System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting a company's own information by a company or a business office, a means for transmitting the inputted company's own information to a server, a means for starting an engine for analyzing the received company's own information, a means for selecting an optimum cooperation destination by the analysis engine, and a means for presenting the selected cooperation destination information to a user.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] When companies and businesses look for partners to collaborate with, they often face the challenge of not having the connections to find the right partners, which hinders mutual customer referrals and joint events. There is a need to solve this problem and provide a system that allows them to efficiently and effectively find the best partners to collaborate with. [Means for solving the problem]

[0005] We provide a system that includes a means for a company or business to input its company information, a means for transmitting the input company information to a server, a means for launching an engine to analyze the received company information, a means for selecting the most suitable partner using the analysis engine, and a means for presenting the selected partner information to the user. This allows the user to efficiently find the most suitable collaboration partner based on the company information they input. Furthermore, by including a means for the user to evaluate and select the presented partner information, more detailed selection becomes possible, and adding a feedback function can improve the accuracy of the system.

[0006] An "enterprise" is an organization of corporations or individual business owners that provides goods or services for profit.

[0007] "Establishment" means the base of operations through which a business or corporation provides goods or services.

[0008] "Company information" refers to information about a company or business, such as what the company or business wants to do, its business situation, and market size.

[0009] A "server" is a computer system that receives and sends data over a network.

[0010] "Analysis Engine" means a program or algorithm that performs analysis on received data to achieve a specific purpose.

[0011] "Partner" refers to a company or business establishment with which we conduct business activities jointly.

[0012] "User" refers to a person in charge of a company or business who uses the system to enter their company information and hopes to find a partner.

[0013] "Presenting" means displaying or providing information such as analysis results to a user.

[0014] "Feedback" refers to a user providing opinions or evaluations of presented information.

[0015] A "system" refers to a group of components that execute a series of processes at a company or business, such as inputting, transmitting, analyzing, and displaying information. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention provides a system that allows companies and businesses to input their own company information and, based on that information, suggests the most suitable partners for cooperation. A specific embodiment of this system will now be described.

[0038] System Configuration

[0039] User Interface

[0040] 1. Input form

[0041] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[0042] What you want to do (e.g. joint marketing, joint events)

[0043] Business situation (e.g., sales, number of employees)

[0044] Market size (e.g., customer demographics, area of ​​operation)

[0045] Server and Analysis Engine

[0046] 2. Receipt and storage of information

[0047] The terminal sends the entered information to the server, which receives the information and temporarily stores it in a database.

[0048] 3. Analysis of Information

[0049] The server launches an analysis engine to analyze the received information. This analysis engine uses the generative AI model ChatGPT (registered trademark). Based on the received information, the analysis engine selects the most suitable collaborator from a database.

[0050] 4. Proposal Generation

[0051] The analysis engine generates multiple candidate partners based on the analysis results, assigns a customized evaluation score to each candidate, and returns the proposed results to the server in structured data format such as JSON.

[0052] Information presentation and selection

[0053] 5. Displaying the results

[0054] The server sends the generated proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0055] 6. Selection of partners

[0056] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0057] Specific examples

[0058] 1. Example of user information entry

[0059] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0060] "What we want to do": Joint marketing campaign

[0061] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0062] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0063] 2. Analyzing the information and generating recommendations

[0064] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0065] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0066] Partner candidate 2: Fitness gym C (rating score: 80)

[0067] Partner candidate 3: Organic food store D (rating score: 78)

[0068] 3. Displaying and selecting results

[0069] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[0070] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user accesses the input form and enters information about their company, including the details of what they want to do, their business situation, and market size, and then clicks the submit button.

[0074] Step 2:

[0075] The device sends the user's input information in JSON format to the server using the HTTPS protocol, which ensures secure data transfer.

[0076] Step 3:

[0077] The server receives the information sent by the user and temporarily stores it in a database. It then checks the integrity of the stored data to make sure there are no omissions or errors.

[0078] Step 4:

[0079] The server starts the analysis engine and passes the stored user information. ChatGPT is used as the analysis engine and sends the data through the API.

[0080] Step 5:

[0081] ChatGPT analyzes the information it receives and extracts the most suitable partners from its database based on the company information provided. The analysis also takes into account past data, industry trends, and complementary relationships.

[0082] Step 6:

[0083] ChatGPT returns the analysis results to the server. The analysis results include multiple collaboration candidates and their respective evaluation scores. The data is returned in structured data format such as JSON.

[0084] Step 7:

[0085] The server receives the analysis results and formats them for presentation to the user. It converts the proposed results into HTML format and sends them to the user's device.

[0086] Step 8:

[0087] The device receives the proposal results and displays them on the user's screen. The display includes a list of potential partners and detailed information about each (company name, industry, and evaluation score).

[0088] Step 9:

[0089] Users can view a list of proposed partners and select the most suitable company. After making a selection, users can contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results.

[0090] This allows users to efficiently select the most suitable partner and build a win-win business relationship.

[0091] Example 1

[0092] 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."

[0093] For companies and businesses to find the best partners based on their own company information requires a great deal of time and effort to organize and analyze the information. Furthermore, conventional systems tend to suggest partners subjectively, lacking in accuracy and objectivity. Therefore, there is a need for a system that can efficiently analyze information and objectively suggest the best partners.

[0094] 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.

[0095] In this invention, the server includes means for temporarily storing the received company information in data storage, means for launching a generative AI model to analyze the stored company information, and means for generating and sending a prompt sentence to the generative AI model to select the most suitable partner, thereby enabling companies and businesses to efficiently and objectively find the most suitable partner based on their needs.

[0096] "Company or establishment" refers to a corporation or sole proprietorship engaged in profit-making activities, and is an organization that provides products or services in the economic context.

[0097] "Company information" refers to specific information held by a company or business, including detailed data such as the type of business the company wants to implement, its business situation, and the size of the market.

[0098] "Information processing device" refers to a computer system or server that has the function of processing, analyzing, and storing data.

[0099] "Data storage" refers to a device or system for storing and managing digital information, including databases and cloud storage.

[0100] A "generative AI model" refers to a program that uses artificial intelligence technology to generate text and analyze data, specifically a solution that uses natural language processing.

[0101] A "prompt" is text data used as input for a generative AI model, and contains questions or instructions for analysis.

[0102] A "structured data format" is a data format that is organized according to a certain format, such as JSON or XML.

[0103] A "user interface" is a screen or operating device that allows a user to directly interact with a system, and includes web browsers and applications.

[0104] "Feedback" refers to the reactions and evaluations from users regarding the system's proposed results, and is information that can be used to improve the system's performance.

[0105] The present invention provides a system in which a company or business inputs its own company information and proposes the most suitable partner based on that information. A specific embodiment of this system will now be described.

[0106] System Configuration

[0107] User Interface

[0108] Input form

[0109] Users use a web form on their device (e.g., a PC or smartphone) to enter their company information. This form includes the following fields:

[0110] What you want to do (e.g. joint marketing, joint events)

[0111] Business situation (e.g., sales, number of employees)

[0112] Market size (e.g., customer demographics, area of ​​operation)

[0113] Server and Analysis Engine

[0114] Receiving and storing information

[0115] The terminal sends the company information entered by the user to the server, which temporarily stores the received information in data storage (for example, a MySQL (registered trademark) or PostgreSQL database).

[0116] Analysis of information

[0117] The server uses the generative AI model ChatGPT to analyze the stored information, then generates a prompt and calls the ChatGPT API, which includes the information entered by the user and asks a question to suggest the best partner.

[0118] example:

[0119] Company A's information:

[0120] What we want to do: Joint marketing campaigns

[0121] Business situation: Annual sales of 100 million yen, number of employees: 50

[0122] Market size: Products mainly targeted at women in their 30s, nationwide

[0123] Please suggest the best partner.

[0124] Generate proposal results

[0125] The analysis engine (ChatGPT) generates collaboration candidates based on the prompt sentence and assigns an evaluation score to each. The generated proposal results are returned to the server in a structured data format such as JSON.

[0126] Information presentation and selection

[0127] Displaying the results

[0128] The server sends the generated proposal results to the device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0129] Selection of partners

[0130] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0131] Specific examples

[0132] Example of user information entry

[0133] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0134] "What we want to do": Joint marketing campaign

[0135] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0136] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0137] Analyzing information and generating recommendations

[0138] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0139] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0140] Partner candidate 2: Fitness gym C (rating score: 80)

[0141] Partner candidate 3: Organic food store D (rating score: 78)

[0142] Displaying and selecting results

[0143] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. Feedback can also be provided if necessary.

[0144] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] System program processing flow

[0147] Step 1: User enters company information.

[0148] Input: The user opens a web browser on their device, accesses the provided URL, and enters information such as "what they want to do," "business situation," and "market size" into the form.

[0149] What happens: The user enters information into the input fields and clicks the "Submit" button.

[0150] Step 2: The terminal sends the entered data to the server.

[0151] Input: Data entered by the user.

[0152] Output: The data to be sent as an HTTP POST request.

[0153] Specific operation: The device sends the information entered by the user to the server in the form of an HTTP POST request, which contains data in JSON format.

[0154] Step 3: The server receives the data and temporarily stores it in the data storage.

[0155] Input: HTTP POST request from the terminal.

[0156] Output: Information stored in a database.

[0157] Specific operation: The server receives the request and issues an INSERT statement to the database (e.g., MySQL, PostgreSQL) to save the information.

[0158] Step 4: The server launches the generative AI model to generate a prompt sentence.

[0159] Input: Your saved company information.

[0160] Output: The generated prompt statement.

[0161] How it works: The server reads the company's information from the database and generates a prompt based on that information. This prompt is then used as input for the generative AI model.

[0162] Step 5: The server sends the prompt to the generative AI model and receives the analysis result.

[0163] Input: The generated prompt statement.

[0164] Output: Analysis results from the generative AI model.

[0165] Specific operation: The server sends the generated prompt to the generative AI model (ChatGPT) via API. The generative AI model analyzes the prompt, generates collaboration candidates and evaluation scores, and returns them in JSON format.

[0166] Step 6: The server sends the analysis results to the device.

[0167] Input: Analysis results from the generative AI model (JSON format).

[0168] Output: HTTP response containing the parsed results.

[0169] Specific operation: The server receives the analysis results from the generative AI model and returns them to the terminal as an HTTP response, either as is or after processing as necessary.

[0170] Step 7: The terminal receives the result and displays it on the user's screen.

[0171] Input: HTTP response (JSON data) from the server.

[0172] Output: A list of potential collaborators displayed on the user's screen.

[0173] Specific operation: The device analyzes the HTTP response and displays the candidate partners and their detailed information (company name, industry, evaluation score, etc.) on the screen. The user selects a partner based on this information.

[0174] Through these steps, the system enables companies and businesses to input their company information and efficiently suggest the most suitable partners.

[0175] (Application example 1)

[0176] 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."

[0177] Modern companies and businesses face challenges in efficiently finding the best partners to meet their needs. This is especially true when planning new business opportunities or marketing campaigns, as analyzing vast amounts of information to find effective partners is time-consuming. Furthermore, there is a lack of reliability in the results of partner selection and a lack of mechanisms for effectively incorporating user feedback. This creates the problem of wasting a lot of time and money in the process of finding the right business partner.

[0178] 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.

[0179] In this invention, the server includes: a means for a company or business to input its company information; a means for transmitting the input company information to the server; a means for launching an analysis engine to analyze the received company information; a means for selecting the most suitable partner using the analysis engine; a means for presenting the selected partner information to the user; a means for providing a user interface that operates on a smartphone; a means for generating a prompt sentence based on the input information using a generative AI model; and a means for generating a proposal result based on the prompt sentence. This allows companies and businesses to efficiently find the partner that best suits their needs. Furthermore, it is possible to effectively reflect user feedback and improve the accuracy of the proposals.

[0180] "Company or establishment" is a general term for organizations or groups whose purpose is to provide products or services.

[0181] "Company information" refers to internal information provided by a company or business, and includes information such as business conditions, market size, and desired implementation.

[0182] A "server" is a computer system for storing, processing, and distributing data over a network.

[0183] An "analysis engine" is a software component that performs analysis based on input information and generates the necessary results and suggestions.

[0184] "Collaborators" means other companies or establishments with which we collaborate on specific business projects or activities.

[0185] "Users" are the people in charge at companies and offices who use the system to input their company information and receive proposals for collaboration.

[0186] "Presentation" refers to the act of displaying the information generated as a result of the analysis engine in a form visible to the user.

[0187] A "smartphone" is a portable computer device that has a variety of functions, including the ability to make calls, run applications, and connect to the Internet.

[0188] "User interface" refers to the screens and operating means through which a user interacts with a system.

[0189] A "generative AI model" is a type of machine learning model that automates specific tasks by training it with large amounts of data in advance, and in this case refers to ChatGPT.

[0190] A "prompt sentence" is an input sentence given to a generative AI model, and includes instructions for analysis and result generation.

[0191] "Proposal results" are information generated by the analysis engine and include the most suitable collaborators.

[0192] The present invention is a system in which a company or business enters its own company information and proposes the most suitable partner based on that information. Specific embodiments of the present invention will be described below.

[0193] System Configuration

[0194] User Interface

[0195] Users enter their company information through an application installed on their smartphone. This information can include:

[0196] What you want to do (e.g. joint marketing, joint events)

[0197] Business situation (e.g., sales, number of employees)

[0198] Market size (e.g., customer demographics, area of ​​operation)

[0199] The entered information is sent to a server and stored for analysis.

[0200] Server and Analysis Engine

[0201] The server has the following functions:

[0202] 1. Receipt and storage of information

[0203] Receives information entered by the user and temporarily stores it in a database.

[0204] 2. Analysis of Information

[0205] The server starts the generative AI model ChatGPT, generates a prompt based on the received information, and generates a proposal for the collaborating partner based on this prompt.

[0206] 3. Proposal generation

[0207] The proposed results generated by the analysis engine are returned to the server as structured data in JSON format or similar, and then sent back to the user's smartphone.

[0208] Displaying the proposed results

[0209] The user's smartphone displays the proposal results sent from the server, which include potential partners and their detailed information (company name, industry, evaluation score).

[0210] Specific examples

[0211] 1. Example of user information entry

[0212] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0213] What we want to do: Joint marketing campaigns

[0214] Business situation: Annual sales of 100 million yen, number of employees: 50

[0215] Market size: Products mainly targeted at women in their 30s, nationwide

[0216] 2. Analyzing the information and generating recommendations

[0217] The server receives the information and uses ChatGPT to generate a prompt like this:

[0218] Given the following business information:

[0219] Project: Joint Marketing Campaign

[0220] Revenue: 100 million yen

[0221] Employees: 50

[0222] Market: Mainly targeting women in their 30s, national expansion

[0223] Find the best partnership opportunities.

[0224] Based on the analysis results, the following proposed results are generated.

[0225] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[0226] Partner candidate 2: Fitness gym (rating score: 80)

[0227] Partner candidate 3: Organic food store (rating score: 78)

[0228] 3. Displaying and selecting results

[0229] The user receives the proposal results and views the list of candidates displayed on the screen. The user can compare the detailed information and select the most suitable partner.

[0230] Hardware and Software

[0231] Hardware: Server (using Heroku or AWS (registered trademark) as cloud services)

[0232] Software: Flask (Python framework), SQLite (database), OpenAI (registered trademark) API (generative AI model ChatGPT)

[0233] This allows companies and businesses to efficiently find partners that best suit their needs, maximizing business opportunities. It also effectively incorporates user feedback to improve the accuracy of the system's proposals.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] Users launch the smartphone app and enter their company information into the application's input form. This information includes the desired implementation, business situation, market size, etc. This information is then sent to the server.

[0237] Step 2:

[0238] The device sends the company information entered by the user to the server, which temporarily stores the received data in a database (SQLite). During this process, it is confirmed that the input data reaches the server in the correct format.

[0239] Step 3:

[0240] The server calls the generative AI model ChatGPT to analyze the stored data. At this time, it generates and sends a prompt to the analysis engine. This prompt is generated based on the information entered by the user. For example, it might be in the format "Given the following business information: ..."

[0241] Step 4:

[0242] The generative AI model, ChatGPT, generates optimal collaboration proposals based on the prompt text. The server receives these proposals as structured data, such as JSON, and temporarily stores them. These proposals include the name, industry, and evaluation score of each potential collaborator.

[0243] Step 5:

[0244] The server sends the generated proposal results to the user's smartphone. The user can view the received proposal results within the app. The results display screen includes multiple potential partners and their respective details.

