System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving and storing new business ideas from individuals or corporations; means for collecting and learning past business ideas and their successful commercialization results; means for analyzing the new business ideas based on evaluation criteria using AI techniques and quantifying their successful commercialization probabilities; means for selecting a company suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas; and means for performing a procedure for transferring the right to the ideas to the company with the highest bid in the auction.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] With the advent of generative AI technology, many companies are finding it difficult to generate and evaluate new business ideas. As a result, many companies are unable to take the first step toward commercializing new services. The purpose of this invention is to solve these corporate challenges, properly evaluate the value of new business ideas, and provide those rights to companies that want to commercialize them. [Means for solving the problem]

[0005] The present invention provides a system comprising:

[0006] A means for receiving and storing new business ideas from individuals or entities;

[0007] A means of collecting and learning from data on past business ideas and their successful commercialization;

[0008] A method to use AI technology to analyze new business ideas based on evaluation criteria and quantify the probability of their commercialization success.

[0009] A means of selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas;

[0010] a means for carrying out the process of transferring the idea rights to the highest bidder in the auction;

[0011] It is a system including:

[0012] "Individual or Corporation" refers to the user who proposes the idea, i.e., the person or company.

[0013] A "new business idea" refers to a novel business concept, plan, or method that has not yet been commercialized.

[0014] "Means for receiving and storing" refers to technology that has the function of capturing business ideas submitted by users and storing them in a database or other storage.

[0015] "Means of collecting and learning" refers to the function of collecting data on past business ideas and their results, and having the AI ​​model learn from this data.

[0016] "Evaluation criteria" refers to standards or indicators generated based on collected data to evaluate the probability of success of an idea.

[0017] "Means of analysis" refers to the use of AI technology to analyze new ideas based on evaluation criteria and calculate their value and the probability of successful commercialization.

[0018] "Means of quantification" refers to the ability to numerically express the probability of successful commercialization of the analyzed idea.

[0019] "Selection method" refers to the process of selecting which companies are suitable for commercializing the idea based on the evaluation results.

[0020] "Means to hold an auction" refers to the ability to hold an online or offline auction event in which selected companies compete for the right to purchase the ideas.

[0021] "Rights Transfer Procedure" refers to the legal and administrative procedures for formally transferring the rights to an idea to the highest bidder as a result of the auction. [Brief explanation of the drawings]

[0022] [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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] This invention is a system that uses AI technology to evaluate new business ideas collected from individuals and corporations, and provides the rights to these ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[0044] 1. Idea collection

[0045] User

[0046] Users log in to the platform and enter the required information in the idea submission form. Required information includes a title, summary, and detailed description. When users press the submit button, this information is sent to the server.

[0047] server

[0048] The submitted ideas are received and stored in the database. Once the storage is complete, a data reception confirmation notice is sent to the user.

[0049] 2. Collecting and learning from past data

[0050] server

[0051] Collect data on the business idea's past success, including target market, revenue, implementation technology, etc.

[0052] This data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[0053] 3. Evaluating ideas

[0054] server

[0055] The collected new business ideas are analyzed based on evaluation criteria, and AI technology is used to quantify the probability of each idea being successfully commercialized.

[0056] The evaluation results are stored in a database and notified to the user.

[0057] 4. Selection of companies suitable for commercialization and holding an auction

[0058] server

[0059] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select suitable companies to hold an auction for these ideas.

[0060] Selected companies will be sent an invitation to participate in the auction via email and notification.

[0061] Corporate Users

[0062] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[0063] 5. Auction Results and Transfer of Rights

[0064] server

[0065] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[0066] Corporate Users

[0067] Once you receive confirmation of your successful bid, you can begin the process of transferring the rights to your idea.

[0068] Specific examples

[0069] As an example, consider the idea of ​​a new content distribution method: "A personalized content suggestion system using AI."

[0070] User

[0071] Access the platform, fill in the form with specific details, and submit it.

[0072] server

[0073] The received ideas are stored and analyzed based on evaluation criteria. If an idea is deemed to have a high probability of commercialization, suitable content distribution service companies will be selected and invited to participate in the auction.

