, a user first uses a smart device to voice-input a company name into a terminal. The smart device uses a voice input system to allow the user to quickly and efficiently obtain information about a specific company.

[1214] The company name entered by the user is sent from the smart device to the server. The server queries the database based on the received company name to retrieve related information. For example, an HTTP request using Python is used to retrieve data matching the company name using an SQL query such as "SELECT FROM company_info WHERE name = 'Company X'".

[1215] Next, if the information retrieved from the database is incomplete, the server uses external APIs to supplement the missing information. External APIs include market information APIs and security risk information APIs, which are used to obtain additional information on the latest market size and security risks. For example, a request is sent to an endpoint such as "http: / / externalapi.com / api / market_info?name=Company X" to supplement the required information.

[1216] The server analyzes and organizes data obtained from databases and external APIs, converting it into a format suitable for the smart device's user interface. During this analysis and organization process, the data is categorized using Python libraries and presented in a format that can be displayed visually. For example, information can be organized by market size, competitors, delivery model, go-to-market strategy, and security risks.

[1217] The organized information is sent from the server to the smart device and displayed on the device's screen in a format that is easy for users to understand visually. This allows users to efficiently check detailed company information on their devices, such as:

[1218] Market size: $5 billion

[1219] Major competitors: Company Y, Company Z

[1220] Delivery model: Subscription-based

[1221] GTM Strategy: Digital Marketing, Customer Journey Map

[1222] Security Risk: Data leakage risk, medium vulnerability

[1223] As a concrete example, to check security risk information for "Company X," use the following prompt:

[1224] "Please provide detailed information about Company X's market size, key competitors, delivery model, go-to-market strategy, and security risks."

[1225] The system allows for fast and efficient acquisition of corporate information and visualization of security risks, significantly improving business intelligence and security assessment.

[1226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1227] Step 1:

[1228] A user inputs a company name using the voice input system of a smart device.

[1229] Input: Company name via voice input (e.g. "Company X")

[1230] Data processing and output: Convert the voice input data into text format and obtain the company name.

[1231] Step 2:

[1232] The terminal transmits the acquired company name to the server.

[1233] Input: Company name in text format

[1234] Data processing and output: An HTTP request is generated and data including the company name is sent to the server.

[1235] Step 3:

[1236] The server queries a database based on the received business name to retrieve relevant information.

[1237] Enter: Company Name (e.g. "Company X")

[1238] Data processing and output: Execute an SQL query to retrieve company information from the database (e.g., "SELECT FROM company_info WHERE name = 'Company X'"). Retrieved information includes market size, competitors, delivery model, go-to-market strategy, and security risk information.

[1239] Step 4:

[1240] The server uses an external API to supplement information that could not be obtained from the database.

[1241] Input: Incomplete Company Information

[1242] Data processing and output: To obtain the necessary information, HTTP requests are sent to external APIs to obtain complementary information. Specifically, market information APIs and security risk information APIs are used.

[1243] Step 5:

[1244] The server analyzes and organizes the information obtained from the database and external APIs, and converts it into a format suitable for the user interface.

[1245] Input: Acquired company information (market size, competitors, service model, go-to-market strategy, security risk information)

[1246] Data processing and output: Categorize the data and format it in a way that can be displayed visually, for example, by converting it to JSON using a Python library.

[1247] Step 6:

[1248] The server then sends the analyzed and organized information to the smart device.

[1249] Input: Formatted company information

[1250] Data processing and output: Generates an HTTP response and sends it to the smart device.

[1251] Step 7:

[1252] The terminal visually displays the received information on the display of the smart device.

[1253] Input: Formatted company information

[1254] Data processing and output: The received data is analyzed and displayed in a format suitable for a graphical user interface, allowing users to visually check company information.

[1255] This process flow allows users to efficiently and quickly obtain company information and provides the information in a visually understandable format.

[1256] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1257] To implement the present invention, a user first operates a terminal to input the name of a company to be surveyed. The terminal then transmits the input company name to a server. The server then compares the received company name with a database to obtain information about the company. Next, the server supplements any missing information not present in the database from an external API. Finally, the server analyzes and organizes the obtained information and displays it on a user interface. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the display of the results accordingly. This allows the user to quickly and efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[1258] Detailed explanation of the program's operation:

[1259] User input

[1260] The user inputs the name of a company into an input field on the terminal. For example, the user inputs "Company A." This determines the name of the company to be researched.