[0245] Step 6:

[0246] The user compares the proposals and selects the most suitable partner. During this selection process, the user checks the detailed information of each partner and uses their evaluation score as a reference. The selection results can be sent to the server as feedback.

[0247] Step 7:

[0248] The server receives and stores feedback from users. Analysis of this feedback data can help improve the accuracy of future suggestions. The analysis results are used to improve the system.

[0249] In this way, a system is created in which users can input their company information and efficiently find the best partners. By using generative AI models and prompts, highly accurate suggestions can be made, allowing users to maximize business opportunities.

[0250] 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.

[0251] This invention relates to a system in which a company or business inputs its own company information and, based on that information, proposes optimal partners. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and has the function of optimizing proposal content based on the user's emotions. Specific embodiments of this system are described below.

[0252] System Configuration

[0253] User Interface and Emotion Engine

[0254] 1. Input form

[0255] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[0256] What you want to do (e.g. joint marketing, joint events)

[0257] Business situation (e.g., sales, number of employees)

[0258] Market size (e.g., customer demographics, area of ​​operation)

[0259] 2. Emotion Engine

[0260] The emotion engine works in conjunction with the user interface to recognize the user's emotions in real time while they are typing. Emotion recognition can be achieved by analyzing facial expressions using a camera, or by analyzing the user's typing speed and patterns.

[0261] Server and Analysis Engine

[0262] 3. Receipt and storage of information

[0263] The device sends the user's input information in JSON format to the server. The server receives the information and temporarily stores it in a database. If necessary, emotion data is also stored.

[0264] 4. Analysis of Information

[0265] The server launches an analysis engine to analyze the received information. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborator from the database.

[0266] 5. Reflecting emotions

[0267] The emotion engine reflects the user's emotional data based on the results of the analysis engine and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, or if the user is excited, the suggestions will be more detailed.

[0268] Information presentation and selection

[0269] 6. Displaying the results

[0270] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[0271] 7. Selection of partners

[0272] Users compare the detailed information of the presented candidate partners and select the most suitable company. After making a selection, users contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results, and this feedback will be used for the next analysis.

[0273] Specific examples

[0274] 1. Example of user information entry

[0275] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0276] "What we want to do": Joint marketing campaign

[0277] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0278] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0279] The emotion engine analyzes the user's facial expressions and recognizes that the user is concentrating.

[0280] 2. Analyzing the information and generating recommendations

[0281] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0282] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0283] Partner candidate 2: Fitness gym C (rating score: 80)

[0284] Partner candidate 3: Organic food store D (rating score: 78)

[0285] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[0286] 3. Displaying and selecting results

[0287] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[0288] This system allows companies and businesses to efficiently find partners that best suit their needs. Furthermore, the introduction of an emotion engine optimizes proposals based on the user's emotions, enabling more effective collaboration.

[0289] The processing flow will be explained below.

[0290] Step 1:

[0291] The user accesses the input form and enters their company information. Here, the user enters specific details such as the business situation, market size, etc., and clicks the submit button.

[0292] Step 2:

[0293] The device sends the user's input information in JSON format to the server, using the HTTPS protocol to ensure secure data transfer.

[0294] Step 3:

[0295] The server receives the information sent by the user and temporarily stores it in a database. It then performs a consistency check on the stored data to ensure there are no omissions or errors.

[0296] Step 4:

[0297] Simultaneously with the input process, the device's built-in emotion engine works to recognize the user's emotions in real time, based on facial expression analysis using a camera and analysis of input speed and patterns.

[0298] Step 5:

[0299] The emotion engine sends the user's emotion data to the server, where it is used for analysis along with company information.

[0300] Step 6:

[0301] The server launches the analysis engine and passes the saved user company information and emotion data. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the optimal partner.

[0302] Step 7:

[0303] ChatGPT returns the analysis results to the server, which include multiple potential partners, their evaluation scores, and the proposed solutions.

[0304] Step 8:

[0305] The emotion engine reflects the user's emotional data based on the analysis results and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, and if the user is excited, the suggestions will be more detailed.

[0306] Step 9:

[0307] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The display includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[0308] Step 10:

[0309] The user browses the list of presented partners and selects the most suitable company. After making a selection, the user contacts the selected partner and begins specific collaboration negotiations. The user can also provide feedback on the proposal results, which will be used for the next analysis.

[0310] By introducing this system, companies and businesses will be able to find the most suitable partners more efficiently and in line with the user's feelings, building win-win business relationships.

[0311] Example 2

[0312] 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."

[0313] The process for companies and businesses to find partners that meet their needs is time-consuming, labor-intensive, and inefficient with conventional methods. Furthermore, suggestions made without considering the user's emotional state are unlikely to be optimal. Therefore, there is a need for a system that can efficiently suggest optimal partners based on the user's input and emotional state.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0315] In this invention, the server includes means for a company or business to input its company information, means for transmitting the input company information to the server, means for saving the received company information, means for starting an analysis engine, means for selecting an optimal partner based on the information received by the analysis engine, means for recognizing the user's emotions during input in real time, means for adjusting the content of proposals based on the emotion recognition results, and means for presenting the selected partner information to the user. This makes it possible to efficiently propose optimal partners that take into account the user's needs and emotional state.

[0316] "Company or establishment" means a legal entity or organization that conducts commercial activities or business.

[0317] "Company information" refers to data and information about a company or business, including, for example, what the company wants to do, its business situation, and the size of its market.

[0318] "Input means" refers to the interface that allows users to input their company information into the system.

[0319] "Transmission means" is a function for transmitting the entered company information from the user's terminal to the server.

[0320] "Means for storing" refers to the method of storing the received company information in a database or other storage device.

[0321] An "analysis engine" is a program or algorithm that analyzes the company's received information and selects the most suitable partner based on specified criteria.

[0322] "Real-time recognition means" refers to the ability to instantly detect and analyze the user's emotional state while they are typing.

[0323] "Emotion recognition result" is data obtained as a result of analyzing the user's emotional state.

[0324] The "means for adjusting the content of the proposal" is a function for changing and optimizing the content of the proposal based on the emotion recognition results.

[0325] The "presentation means" is a method for displaying information about the ultimately selected collaborator on the user's terminal.

[0326] User Interface and Emotion Engine

[0327] The system provides a web form for users to enter information about their company. In this form, users can enter information such as the business operations they wish to carry out, their business situation, and market size. The system also incorporates an emotion engine that recognizes emotions in real time while users are typing. Emotion recognition is performed by analyzing the user's facial expressions using a camera, as well as by analyzing the typing speed and patterns.

[0328] Server and Analysis Engine

[0329] Once the company information is entered, the device sends this information in JSON format to the server. The server stores the received information in a database. The received information is analyzed using a generative AI model (e.g., ChatGPT) as an analytical engine. The analytical engine then selects the most suitable partner from the database and generates a proposal based on that.

[0330] Reflecting emotions and adjusting proposals

[0331] The emotion engine adjusts the suggestions based on the analysis engine's suggestions and reflects the user's emotional data. For example, if the user is feeling stressed, the suggestion content will be simplified, but if the user is excited, the suggestion will be more detailed.

[0332] Information presentation and selection

[0333] The server sends the final proposal results to the user's device. The device then displays the received proposal results on the user's screen. The displayed content includes a list of potential partners and detailed information about each (company name, industry, and evaluation score). The user compares the presented candidates and selects the most suitable company. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can provide feedback on the proposal results to the system, which will be used for the next analysis.

[0334] Specific examples

[0335] Example of user information entry

[0336] A company wants to run a "co-marketing campaign" and enters the following information:

[0337] What we want to do: Joint marketing campaigns

[0338] Business situation: Annual sales of 100 million yen, number of employees: 50

[0339] Market size: Products aimed primarily at women in their 30s, nationwide distribution

[0340] The emotion engine analyzes the user's facial expression and recognizes that the user is concentrating.

[0341] Analyzing information and generating recommendations

[0342] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0343] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[0344] Partner candidate 2: Fitness gym (rating score: 80)

[0345] Partner candidate 3: Organic food store (rating score: 78)

[0346] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[0347] Displaying and selecting results

[0348] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects the beauty product manufacturer that is the best partner for cooperation. If necessary, the user can also provide feedback.

[0349] Prompt Sentence Examples

[0350] If a company has an annual turnover of 100 million yen, has 50 employees, and sells products aimed at women in their 30s nationwide, please use this information to propose the most suitable partner.

[0351] This system allows companies and businesses to efficiently find the best collaborators based on their needs and emotional state, and by incorporating an emotion engine, it can improve the user experience and realize more effective collaboration.

[0352] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0353] Step 1:

[0354] The user enters their company information.

[0355] Specific operation: The user accesses a web form using a device and enters information such as the desired action, business situation, market size, etc. While the user is entering information, the emotion engine uses the camera to analyze the user's facial expressions and obtains emotion data in real time.

[0356] Input: User input information (e.g., joint marketing campaign, annual sales of 100 million yen, number of employees: 50, targeting women in their 30s, nationwide deployment)

[0357] Output: User input and emotion data

[0358] Step 2:

[0359] The terminal transmits the input information to the server.

[0360] Specific operation: The device converts the user's input information and emotion data into JSON format and sends it to the server.

[0361] Input: User input and emotion data

[0362] Output: User input information and emotion data in JSON format

[0363] Step 3:

[0364] The server receives and stores the information.

[0365] Specific operation: The server receives the JSON data sent from the device and stores it in a database. It also stores emotion data in the database.

[0366] Input: User input information and emotion data in JSON format

[0367] Output: User input information and emotion data stored in a database

[0368] Step 4:

[0369] Launch the analysis engine to analyze the information.

[0370] Specific operation: The server launches the analysis engine (generative AI model ChatGPT) and analyzes the user's input information. The analysis engine selects the most suitable collaborator from the database based on the prompt text.

[0371] Input: User input stored in the database

[0372] Output: Proposal results from the analysis engine (list of optimal partners)

[0373] Step 5:

[0374] Tailor your suggestions based on sentiment data.

[0375] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the analysis engine's suggestions. For example, if the user is feeling stressed, the suggestions will be simplified.

[0376] Input: Suggestion results from the analysis engine, emotion data

[0377] Output: Adjusted proposal results

[0378] Step 6:

[0379] The adjusted proposal results are presented to the user.

[0380] Specific operation: The server sends the adjusted proposal results to the device, which then displays them to the user. The proposal results include a list of potential collaborators and detailed information.

[0381] Input: Adjusted proposal results

[0382] Output: Proposal results displayed on the user's device (list of potential partners and detailed information)

[0383] Step 7:

[0384] Users select collaborators and provide feedback.

[0385] Specific operation: The user compares the presented list of potential partners and selects the most suitable partner. Then, the user contacts the selected partner. In addition, the user provides feedback on the proposal results to the system.

[0386] Input: Information about the collaborators selected by the user, feedback

[0387] Output: Feedback is registered in the system and used for the next analysis.

[0388] (Application example 2)

[0389] 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."

[0390] Conventional systems used by companies and businesses to find partners do not take user emotions into consideration when making proposals, resulting in a dissatisfied user experience. Furthermore, the accuracy of proposals may not be in line with the user's actual needs, making it difficult to efficiently select partners. Therefore, there is a need for a system that can recognize the user's emotional state in real time and optimize proposal content based on that information.

[0391] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company or business to input its company information, a means for transmitting the input company information to the server, and a means for starting an engine for analyzing the received company information. This makes it possible to recognize the user's emotional state in real time and optimize the content of suggestions based on that.

[0392] "Enterprise or establishment" refers to a legal entity or organization engaged in commercial activities.

[0393] "Company information" refers to information that a company or business has about its business situation, market size, what it wants to do, etc.

[0394] "Input means" refers to the interface that allows users to input their company information into the system.

[0395] "Means of transmission" refers to the communication means or protocol used to send the entered company information to the server.

[0396] An "analysis engine" refers to artificial intelligence or algorithms that select the most suitable partner based on the company's information received.

[0397] "Means of selection" refers to the mechanisms and methods for using an analytical engine to select the most suitable collaborators.

[0398] "Presentation means" refers to an interface or method for displaying the selected collaboration partner information to the user.

[0399] An "emotion engine" refers to technology that recognizes a user's emotional state in real time and optimizes suggestions based on the results.

[0400] "Optimization means" refers to a method for adjusting the content of suggestions based on emotional data obtained from the emotion engine and providing the most appropriate information to the user.

[0401] The present invention relates to a system that recognizes user emotions in real time and optimizes proposals when a company or business is looking for a partner. Specific embodiments for carrying out the present invention will be described below.

[0402] System Configuration

[0403] User Interface and Emotion Engine

[0404] 1. Input form

[0405] The terminal provides an interface for users to input information about their company, such as the type of business they wish to implement (e.g., joint marketing), their business situation (e.g., sales, number of employees), and market size (e.g., customer demographics, area of ​​operation).

[0406] 2. Emotion Engine

[0407] The device works in conjunction with the input form and recognizes the user's emotions in real time based on the camera and input speed. Specifically, it uses OpenCV to analyze facial expressions and obtain the user's emotions.

[0408] Server and Analysis Engine

[0409] 3. Receipt and storage of information

[0410] The device sends the company information entered in JSON format to the server, which temporarily stores the information in a database. Emotion data is also stored at this stage.

[0411] 4. Analysis of Information

[0412] Based on the information stored on the server, analysis is performed using a generative AI model (such as ChatGPT). The analysis engine selects the most suitable collaborators from the database based on the received information.

[0413] 5. Reflecting emotions

[0414] The server then incorporates emotional data into the results obtained by the analysis engine to optimize the content of suggestions. For example, if the user is feeling stressed, the server will simplify the suggestions, and if the user is excited, it will provide more detailed suggestions.

[0415] Information presentation and selection

[0416] 6. Displaying the results

[0417] The server sends the optimized proposal results to the user's device. The device displays the received proposal results to the user. The displayed content includes a list of potential partners and their detailed information (company name, industry, evaluation score).

[0418] 7. Selection of partners

[0419] The user selects the most suitable company from the presented list of potential partners. After the selection, specific business negotiations for collaboration begin. The user also uses the feedback function to evaluate the proposal. This feedback will be used for future analysis.

[0420] Specific examples

[0421] For example, consider a user searching for a specific beauty product. The user enters "beauty," "5,000-15,000 yen," and "emotion boost" into the input form. If the emotion engine detects the user's stress, the system will provide concise and intuitive suggestions. The generative AI model (ChatGPT) will provide suggestions such as:

[0422] "The user is interested in beauty products and is considering a price range of 5,000-15,000 yen. The user is feeling a bit stressed and is looking for a product that will lift their spirits. Please suggest products that fit this criteria."

[0423] In this way, the present invention makes it possible to propose the most suitable partner in accordance with the user's feelings.

[0424] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0425] Step 1:

[0426] The user enters company information (e.g., what they want to do, business situation, market size) using an input form on the device. The entered information is converted to JSON format inside the device. At the same time, the emotion engine analyzes the device's camera and input speed to obtain the user's emotion data. The output is the user's company information and emotion data.

[0427] Step 2:

[0428] The device sends the collected company information and emotion data to a server. The server receives this data and temporarily stores it in a database. Specifically, HTTPS is used as the transmission protocol, and the data is stored in a temporary database (e.g., MySQL). The output is company information and emotion data stored on the server.

[0429] Step 3:

[0430] The server passes the saved company information to the analysis engine. The analysis engine (generative AI model ChatGPT) starts up and selects the most suitable partner based on the input information. The input data (company information) is converted into a prompt statement format and sent to ChatGPT. The output is a list of the most suitable candidate partners.

[0431] Step 4:

[0432] The server receives the analysis results and reflects the emotional data in the emotion engine. The suggestion content is optimized based on the emotional data. For example, if the user is stressed, the list is simplified, and if the user is excited, more detailed information is added. The output is an optimized list of potential collaborators.

[0433] Step 5:

[0434] The server sends the optimized list of potential partners to the terminal. The terminal displays the received list to the user. Specifically, the terminal displays the names of the potential partners' companies, their industries, evaluation scores, etc. through a user interface. The output is a list of potential partners that the user can view.

[0435] Step 6:

[0436] The user reviews the displayed list of potential partners and selects the company that best suits them. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can use the feedback function to evaluate the proposal. The output is feedback on the proposal and the selected partner.

[0437] 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.

[0438] 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 (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.

[0439] 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.

[0440] [Second embodiment]

[0441] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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."

[0453] The present invention provides a system that allows companies and businesses to input their own company information and, based on that information, suggests the most suitable partners for cooperation. A specific embodiment of this system will now be described.