[0074] Corporate Users

[0075] Companies participate in the auction, and the highest bidder acquires the rights to the idea. They then develop new services based on the acquired rights and bring them to market.

[0076] In this way, the present invention realizes a system that utilizes AI technology to appropriately evaluate many business ideas and provide them to companies that can make the most use of them.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] User: Log in to the platform, access the idea submission form, enter the required information (title, summary, detailed description), and click the submit button.

[0080] Step 2:

[0081] Server: Receives ideas sent by users via the REST API, saves the received data in a database, and notifies the user when the data has been saved.

[0082] Step 3:

[0083] Server: Collects data on past business ideas and their success (target market, revenue, implementation technology, etc.).

[0084] Step 4:

[0085] Server: Inputs the collected data into the AI ​​model, allowing it to learn, then generates criteria for evaluating new business ideas and stores those criteria in a database.

[0086] Step 5:

[0087] Server: Analyzes new business ideas received from users based on evaluation criteria, and uses AI technology to score the probability of commercialization success for each idea.

[0088] Step 6:

[0089] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[0090] Step 7:

[0091] Server: Based on the evaluation results, it lists ideas with a high probability of commercialization success and selects companies that can easily commercialize those ideas.

[0092] Step 8:

[0093] Server: Sends invitations to selected companies to participate in the auction via email or notification.

[0094] Step 9:

[0095] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[0096] Step 10:

[0097] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[0098] Step 11:

[0099] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[0100] Step 12:

[0101] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[0102] Example 1

[0103] 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."

[0104] In conventional business idea evaluation systems, ideas collected from individuals and corporations are often not properly evaluated, resulting in ideas being left unattended without sufficient consideration of their commercialization potential. Furthermore, the evaluation criteria are inconsistent, leading to unreliable evaluation results. Furthermore, the process for effectively selecting companies suitable for commercialization and holding auctions is insufficient, resulting in delays in the realization of ideas.

[0105] 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.

[0106] In this invention, the server includes a means for receiving and storing new business ideas from individuals or corporations, a means for collecting and learning from past data on business ideas and their commercialization success records, and a means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success. This enables a consistent and efficient process for evaluating and commercializing new business ideas. Furthermore, users can log in to the platform and submit their ideas, making the system easy to use. Furthermore, the AI ​​model is used to generate evaluation criteria and quantify the probability of commercialization success, improving the reliability of the evaluation results. Selected companies are invited to participate in an auction, and a means for companies to participate in the auction and acquire ideas allows for the rapid realization of business ideas.

[0107] "Individual or Legal Entity" means the entity that creates and submits a business idea to the system.

[0108] A "new business idea" is an innovative business concept or technology that has not yet appeared on the market.

[0109] "Means for receiving and storing" refers to the mechanism by which the system receives business ideas sent by users and stores them in a database or storage.

[0110] "Past data on business ideas" refers to information about previously submitted business ideas, including data on past successes and market trends.

[0111] "Commercialization success data" is information indicating whether past business ideas have actually been brought to market and achieved success.

[0112] "Means of collecting and learning" refers to the process of statistically analyzing past business ideas and their success stories, inputting them into an AI model, and having it learn.

[0113] "AI technology" refers to artificial intelligence technology that can mimic human judgment and analyze large data sets. Typical examples include machine learning and deep learning.

[0114] "Evaluation criteria" are indicators used to analyze new business ideas and evaluate the probability of commercialization success.

[0115] "Means of analysis and quantification" refers to a method of using AI technology to evaluate business ideas as a numerical score.

[0116] The "evaluation result" is a score that indicates the probability of successful commercialization after analyzing a business idea using AI technology.

[0117] "Companies suitable for commercialization" are those that are judged based on the evaluation results to have a high probability of realizing new business ideas in the market.

[0118] An "idea purchase rights auction" is a process in which companies bid for the rights to a new business idea, and the highest bidder acquires the rights.

[0119] An "Invitation to Auction" is an official communication offering selected companies the opportunity to acquire the idea rights.

[0120] The "Transfer of Rights Process" is a set of legal and business procedures for formally transferring ownership of a business idea to the highest bidder after the auction ends.

[0121] "Means for logging into the platform" means the authentication mechanism by which a user accesses the system and logs into their account.