[1261] Starting Data Collection

[1262] The terminal sends the entered company name "Company A" to the server. The terminal generates an HTTP request and sends JSON format data including "Company A" as the payload to the server.

[1263] Database Matching

[1264] The server queries the internal database based on the received company name "Company A" to retrieve relevant information. For example, it sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS) to retrieve information about the market size, competition, offering model, and GTM strategy in the database.

[1265] Using external APIs

[1266] If the information retrieved from the database is incomplete, the server uses an external API to supplement the missing information. For example, the server sends an HTTP request to the "Market Information API" to retrieve the latest market size related to "Company A."

[1267] Data analysis and organization

[1268] The server analyzes the acquired data and classifies and organizes it according to the necessary items. For example, it separates the information into categories such as market size, competition, service model, and GTM strategy, and performs the necessary analysis on each. Once the analysis is complete, the information is converted into a format suitable for the user interface.

[1269] Emotion recognition by emotion engine

[1270] The device has an emotion engine that recognizes emotions from the user's face, voice, etc. For example, it analyzes the user's facial expressions and tone of voice through a camera and microphone to detect whether the user is happy, surprised, or anxious.

[1271] Adjusting outcomes according to emotions

[1272] The server adjusts the displayed information and interface based on the emotional data obtained from the emotion engine. For example, if the user is feeling anxious, the server may adjust the information display to be more friendly or add guides or hints.

[1273] Displaying the results

[1274] The analyzed data is sent from the server to the terminal, and the terminal displays the received data on the user interface. For example, the following information is displayed on the terminal screen:

[1275] Market size: $5 billion

[1276] Major competitors: Company B, Company C

[1277] Delivery model: Subscription-based

[1278] GTM Strategy: Digital Marketing, Customer Journey Map

[1279] Additionally, if the user's emotions are recognized, the display can be customized accordingly, for example by using relaxing language and color schemes to alleviate anxiety.

[1280] This system allows users to efficiently gain deep insights into companies, significantly reducing research efforts, and providing an optimal user experience based on emotions.

[1281] The processing flow will be explained below.

[1282] Step 1:

[1283] The user enters the name of the company to be surveyed in the input field of the terminal. For example, the user enters "Company A" and clicks the "Submit" button.

[1284] Step 2:

[1285] The terminal generates an HTTP request to send the company name "Company A" entered by the user to the server. The request sends JSON-formatted data including the company name as a payload to the server.

[1286] Step 3:

[1287] The server analyzes the received company name "Company A" and generates an SQL statement to query the database. The server sends the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to the database management system (DBMS).

[1288] Step 4:

[1289] The server receives the query results returned from the database and stores them in temporary storage (such as memory). This information includes market size, competition, delivery model, GTM strategy, etc.

[1290] Step 5:

[1291] If the information obtained from the database is insufficient, the server uses an external API to obtain additional information. For example, it sends an HTTP request to the "Market Information API" including the company name "Company A" to obtain the latest market size information.

[1292] Step 6:

[1293] The server receives additional information from external APIs, stores it in temporary storage, and complements the existing data set with the acquired data to create a complete company profile.

[1294] Step 7:

[1295] The server analyzes the data set and classifies and organizes it by information category (market size, competitors, service model, GTM strategy). The organized data is converted into a user-friendly format (HTML or JSON).

[1296] Step 8:

[1297] The device runs an emotion engine that analyzes the user's facial expressions and tone of voice. The device captures the user's facial expressions and tone of voice through a camera and microphone and generates emotion data.

[1298] Step 9:

[1299] The terminal transmits the generated emotion data to the server, for example, emotion data including information on whether the user is in a relaxed state or an anxious state.

[1300] Step 10:

[1301] The server analyzes the emotion data and adjusts the information and interface displayed according to the user's emotion. For example, if the user is in an anxious state, the server will simplify the information presentation and provide easy-to-understand guidance.

[1302] Step 11:

[1303] The server sends the final dataset, which reflects the analyzed and organized data and adjustments made by the emotion engine, to the terminal and returns the data as an HTTP response.