[0454] System Configuration

[0455] User Interface

[0456] 1. Input form

[0457] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[0458] What you want to do (e.g. joint marketing, joint events)

[0459] Business situation (e.g., sales, number of employees)

[0460] Market size (e.g., customer demographics, area of ​​operation)

[0461] Server and Analysis Engine

[0462] 2. Receipt and storage of information

[0463] The terminal sends the entered information to the server, which receives the information and temporarily stores it in a database.

[0464] 3. Analysis of Information

[0465] The server launches an analysis engine to analyze the received information. This analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborators from a database.

[0466] 4. Proposal Generation

[0467] The analysis engine generates multiple candidate partners based on the analysis results, assigns a customized evaluation score to each candidate, and returns the proposed results to the server in structured data format such as JSON.

[0468] Information presentation and selection

[0469] 5. Displaying the results

[0470] The server sends the generated proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0471] 6. Selection of partners

[0472] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0473] Specific examples

[0474] 1. Example of user information entry

[0475] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0476] "What we want to do": Joint marketing campaign

[0477] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0478] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0479] 2. Analyzing the information and generating recommendations

[0480] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0481] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0482] Partner candidate 2: Fitness gym C (rating score: 80)

[0483] Partner candidate 3: Organic food store D (rating score: 78)

[0484] 3. Displaying and selecting results

[0485] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[0486] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0487] The processing flow will be explained below.

[0488] Step 1:

[0489] The user accesses the input form and enters information about their company, including the details of what they want to do, their business situation, and market size, and then clicks the submit button.

[0490] Step 2:

[0491] The device sends the user's input information in JSON format to the server using the HTTPS protocol, which ensures secure data transfer.

[0492] Step 3:

[0493] The server receives the information sent by the user and temporarily stores it in a database. It then checks the integrity of the stored data to make sure there are no omissions or errors.

[0494] Step 4:

[0495] The server starts the analysis engine and passes the stored user information. ChatGPT is used as the analysis engine and sends the data through the API.

[0496] Step 5:

[0497] ChatGPT analyzes the information it receives and extracts the most suitable partners from its database based on the company information provided. The analysis also takes into account past data, industry trends, and complementary relationships.

[0498] Step 6:

[0499] ChatGPT returns the analysis results to the server. The analysis results include multiple collaboration candidates and their respective evaluation scores. The data is returned in structured data format such as JSON.

[0500] Step 7:

[0501] The server receives the analysis results and formats them for presentation to the user. It converts the proposed results into HTML format and sends them to the user's device.

[0502] Step 8:

[0503] The device receives the proposal results and displays them on the user's screen. The display includes a list of potential partners and detailed information about each (company name, industry, and evaluation score).

[0504] Step 9:

[0505] Users can view a list of proposed partners and select the most suitable company. After making a selection, users can contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results.

[0506] This allows users to efficiently select the most suitable partner and build a win-win business relationship.

[0507] Example 1

[0508] 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."

[0509] For companies and businesses to find the best partners based on their own company information requires a great deal of time and effort to organize and analyze the information. Furthermore, conventional systems tend to suggest partners subjectively, lacking in accuracy and objectivity. Therefore, there is a need for a system that can efficiently analyze information and objectively suggest the best partners.

[0510] 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.

[0511] In this invention, the server includes means for temporarily storing the received company information in data storage, means for launching a generative AI model to analyze the stored company information, and means for generating and sending a prompt sentence to the generative AI model to select the most suitable partner, thereby enabling companies and businesses to efficiently and objectively find the most suitable partner based on their needs.

[0512] "Company or establishment" refers to a corporation or sole proprietorship engaged in profit-making activities, and is an organization that provides products or services in the economic context.

[0513] "Company information" refers to specific information held by a company or business, including detailed data such as the type of business the company wants to implement, its business situation, and the size of the market.

[0514] "Information processing device" refers to a computer system or server that has the function of processing, analyzing, and storing data.

[0515] "Data storage" refers to a device or system for storing and managing digital information, including databases and cloud storage.

[0516] A "generative AI model" refers to a program that uses artificial intelligence technology to generate text and analyze data, specifically a solution that uses natural language processing.

[0517] A "prompt" is text data used as input for a generative AI model, and contains questions or instructions for analysis.

[0518] A "structured data format" is a data format that is organized according to a certain format, such as JSON or XML.

[0519] A "user interface" is a screen or operating device that allows a user to directly interact with a system, and includes web browsers and applications.

[0520] "Feedback" refers to the reactions and evaluations from users regarding the system's proposed results, and is information that can be used to improve the system's performance.

[0521] The present invention provides a system in which a company or business inputs its own company information and proposes the most suitable partner based on that information. A specific embodiment of this system will now be described.

[0522] System Configuration

[0523] User Interface

[0524] Input form

[0525] Users use a web form on their device (e.g., a PC or smartphone) to enter their company information. This form includes the following fields:

[0526] What you want to do (e.g. joint marketing, joint events)

[0527] Business situation (e.g., sales, number of employees)

[0528] Market size (e.g., customer demographics, area of ​​operation)

[0529] Server and Analysis Engine

[0530] Receiving and storing information

[0531] The device sends the company information entered by the user to the server, which temporarily stores the received information in a data storage (for example, a MySQL or PostgreSQL database).

[0532] Analysis of information

[0533] The server uses the generative AI model ChatGPT to analyze the stored information, then generates a prompt and calls the ChatGPT API, which includes the information entered by the user and asks a question to suggest the best partner.

[0534] example:

[0535] Company A's information:

[0536] What we want to do: Joint marketing campaigns

[0537] Business situation: Annual sales of 100 million yen, number of employees: 50

[0538] Market size: Products mainly targeted at women in their 30s, nationwide

[0539] Please suggest the best partner.

[0540] Generate proposal results

[0541] The analysis engine (ChatGPT) generates collaboration candidates based on the prompt sentence and assigns an evaluation score to each. The generated proposal results are returned to the server in a structured data format such as JSON.

[0542] Information presentation and selection

[0543] Displaying the results

[0544] The server sends the generated proposal results to the device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0545] Selection of partners

[0546] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0547] Specific examples

[0548] Example of user information entry

[0549] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0550] "What we want to do": Joint marketing campaign

[0551] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0552] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0553] Analyzing information and generating recommendations

[0554] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0555] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0556] Partner candidate 2: Fitness gym C (rating score: 80)

[0557] Partner candidate 3: Organic food store D (rating score: 78)

[0558] Displaying and selecting results

[0559] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. Feedback can also be provided if necessary.

[0560] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0561] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0562] System program processing flow

[0563] Step 1: User enters company information.

[0564] Input: The user opens a web browser on their device, accesses the provided URL, and enters information such as "what they want to do," "business situation," and "market size" into the form.

[0565] What happens: The user enters information into the input fields and clicks the "Submit" button.

[0566] Step 2: The terminal sends the entered data to the server.

[0567] Input: Data entered by the user.

[0568] Output: The data to be sent as an HTTP POST request.

[0569] Specific operation: The device sends the information entered by the user to the server in the form of an HTTP POST request, which contains data in JSON format.

[0570] Step 3: The server receives the data and temporarily stores it in the data storage.

[0571] Input: HTTP POST request from the terminal.

[0572] Output: Information stored in a database.

[0573] Specific operation: The server receives the request and issues an INSERT statement to the database (e.g., MySQL, PostgreSQL) to save the information.

[0574] Step 4: The server launches the generative AI model to generate a prompt sentence.

[0575] Input: Your saved company information.

[0576] Output: The generated prompt statement.

[0577] How it works: The server reads the company's information from the database and generates a prompt based on that information. This prompt is then used as input for the generative AI model.

[0578] Step 5: The server sends the prompt to the generative AI model and receives the analysis result.

[0579] Input: The generated prompt statement.

[0580] Output: Analysis results from the generative AI model.

[0581] Specific operation: The server sends the generated prompt to the generative AI model (ChatGPT) via API. The generative AI model analyzes the prompt, generates collaboration candidates and evaluation scores, and returns them in JSON format.

[0582] Step 6: The server sends the analysis results to the device.

[0583] Input: Analysis results from the generative AI model (JSON format).

[0584] Output: HTTP response containing the parsed results.

[0585] Specific operation: The server receives the analysis results from the generative AI model and returns them to the terminal as an HTTP response, either as is or after processing as necessary.

[0586] Step 7: The terminal receives the result and displays it on the user's screen.

[0587] Input: HTTP response (JSON data) from the server.

[0588] Output: A list of potential collaborators displayed on the user's screen.

[0589] Specific operation: The device analyzes the HTTP response and displays the candidate partners and their detailed information (company name, industry, evaluation score, etc.) on the screen. The user selects a partner based on this information.

[0590] Through these steps, the system enables companies and businesses to input their company information and efficiently suggest the most suitable partners.

[0591] (Application example 1)

[0592] 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."

[0593] Modern companies and businesses face challenges in efficiently finding the best partners to meet their needs. This is especially true when planning new business opportunities or marketing campaigns, as analyzing vast amounts of information to find effective partners is time-consuming. Furthermore, there is a lack of reliability in the results of partner selection and a lack of mechanisms for effectively incorporating user feedback. This creates the problem of wasting a lot of time and money in the process of finding the right business partner.

[0594] 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.

[0595] In this invention, the server includes: a means for a company or business to input its company information; a means for transmitting the input company information to the server; a means for launching an analysis engine to analyze the received company information; a means for selecting the most suitable partner using the analysis engine; a means for presenting the selected partner information to the user; a means for providing a user interface that operates on a smartphone; a means for generating a prompt sentence based on the input information using a generative AI model; and a means for generating a proposal result based on the prompt sentence. This allows companies and businesses to efficiently find the partner that best suits their needs. Furthermore, it is possible to effectively reflect user feedback and improve the accuracy of the proposals.

[0596] "Company or establishment" is a general term for organizations or groups whose purpose is to provide products or services.

[0597] "Company information" refers to internal information provided by a company or business, and includes information such as business conditions, market size, and desired implementation.

[0598] A "server" is a computer system for storing, processing, and distributing data over a network.

[0599] An "analysis engine" is a software component that performs analysis based on input information and generates the necessary results and suggestions.

[0600] "Collaborators" means other companies or establishments with which we collaborate on specific business projects or activities.

[0601] "Users" are the people in charge at companies and offices who use the system to input their company information and receive proposals for collaboration.

[0602] "Presentation" refers to the act of displaying the information generated as a result of the analysis engine in a form visible to the user.

[0603] A "smartphone" is a portable computer device that has a variety of functions, including the ability to make calls, run applications, and connect to the Internet.

[0604] "User interface" refers to the screens and operating means through which a user interacts with a system.

[0605] A "generative AI model" is a type of machine learning model that automates specific tasks by training it with large amounts of data in advance, and in this case refers to ChatGPT.

[0606] A "prompt sentence" is an input sentence given to a generative AI model, and includes instructions for analysis and result generation.

[0607] "Proposal results" are information generated by the analysis engine and include the most suitable collaborators.

[0608] The present invention is a system in which a company or business enters its own company information and proposes the most suitable partner based on that information. Specific embodiments of the present invention will be described below.

[0609] System Configuration

[0610] User Interface

[0611] Users enter their company information through an application installed on their smartphone. This information can include:

[0612] What you want to do (e.g. joint marketing, joint events)

[0613] Business situation (e.g., sales, number of employees)

[0614] Market size (e.g., customer demographics, area of ​​operation)

[0615] The entered information is sent to a server and stored for analysis.

[0616] Server and Analysis Engine

[0617] The server has the following functions:

[0618] 1. Receipt and storage of information

[0619] Receives information entered by the user and temporarily stores it in a database.

[0620] 2. Analysis of Information

[0621] The server starts the generative AI model ChatGPT, generates a prompt based on the received information, and generates a proposal for the collaborating partner based on this prompt.

[0622] 3. Proposal generation

[0623] The proposed results generated by the analysis engine are returned to the server as structured data in JSON format or similar, and then sent back to the user's smartphone.

[0624] Displaying the proposed results

[0625] The user's smartphone displays the proposal results sent from the server, which include potential partners and their detailed information (company name, industry, evaluation score).

[0626] Specific examples

[0627] 1. Example of user information entry

[0628] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0629] What we want to do: Joint marketing campaigns

[0630] Business situation: Annual sales of 100 million yen, number of employees: 50

[0631] Market size: Products mainly targeted at women in their 30s, nationwide

[0632] 2. Analyzing the information and generating recommendations

[0633] The server receives the information and uses ChatGPT to generate a prompt like this:

[0634] Given the following business information:

[0635] Project: Joint Marketing Campaign

[0636] Revenue: 100 million yen

[0637] Employees: 50

[0638] Market: Mainly targeting women in their 30s, national expansion

[0639] Find the best partnership opportunities.

[0640] Based on the analysis results, the following proposed results are generated.

[0641] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[0642] Partner candidate 2: Fitness gym (rating score: 80)

[0643] Partner candidate 3: Organic food store (rating score: 78)

[0644] 3. Displaying and selecting results

[0645] The user receives the proposal results and views the list of candidates displayed on the screen. The user can compare the detailed information and select the most suitable partner.

[0646] Hardware and Software

[0647] Hardware: Server (using Heroku or AWS as cloud services)

[0648] Software: Flask (Python framework), SQLite (database), OpenAI API (generative AI model ChatGPT)

[0649] This allows companies and businesses to efficiently find partners that best suit their needs, maximizing business opportunities. It also effectively incorporates user feedback to improve the accuracy of the system's proposals.

[0650] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0651] Step 1:

[0652] Users launch the smartphone app and enter their company information into the application's input form. This information includes the desired implementation, business situation, market size, etc. This information is then sent to the server.

[0653] Step 2:

[0654] The device sends the company information entered by the user to the server, which temporarily stores the received data in a database (SQLite). During this process, it is confirmed that the input data reaches the server in the correct format.

[0655] Step 3:

[0656] The server calls the generative AI model ChatGPT to analyze the stored data. At this time, it generates and sends a prompt to the analysis engine. This prompt is generated based on the information entered by the user. For example, it might be in the format "Given the following business information: ..."

[0657] Step 4:

[0658] The generative AI model, ChatGPT, generates optimal collaboration proposals based on the prompt text. The server receives these proposals as structured data, such as JSON, and temporarily stores them. These proposals include the name, industry, and evaluation score of each potential collaborator.

[0659] Step 5:

[0660] The server sends the generated proposal results to the user's smartphone. The user can view the received proposal results within the app. The results display screen includes multiple potential partners and their respective details.

[0661] Step 6:

[0662] The user compares the proposals and selects the most suitable partner. During this selection process, the user checks the detailed information of each partner and uses their evaluation score as a reference. The selection results can be sent to the server as feedback.

[0663] Step 7:

[0664] The server receives and stores feedback from users. Analysis of this feedback data can help improve the accuracy of future suggestions. The analysis results are used to improve the system.

[0665] In this way, a system is created in which users can input their company information and efficiently find the best partners. By using generative AI models and prompts, highly accurate suggestions can be made, allowing users to maximize business opportunities.

[0666] 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.

[0667] This invention relates to a system in which a company or business inputs its own company information and, based on that information, proposes optimal partners. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and has the function of optimizing proposal content based on the user's emotions. Specific embodiments of this system are described below.

[0668] System Configuration

[0669] User Interface and Emotion Engine

[0670] 1. Input form

[0671] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[0672] What you want to do (e.g. joint marketing, joint events)

[0673] Business situation (e.g., sales, number of employees)

[0674] Market size (e.g., customer demographics, area of ​​operation)

[0675] 2. Emotion Engine

[0676] The emotion engine works in conjunction with the user interface to recognize the user's emotions in real time while they are typing. Emotion recognition can be achieved by analyzing facial expressions using a camera, or by analyzing the user's typing speed and patterns.

[0677] Server and Analysis Engine

[0678] 3. Receipt and storage of information

[0679] The device sends the user's input information in JSON format to the server. The server receives the information and temporarily stores it in a database. If necessary, emotion data is also stored.

[0680] 4. Analysis of Information

[0681] The server launches an analysis engine to analyze the received information. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborator from the database.

[0682] 5. Reflecting emotions

[0683] The emotion engine reflects the user's emotional data based on the results of the analysis engine and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, or if the user is excited, the suggestions will be more detailed.

[0684] Information presentation and selection

[0685] 6. Displaying the results

[0686] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[0687] 7. Selection of partners

[0688] Users compare the detailed information of the presented candidate partners and select the most suitable company. After making a selection, users contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results, and this feedback will be used for the next analysis.