[0122] "Means for submitting ideas by entering necessary information" is a function for entering information such as a title, summary, detailed description, etc. and sending it to the server.

[0123] "Means of inputting past data and data on successful performance into an AI model, allowing it to learn and generate" refers to a function that inputs collected data into an AI model to generate evaluation criteria and automatically updates the evaluation criteria.

[0124] "Method of analyzing new business ideas using AI technology and quantifying the probability of commercialization success" is a method of analyzing business ideas using AI technology and expressing the probability of commercialization success as a score.

[0125] The "means for inviting participants to participate in the auction" is a function for sending invitations to selected companies to participate in the auction of idea rights.

[0126] "A process by which companies participating in an auction bid for the right to purchase an idea" is a process by which selected companies compete in an auction for the right to purchase an idea.

[0127] This invention is a system for evaluating new business ideas submitted by individuals or corporations and providing them to companies suitable for commercialization. This system is composed of a server, terminals, and users.

[0128] 1. Idea collection

[0129] User:

[0130] First, users access the platform and are authenticated by entering their username and password on the login screen. After successfully logging in, they proceed to the idea submission form from the dashboard, enter the title, summary, and detailed description, and submit.

[0131] server:

[0132] The server receives the idea information sent by the user and stores it in a database. Once the data has been saved, it sends a notification to the user confirming receipt of the data. The platform's authentication and data storage functions are implemented using standard web servers (e.g., Apache or Nginx) and database servers (e.g., MySQL or PostgreSQL).

[0133] 2. Collecting and learning from past data

[0134] server:

[0135] The server collects past data on business ideas and commercial success data from external APIs or internal databases. The server inputs the collected data into an AI model and performs learning to generate evaluation criteria. Specifically, the AI ​​model is trained using frameworks such as TensorFlow and PyTorch. The training progress is displayed to the administrator in real time on the terminal.

[0136] 3. Evaluating ideas

[0137] server:

[0138] The server reads new business ideas collected from the database and analyzes them based on evaluation criteria using AI technology. The probability of commercialization success is quantified as a score and the evaluation results are saved in the database. After the evaluation results are generated, they are notified to the user.

[0139] 4. Selection of companies suitable for commercialization and holding an auction

[0140] server:

[0141] Based on the evaluation results, the server creates a list of business ideas with a high probability of commercialization success and selects the most suitable companies. The server determines suitability using past transaction data and company profiles. Selected companies are notified by email with an invitation to participate in the auction.

[0142] Corporate users:

[0143] Selected corporate users will receive an invitation email and log in to the auction platform to bid for the right to purchase the business idea. The server updates the bidding information in real time and monitors the auction status.

[0144] 5. Auction Results and Transfer of Rights

[0145] server:

[0146] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. Once the transfer procedure is complete, the server records the information in a database and notifies the parties involved.

[0147] Corporate users:

[0148] The highest bidder, the corporate user, will receive a notice of successful bid and proceed with the idea rights transfer procedure, allowing the company to develop a new service based on the purchased business idea and bring it to market.

[0149] Examples and prompts

[0150] As a concrete example, let's take a business idea called "a system for proposing personalized content using AI." When this idea is submitted, the user logs into the platform, enters the title and details of the idea into a form, and submits it. The server receives the idea, evaluates it using an AI model, and calculates a score representing the probability of commercialization success. If the score is high, suitable companies are invited to participate in the auction. Corporate users then participate in the auction and acquire the rights to the idea.

[0151] Examples of prompts include:

[0152] "What information do I need in a dataset to train an AI model that will assess the success probability of a new business idea?"

[0153] "How can I provide a business idea with potential for commercialization to the right company?"

[0154] Using such prompts increases the accuracy and efficiency of the system, which leverages AI technology to quickly and accurately evaluate business ideas and provide them to the right companies, facilitating their realization.

[0155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0156] Step 1:

[0157] User accesses the platform

[0158] Input: Username, Password

[0159] How it works: A user accesses the platform's login screen and enters their username and password.

[0160] Output: Sending authentication information

[0161] The server performs authentication

[0162] Input: Username, Password

[0163] Data calculation: The server checks the entered username and password against the credentials stored in the database.