[1304] Step 12:

[1305] The terminal analyzes the final data set received from the server and displays it in a user interface. The terminal screen displays the following information:

[1306] Market size: $5 billion

[1307] Major competitors: Company B, Company C

[1308] Delivery model: Subscription-based

[1309] GTM Strategy: Digital Marketing, Customer Journey Map

[1310] Additionally, the UI may be adjusted based on the emotional data, such as a relaxing color scheme or additional guidance.

[1311] In this way, the user can efficiently obtain detailed information about the company, and furthermore, an optimal user experience is provided according to the user's feelings.

[1312] Example 2

[1313] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1314] When collecting detailed company information and market data, it is difficult to efficiently obtain information due to the fragmented nature of the information and the incompleteness of the data. Another challenge is providing an appropriate interface that responds to the user's emotions.

[1315] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collating a database based on the company name and acquiring information, a means for supplementing missing information from an external API, a means for analyzing and organizing the acquired information and displaying it on a user interface, and a means for adjusting the display content based on the emotion recognition result. This makes it possible to efficiently collect detailed company information and provide an optimal interface according to the user's emotions.

[1316] "Company name" is a unique name used to identify a company.

[1317] A "server" is a computer system that provides information and services to clients over a network.

[1318] A "database" is a collection of information that is systematically managed so that data can be stored and easily searched and manipulated.

[1319] An "external API" is an interface for communicating with other software or services, providing functions that can be used externally.

[1320] "User interface" refers to the display screen and operating means that allow the user to directly interact with the system.

[1321] An "emotion engine" is an algorithm or system that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[1322] "Market size" is an indicator that shows the total trading volume or total sales of products or services in a particular market.

[1323] "Competitors" refers to multiple companies or businesses that offer similar products or services in the same market.

[1324] A "delivery model" is a business strategy or method for how a company delivers products or services to customers.

[1325] A "go-to-market strategy" is a plan or strategy for bringing a new product or service to market and reaching customers.

[1326] The present invention is a system for efficiently collecting corporate information and providing a user with an appropriate interface according to their emotions. A specific method for carrying out the present invention will be described below.

[1327] First, the user uses the terminal to input the name of the company to be researched. The terminal has an input field where the user can input the name of the company they want to research. For example, if the user inputs "Company A," this company will be the subject of research.

[1328] Next, the device sends the entered company name "Company A" to the server. The device generates an HTTP POST request and sends JSON-formatted data including the company name to the server. At this time, the device communicates with the server via the Internet.

[1329] The server queries its internal database based on the received company name, "Company A," to retrieve relevant information. For example, it executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to collate data with the database management system (DBMS). This database stores company information such as market size, competitors, service model, and go-to-market strategy.

[1330] If the server cannot obtain the necessary information from its internal database, it uses an external API to fill in the missing information. For example, it sends an HTTP request to the "Market Information API" to obtain the latest market size data for "Company A." Data from the external API is also returned in JSON format.

[1331] The server analyzes the information obtained from the database and external APIs, classifying and organizing it according to the required items. For example, it converts the information into a data frame using Python's Pandas library and performs analysis according to each category (market size, competition, delivery model, go-to-market strategy). It then formats the information into a user interface format.

[1332] The device is equipped with an emotion engine that analyzes the user's face and voice to recognize emotions. For example, a facial recognition camera captures the user's facial expressions and inputs the data into an emotion recognition algorithm. A microphone also collects audio and analyzes the tone of voice. This analyzed data is sent to a server.

[1333] The server adjusts the information display and interface based on the emotional data sent from the device. For example, if the user is feeling anxious, the server changes the display to a more friendly format and adds guides and hints, allowing the user to view the necessary information in a relaxed manner.

[1334] Finally, the organized and analyzed data is sent from the server to the device and displayed on the device's user interface. For example, the following information is displayed:

[1335] Market size: $5 billion

[1336] Major competitors: Company B, Company C

[1337] Delivery model: Subscription-based

[1338] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[1339] It also customizes the experience based on the user's emotions, adding relaxing color schemes and effective explanatory text to optimize the user experience.

[1340] Example prompt sentence:

[1341] Please explain in detail the processing steps of the program in which the user enters the company name "Company A," the server uses the internal database and external API to collect the necessary information, and displays it to the user.

[1342] In this way, users can quickly and efficiently obtain detailed information about a company, and an optimal interface is provided that responds to the user's emotions.