[0689] Specific examples

[0690] 1. Example of user information entry

[0691] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0692] "What we want to do": Joint marketing campaign

[0693] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0694] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0695] The emotion engine analyzes the user's facial expressions and recognizes that the user is concentrating.

[0696] 2. Analyzing the information and generating recommendations

[0697] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0698] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0699] Partner candidate 2: Fitness gym C (rating score: 80)

[0700] Partner candidate 3: Organic food store D (rating score: 78)

[0701] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[0702] 3. Displaying and selecting results

[0703] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[0704] This system allows companies and businesses to efficiently find partners that best suit their needs. Furthermore, the introduction of an emotion engine optimizes proposals based on the user's emotions, enabling more effective collaboration.

[0705] The processing flow will be explained below.

[0706] Step 1:

[0707] The user accesses the input form and enters their company information. Here, the user enters specific details such as the business situation, market size, etc., and clicks the submit button.

[0708] Step 2:

[0709] The device sends the user's input information in JSON format to the server, using the HTTPS protocol to ensure secure data transfer.

[0710] Step 3:

[0711] The server receives the information sent by the user and temporarily stores it in a database. It then performs a consistency check on the stored data to ensure there are no omissions or errors.

[0712] Step 4:

[0713] Simultaneously with the input process, the device's built-in emotion engine works to recognize the user's emotions in real time, based on facial expression analysis using a camera and analysis of input speed and patterns.

[0714] Step 5:

[0715] The emotion engine sends the user's emotion data to the server, where it is used for analysis along with company information.

[0716] Step 6:

[0717] The server launches the analysis engine and passes the saved user company information and emotion data. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the optimal partner.

[0718] Step 7:

[0719] ChatGPT returns the analysis results to the server, which include multiple potential partners, their evaluation scores, and the proposed solutions.

[0720] Step 8:

[0721] The emotion engine reflects the user's emotional data based on the analysis results and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, and if the user is excited, the suggestions will be more detailed.

[0722] Step 9:

[0723] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The display includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[0724] Step 10:

[0725] The user browses the list of presented partners and selects the most suitable company. After making a selection, the user contacts the selected partner and begins specific collaboration negotiations. The user can also provide feedback on the proposal results, which will be used for the next analysis.

[0726] By introducing this system, companies and businesses will be able to find the most suitable partners more efficiently and in line with the user's feelings, building win-win business relationships.

[0727] Example 2

[0728] 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."

[0729] The process for companies and businesses to find partners that meet their needs is time-consuming, labor-intensive, and inefficient with conventional methods. Furthermore, suggestions made without considering the user's emotional state are unlikely to be optimal. Therefore, there is a need for a system that can efficiently suggest optimal partners based on the user's input and emotional state.

[0730] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0731] In this invention, the server includes means for a company or business to input its company information, means for transmitting the input company information to the server, means for saving the received company information, means for starting an analysis engine, means for selecting an optimal partner based on the information received by the analysis engine, means for recognizing the user's emotions during input in real time, means for adjusting the content of proposals based on the emotion recognition results, and means for presenting the selected partner information to the user. This makes it possible to efficiently propose optimal partners that take into account the user's needs and emotional state.

[0732] "Company or establishment" means a legal entity or organization that conducts commercial activities or business.

[0733] "Company information" refers to data and information about a company or business, including, for example, what the company wants to do, its business situation, and the size of its market.

[0734] "Input means" refers to the interface that allows users to input their company information into the system.

[0735] "Transmission means" is a function for transmitting the entered company information from the user's terminal to the server.

[0736] "Means for storing" refers to the method of storing the received company information in a database or other storage device.

[0737] An "analysis engine" is a program or algorithm that analyzes the company's received information and selects the most suitable partner based on specified criteria.

[0738] "Real-time recognition means" refers to the ability to instantly detect and analyze the user's emotional state while they are typing.

[0739] "Emotion recognition result" is data obtained as a result of analyzing the user's emotional state.

[0740] The "means for adjusting the content of the proposal" is a function for changing and optimizing the content of the proposal based on the emotion recognition results.

[0741] The "presentation means" is a method for displaying information about the ultimately selected collaborator on the user's terminal.

[0742] User Interface and Emotion Engine

[0743] The system provides a web form for users to enter information about their company. In this form, users can enter information such as the business operations they wish to carry out, their business situation, and market size. The system also incorporates an emotion engine that recognizes emotions in real time while users are typing. Emotion recognition is performed by analyzing the user's facial expressions using a camera, as well as by analyzing the typing speed and patterns.

[0744] Server and Analysis Engine

[0745] Once the company information is entered, the device sends this information in JSON format to the server. The server stores the received information in a database. The received information is analyzed using a generative AI model (e.g., ChatGPT) as an analytical engine. The analytical engine then selects the most suitable partner from the database and generates a proposal based on that.

[0746] Reflecting emotions and adjusting proposals

[0747] The emotion engine adjusts the suggestions based on the analysis engine's suggestions and reflects the user's emotional data. For example, if the user is feeling stressed, the suggestion content will be simplified, but if the user is excited, the suggestion will be more detailed.

[0748] Information presentation and selection

[0749] The server sends the final proposal results to the user's device. The device then displays the received proposal results on the user's screen. The displayed content includes a list of potential partners and detailed information about each (company name, industry, and evaluation score). The user compares the presented candidates and selects the most suitable company. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can provide feedback on the proposal results to the system, which will be used for the next analysis.

[0750] Specific examples

[0751] Example of user information entry

[0752] A company wants to run a "co-marketing campaign" and enters the following information:

[0753] What we want to do: Joint marketing campaigns

[0754] Business situation: Annual sales of 100 million yen, number of employees: 50

[0755] Market size: Products aimed primarily at women in their 30s, nationwide distribution

[0756] The emotion engine analyzes the user's facial expression and recognizes that the user is concentrating.

[0757] Analyzing information and generating recommendations

[0758] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0759] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[0760] Partner candidate 2: Fitness gym (rating score: 80)

[0761] Partner candidate 3: Organic food store (rating score: 78)

[0762] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[0763] Displaying and selecting results

[0764] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects the beauty product manufacturer that is the best partner for cooperation. If necessary, the user can also provide feedback.

[0765] Prompt Sentence Examples

[0766] If a company has an annual turnover of 100 million yen, has 50 employees, and sells products aimed at women in their 30s nationwide, please use this information to propose the most suitable partner.

[0767] This system allows companies and businesses to efficiently find the best collaborators based on their needs and emotional state, and by incorporating an emotion engine, it can improve the user experience and realize more effective collaboration.

[0768] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0769] Step 1:

[0770] The user enters their company information.

[0771] Specific operation: The user accesses a web form using a device and enters information such as the desired action, business situation, market size, etc. While the user is entering information, the emotion engine uses the camera to analyze the user's facial expressions and obtains emotion data in real time.

[0772] Input: User input information (e.g., joint marketing campaign, annual sales of 100 million yen, number of employees: 50, targeting women in their 30s, nationwide deployment)

[0773] Output: User input and emotion data

[0774] Step 2:

[0775] The terminal transmits the input information to the server.

[0776] Specific operation: The device converts the user's input information and emotion data into JSON format and sends it to the server.

[0777] Input: User input and emotion data

[0778] Output: User input information and emotion data in JSON format

[0779] Step 3:

[0780] The server receives and stores the information.

[0781] Specific operation: The server receives the JSON data sent from the device and stores it in a database. It also stores emotion data in the database.

[0782] Input: User input information and emotion data in JSON format

[0783] Output: User input information and emotion data stored in a database

[0784] Step 4:

[0785] Launch the analysis engine to analyze the information.

[0786] Specific operation: The server launches the analysis engine (generative AI model ChatGPT) and analyzes the user's input information. The analysis engine selects the most suitable collaborator from the database based on the prompt text.

[0787] Input: User input stored in the database

[0788] Output: Proposal results from the analysis engine (list of optimal partners)

[0789] Step 5:

[0790] Tailor your suggestions based on sentiment data.

[0791] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the analysis engine's suggestions. For example, if the user is feeling stressed, the suggestions will be simplified.

[0792] Input: Suggestion results from the analysis engine, emotion data

[0793] Output: Adjusted proposal results

[0794] Step 6:

[0795] The adjusted proposal results are presented to the user.

[0796] Specific operation: The server sends the adjusted proposal results to the device, which then displays them to the user. The proposal results include a list of potential collaborators and detailed information.

[0797] Input: Adjusted proposal results

[0798] Output: Proposal results displayed on the user's device (list of potential partners and detailed information)

[0799] Step 7:

[0800] Users select collaborators and provide feedback.

[0801] Specific operation: The user compares the presented list of potential partners and selects the most suitable partner. Then, the user contacts the selected partner. In addition, the user provides feedback on the proposal results to the system.

[0802] Input: Information about the collaborators selected by the user, feedback

[0803] Output: Feedback is registered in the system and used for the next analysis.

[0804] (Application example 2)

[0805] 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."

[0806] Conventional systems used by companies and businesses to find partners do not take user emotions into consideration when making proposals, resulting in a dissatisfied user experience. Furthermore, the accuracy of proposals may not be in line with the user's actual needs, making it difficult to efficiently select partners. Therefore, there is a need for a system that can recognize the user's emotional state in real time and optimize proposal content based on that information.

[0807] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company or business to input its company information, a means for transmitting the input company information to the server, and a means for starting an engine for analyzing the received company information. This makes it possible to recognize the user's emotional state in real time and optimize the content of suggestions based on that.

[0808] "Enterprise or establishment" refers to a legal entity or organization engaged in commercial activities.

[0809] "Company information" refers to information that a company or business has about its business situation, market size, what it wants to do, etc.

[0810] "Input means" refers to the interface that allows users to input their company information into the system.

[0811] "Means of transmission" refers to the communication means or protocol used to send the entered company information to the server.

[0812] An "analysis engine" refers to artificial intelligence or algorithms that select the most suitable partner based on the company's information received.

[0813] "Means of selection" refers to the mechanisms and methods for using an analytical engine to select the most suitable collaborators.

[0814] "Presentation means" refers to an interface or method for displaying the selected collaboration partner information to the user.

[0815] An "emotion engine" refers to technology that recognizes a user's emotional state in real time and optimizes suggestions based on the results.

[0816] "Optimization means" refers to a method for adjusting the content of suggestions based on emotional data obtained from the emotion engine and providing the most appropriate information to the user.

[0817] The present invention relates to a system that recognizes user emotions in real time and optimizes proposals when a company or business is looking for a partner. Specific embodiments for carrying out the present invention will be described below.

[0818] System Configuration

[0819] User Interface and Emotion Engine

[0820] 1. Input form

[0821] The terminal provides an interface for users to input information about their company, such as the type of business they wish to implement (e.g., joint marketing), their business situation (e.g., sales, number of employees), and market size (e.g., customer demographics, area of ​​operation).

[0822] 2. Emotion Engine

[0823] The device works in conjunction with the input form and recognizes the user's emotions in real time based on the camera and input speed. Specifically, it uses OpenCV to analyze facial expressions and obtain the user's emotions.

[0824] Server and Analysis Engine

[0825] 3. Receipt and storage of information

[0826] The device sends the company information entered in JSON format to the server, which temporarily stores the information in a database. Emotion data is also stored at this stage.

[0827] 4. Analysis of Information

[0828] Based on the information stored on the server, analysis is performed using a generative AI model (such as ChatGPT). The analysis engine selects the most suitable collaborators from the database based on the received information.

[0829] 5. Reflecting emotions

[0830] The server then incorporates emotional data into the results obtained by the analysis engine to optimize the content of suggestions. For example, if the user is feeling stressed, the server will simplify the suggestions, and if the user is excited, it will provide more detailed suggestions.

[0831] Information presentation and selection

[0832] 6. Displaying the results

[0833] The server sends the optimized proposal results to the user's device. The device displays the received proposal results to the user. The displayed content includes a list of potential partners and their detailed information (company name, industry, evaluation score).

[0834] 7. Selection of partners

[0835] The user selects the most suitable company from the presented list of potential partners. After the selection, specific business negotiations for collaboration begin. The user also uses the feedback function to evaluate the proposal. This feedback will be used for future analysis.

[0836] Specific examples

[0837] For example, consider a user searching for a specific beauty product. The user enters "beauty," "5,000-15,000 yen," and "emotion boost" into the input form. If the emotion engine detects the user's stress, the system will provide concise and intuitive suggestions. The generative AI model (ChatGPT) will provide suggestions such as:

[0838] "The user is interested in beauty products and is considering a price range of 5,000-15,000 yen. The user is feeling a bit stressed and is looking for a product that will lift their spirits. Please suggest products that fit this criteria."

[0839] In this way, the present invention makes it possible to propose the most suitable partner in accordance with the user's feelings.

[0840] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0841] Step 1:

[0842] The user enters company information (e.g., what they want to do, business situation, market size) using an input form on the device. The entered information is converted to JSON format inside the device. At the same time, the emotion engine analyzes the device's camera and input speed to obtain the user's emotion data. The output is the user's company information and emotion data.

[0843] Step 2:

[0844] The device sends the collected company information and emotion data to a server. The server receives this data and temporarily stores it in a database. Specifically, HTTPS is used as the transmission protocol, and the data is stored in a temporary database (e.g., MySQL). The output is company information and emotion data stored on the server.

[0845] Step 3:

[0846] The server passes the saved company information to the analysis engine. The analysis engine (generative AI model ChatGPT) starts up and selects the most suitable partner based on the input information. The input data (company information) is converted into a prompt statement format and sent to ChatGPT. The output is a list of the most suitable candidate partners.

[0847] Step 4:

[0848] The server receives the analysis results and reflects the emotional data in the emotion engine. The suggestion content is optimized based on the emotional data. For example, if the user is stressed, the list is simplified, and if the user is excited, more detailed information is added. The output is an optimized list of potential collaborators.

[0849] Step 5:

[0850] The server sends the optimized list of potential partners to the terminal. The terminal displays the received list to the user. Specifically, the terminal displays the names of the potential partners' companies, their industries, evaluation scores, etc. through a user interface. The output is a list of potential partners that the user can view.

[0851] Step 6:

[0852] The user reviews the displayed list of potential partners and selects the company that best suits them. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can use the feedback function to evaluate the proposal. The output is feedback on the proposal and the selected partner.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] [Third embodiment]

[0857] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0858] 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.

[0859] 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).

[0860] 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.

[0861] 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.

[0862] 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).

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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."

[0869] The present invention provides a system that allows companies and businesses to input their own company information and, based on that information, suggests the most suitable partners for cooperation. A specific embodiment of this system will now be described.

[0870] System Configuration

[0871] User Interface

[0872] 1. Input form

[0873] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[0874] What you want to do (e.g. joint marketing, joint events)

[0875] Business situation (e.g., sales, number of employees)

[0876] Market size (e.g., customer demographics, area of ​​operation)

[0877] Server and Analysis Engine

[0878] 2. Receipt and storage of information

[0879] The terminal sends the entered information to the server, which receives the information and temporarily stores it in a database.

[0880] 3. Analysis of Information

[0881] The server launches an analysis engine to analyze the received information. This analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborators from a database.

[0882] 4. Proposal Generation

[0883] The analysis engine generates multiple candidate partners based on the analysis results, assigns a customized evaluation score to each candidate, and returns the proposed results to the server in structured data format such as JSON.

[0884] Information presentation and selection

[0885] 5. Displaying the results

[0886] The server sends the generated proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0887] 6. Selection of partners

[0888] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0889] Specific examples

[0890] 1. Example of user information entry

[0891] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0892] "What we want to do": Joint marketing campaign

[0893] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0894] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0895] 2. Analyzing the information and generating recommendations

[0896] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0897] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0898] Partner candidate 2: Fitness gym C (rating score: 80)

[0899] Partner candidate 3: Organic food store D (rating score: 78)

[0900] 3. Displaying and selecting results

[0901] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[0902] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0903] The processing flow will be explained below.

[0904] Step 1:

[0905] The user accesses the input form and enters information about their company, including the details of what they want to do, their business situation, and market size, and then clicks the submit button.

[0906] Step 2:

[0907] The device sends the user's input information in JSON format to the server using the HTTPS protocol, which ensures secure data transfer.

[0908] Step 3:

[0909] The server receives the information sent by the user and temporarily stores it in a database. It then checks the integrity of the stored data to make sure there are no omissions or errors.

[0910] Step 4:

[0911] The server starts the analysis engine and passes the stored user information. ChatGPT is used as the analysis engine and sends the data through the API.

[0912] Step 5:

[0913] ChatGPT analyzes the information it receives and extracts the most suitable partners from its database based on the company information provided. The analysis also takes into account past data, industry trends, and complementary relationships.