[0164] Output: Authentication result

[0165] The device displays the dashboard

[0166] Input: Authentication result

[0167] Behavior: If authentication is successful, the user's dashboard screen is displayed on the device.

[0168] Output: Dashboard screen

[0169] Step 2:

[0170] User proceeds to idea submission form

[0171] Input: User actions

[0172] How it works: A user navigates to the idea submission form from the dashboard and fills in the fields, specifically the title, summary, and description.

[0173] Output: Idea information

[0174] The device temporarily stores and transmits the idea information

[0175] Input: Idea information

[0176] Data processing: Idea information is temporarily stored in cache memory.

[0177] Behavior: When the user presses the submit button, the idea information is sent to the server as a POST request.

[0178] Output: POST request

[0179] The server receives and stores the idea information

[0180] Input: POST request

[0181] Data processing: idea information is stored in a database.

[0182] Behavior: Once the data has been saved, the server will send a confirmation to the user.

[0183] Output: Save completion notification

[0184] Step 3:

[0185] The server collects past data

[0186] Input: Request to external API or internal database

[0187] Data collection: The server collects historical data on business ideas and their commercial success.

[0188] Output: Historical data

[0189] The server inputs data into the AI ​​model and it learns

[0190] Input: Historical data

[0191] Data calculation: The data collected by the server is input into an AI model (e.g., TensorFlow or PyTorch) and trained to generate evaluation criteria.

[0192] Output: Evaluation criteria

[0193] Your device displays your learning progress

[0194] Input: Learning progress

[0195] What it does: Shows learning progress to administrators in real time.

[0196] Output: progress indicator

[0197] Step 4:

[0198] Servers evaluate new ideas

[0199] Input: New business idea, evaluation criteria

[0200] Data calculation: The server analyzes new business ideas based on evaluation criteria and quantifies the probability of commercial success.

[0201] Output: Probability of commercial success score

[0202] The server saves the evaluation results and notifies you.

[0203] Input: Probability of commercial success score

[0204] Data processing: Save the scores to a database.

[0205] Action: Sends the user a notification of the evaluation results.

[0206] Output: Notification

[0207] Step 5:

[0208] Select a company suitable for commercialization of the server

[0209] Input: Evaluation results, company profile data

[0210] Data calculation: Based on the evaluation results and company profile data, companies with a high probability of commercialization success are selected.

[0211] Output: Selection result

[0212] The server sends the invitation to the company

[0213] Input: Selection result

[0214] How it works: The server sends email invitations to selected companies to participate in the auction.

[0215] Output: Invitation email

[0216] Corporate users participate in the auction and bid

[0217] Input: Invitation email

[0218] How it works: A corporate user receives an invitation email, logs into the auction platform, and places a bid for the right to purchase an idea from their account.

[0219] Output: Bid information

[0220] The server checks the auction results and starts the process

[0221] Input: Bid Information

[0222] Data calculation: Identify the highest bidder and initiate the idea rights transfer process.

[0223] Output: Notification of start of transfer procedure

[0224] Corporate users proceed with the rights transfer procedure

[0225] Input: Notice of commencement of transfer procedure

[0226] How it works: A corporate user goes through the transfer of rights process and prepares and completes the necessary paperwork.

[0227] Output: Completion report

[0228] The server records and notifies the completion of the transfer

[0229] Input: Completion report

[0230] Data processing: Record the transfer completion information in the database.

[0231] What it does: Sends notification to the parties involved that the transfer is complete.

[0232] Output: Completion notification

[0233] (Application example 1)

[0234] 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."

[0235] Previous business idea evaluation systems had unclear criteria for increasing the probability of commercialization success, and the evaluations were not always accurate. Furthermore, the process for providing evaluated business ideas to the most suitable companies was unclear, which could result in missed business opportunities. Furthermore, the means for participating in auctions for evaluated ideas were limited, making it inconvenient for companies.

[0236] 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.