[1343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1344] Step 1:

[1345] The user inputs the name of a company into the input field of the terminal. For example, by inputting "Company A," the research target is determined. This input is the input data.

[1346] Step 2:

[1347] The terminal structures the company name "Company A" entered by the user as JSON format data and generates an HTTP POST request. The terminal sends this request to the server. The input is the company name, and the output is the request to the server.

[1348] Step 3:

[1349] The server queries its internal database based on the received company name "Company A". It executes the SQL query "SELECT FROM company_info WHERE name = 'Company A'" to retrieve relevant information. The input is the company name and the output is information from the database.

[1350] Step 4:

[1351] The server checks the information retrieved from the database and identifies any missing information. For example, if market size or competitive information is missing, it uses an external API to supplement this information. The input is information from the database, and the output is the supplemented information.

[1352] Step 5:

[1353] The server sends an HTTP request to an external API to obtain the missing information. For example, the server obtains market size data for "Company A" from the "Market Information API." The input is the server request, and the output is data from the external API.

[1354] Step 6:

[1355] The server analyzes, classifies, and organizes the acquired information. It uses Python's Pandas library to convert the data into a data frame format and analyzes it by category (market size, competitors, delivery model, go-to-market strategy). The input is information from the database and external API, and the output is the analyzed data.

[1356] Step 7:

[1357] The device uses an emotion engine to recognize the user's emotions. It uses a camera and microphone to collect and analyze the user's facial expressions and voice. For example, if the user is surprised, the emotion engine analyzes their facial expressions and tone of voice. The input is the user's facial expressions and voice, and the output is emotion data.

[1358] Step 8:

[1359] The device sends the recognized emotion data to the server. The input is the emotion data of the device, and the output is the transmission of the emotion data to the server.

[1360] Step 9:

[1361] The server adjusts the displayed information and interface based on the emotional data. For example, if the user feels anxious, it makes the interface more friendly and adds guides and hints. The input is emotional data, and the output is adjusted interface information.

[1362] Step 10:

[1363] The server sends the organized and analyzed data and interface information to the terminal. The input is the organized data and adjusted interface information in the server, and the output is sent to the terminal.

[1364] Step 11:

[1365] The device displays the received data in a user interface. The user can see the following information on the device screen:

[1366] Market size: $5 billion

[1367] Main competitors: Other company B, other company C

[1368] Delivery model: Subscription

[1369] Go-To-Market Strategy: Digital Marketing, Customer Journey Map

[1370] Furthermore, it provides an interface that is customized according to the user's emotions. The input is data from the server, and the output is a display on the user interface.

[1371] (Application example 2)

[1372] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1373] Collecting and analyzing corporate information requires a lot of time and effort due to the wide range of information involved. Furthermore, the user experience is not sufficiently improved because the information is not displayed optimally according to the user's emotional state. Therefore, there is a need for the development of a system that efficiently acquires necessary information and displays it appropriately according to the user's emotional state.

[1374] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1375] In this invention, the server includes means for transmitting the input company name, means for collating the company name with a database to obtain information, means for supplementing missing information from an external API, means for analyzing and organizing the obtained information and displaying it on a user interface, and means for recognizing the user's emotions and adjusting the display results. This enables the user to efficiently obtain the company information they need and provides an optimal interface according to their emotions.

[1376] A "company name" is a name used to identify a specific business entity.

[1377] A "server" is a computer system that processes and stores data and provides information in response to user requests.

[1378] A "database" is a collection of data that can be efficiently stored, managed, and searched.

[1379] An "external API" is an external programming interface provided in a form that can be accessed by other systems or applications.

[1380] A "user interface" is the part where information is exchanged between the user and the system, and provides operation and display functions.

[1381] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's response based on that information.

[1382] "Analysis" is the process of examining collected data in detail and extracting the necessary information.

[1383] "Organizing" is the process of classifying acquired data into categories and converting them into an easy-to-read format.

[1384] "Market size" is information about the total sales or total volume of transactions of a product in a particular market.

[1385] "Competitors" are other entities in the same market that offer similar products or services and compete for customers.

[1386] A "delivery model" is a specific method or business model for providing products or services to customers.

[1387] A "Go-To-Market Strategy" is a sales strategy or marketing plan for introducing new products or services to the market.

[1388] "Store information" refers to detailed information about a specific commercial facility or retail store, including its location, opening hours, and the products and services it offers.