[0914] Step 6:

[0915] ChatGPT returns the analysis results to the server. The analysis results include multiple collaboration candidates and their respective evaluation scores. The data is returned in structured data format such as JSON.

[0916] Step 7:

[0917] The server receives the analysis results and formats them for presentation to the user. It converts the proposed results into HTML format and sends them to the user's device.

[0918] Step 8:

[0919] The device receives the proposal results and displays them on the user's screen. The display includes a list of potential partners and detailed information about each (company name, industry, and evaluation score).

[0920] Step 9:

[0921] Users can view a list of proposed partners and select the most suitable company. After making a selection, users can contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results.

[0922] This allows users to efficiently select the most suitable partner and build a win-win business relationship.

[0923] Example 1

[0924] 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."

[0925] For companies and businesses to find the best partners based on their own company information requires a great deal of time and effort to organize and analyze the information. Furthermore, conventional systems tend to suggest partners subjectively, lacking in accuracy and objectivity. Therefore, there is a need for a system that can efficiently analyze information and objectively suggest the best partners.

[0926] 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.

[0927] In this invention, the server includes means for temporarily storing the received company information in data storage, means for launching a generative AI model to analyze the stored company information, and means for generating and sending a prompt sentence to the generative AI model to select the most suitable partner, thereby enabling companies and businesses to efficiently and objectively find the most suitable partner based on their needs.

[0928] "Company or establishment" refers to a corporation or sole proprietorship engaged in profit-making activities, and is an organization that provides products or services in the economic context.

[0929] "Company information" refers to specific information held by a company or business, including detailed data such as the type of business the company wants to implement, its business situation, and the size of the market.

[0930] "Information processing device" refers to a computer system or server that has the function of processing, analyzing, and storing data.

[0931] "Data storage" refers to a device or system for storing and managing digital information, including databases and cloud storage.

[0932] A "generative AI model" refers to a program that uses artificial intelligence technology to generate text and analyze data, specifically a solution that uses natural language processing.

[0933] A "prompt" is text data used as input for a generative AI model, and contains questions or instructions for analysis.

[0934] A "structured data format" is a data format that is organized according to a certain format, such as JSON or XML.

[0935] A "user interface" is a screen or operating device that allows a user to directly interact with a system, and includes web browsers and applications.

[0936] "Feedback" refers to the reactions and evaluations from users regarding the system's proposed results, and is information that can be used to improve the system's performance.

[0937] The present invention provides a system in which a company or business inputs its own company information and proposes the most suitable partner based on that information. A specific embodiment of this system will now be described.

[0938] System Configuration

[0939] User Interface

[0940] Input form

[0941] Users use a web form on their device (e.g., a PC or smartphone) to enter their company information. This form includes the following fields:

[0942] What you want to do (e.g. joint marketing, joint events)

[0943] Business situation (e.g., sales, number of employees)

[0944] Market size (e.g., customer demographics, area of ​​operation)

[0945] Server and Analysis Engine

[0946] Receiving and storing information

[0947] The device sends the company information entered by the user to the server, which temporarily stores the received information in a data storage (for example, a MySQL or PostgreSQL database).

[0948] Analysis of information

[0949] The server uses the generative AI model ChatGPT to analyze the stored information, then generates a prompt and calls the ChatGPT API, which includes the information entered by the user and asks a question to suggest the best partner.

[0950] example:

[0951] Company A's information:

[0952] What we want to do: Joint marketing campaigns

[0953] Business situation: Annual sales of 100 million yen, number of employees: 50

[0954] Market size: Products mainly targeted at women in their 30s, nationwide

[0955] Please suggest the best partner.

[0956] Generate proposal results

[0957] The analysis engine (ChatGPT) generates collaboration candidates based on the prompt sentence and assigns an evaluation score to each. The generated proposal results are returned to the server in a structured data format such as JSON.

[0958] Information presentation and selection

[0959] Displaying the results

[0960] The server sends the generated proposal results to the device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[0961] Selection of partners

[0962] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[0963] Specific examples

[0964] Example of user information entry

[0965] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[0966] "What we want to do": Joint marketing campaign

[0967] "Business situation": Annual sales of 100 million yen, number of employees: 50

[0968] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[0969] Analyzing information and generating recommendations

[0970] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[0971] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[0972] Partner candidate 2: Fitness gym C (rating score: 80)

[0973] Partner candidate 3: Organic food store D (rating score: 78)

[0974] Displaying and selecting results

[0975] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. Feedback can also be provided if necessary.

[0976] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[0977] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0978] System program processing flow

[0979] Step 1: User enters company information.

[0980] Input: The user opens a web browser on their device, accesses the provided URL, and enters information such as "what they want to do," "business situation," and "market size" into the form.

[0981] What happens: The user enters information into the input fields and clicks the "Submit" button.

[0982] Step 2: The terminal sends the entered data to the server.

[0983] Input: Data entered by the user.

[0984] Output: The data to be sent as an HTTP POST request.

[0985] Specific operation: The device sends the information entered by the user to the server in the form of an HTTP POST request, which contains data in JSON format.

[0986] Step 3: The server receives the data and temporarily stores it in the data storage.

[0987] Input: HTTP POST request from the terminal.

[0988] Output: Information stored in a database.

[0989] Specific operation: The server receives the request and issues an INSERT statement to the database (e.g., MySQL, PostgreSQL) to save the information.

[0990] Step 4: The server launches the generative AI model to generate a prompt sentence.

[0991] Input: Your saved company information.

[0992] Output: The generated prompt statement.

[0993] How it works: The server reads the company's information from the database and generates a prompt based on that information. This prompt is then used as input for the generative AI model.

[0994] Step 5: The server sends the prompt to the generative AI model and receives the analysis result.

[0995] Input: The generated prompt statement.

[0996] Output: Analysis results from the generative AI model.

[0997] Specific operation: The server sends the generated prompt to the generative AI model (ChatGPT) via API. The generative AI model analyzes the prompt, generates collaboration candidates and evaluation scores, and returns them in JSON format.

[0998] Step 6: The server sends the analysis results to the device.

[0999] Input: Analysis results from the generative AI model (JSON format).

[1000] Output: HTTP response containing the parsed results.

[1001] Specific operation: The server receives the analysis results from the generative AI model and returns them to the terminal as an HTTP response, either as is or after processing as necessary.

[1002] Step 7: The terminal receives the result and displays it on the user's screen.

[1003] Input: HTTP response (JSON data) from the server.

[1004] Output: A list of potential collaborators displayed on the user's screen.

[1005] Specific operation: The device analyzes the HTTP response and displays the candidate partners and their detailed information (company name, industry, evaluation score, etc.) on the screen. The user selects a partner based on this information.

[1006] Through these steps, the system enables companies and businesses to input their company information and efficiently suggest the most suitable partners.

[1007] (Application example 1)

[1008] 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."

[1009] Modern companies and businesses face challenges in efficiently finding the best partners to meet their needs. This is especially true when planning new business opportunities or marketing campaigns, as analyzing vast amounts of information to find effective partners is time-consuming. Furthermore, there is a lack of reliability in the results of partner selection and a lack of mechanisms for effectively incorporating user feedback. This creates the problem of wasting a lot of time and money in the process of finding the right business partner.

[1010] 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.

[1011] In this invention, the server includes: a means for a company or business to input its company information; a means for transmitting the input company information to the server; a means for launching an analysis engine to analyze the received company information; a means for selecting the most suitable partner using the analysis engine; a means for presenting the selected partner information to the user; a means for providing a user interface that operates on a smartphone; a means for generating a prompt sentence based on the input information using a generative AI model; and a means for generating a proposal result based on the prompt sentence. This allows companies and businesses to efficiently find the partner that best suits their needs. Furthermore, it is possible to effectively reflect user feedback and improve the accuracy of the proposals.

[1012] "Company or establishment" is a general term for organizations or groups whose purpose is to provide products or services.

[1013] "Company information" refers to internal information provided by a company or business, and includes information such as business conditions, market size, and desired implementation.

[1014] A "server" is a computer system for storing, processing, and distributing data over a network.

[1015] An "analysis engine" is a software component that performs analysis based on input information and generates the necessary results and suggestions.

[1016] "Collaborators" means other companies or establishments with which we collaborate on specific business projects or activities.

[1017] "Users" are the people in charge at companies and offices who use the system to input their company information and receive proposals for collaboration.

[1018] "Presentation" refers to the act of displaying the information generated as a result of the analysis engine in a form visible to the user.

[1019] A "smartphone" is a portable computer device that has a variety of functions, including the ability to make calls, run applications, and connect to the Internet.

[1020] "User interface" refers to the screens and operating means through which a user interacts with a system.

[1021] A "generative AI model" is a type of machine learning model that automates specific tasks by training it with large amounts of data in advance, and in this case refers to ChatGPT.

[1022] A "prompt sentence" is an input sentence given to a generative AI model, and includes instructions for analysis and result generation.

[1023] "Proposal results" are information generated by the analysis engine and include the most suitable collaborators.

[1024] The present invention is a system in which a company or business enters its own company information and proposes the most suitable partner based on that information. Specific embodiments of the present invention will be described below.

[1025] System Configuration

[1026] User Interface

[1027] Users enter their company information through an application installed on their smartphone. This information can include:

[1028] What you want to do (e.g. joint marketing, joint events)

[1029] Business situation (e.g., sales, number of employees)

[1030] Market size (e.g., customer demographics, area of ​​operation)

[1031] The entered information is sent to a server and stored for analysis.

[1032] Server and Analysis Engine

[1033] The server has the following functions:

[1034] 1. Receipt and storage of information

[1035] Receives information entered by the user and temporarily stores it in a database.

[1036] 2. Analysis of Information

[1037] The server starts the generative AI model ChatGPT, generates a prompt based on the received information, and generates a proposal for the collaborating partner based on this prompt.

[1038] 3. Proposal generation

[1039] The proposed results generated by the analysis engine are returned to the server as structured data in JSON format or similar, and then sent back to the user's smartphone.

[1040] Displaying the proposed results

[1041] The user's smartphone displays the proposal results sent from the server, which include potential partners and their detailed information (company name, industry, evaluation score).

[1042] Specific examples

[1043] 1. Example of user information entry

[1044] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1045] What we want to do: Joint marketing campaigns

[1046] Business situation: Annual sales of 100 million yen, number of employees: 50

[1047] Market size: Products mainly targeted at women in their 30s, nationwide

[1048] 2. Analyzing the information and generating recommendations

[1049] The server receives the information and uses ChatGPT to generate a prompt like this:

[1050] Given the following business information:

[1051] Project: Joint Marketing Campaign

[1052] Revenue: 100 million yen

[1053] Employees: 50

[1054] Market: Mainly targeting women in their 30s, national expansion

[1055] Find the best partnership opportunities.

[1056] Based on the analysis results, the following proposed results are generated.

[1057] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[1058] Partner candidate 2: Fitness gym (rating score: 80)

[1059] Partner candidate 3: Organic food store (rating score: 78)

[1060] 3. Displaying and selecting results

[1061] The user receives the proposal results and views the list of candidates displayed on the screen. The user can compare the detailed information and select the most suitable partner.

[1062] Hardware and Software

[1063] Hardware: Server (using Heroku or AWS as cloud services)

[1064] Software: Flask (Python framework), SQLite (database), OpenAI API (generative AI model ChatGPT)

[1065] This allows companies and businesses to efficiently find partners that best suit their needs, maximizing business opportunities. It also effectively incorporates user feedback to improve the accuracy of the system's proposals.

[1066] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1067] Step 1:

[1068] Users launch the smartphone app and enter their company information into the application's input form. This information includes the desired implementation, business situation, market size, etc. This information is then sent to the server.

[1069] Step 2:

[1070] The device sends the company information entered by the user to the server, which temporarily stores the received data in a database (SQLite). During this process, it is confirmed that the input data reaches the server in the correct format.

[1071] Step 3:

[1072] The server calls the generative AI model ChatGPT to analyze the stored data. At this time, it generates and sends a prompt to the analysis engine. This prompt is generated based on the information entered by the user. For example, it might be in the format "Given the following business information: ..."

[1073] Step 4:

[1074] The generative AI model, ChatGPT, generates optimal collaboration proposals based on the prompt text. The server receives these proposals as structured data, such as JSON, and temporarily stores them. These proposals include the name, industry, and evaluation score of each potential collaborator.

[1075] Step 5:

[1076] The server sends the generated proposal results to the user's smartphone. The user can view the received proposal results within the app. The results display screen includes multiple potential partners and their respective details.

[1077] Step 6:

[1078] The user compares the proposals and selects the most suitable partner. During this selection process, the user checks the detailed information of each partner and uses their evaluation score as a reference. The selection results can be sent to the server as feedback.

[1079] Step 7:

[1080] The server receives and stores feedback from users. Analysis of this feedback data can help improve the accuracy of future suggestions. The analysis results are used to improve the system.

[1081] In this way, a system is created in which users can input their company information and efficiently find the best partners. By using generative AI models and prompts, highly accurate suggestions can be made, allowing users to maximize business opportunities.

[1082] 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.

[1083] This invention relates to a system in which a company or business inputs its own company information and, based on that information, proposes optimal partners. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and has the function of optimizing proposal content based on the user's emotions. Specific embodiments of this system are described below.

[1084] System Configuration

[1085] User Interface and Emotion Engine

[1086] 1. Input form

[1087] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[1088] What you want to do (e.g. joint marketing, joint events)

[1089] Business situation (e.g., sales, number of employees)

[1090] Market size (e.g., customer demographics, area of ​​operation)

[1091] 2. Emotion Engine

[1092] The emotion engine works in conjunction with the user interface to recognize the user's emotions in real time while they are typing. Emotion recognition can be achieved by analyzing facial expressions using a camera, or by analyzing the user's typing speed and patterns.

[1093] Server and Analysis Engine

[1094] 3. Receipt and storage of information

[1095] The device sends the user's input information in JSON format to the server. The server receives the information and temporarily stores it in a database. If necessary, emotion data is also stored.

[1096] 4. Analysis of Information

[1097] The server launches an analysis engine to analyze the received information. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborator from the database.

[1098] 5. Reflecting emotions

[1099] The emotion engine reflects the user's emotional data based on the results of the analysis engine and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, or if the user is excited, the suggestions will be more detailed.

[1100] Information presentation and selection

[1101] 6. Displaying the results

[1102] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[1103] 7. Selection of partners

[1104] Users compare the detailed information of the presented candidate partners and select the most suitable company. After making a selection, users contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results, and this feedback will be used for the next analysis.

[1105] Specific examples

[1106] 1. Example of user information entry

[1107] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1108] "What we want to do": Joint marketing campaign

[1109] "Business situation": Annual sales of 100 million yen, number of employees: 50

[1110] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[1111] The emotion engine analyzes the user's facial expressions and recognizes that the user is concentrating.

[1112] 2. Analyzing the information and generating recommendations

[1113] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1114] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[1115] Partner candidate 2: Fitness gym C (rating score: 80)

[1116] Partner candidate 3: Organic food store D (rating score: 78)

[1117] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[1118] 3. Displaying and selecting results

[1119] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[1120] This system allows companies and businesses to efficiently find partners that best suit their needs. Furthermore, the introduction of an emotion engine optimizes proposals based on the user's emotions, enabling more effective collaboration.

[1121] The processing flow will be explained below.

[1122] Step 1:

[1123] The user accesses the input form and enters their company information. Here, the user enters specific details such as the business situation, market size, etc., and clicks the submit button.

[1124] Step 2:

[1125] The device sends the user's input information in JSON format to the server, using the HTTPS protocol to ensure secure data transfer.

[1126] Step 3:

[1127] The server receives the information sent by the user and temporarily stores it in a database. It then performs a consistency check on the stored data to ensure there are no omissions or errors.

[1128] Step 4:

[1129] Simultaneously with the input process, the device's built-in emotion engine works to recognize the user's emotions in real time, based on facial expression analysis using a camera and analysis of input speed and patterns.

[1130] Step 5:

[1131] The emotion engine sends the user's emotion data to the server, where it is used for analysis along with company information.

[1132] Step 6:

[1133] The server launches the analysis engine and passes the saved user company information and emotion data. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the optimal partner.

[1134] Step 7:

[1135] ChatGPT returns the analysis results to the server, which include multiple potential partners, their evaluation scores, and the proposed solutions.

[1136] Step 8:

[1137] The emotion engine reflects the user's emotional data based on the analysis results and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, and if the user is excited, the suggestions will be more detailed.