[0237] In this invention, the server includes: means for receiving and storing new business proposals from individuals or corporations; means for collecting and learning data on past business proposals and their commercial success; means for using AI technology to analyze new business proposals based on evaluation criteria and quantify their commercialization success rates; means for selecting companies suitable for commercializing the evaluated business proposals and holding an auction for the right to purchase the proposals; means for transferring the proposal rights to the highest bidder in the auction; and, in the case of proposals related to content distribution services, means for companies to participate in the auction via a smartphone application for proposals that receive an evaluation score above a certain level. This enables accurate evaluation of business proposals and prompt provision of the proposals to the most suitable companies. Furthermore, companies can easily participate in the auction via the smartphone application, greatly improving convenience.

[0238] A "new business idea" is a proposal or concept for a new business devised by an individual or corporation.

[0239] "Past business proposals" are business proposals or ideas that have been proposed and implemented in some form.

[0240] "Commercialization success data" refers to data on the track record and results of business ideas that have been commercialized in the past.

[0241] "AI technology" refers to technology that uses artificial intelligence and makes decisions and predictions through machine learning and data analysis.

[0242] "Evaluation criteria" are standards for evaluating new business ideas, and include factors such as probability of success and market adaptability.

[0243] "Quantification" means expressing the evaluation of the target business proposal in concrete numerical terms.

[0244] An "auction" is a trading method in which multiple companies participate and bid for the right to purchase a target business proposal.

[0245] "Proposal Purchase Rights" means the right of the highest bidder in an auction to purchase a particular business proposal.

[0246] The "proposal rights transfer procedure" refers to the procedure for officially transferring the rights of a business proposal that has been won in an auction to the bidding company.

[0247] "Content distribution service" is a general term for services that distribute digital content to users.

[0248] A "smartphone application" is a software program that runs on a smartphone.

[0249] An "evaluation score" is a numerical representation of the evaluation result of a business proposal, and indicates the value and probability of success of the proposal.

[0250] An "enterprise" is a legal entity that operates with a specific business purpose.

[0251] The present invention is a system that uses AI technology to evaluate new business ideas collected from individuals or corporations and provides the rights to companies for commercialization. The following describes the details of the embodiment of this system and the operation of the program.

[0252] 1. Idea collection

[0253] User

[0254] Users log in to the platform and enter the necessary information (title, summary, detailed description) into the business proposal submission form. When the submit button is pressed, the information is sent to the server.

[0255] server

[0256] The server receives the business proposal and stores it in the database. Once the storage is complete, it sends a data reception confirmation notice to the user.

[0257] 2. Collecting and learning from past data

[0258] server

[0259] The server collects data on past business proposals and successful commercialization, including information on target markets, revenue, and implementation technologies. This data is input into an AI model, which learns to generate evaluation criteria. The generated evaluation criteria are stored in a database.

[0260] 3. Evaluating ideas

[0261] server

[0262] The server analyzes the collected new business ideas based on the evaluation criteria. At this time, AI technology is used to quantify the probability of commercialization success for each idea. The evaluation results are stored in a database and notified to the user.

[0263] 4. Selection of companies suitable for commercialization and holding an auction

[0264] server

[0265] Based on the evaluation results, the server will create a list of business proposals with a high probability of commercialization success. It will then select suitable companies to hold an auction for these proposals. It will then send invitations to the selected companies to participate in the auction via email and notifications.

[0266] Corporate Users

[0267] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to acquire the right to purchase the proposal.

[0268] 5. Auction Results and Transfer of Rights

[0269] server

[0270] At the end of the auction, the server identifies the highest bidder, initiates the transfer of the rights, records the completion of the transfer in the database, and notifies the parties involved.

[0271] Corporate Users

[0272] The corporate user receives a confirmation of the successful bid and proceeds with the proposal rights transfer procedure.

[0273] Example

[0274] Consider a business proposal called "a new personalized content proposal system." Users access the platform, enter specific details into a form, and submit it. The server saves the received proposal and analyzes it based on evaluation criteria. If the proposal is deemed to have a high probability of commercial success, a suitable content distribution service company is selected and invited to participate in an auction. The company participates in the auction and, as the highest bidder, acquires the rights to the proposal. A new service is developed based on the acquired rights and launched in the market.