[1389] To implement this invention, the user must first operate the terminal to input the name of the company to be surveyed. For example, the user inputs the company name into an input field of the smartphone app "Brick Store Analyzer."

[1390] The device then sends the entered company name to the server. The device generates an HTTP request and sends JSON-formatted data containing the company name as a payload to the server. At this point, a database match is performed on the server side. The server issues a query to its internal database to retrieve information about the company. For example, the SQL query "SELECT FROM store_info WHERE name = 'Company A'" is used. MySQL is a commonly used database management system (DBMS).

[1391] If the information the server retrieves from the database is incomplete, the server uses external APIs. The missing information is retrieved from external market information APIs or competitive information APIs. The server sends HTTP requests to these external APIs to complete the missing information.

[1392] The server then analyzes and organizes all the information it has acquired. This analysis is performed using data analysis tools such as Python and R, as well as ML libraries (e.g., scikit-learn). The information is categorized into categories such as market size, competitors, service model, GTM strategy, and store information. The analysis results are then converted into a format suitable for the user interface.

[1393] The device is equipped with an emotion recognition function that recognizes the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice through the smartphone's camera and microphone to understand the user's emotional state. This emotion recognition uses technologies such as TensorFlow and OpenCV.

[1394] The server adjusts the displayed information and interface based on the emotional data. For example, if the user has an anxious expression, the information display will be more friendly and additional guidance and hints will be provided.

[1395] Finally, the analyzed and organized data is sent from the server to the terminal, which displays it on the user interface. For example, the following information is displayed on the terminal screen:

[1396] Market size: $5 billion

[1397] Main competitors: Store B, Store C

[1398] Delivery model: Subscription-based

[1399] GTM Strategy: Digital Marketing, Customer Journey Map

[1400] This series of processes enables users to efficiently obtain the necessary company information and provides an optimal interface that responds to their emotions.

[1401] An example prompt is:

[1402] "Get Company A's market size, key competitors, delivery model, and GTM strategy, and present it in a format that's easy for users to use. If users are unsure, provide the information in a way that puts them at ease."

[1403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1404] Step 1:

[1405] The user operates the terminal and inputs the name of the company to be investigated. In the input field, the name of the company to be investigated (e.g., "Company A") is entered. The input company name then becomes the input data for the next processing step.

[1406] Step 2:

[1407] The terminal sends the entered company name to the server. Specifically, it generates an HTTP request and sends JSON-formatted data including the company name as a payload to the server. At this point, the input data is the company name, and the output data is the HTTP request sent to the server.

[1408] Step 3:

[1409] The server issues a query to its internal database based on the received company name. For example, it executes the SQL query "SELECT FROM store_info WHERE name = 'Company A'" to retrieve related information. The input data for this step is the company name, and the output data is the information retrieved from the database.

[1410] Step 4:

[1411] If the information obtained by the server is incomplete, it supplements the missing information from an external API. Specifically, it sends an HTTP request to an external market information API or competitive information API to obtain the necessary information. In this process, the input data is incomplete company information, and the output data is the supplemented, complete information.

[1412] Step 5:

[1413] The server analyzes and organizes all the acquired information. Using data analysis tools such as Python and R, the information is categorized into market size, competitors, service models, GTM strategies, and store information. The input data for this step is the completed company information, and the output data is the analyzed and classified information.

[1414] Step 6:

[1415] The device recognizes the user's emotional state by using an emotion engine to analyze the user's facial expressions and tone of voice via the smartphone's camera and microphone. The input data for this process is the user's real-time facial expressions and voice data, and the output data is the analyzed emotional information.

[1416] Step 7:

[1417] The server adjusts the display content and interface based on the emotion data. For example, if the user is anxious, the information display will be made more friendly and guides and hints will be added. The input data for this step are emotion data and analyzed and classified company information, and the output data is the adjusted display content.

[1418] Step 8:

[1419] The server sends the organized information to the terminal, which then displays the received information on the user interface. For example, information such as market size, major competitors, offering model, and GTM strategy is displayed appropriately on the screen. In this final step, the input data is the adjusted company information, and the output data is the information displayed on the user interface.

[1420] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1421] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1422] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1423] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1424] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1425] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1426] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1427] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1428] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1429] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1430] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1431] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1432] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1433] 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.