[1138] Step 9:

[1139] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The display includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[1140] Step 10:

[1141] The user browses the list of presented partners and selects the most suitable company. After making a selection, the user contacts the selected partner and begins specific collaboration negotiations. The user can also provide feedback on the proposal results, which will be used for the next analysis.

[1142] By introducing this system, companies and businesses will be able to find the most suitable partners more efficiently and in line with the user's feelings, building win-win business relationships.

[1143] Example 2

[1144] 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."

[1145] The process for companies and businesses to find partners that meet their needs is time-consuming, labor-intensive, and inefficient with conventional methods. Furthermore, suggestions made without considering the user's emotional state are unlikely to be optimal. Therefore, there is a need for a system that can efficiently suggest optimal partners based on the user's input and emotional state.

[1146] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1147] In this invention, the server includes means for a company or business to input its company information, means for transmitting the input company information to the server, means for saving the received company information, means for starting an analysis engine, means for selecting an optimal partner based on the information received by the analysis engine, means for recognizing the user's emotions during input in real time, means for adjusting the content of proposals based on the emotion recognition results, and means for presenting the selected partner information to the user. This makes it possible to efficiently propose optimal partners that take into account the user's needs and emotional state.

[1148] "Company or establishment" means a legal entity or organization that conducts commercial activities or business.

[1149] "Company information" refers to data and information about a company or business, including, for example, what the company wants to do, its business situation, and the size of its market.

[1150] "Input means" refers to the interface that allows users to input their company information into the system.

[1151] "Transmission means" is a function for transmitting the entered company information from the user's terminal to the server.

[1152] "Means for storing" refers to the method of storing the received company information in a database or other storage device.

[1153] An "analysis engine" is a program or algorithm that analyzes the company's received information and selects the most suitable partner based on specified criteria.

[1154] "Real-time recognition means" refers to the ability to instantly detect and analyze the user's emotional state while they are typing.

[1155] "Emotion recognition result" is data obtained as a result of analyzing the user's emotional state.

[1156] The "means for adjusting the content of the proposal" is a function for changing and optimizing the content of the proposal based on the emotion recognition results.

[1157] The "presentation means" is a method for displaying information about the ultimately selected collaborator on the user's terminal.

[1158] User Interface and Emotion Engine

[1159] The system provides a web form for users to enter information about their company. In this form, users can enter information such as the business operations they wish to carry out, their business situation, and market size. The system also incorporates an emotion engine that recognizes emotions in real time while users are typing. Emotion recognition is performed by analyzing the user's facial expressions using a camera, as well as by analyzing the typing speed and patterns.

[1160] Server and Analysis Engine

[1161] Once the company information is entered, the device sends this information in JSON format to the server. The server stores the received information in a database. The received information is analyzed using a generative AI model (e.g., ChatGPT) as an analytical engine. The analytical engine then selects the most suitable partner from the database and generates a proposal based on that.

[1162] Reflecting emotions and adjusting proposals

[1163] The emotion engine adjusts the suggestions based on the analysis engine's suggestions and reflects the user's emotional data. For example, if the user is feeling stressed, the suggestion content will be simplified, but if the user is excited, the suggestion will be more detailed.

[1164] Information presentation and selection

[1165] The server sends the final proposal results to the user's device. The device then displays the received proposal results on the user's screen. The displayed content includes a list of potential partners and detailed information about each (company name, industry, and evaluation score). The user compares the presented candidates and selects the most suitable company. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can provide feedback on the proposal results to the system, which will be used for the next analysis.

[1166] Specific examples

[1167] Example of user information entry

[1168] A company wants to run a "co-marketing campaign" and enters the following information:

[1169] What we want to do: Joint marketing campaigns

[1170] Business situation: Annual sales of 100 million yen, number of employees: 50

[1171] Market size: Products aimed primarily at women in their 30s, nationwide distribution

[1172] The emotion engine analyzes the user's facial expression and recognizes that the user is concentrating.

[1173] Analyzing information and generating recommendations

[1174] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1175] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[1176] Partner candidate 2: Fitness gym (rating score: 80)

[1177] Partner candidate 3: Organic food store (rating score: 78)

[1178] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[1179] Displaying and selecting results

[1180] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects the beauty product manufacturer that is the best partner for cooperation. If necessary, the user can also provide feedback.

[1181] Prompt Sentence Examples

[1182] If a company has an annual turnover of 100 million yen, has 50 employees, and sells products aimed at women in their 30s nationwide, please use this information to propose the most suitable partner.

[1183] This system allows companies and businesses to efficiently find the best collaborators based on their needs and emotional state, and by incorporating an emotion engine, it can improve the user experience and realize more effective collaboration.

[1184] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1185] Step 1:

[1186] The user enters their company information.

[1187] Specific operation: The user accesses a web form using a device and enters information such as the desired action, business situation, market size, etc. While the user is entering information, the emotion engine uses the camera to analyze the user's facial expressions and obtains emotion data in real time.

[1188] Input: User input information (e.g., joint marketing campaign, annual sales of 100 million yen, number of employees: 50, targeting women in their 30s, nationwide deployment)

[1189] Output: User input and emotion data

[1190] Step 2:

[1191] The terminal transmits the input information to the server.

[1192] Specific operation: The device converts the user's input information and emotion data into JSON format and sends it to the server.

[1193] Input: User input and emotion data

[1194] Output: User input information and emotion data in JSON format

[1195] Step 3:

[1196] The server receives and stores the information.

[1197] Specific operation: The server receives the JSON data sent from the device and stores it in a database. It also stores emotion data in the database.

[1198] Input: User input information and emotion data in JSON format

[1199] Output: User input information and emotion data stored in a database

[1200] Step 4:

[1201] Launch the analysis engine to analyze the information.

[1202] Specific operation: The server launches the analysis engine (generative AI model ChatGPT) and analyzes the user's input information. The analysis engine selects the most suitable collaborator from the database based on the prompt text.

[1203] Input: User input stored in the database

[1204] Output: Proposal results from the analysis engine (list of optimal partners)

[1205] Step 5:

[1206] Tailor your suggestions based on sentiment data.

[1207] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the analysis engine's suggestions. For example, if the user is feeling stressed, the suggestions will be simplified.

[1208] Input: Suggestion results from the analysis engine, emotion data

[1209] Output: Adjusted proposal results

[1210] Step 6:

[1211] The adjusted proposal results are presented to the user.

[1212] Specific operation: The server sends the adjusted proposal results to the device, which then displays them to the user. The proposal results include a list of potential collaborators and detailed information.

[1213] Input: Adjusted proposal results

[1214] Output: Proposal results displayed on the user's device (list of potential partners and detailed information)

[1215] Step 7:

[1216] Users select collaborators and provide feedback.

[1217] Specific operation: The user compares the presented list of potential partners and selects the most suitable partner. Then, the user contacts the selected partner. In addition, the user provides feedback on the proposal results to the system.

[1218] Input: Information about the collaborators selected by the user, feedback

[1219] Output: Feedback is registered in the system and used for the next analysis.

[1220] (Application example 2)

[1221] 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."

[1222] Conventional systems used by companies and businesses to find partners do not take user emotions into consideration when making proposals, resulting in a dissatisfied user experience. Furthermore, the accuracy of proposals may not be in line with the user's actual needs, making it difficult to efficiently select partners. Therefore, there is a need for a system that can recognize the user's emotional state in real time and optimize proposal content based on that information.

[1223] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company or business to input its company information, a means for transmitting the input company information to the server, and a means for starting an engine for analyzing the received company information. This makes it possible to recognize the user's emotional state in real time and optimize the content of suggestions based on that.

[1224] "Enterprise or establishment" refers to a legal entity or organization engaged in commercial activities.

[1225] "Company information" refers to information that a company or business has about its business situation, market size, what it wants to do, etc.

[1226] "Input means" refers to the interface that allows users to input their company information into the system.

[1227] "Means of transmission" refers to the communication means or protocol used to send the entered company information to the server.

[1228] An "analysis engine" refers to artificial intelligence or algorithms that select the most suitable partner based on the company's information received.

[1229] "Means of selection" refers to the mechanisms and methods for using an analytical engine to select the most suitable collaborators.

[1230] "Presentation means" refers to an interface or method for displaying the selected collaboration partner information to the user.

[1231] An "emotion engine" refers to technology that recognizes a user's emotional state in real time and optimizes suggestions based on the results.

[1232] "Optimization means" refers to a method for adjusting the content of suggestions based on emotional data obtained from the emotion engine and providing the most appropriate information to the user.

[1233] The present invention relates to a system that recognizes user emotions in real time and optimizes proposals when a company or business is looking for a partner. Specific embodiments for carrying out the present invention will be described below.

[1234] System Configuration

[1235] User Interface and Emotion Engine

[1236] 1. Input form

[1237] The terminal provides an interface for users to input information about their company, such as the type of business they wish to implement (e.g., joint marketing), their business situation (e.g., sales, number of employees), and market size (e.g., customer demographics, area of ​​operation).

[1238] 2. Emotion Engine

[1239] The device works in conjunction with the input form and recognizes the user's emotions in real time based on the camera and input speed. Specifically, it uses OpenCV to analyze facial expressions and obtain the user's emotions.

[1240] Server and Analysis Engine

[1241] 3. Receipt and storage of information

[1242] The device sends the company information entered in JSON format to the server, which temporarily stores the information in a database. Emotion data is also stored at this stage.

[1243] 4. Analysis of Information

[1244] Based on the information stored on the server, analysis is performed using a generative AI model (such as ChatGPT). The analysis engine selects the most suitable collaborators from the database based on the received information.

[1245] 5. Reflecting emotions

[1246] The server then incorporates emotional data into the results obtained by the analysis engine to optimize the content of suggestions. For example, if the user is feeling stressed, the server will simplify the suggestions, and if the user is excited, it will provide more detailed suggestions.

[1247] Information presentation and selection

[1248] 6. Displaying the results

[1249] The server sends the optimized proposal results to the user's device. The device displays the received proposal results to the user. The displayed content includes a list of potential partners and their detailed information (company name, industry, evaluation score).

[1250] 7. Selection of partners

[1251] The user selects the most suitable company from the presented list of potential partners. After the selection, specific business negotiations for collaboration begin. The user also uses the feedback function to evaluate the proposal. This feedback will be used for future analysis.

[1252] Specific examples

[1253] For example, consider a user searching for a specific beauty product. The user enters "beauty," "5,000-15,000 yen," and "emotion boost" into the input form. If the emotion engine detects the user's stress, the system will provide concise and intuitive suggestions. The generative AI model (ChatGPT) will provide suggestions such as:

[1254] "The user is interested in beauty products and is considering a price range of 5,000-15,000 yen. The user is feeling a bit stressed and is looking for a product that will lift their spirits. Please suggest products that fit this criteria."

[1255] In this way, the present invention makes it possible to propose the most suitable partner in accordance with the user's feelings.

[1256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1257] Step 1:

[1258] The user enters company information (e.g., what they want to do, business situation, market size) using an input form on the device. The entered information is converted to JSON format inside the device. At the same time, the emotion engine analyzes the device's camera and input speed to obtain the user's emotion data. The output is the user's company information and emotion data.

[1259] Step 2:

[1260] The device sends the collected company information and emotion data to a server. The server receives this data and temporarily stores it in a database. Specifically, HTTPS is used as the transmission protocol, and the data is stored in a temporary database (e.g., MySQL). The output is company information and emotion data stored on the server.

[1261] Step 3:

[1262] The server passes the saved company information to the analysis engine. The analysis engine (generative AI model ChatGPT) starts up and selects the most suitable partner based on the input information. The input data (company information) is converted into a prompt statement format and sent to ChatGPT. The output is a list of the most suitable candidate partners.

[1263] Step 4:

[1264] The server receives the analysis results and reflects the emotional data in the emotion engine. The suggestion content is optimized based on the emotional data. For example, if the user is stressed, the list is simplified, and if the user is excited, more detailed information is added. The output is an optimized list of potential collaborators.

[1265] Step 5:

[1266] The server sends the optimized list of potential partners to the terminal. The terminal displays the received list to the user. Specifically, the terminal displays the names of the potential partners' companies, their industries, evaluation scores, etc. through a user interface. The output is a list of potential partners that the user can view.

[1267] Step 6:

[1268] The user reviews the displayed list of potential partners and selects the company that best suits them. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can use the feedback function to evaluate the proposal. The output is feedback on the proposal and the selected partner.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] [Fourth embodiment]

[1273] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1274] 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.

[1275] 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).

[1276] 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.

[1277] 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.

[1278] 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).

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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.

[1284] 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.

[1285] 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."

[1286] The present invention provides a system that allows companies and businesses to input their own company information and, based on that information, suggests the most suitable partners for cooperation. A specific embodiment of this system will now be described.

[1287] System Configuration

[1288] User Interface

[1289] 1. Input form

[1290] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[1291] What you want to do (e.g. joint marketing, joint events)

[1292] Business situation (e.g., sales, number of employees)

[1293] Market size (e.g., customer demographics, area of ​​operation)

[1294] Server and Analysis Engine

[1295] 2. Receipt and storage of information

[1296] The terminal sends the entered information to the server, which receives the information and temporarily stores it in a database.

[1297] 3. Analysis of Information

[1298] The server launches an analysis engine to analyze the received information. This analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborators from a database.

[1299] 4. Proposal Generation

[1300] The analysis engine generates multiple candidate partners based on the analysis results, assigns a customized evaluation score to each candidate, and returns the proposed results to the server in structured data format such as JSON.

[1301] Information presentation and selection

[1302] 5. Displaying the results

[1303] The server sends the generated proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[1304] 6. Selection of partners

[1305] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[1306] Specific examples

[1307] 1. Example of user information entry

[1308] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1309] "What we want to do": Joint marketing campaign

[1310] "Business situation": Annual sales of 100 million yen, number of employees: 50

[1311] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[1312] 2. Analyzing the information and generating recommendations

[1313] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1314] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[1315] Partner candidate 2: Fitness gym C (rating score: 80)

[1316] Partner candidate 3: Organic food store D (rating score: 78)

[1317] 3. Displaying and selecting results

[1318] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[1319] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[1320] The processing flow will be explained below.

[1321] Step 1:

[1322] The user accesses the input form and enters information about their company, including the details of what they want to do, their business situation, and market size, and then clicks the submit button.

[1323] Step 2:

[1324] The device sends the user's input information in JSON format to the server using the HTTPS protocol, which ensures secure data transfer.

[1325] Step 3:

[1326] The server receives the information sent by the user and temporarily stores it in a database. It then checks the integrity of the stored data to make sure there are no omissions or errors.

[1327] Step 4:

[1328] The server starts the analysis engine and passes the stored user information. ChatGPT is used as the analysis engine and sends the data through the API.

[1329] Step 5:

[1330] ChatGPT analyzes the information it receives and extracts the most suitable partners from its database based on the company information provided. The analysis also takes into account past data, industry trends, and complementary relationships.

[1331] Step 6:

[1332] ChatGPT returns the analysis results to the server. The analysis results include multiple collaboration candidates and their respective evaluation scores. The data is returned in structured data format such as JSON.

[1333] Step 7:

[1334] The server receives the analysis results and formats them for presentation to the user. It converts the proposed results into HTML format and sends them to the user's device.

[1335] Step 8:

[1336] The device receives the proposal results and displays them on the user's screen. The display includes a list of potential partners and detailed information about each (company name, industry, and evaluation score).

[1337] Step 9:

[1338] Users can view a list of proposed partners and select the most suitable company. After making a selection, users can contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results.

[1339] This allows users to efficiently select the most suitable partner and build a win-win business relationship.

[1340] Example 1

[1341] 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."

[1342] For companies and businesses to find the best partners based on their own company information requires a great deal of time and effort to organize and analyze the information. Furthermore, conventional systems tend to suggest partners subjectively, lacking in accuracy and objectivity. Therefore, there is a need for a system that can efficiently analyze information and objectively suggest the best partners.

[1343] 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.

[1344] In this invention, the server includes means for temporarily storing the received company information in data storage, means for launching a generative AI model to analyze the stored company information, and means for generating and sending a prompt sentence to the generative AI model to select the most suitable partner, thereby enabling companies and businesses to efficiently and objectively find the most suitable partner based on their needs.

[1345] "Company or establishment" refers to a corporation or sole proprietorship engaged in profit-making activities, and is an organization that provides products or services in the economic context.

[1346] "Company information" refers to specific information held by a company or business, including detailed data such as the type of business the company wants to implement, its business situation, and the size of the market.

[1347] "Information processing device" refers to a computer system or server that has the function of processing, analyzing, and storing data.

[1348] "Data storage" refers to a device or system for storing and managing digital information, including databases and cloud storage.