[0275] Hardware and software used

[0276] Server: AWS EC2 (server hosting)

[0277] Database: AWS RDS (database management)

[0278] AI technology: scikit-learn (machine learning library)

[0279] Web framework: Flask (Python web framework)

[0280] API documentation: Swagger

[0281] Prompt Sentence Examples

[0282] Post a new personalized content suggestion system.

[0283] example:

[0284] Title: AI-powered personalized content suggestion system

[0285] What it is: AI suggests the best content based on a customer's browsing history.

[0286] Description: The system analyzes users' past browsing history and suggests content that best suits their interests.

[0287] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0288] Step 1:

[0289] Users log in to the platform, enter the required information (title, summary, detailed description) in the business proposal submission form, and submit it.

[0290] Input: Title, summary, detailed description

[0291] Output: Send data to the server

[0292] Specific operations: The user uses a web browser or smartphone application to access the platform's business proposal submission page, enter the required information, and press the submit button.

[0293] Step 2:

[0294] The server receives the submitted business proposal, stores it in a database, and sends a data reception confirmation notice to the user once the saving is complete.

[0295] Input: Business proposal data submitted by the user

[0296] Output: Save to database and confirmation notification

[0297] Specific operation: The server receives the sent data, stores it in the AWS RDS database, and sends a notification to the user after the data is saved.

[0298] Step 3:

[0299] The server collects data on past business proposals and successful commercializations to create a learning dataset.

[0300] Input: Existing business plan data and its commercial success record data

[0301] Output: Training dataset

[0302] Specific operation: The server collects past business plans and their performance data from the Internet and internal databases, and uses this to generate a learning dataset.

[0303] Step 4:

[0304] The server uses a generative AI model to learn the training dataset and generate evaluation criteria.

[0305] Input: Training dataset

[0306] Output: Evaluation criteria

[0307] Specific operation: The server uses the scikit-learn library to input the training dataset into the model, generate evaluation criteria, and store them in the database.

[0308] Step 5:

[0309] The server analyzes new business ideas sent by users based on evaluation criteria and quantifies the probability of commercial success as a score.

[0310] Input: New business idea data, evaluation criteria

[0311] Output: Probability of commercial success score

[0312] Specific operation: The server analyzes new business idea data based on the evaluation criteria and calculates the probability of commercial success as a score using a random forest model.

[0313] Step 6:

[0314] The server selects corporate users suitable for commercialization based on the scores of the evaluated business proposals and holds an auction for the right to purchase the proposals.

[0315] Input: Probability of commercial success score

[0316] Output: Selection and notification of auction participants

[0317] Specific operation: The server selects suitable corporate users for business proposals with high evaluation scores and sends them invitation emails containing a link to the auction platform.

[0318] Step 7:

[0319] Corporate users receive an invitation email, log in to the auction platform, and place a bid to win the right to purchase the proposal.

[0320] Input: Corporate user bid amount

[0321] Output: Record of bidding results

[0322] Specific operation: The corporate user clicks the link in the invitation email, logs in to the auction platform, enters the bid amount, and presses the bid button. The bid results are recorded on the server.

[0323] Step 8:

[0324] At the end of the auction, the server identifies the highest bidder and initiates the process of transferring the business proposal rights.

[0325] Input: Auction bid results

[0326] Output: Initiation and notification of transfer procedure

[0327] Specific operation: After the auction ends, the server checks the highest bid and notifies the bidding company of the details of the procedure for transferring the bid rights.

[0328] Step 9:

[0329] The corporate user will receive a confirmation of the successful bid and proceed with the rights transfer procedure for the business proposal.

[0330] Input: Notification of details of rights transfer procedure

[0331] Output: Transfer of rights completed

[0332] Specific operation: The corporate user provides the necessary information for the rights transfer according to the notified procedure, and the rights transfer is finally completed.

[0333] 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.

[0334] This invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[0335] 1. Idea collection

[0336] User

[0337] Log in to the platform and access the idea submission form. When entering the required information (title, summary, detailed description), the emotion engine is also used to obtain the user's emotional data at the time of entry. When the user presses the submit button, this information is sent to the server.

[0338] server

[0339] The submitted idea and emotion data is received and stored in the database. Once the data is stored, a data reception confirmation notification is sent to the user.