[1434] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1435] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1436] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1437] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1438] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1439] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1440] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1441] The following is further disclosed regarding the above embodiment.

[1442] (Claim 1)

[1443] means for transmitting the inputted company name to a server;

[1444] A means for the server to retrieve information by checking a database based on the company name;

[1445] A means to supplement missing information from external APIs,

[1446] A means for analyzing and organizing the acquired information and displaying it on a user interface;

[1447] A system including:

[1448] (Claim 2)

[1449] 2. The system according to claim 1, wherein the information acquired by the server includes market size, competition, offering model, and go-to-market strategy.

[1450] (Claim 3)

[1451] 10. The system of claim 1, further comprising means for utilizing an external API to obtain up-to-date market information.

[1452] "Example 1"

[1453] (Claim 1)

[1454] a means for a user to input a business name into an input field;

[1455] means for transmitting the inputted company name to a server by the terminal;

[1456] a means for the server to query a database based on the business name to obtain information;

[1457] A means for the server to call an external API to supplement the missing information when the information retrieved from the database is incomplete;

[1458] A means for analyzing the information acquired by the server and classifying and organizing it by item;

[1459] a means for transmitting the organized information from the server to the terminal and for the terminal to display the information on a user interface;

[1460] A system including:

[1461] (Claim 2)

[1462] 10. The system of claim 1, further comprising a server that obtains information including market size, competition, offering model, and go-to-market strategy.

[1463] (Claim 3)

[1464] 10. The system of claim 1, further comprising means for utilizing an external API to obtain up-to-date market information.

[1465] "Application Example 1"

[1466] (Claim 1)

[1467] means for transmitting the inputted company name to a server;

[1468] A means for the server to retrieve information by checking a database based on the company name;

[1469] A means to supplement missing information from external APIs,

[1470] A means for analyzing and organizing the acquired information and displaying it on a user interface;

[1471] a means for visually displaying the information on a display of the smart device;

[1472] means for inputting a company name via voice input;

[1473] A system including:

[1474] (Claim 2)

[1475] 2. The system according to claim 1, wherein the information acquired by the server includes market size, competition, supply model, go-to-market strategy, and security risk information.

[1476] (Claim 3)

[1477] 2. The system according to claim 1, further comprising means for obtaining the latest market information and security risk information using an external API.

[1478] "Example 2: Combining Emotion Engines"

[1479] (Claim 1)

[1480] a means for a user to input a business name into an input field;

[1481] means for transmitting the inputted company name to a server by the terminal;

[1482] A means for the server to retrieve information by checking a database based on the company name;

[1483] A means to supplement the information that the server lacks from external APIs,

[1484] A means for analyzing and organizing the information acquired by the server and displaying it on a user interface;

[1485] a means for the terminal to include an emotion engine for recognizing the emotion of the user;

[1486] A means for the server to adjust display content based on the emotion recognition result;

[1487] A system including:

[1488] (Claim 2)

[1489] 2. The system according to claim 1, wherein the information acquired by the server includes market size, competition, offering model, and go-to-market strategy.

[1490] (Claim 3)

[1491] 10. The system of claim 1, further comprising means for utilizing an external API to obtain up-to-date market information.

[1492] "Application example 2 when combining emotion engines"

[1493] (Claim 1)

[1494] means for transmitting the inputted company name to a server;

[1495] A means for the server to retrieve information by checking a database based on the company name;

[1496] A means to supplement missing information from external APIs,

[1497] A means for analyzing and organizing the acquired information and displaying it on a user interface;

[1498] means for recognizing a user's emotion and adjusting the display results;

[1499] A system including:

[1500] (Claim 2)

[1501] 2. The system according to claim 1, wherein the information acquired by the server includes store information in addition to market size, competition, offering model, and go-to-market strategy.

[1502] (Claim 3)

[1503] The system according to claim 1, further comprising means for obtaining the latest market information and store information using an external API. [Explanation of symbols]

[1504] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for transmitting the inputted company name to a server; A means for the server to retrieve information by checking a database based on the company name; A means to supplement missing information from external APIs, A means for analyzing and organizing the acquired information and displaying it on a user interface; A system including:

2. 2. The system according to claim 1, wherein the information acquired by the server includes market size, competition, supply model, and go-to-market strategy.

3. 10. The system of claim 1, further comprising means for obtaining up-to-date market information using an external API.

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