[1349] A "generative AI model" refers to a program that uses artificial intelligence technology to generate text and analyze data, specifically a solution that uses natural language processing.

[1350] A "prompt" is text data used as input for a generative AI model, and contains questions or instructions for analysis.

[1351] A "structured data format" is a data format that is organized according to a certain format, such as JSON or XML.

[1352] A "user interface" is a screen or operating device that allows a user to directly interact with a system, and includes web browsers and applications.

[1353] "Feedback" refers to the reactions and evaluations from users regarding the system's proposed results, and is information that can be used to improve the system's performance.

[1354] The present invention provides a system in which a company or business inputs its own company information and proposes the most suitable partner based on that information. A specific embodiment of this system will now be described.

[1355] System Configuration

[1356] User Interface

[1357] Input form

[1358] Users use a web form on their device (e.g., a PC or smartphone) to enter their company information. This form includes the following fields:

[1359] What you want to do (e.g. joint marketing, joint events)

[1360] Business situation (e.g., sales, number of employees)

[1361] Market size (e.g., customer demographics, area of ​​operation)

[1362] Server and Analysis Engine

[1363] Receiving and storing information

[1364] The device sends the company information entered by the user to the server, which temporarily stores the received information in a data storage (for example, a MySQL or PostgreSQL database).

[1365] Analysis of information

[1366] The server uses the generative AI model ChatGPT to analyze the stored information, then generates a prompt and calls the ChatGPT API, which includes the information entered by the user and asks a question to suggest the best partner.

[1367] example:

[1368] Company A's information:

[1369] What we want to do: Joint marketing campaigns

[1370] Business situation: Annual sales of 100 million yen, number of employees: 50

[1371] Market size: Products mainly targeted at women in their 30s, nationwide

[1372] Please suggest the best partner.

[1373] Generate proposal results

[1374] The analysis engine (ChatGPT) generates collaboration candidates based on the prompt sentence and assigns an evaluation score to each. The generated proposal results are returned to the server in a structured data format such as JSON.

[1375] Information presentation and selection

[1376] Displaying the results

[1377] The server sends the generated proposal results to the device, which then displays the received results on the user's screen. The displayed content includes multiple potential partners and their detailed information (e.g., company name, industry, and evaluation score for mutual complementarity).

[1378] Selection of partners

[1379] Users can compare the detailed information of the presented potential partners and select the most suitable company. They can also provide feedback during the selection process to improve the system's accuracy.

[1380] Specific examples

[1381] Example of user information entry

[1382] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1383] "What we want to do": Joint marketing campaign

[1384] "Business situation": Annual sales of 100 million yen, number of employees: 50

[1385] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[1386] Analyzing information and generating recommendations

[1387] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1388] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[1389] Partner candidate 2: Fitness gym C (rating score: 80)

[1390] Partner candidate 3: Organic food store D (rating score: 78)

[1391] Displaying and selecting results

[1392] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. Feedback can also be provided if necessary.

[1393] This system allows companies and businesses to efficiently find partners that best suit their needs, making it possible to maximize business opportunities such as mutual customer referrals and joint events.

[1394] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1395] System program processing flow

[1396] Step 1: User enters company information.

[1397] Input: The user opens a web browser on their device, accesses the provided URL, and enters information such as "what they want to do," "business situation," and "market size" into the form.

[1398] What happens: The user enters information into the input fields and clicks the "Submit" button.

[1399] Step 2: The terminal sends the entered data to the server.

[1400] Input: Data entered by the user.

[1401] Output: The data to be sent as an HTTP POST request.

[1402] Specific operation: The device sends the information entered by the user to the server in the form of an HTTP POST request, which contains data in JSON format.

[1403] Step 3: The server receives the data and temporarily stores it in the data storage.

[1404] Input: HTTP POST request from the terminal.

[1405] Output: Information stored in a database.

[1406] Specific operation: The server receives the request and issues an INSERT statement to the database (e.g., MySQL, PostgreSQL) to save the information.

[1407] Step 4: The server launches the generative AI model to generate a prompt sentence.

[1408] Input: Your saved company information.

[1409] Output: The generated prompt statement.

[1410] How it works: The server reads the company's information from the database and generates a prompt based on that information. This prompt is then used as input for the generative AI model.

[1411] Step 5: The server sends the prompt to the generative AI model and receives the analysis result.

[1412] Input: The generated prompt statement.

[1413] Output: Analysis results from the generative AI model.

[1414] Specific operation: The server sends the generated prompt to the generative AI model (ChatGPT) via API. The generative AI model analyzes the prompt, generates collaboration candidates and evaluation scores, and returns them in JSON format.

[1415] Step 6: The server sends the analysis results to the device.

[1416] Input: Analysis results from the generative AI model (JSON format).

[1417] Output: HTTP response containing the parsed results.

[1418] Specific operation: The server receives the analysis results from the generative AI model and returns them to the terminal as an HTTP response, either as is or after processing as necessary.

[1419] Step 7: The terminal receives the result and displays it on the user's screen.

[1420] Input: HTTP response (JSON data) from the server.

[1421] Output: A list of potential collaborators displayed on the user's screen.

[1422] Specific operation: The device analyzes the HTTP response and displays the candidate partners and their detailed information (company name, industry, evaluation score, etc.) on the screen. The user selects a partner based on this information.

[1423] Through these steps, the system enables companies and businesses to input their company information and efficiently suggest the most suitable partners.

[1424] (Application example 1)

[1425] 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."

[1426] Modern companies and businesses face challenges in efficiently finding the best partners to meet their needs. This is especially true when planning new business opportunities or marketing campaigns, as analyzing vast amounts of information to find effective partners is time-consuming. Furthermore, there is a lack of reliability in the results of partner selection and a lack of mechanisms for effectively incorporating user feedback. This creates the problem of wasting a lot of time and money in the process of finding the right business partner.

[1427] 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.

[1428] In this invention, the server includes: a means for a company or business to input its company information; a means for transmitting the input company information to the server; a means for launching an analysis engine to analyze the received company information; a means for selecting the most suitable partner using the analysis engine; a means for presenting the selected partner information to the user; a means for providing a user interface that operates on a smartphone; a means for generating a prompt sentence based on the input information using a generative AI model; and a means for generating a proposal result based on the prompt sentence. This allows companies and businesses to efficiently find the partner that best suits their needs. Furthermore, it is possible to effectively reflect user feedback and improve the accuracy of the proposals.

[1429] "Company or establishment" is a general term for organizations or groups whose purpose is to provide products or services.

[1430] "Company information" refers to internal information provided by a company or business, and includes information such as business conditions, market size, and desired implementation.

[1431] A "server" is a computer system for storing, processing, and distributing data over a network.

[1432] An "analysis engine" is a software component that performs analysis based on input information and generates the necessary results and suggestions.

[1433] "Collaborators" means other companies or establishments with which we collaborate on specific business projects or activities.

[1434] "Users" are the people in charge at companies and offices who use the system to input their company information and receive proposals for collaboration.

[1435] "Presentation" refers to the act of displaying the information generated as a result of the analysis engine in a form visible to the user.

[1436] A "smartphone" is a portable computer device that has a variety of functions, including the ability to make calls, run applications, and connect to the Internet.

[1437] "User interface" refers to the screens and operating means through which a user interacts with a system.

[1438] A "generative AI model" is a type of machine learning model that automates specific tasks by training it with large amounts of data in advance, and in this case refers to ChatGPT.

[1439] A "prompt sentence" is an input sentence given to a generative AI model, and includes instructions for analysis and result generation.

[1440] "Proposal results" are information generated by the analysis engine and include the most suitable collaborators.

[1441] The present invention is a system in which a company or business enters its own company information and proposes the most suitable partner based on that information. Specific embodiments of the present invention will be described below.

[1442] System Configuration

[1443] User Interface

[1444] Users enter their company information through an application installed on their smartphone. This information can include:

[1445] What you want to do (e.g. joint marketing, joint events)

[1446] Business situation (e.g., sales, number of employees)

[1447] Market size (e.g., customer demographics, area of ​​operation)

[1448] The entered information is sent to a server and stored for analysis.

[1449] Server and Analysis Engine

[1450] The server has the following functions:

[1451] 1. Receipt and storage of information

[1452] Receives information entered by the user and temporarily stores it in a database.

[1453] 2. Analysis of Information

[1454] The server starts the generative AI model ChatGPT, generates a prompt based on the received information, and generates a proposal for the collaborating partner based on this prompt.

[1455] 3. Proposal generation

[1456] The proposed results generated by the analysis engine are returned to the server as structured data in JSON format or similar, and then sent back to the user's smartphone.

[1457] Displaying the proposed results

[1458] The user's smartphone displays the proposal results sent from the server, which include potential partners and their detailed information (company name, industry, evaluation score).

[1459] Specific examples

[1460] 1. Example of user information entry

[1461] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1462] What we want to do: Joint marketing campaigns

[1463] Business situation: Annual sales of 100 million yen, number of employees: 50

[1464] Market size: Products mainly targeted at women in their 30s, nationwide

[1465] 2. Analyzing the information and generating recommendations

[1466] The server receives the information and uses ChatGPT to generate a prompt like this:

[1467] Given the following business information:

[1468] Project: Joint Marketing Campaign

[1469] Revenue: 100 million yen

[1470] Employees: 50

[1471] Market: Mainly targeting women in their 30s, national expansion

[1472] Find the best partnership opportunities.

[1473] Based on the analysis results, the following proposed results are generated.

[1474] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[1475] Partner candidate 2: Fitness gym (rating score: 80)

[1476] Partner candidate 3: Organic food store (rating score: 78)

[1477] 3. Displaying and selecting results

[1478] The user receives the proposal results and views the list of candidates displayed on the screen. The user can compare the detailed information and select the most suitable partner.

[1479] Hardware and Software

[1480] Hardware: Server (using Heroku or AWS as cloud services)

[1481] Software: Flask (Python framework), SQLite (database), OpenAI API (generative AI model ChatGPT)

[1482] This allows companies and businesses to efficiently find partners that best suit their needs, maximizing business opportunities. It also effectively incorporates user feedback to improve the accuracy of the system's proposals.

[1483] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1484] Step 1:

[1485] Users launch the smartphone app and enter their company information into the application's input form. This information includes the desired implementation, business situation, market size, etc. This information is then sent to the server.

[1486] Step 2:

[1487] The device sends the company information entered by the user to the server, which temporarily stores the received data in a database (SQLite). During this process, it is confirmed that the input data reaches the server in the correct format.

[1488] Step 3:

[1489] The server calls the generative AI model ChatGPT to analyze the stored data. At this time, it generates and sends a prompt to the analysis engine. This prompt is generated based on the information entered by the user. For example, it might be in the format "Given the following business information: ..."

[1490] Step 4:

[1491] The generative AI model, ChatGPT, generates optimal collaboration proposals based on the prompt text. The server receives these proposals as structured data, such as JSON, and temporarily stores them. These proposals include the name, industry, and evaluation score of each potential collaborator.

[1492] Step 5:

[1493] The server sends the generated proposal results to the user's smartphone. The user can view the received proposal results within the app. The results display screen includes multiple potential partners and their respective details.

[1494] Step 6:

[1495] The user compares the proposals and selects the most suitable partner. During this selection process, the user checks the detailed information of each partner and uses their evaluation score as a reference. The selection results can be sent to the server as feedback.

[1496] Step 7:

[1497] The server receives and stores feedback from users. Analysis of this feedback data can help improve the accuracy of future suggestions. The analysis results are used to improve the system.

[1498] In this way, a system is created in which users can input their company information and efficiently find the best partners. By using generative AI models and prompts, highly accurate suggestions can be made, allowing users to maximize business opportunities.

[1499] 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.

[1500] This invention relates to a system in which a company or business inputs its own company information and, based on that information, proposes optimal partners. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and has the function of optimizing proposal content based on the user's emotions. Specific embodiments of this system are described below.

[1501] System Configuration

[1502] User Interface and Emotion Engine

[1503] 1. Input form

[1504] A web form is provided for users to enter their company information. Here, users (persons in charge of companies or offices) enter the following items:

[1505] What you want to do (e.g. joint marketing, joint events)

[1506] Business situation (e.g., sales, number of employees)

[1507] Market size (e.g., customer demographics, area of ​​operation)

[1508] 2. Emotion Engine

[1509] The emotion engine works in conjunction with the user interface to recognize the user's emotions in real time while they are typing. Emotion recognition can be achieved by analyzing facial expressions using a camera, or by analyzing the user's typing speed and patterns.

[1510] Server and Analysis Engine

[1511] 3. Receipt and storage of information

[1512] The device sends the user's input information in JSON format to the server. The server receives the information and temporarily stores it in a database. If necessary, emotion data is also stored.

[1513] 4. Analysis of Information

[1514] The server launches an analysis engine to analyze the received information. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the most suitable collaborator from the database.

[1515] 5. Reflecting emotions

[1516] The emotion engine reflects the user's emotional data based on the results of the analysis engine and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, or if the user is excited, the suggestions will be more detailed.

[1517] Information presentation and selection

[1518] 6. Displaying the results

[1519] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The displayed content includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[1520] 7. Selection of partners

[1521] Users compare the detailed information of the presented candidate partners and select the most suitable company. After making a selection, users contact the selected partner and begin specific collaboration negotiations. Users can also use the feedback function to provide their opinions and evaluations of the proposal results, and this feedback will be used for the next analysis.

[1522] Specific examples

[1523] 1. Example of user information entry

[1524] Company A wants to conduct a "joint marketing campaign" and enters the following information:

[1525] "What we want to do": Joint marketing campaign

[1526] "Business situation": Annual sales of 100 million yen, number of employees: 50

[1527] Market size: Products primarily aimed at women in their 30s, nationwide distribution

[1528] The emotion engine analyzes the user's facial expressions and recognizes that the user is concentrating.

[1529] 2. Analyzing the information and generating recommendations

[1530] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1531] Partner candidate 1: Beauty product manufacturer B (rating score: 85)

[1532] Partner candidate 2: Fitness gym C (rating score: 80)

[1533] Partner candidate 3: Organic food store D (rating score: 78)

[1534] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[1535] 3. Displaying and selecting results

[1536] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects beauty product manufacturer B as the most suitable partner. If necessary, the user can also provide feedback.

[1537] This system allows companies and businesses to efficiently find partners that best suit their needs. Furthermore, the introduction of an emotion engine optimizes proposals based on the user's emotions, enabling more effective collaboration.

[1538] The processing flow will be explained below.

[1539] Step 1:

[1540] The user accesses the input form and enters their company information. Here, the user enters specific details such as the business situation, market size, etc., and clicks the submit button.

[1541] Step 2:

[1542] The device sends the user's input information in JSON format to the server, using the HTTPS protocol to ensure secure data transfer.

[1543] Step 3:

[1544] The server receives the information sent by the user and temporarily stores it in a database. It then performs a consistency check on the stored data to ensure there are no omissions or errors.

[1545] Step 4:

[1546] Simultaneously with the input process, the device's built-in emotion engine works to recognize the user's emotions in real time, based on facial expression analysis using a camera and analysis of input speed and patterns.

[1547] Step 5:

[1548] The emotion engine sends the user's emotion data to the server, where it is used for analysis along with company information.

[1549] Step 6:

[1550] The server launches the analysis engine and passes the saved user company information and emotion data. The analysis engine uses the generative AI model ChatGPT. Based on the received information, the analysis engine selects the optimal partner.

[1551] Step 7:

[1552] ChatGPT returns the analysis results to the server, which include multiple potential partners, their evaluation scores, and the proposed solutions.

[1553] Step 8:

[1554] The emotion engine reflects the user's emotional data based on the analysis results and adjusts the suggestions. For example, if the user is feeling stressed, the suggestions will be simplified, and if the user is excited, the suggestions will be more detailed.

[1555] Step 9:

[1556] The server sends the final proposal results to the user's device, which then displays the received results on the user's screen. The display includes a list of potential partners and their detailed information (company name, industry, and evaluation score).

[1557] Step 10:

[1558] The user browses the list of presented partners and selects the most suitable company. After making a selection, the user contacts the selected partner and begins specific collaboration negotiations. The user can also provide feedback on the proposal results, which will be used for the next analysis.

[1559] By introducing this system, companies and businesses will be able to find the most suitable partners more efficiently and in line with the user's feelings, building win-win business relationships.

[1560] Example 2

[1561] 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."

[1562] The process for companies and businesses to find partners that meet their needs is time-consuming, labor-intensive, and inefficient with conventional methods. Furthermore, suggestions made without considering the user's emotional state are unlikely to be optimal. Therefore, there is a need for a system that can efficiently suggest optimal partners based on the user's input and emotional state.

[1563] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1564] In this invention, the server includes means for a company or business to input its company information, means for transmitting the input company information to the server, means for saving the received company information, means for starting an analysis engine, means for selecting an optimal partner based on the information received by the analysis engine, means for recognizing the user's emotions during input in real time, means for adjusting the content of proposals based on the emotion recognition results, and means for presenting the selected partner information to the user. This makes it possible to efficiently propose optimal partners that take into account the user's needs and emotional state.

[1565] "Company or establishment" means a legal entity or organization that conducts commercial activities or business.

[1566] "Company information" refers to data and information about a company or business, including, for example, what the company wants to do, its business situation, and the size of its market.

[1567] "Input means" refers to the interface that allows users to input their company information into the system.

[1568] "Transmission means" is a function for transmitting the entered company information from the user's terminal to the server.

[1569] "Means for storing" refers to the method of storing the received company information in a database or other storage device.

[1570] An "analysis engine" is a program or algorithm that analyzes the company's received information and selects the most suitable partner based on specified criteria.

[1571] "Real-time recognition means" refers to the ability to instantly detect and analyze the user's emotional state while they are typing.

[1572] "Emotion recognition result" is data obtained as a result of analyzing the user's emotional state.

[1573] The "means for adjusting the content of the proposal" is a function for changing and optimizing the content of the proposal based on the emotion recognition results.

[1574] The "presentation means" is a method for displaying information about the ultimately selected collaborator on the user's terminal.

[1575] User Interface and Emotion Engine

[1576] The system provides a web form for users to enter information about their company. In this form, users can enter information such as the business operations they wish to carry out, their business situation, and market size. The system also incorporates an emotion engine that recognizes emotions in real time while users are typing. Emotion recognition is performed by analyzing the user's facial expressions using a camera, as well as by analyzing the typing speed and patterns.

[1577] Server and Analysis Engine

[1578] Once the company information is entered, the device sends this information in JSON format to the server. The server stores the received information in a database. The received information is analyzed using a generative AI model (e.g., ChatGPT) as an analytical engine. The analytical engine then selects the most suitable partner from the database and generates a proposal based on that.

[1579] Reflecting emotions and adjusting proposals

[1580] The emotion engine adjusts the suggestions based on the analysis engine's suggestions and reflects the user's emotional data. For example, if the user is feeling stressed, the suggestion content will be simplified, but if the user is excited, the suggestion will be more detailed.

[1581] Information presentation and selection

[1582] The server sends the final proposal results to the user's device. The device then displays the received proposal results on the user's screen. The displayed content includes a list of potential partners and detailed information about each (company name, industry, and evaluation score). The user compares the presented candidates and selects the most suitable company. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can provide feedback on the proposal results to the system, which will be used for the next analysis.

[1583] Specific examples

[1584] Example of user information entry

[1585] A company wants to run a "co-marketing campaign" and enters the following information:

[1586] What we want to do: Joint marketing campaigns

[1587] Business situation: Annual sales of 100 million yen, number of employees: 50

[1588] Market size: Products aimed primarily at women in their 30s, nationwide distribution

[1589] The emotion engine analyzes the user's facial expression and recognizes that the user is concentrating.

[1590] Analyzing information and generating recommendations

[1591] The server receives the information and analyzes it using ChatGPT. Based on the analysis results, the following proposals are generated:

[1592] Partner candidate 1: Beauty product manufacturer (rating score: 85)

[1593] Partner candidate 2: Fitness gym (rating score: 80)

[1594] Partner candidate 3: Organic food store (rating score: 78)

[1595] The emotion engine reflects the user's high level of concentration and displays suggestion results with detailed information.

[1596] Displaying and selecting results

[1597] The user receives the proposal results and views the list of candidates displayed on the screen. The user compares the detailed information and selects the beauty product manufacturer that is the best partner for cooperation. If necessary, the user can also provide feedback.

[1598] Prompt Sentence Examples

[1599] If a company has an annual turnover of 100 million yen, has 50 employees, and sells products aimed at women in their 30s nationwide, please use this information to propose the most suitable partner.

[1600] This system allows companies and businesses to efficiently find the best collaborators based on their needs and emotional state, and by incorporating an emotion engine, it can improve the user experience and realize more effective collaboration.

[1601] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1602] Step 1:

[1603] The user enters their company information.

[1604] Specific operation: The user accesses a web form using a device and enters information such as the desired action, business situation, market size, etc. While the user is entering information, the emotion engine uses the camera to analyze the user's facial expressions and obtains emotion data in real time.

[1605] Input: User input information (e.g., joint marketing campaign, annual sales of 100 million yen, number of employees: 50, targeting women in their 30s, nationwide deployment)

[1606] Output: User input and emotion data

[1607] Step 2:

[1608] The terminal transmits the input information to the server.

[1609] Specific operation: The device converts the user's input information and emotion data into JSON format and sends it to the server.

[1610] Input: User input and emotion data

[1611] Output: User input information and emotion data in JSON format

[1612] Step 3:

[1613] The server receives and stores the information.

[1614] Specific operation: The server receives the JSON data sent from the device and stores it in a database. It also stores emotion data in the database.

[1615] Input: User input information and emotion data in JSON format

[1616] Output: User input information and emotion data stored in a database

[1617] Step 4:

[1618] Launch the analysis engine to analyze the information.

[1619] Specific operation: The server launches the analysis engine (generative AI model ChatGPT) and analyzes the user's input information. The analysis engine selects the most suitable collaborator from the database based on the prompt text.

[1620] Input: User input stored in the database

[1621] Output: Proposal results from the analysis engine (list of optimal partners)

[1622] Step 5:

[1623] Tailor your suggestions based on sentiment data.

[1624] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the analysis engine's suggestions. For example, if the user is feeling stressed, the suggestions will be simplified.

[1625] Input: Suggestion results from the analysis engine, emotion data

[1626] Output: Adjusted proposal results

[1627] Step 6:

[1628] The adjusted proposal results are presented to the user.

[1629] Specific operation: The server sends the adjusted proposal results to the device, which then displays them to the user. The proposal results include a list of potential collaborators and detailed information.

[1630] Input: Adjusted proposal results

[1631] Output: Proposal results displayed on the user's device (list of potential partners and detailed information)

[1632] Step 7:

[1633] Users select collaborators and provide feedback.

[1634] Specific operation: The user compares the presented list of potential partners and selects the most suitable partner. Then, the user contacts the selected partner. In addition, the user provides feedback on the proposal results to the system.

[1635] Input: Information about the collaborators selected by the user, feedback

[1636] Output: Feedback is registered in the system and used for the next analysis.

[1637] (Application example 2)

[1638] 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."

[1639] Conventional systems used by companies and businesses to find partners do not take user emotions into consideration when making proposals, resulting in a dissatisfied user experience. Furthermore, the accuracy of proposals may not be in line with the user's actual needs, making it difficult to efficiently select partners. Therefore, there is a need for a system that can recognize the user's emotional state in real time and optimize proposal content based on that information.

[1640] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company or business to input its company information, a means for transmitting the input company information to the server, and a means for starting an engine for analyzing the received company information. This makes it possible to recognize the user's emotional state in real time and optimize the content of suggestions based on that.

[1641] "Enterprise or establishment" refers to a legal entity or organization engaged in commercial activities.

[1642] "Company information" refers to information that a company or business has about its business situation, market size, what it wants to do, etc.

[1643] "Input means" refers to the interface that allows users to input their company information into the system.

[1644] "Means of transmission" refers to the communication means or protocol used to send the entered company information to the server.

[1645] An "analysis engine" refers to artificial intelligence or algorithms that select the most suitable partner based on the company's information received.

[1646] "Means of selection" refers to the mechanisms and methods for using an analytical engine to select the most suitable collaborators.

[1647] "Presentation means" refers to an interface or method for displaying the selected collaboration partner information to the user.

[1648] An "emotion engine" refers to technology that recognizes a user's emotional state in real time and optimizes suggestions based on the results.

[1649] "Optimization means" refers to a method for adjusting the content of suggestions based on emotional data obtained from the emotion engine and providing the most appropriate information to the user.

[1650] The present invention relates to a system that recognizes user emotions in real time and optimizes proposals when a company or business is looking for a partner. Specific embodiments for carrying out the present invention will be described below.

[1651] System Configuration

[1652] User Interface and Emotion Engine

[1653] 1. Input form

[1654] The terminal provides an interface for users to input information about their company, such as the type of business they wish to implement (e.g., joint marketing), their business situation (e.g., sales, number of employees), and market size (e.g., customer demographics, area of ​​operation).

[1655] 2. Emotion Engine

[1656] The device works in conjunction with the input form and recognizes the user's emotions in real time based on the camera and input speed. Specifically, it uses OpenCV to analyze facial expressions and obtain the user's emotions.

[1657] Server and Analysis Engine

[1658] 3. Receipt and storage of information

[1659] The device sends the company information entered in JSON format to the server, which temporarily stores the information in a database. Emotion data is also stored at this stage.

[1660] 4. Analysis of Information

[1661] Based on the information stored on the server, analysis is performed using a generative AI model (such as ChatGPT). The analysis engine selects the most suitable collaborators from the database based on the received information.

[1662] 5. Reflecting emotions

[1663] The server then incorporates emotional data into the results obtained by the analysis engine to optimize the content of suggestions. For example, if the user is feeling stressed, the server will simplify the suggestions, and if the user is excited, it will provide more detailed suggestions.

[1664] Information presentation and selection

[1665] 6. Displaying the results

[1666] The server sends the optimized proposal results to the user's device. The device displays the received proposal results to the user. The displayed content includes a list of potential partners and their detailed information (company name, industry, evaluation score).

[1667] 7. Selection of partners

[1668] The user selects the most suitable company from the presented list of potential partners. After the selection, specific business negotiations for collaboration begin. The user also uses the feedback function to evaluate the proposal. This feedback will be used for future analysis.

[1669] Specific examples

[1670] For example, consider a user searching for a specific beauty product. The user enters "beauty," "5,000-15,000 yen," and "emotion boost" into the input form. If the emotion engine detects the user's stress, the system will provide concise and intuitive suggestions. The generative AI model (ChatGPT) will provide suggestions such as:

[1671] "The user is interested in beauty products and is considering a price range of 5,000-15,000 yen. The user is feeling a bit stressed and is looking for a product that will lift their spirits. Please suggest products that fit this criteria."

[1672] In this way, the present invention makes it possible to propose the most suitable partner in accordance with the user's feelings.

[1673] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1674] Step 1:

[1675] The user enters company information (e.g., what they want to do, business situation, market size) using an input form on the device. The entered information is converted to JSON format inside the device. At the same time, the emotion engine analyzes the device's camera and input speed to obtain the user's emotion data. The output is the user's company information and emotion data.

[1676] Step 2:

[1677] The device sends the collected company information and emotion data to a server. The server receives this data and temporarily stores it in a database. Specifically, HTTPS is used as the transmission protocol, and the data is stored in a temporary database (e.g., MySQL). The output is company information and emotion data stored on the server.

[1678] Step 3:

[1679] The server passes the saved company information to the analysis engine. The analysis engine (generative AI model ChatGPT) starts up and selects the most suitable partner based on the input information. The input data (company information) is converted into a prompt statement format and sent to ChatGPT. The output is a list of the most suitable candidate partners.

[1680] Step 4:

[1681] The server receives the analysis results and reflects the emotional data in the emotion engine. The suggestion content is optimized based on the emotional data. For example, if the user is stressed, the list is simplified, and if the user is excited, more detailed information is added. The output is an optimized list of potential collaborators.

[1682] Step 5:

[1683] The server sends the optimized list of potential partners to the terminal. The terminal displays the received list to the user. Specifically, the terminal displays the names of the potential partners' companies, their industries, evaluation scores, etc. through a user interface. The output is a list of potential partners that the user can view.

[1684] Step 6:

[1685] The user reviews the displayed list of potential partners and selects the company that best suits them. After making a selection, the user contacts the selected partner and begins collaboration negotiations. In addition, the user can use the feedback function to evaluate the proposal. The output is feedback on the proposal and the selected partner.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] 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.

[1691] 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.

[1692] 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).

[1693] 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.

[1694] 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."

[1695] 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.

[1696] 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).

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] 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.

[1703] 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.

[1704] 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.

[1705] 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.

[1706] 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.

[1707] The following is further disclosed regarding the above embodiment.

[1708] (Claim 1)

[1709] A means for companies and businesses to enter their company information,

[1710] A means for transmitting the input company information to a server;

[1711] A means for launching an engine for analyzing the received company information;

[1712] A means to select the most suitable partner using an analysis engine,

[1713] a means for presenting information about the selected collaborators to a user;

[1714] A system including:

[1715] (Claim 2)

[1716] 10. The system of claim 1, further comprising means for a user to evaluate and select the presented collaboration information.

[1717] (Claim 3)

[1718] 10. The system of claim 1, further comprising means for the user to provide feedback on the proposed collaborator information.

[1719] "Example 1"

[1720] (Claim 1)

[1721] A means for companies and businesses to enter their company information,

[1722] means for transmitting the input company information to the information processing device;

[1723] A means for temporarily storing the received company information in data storage;

[1724] A means to launch a generative AI model to analyze the stored company information; and

[1725] A means for generating prompt sentences and sending them to the generative AI model to select the optimal collaborator;

[1726] A means for returning information about the selected collaborators in a structured data format;

[1727] means for displaying the returned partner information on a user interface;

[1728] A system including:

[1729] (Claim 2)

[1730] 2. The system according to claim 1, further comprising means for allowing a user to evaluate and select the presented collaboration information.

[1731] (Claim 3)

[1732] 10. The system of claim 1, further comprising means for users to provide feedback on the proposed collaboration information.

[1733] "Application Example 1"

[1734] (Claim 1)

[1735] A means for companies and businesses to enter their company information,

[1736] A means for transmitting the input company information to a server;

[1737] A means for launching an analysis engine for analyzing the received company information;

[1738] A means to select the most suitable partner using an analysis engine,

[1739] a means for presenting information about the selected collaborators to a user;

[1740] A means for providing a user interface that operates on a smartphone;

[1741] a means for generating a prompt sentence based on input information using a generative AI model;

[1742] means for generating a suggestion result based on the prompt sentence;

[1743] A system including:

[1744] (Claim 2)

[1745] 10. The system of claim 1, further comprising means for a user to evaluate and select the presented collaboration information.

[1746] (Claim 3)

[1747] 10. The system of claim 1, further comprising means for the user to provide feedback on the proposed collaborator information.

[1748] "Example 2: Combining Emotion Engines"

[1749] (Claim 1)

[1750] A means for companies and businesses to enter their company information,

[1751] A means for transmitting the input company information to a server;

[1752] A means for storing the received company information;

[1753] a means for launching the analysis engine;

[1754] A means for selecting the most suitable partner based on the information received by the analysis engine;

[1755] A means for recognizing the user's emotions in real time while inputting;

[1756] a means for adjusting the content of the suggestions based on the emotion recognition results;

[1757] a means for presenting information about the selected collaborators to a user;

[1758] A system including:

[1759] (Claim 2)

[1760] 10. The system of claim 1, further comprising means for a user to evaluate and select the presented collaboration information.

[1761] (Claim 3)

[1762] 10. The system of claim 1, further comprising means for the user to provide feedback on the proposed collaborator information.

[1763] "Application example 2 when combining emotion engines"

[1764] (Claim 1)

[1765] A means for companies and businesses to enter their company information,

[1766] A means for transmitting the input company information to a server;

[1767] A means for launching an engine for analyzing the received company information;

[1768] A means to select the most suitable partner using an analysis engine,

[1769] a means for presenting information about the selected collaborators to a user;

[1770] A means for optimizing the content of suggestions using an emotion engine that recognizes user emotions in real time;

[1771] A system including:

[1772] (Claim 2)

[1773] 10. The system of claim 1, further comprising means for a user to evaluate and select the presented collaboration information.

[1774] (Claim 3)

[1775] 10. The system of claim 1, further comprising means for the user to provide feedback on the proposed collaborator information. [Explanation of symbols]

[1776] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for companies and businesses to enter their company information, A means for transmitting the input company information to a server; A means for launching an engine for analyzing the received company information; A means to select the most suitable partner using an analysis engine, a means for presenting information about the selected collaborators to a user; A system including:

2. 2. The system according to claim 1, further comprising means for allowing a user to evaluate and select the presented collaboration partner information.

3. The system of claim 1 further comprising means for the user to provide feedback on the proposed collaborator information.

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