[0340] 2. Collecting and learning from past data

[0341] server

[0342] Collect historical data on business ideas and their success (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[0343] The collected data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[0344] 3. Evaluating ideas

[0345] server

[0346] The emotional data obtained by the emotion engine, along with new business ideas received from users, is analyzed based on evaluation criteria. Using AI technology, the emotional data is reflected when quantifying the probability of commercialization success for each idea.

[0347] The evaluation results are stored in a database, and the user is notified of the evaluation results of the idea.

[0348] 4. Selection of companies suitable for commercialization and holding an auction

[0349] server

[0350] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select companies that can easily commercialize these ideas.

[0351] Selected companies will be sent an invitation to participate in the auction via email or notification.

[0352] Corporate Users

[0353] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[0354] 5. Auction Results and Transfer of Rights

[0355] server

[0356] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[0357] Corporate Users

[0358] Once you receive the successful bid, you will proceed with the procedures to acquire the idea rights.

[0359] Specific examples

[0360] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[0361] User

[0362] Access the platform and enter "AI-based personalized content suggestion system" as the title. Enter a summary and detailed description, and emotional data will be collected in real time as you enter it. Send all information and emotional data.

[0363] server

[0364] The received ideas and sentiment data are stored and analyzed. If the idea is deemed to have a high probability of commercialization, a suitable content distribution service company will be selected and invited to participate in the auction.

[0365] Corporate Users

[0366] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[0367] Through the above process, the present invention provides a system that utilizes an emotion engine to evaluate and commercialize new business ideas while taking into account the emotional value of users. This system improves the accuracy of evaluation and the likelihood of commercialization.

[0368] The processing flow will be explained below.

[0369] Step 1:

[0370] User: Logs in to the platform and accesses the idea submission form. While entering the title, summary, and detailed description, the emotion engine also collects the user's emotion data in real time. After entering all the information and emotion data, the user clicks the submit button.

[0371] Step 2:

[0372] Server: Receives business ideas and sentiment data sent by users via REST API, saves the data in the database, and notifies the user that the data has been saved.

[0373] Step 3:

[0374] Server: Collects historical data on business ideas and their success stories (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[0375] Step 4:

[0376] Server: The collected data is input into the AI ​​model and it learns, generating evaluation criteria for new business ideas and saving them in a database.

[0377] Step 5:

[0378] Server: Analyzes new business ideas received from users and the emotional data acquired by the emotion engine based on evaluation criteria. AI technology is used to quantify the probability of commercialization success for each idea, and the emotional data is reflected in the score.

[0379] Step 6:

[0380] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[0381] Step 7:

[0382] Server: Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success. We will then select companies that can easily commercialize these ideas.

[0383] Step 8:

[0384] Server: Sends emails or notifications to selected companies inviting them to participate in the auction.

[0385] Step 9:

[0386] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[0387] Step 10:

[0388] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[0389] Step 11:

[0390] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[0391] Step 12:

[0392] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[0393] Example 2

[0394] 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."

[0395] Conventional systems evaluate new business ideas without considering their emotional value, which means they cannot accurately reflect the true potential of the ideas submitted by users. Furthermore, they lack important information, such as emotional data, in the idea evaluation and commercialization process, which reduces the accuracy of predicting the probability of success.

[0396] 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.

[0397] In this invention, the server includes a means for receiving new business ideas from individuals or corporations and storing them together with emotional data, a means for collecting and learning data on past business ideas and their commercial successes, as well as past emotional data, and a means for using AI technology to analyze new business ideas based on evaluation criteria and taking the emotional data into account when quantifying the probability of their commercial success. This enables more accurate evaluation of business ideas and prediction of the probability of commercial success by taking the emotional data into account.

[0398] "Individual or Legal Entity" refers to a user as an individual or a legal entity such as a company or organization.

[0399] "Business ideas" refer to business proposals and plans for new products, services, business models, etc.

[0400] "Emotion data" refers to data that expresses the user's emotional state in the form of numbers, text, or the like.

[0401] "Means for storing" refers to the function of storing received information in a database or storage.

[0402] "Past business ideas" refers to historical data on business ideas that have been submitted to date.

[0403] "Commercialization success data" refers to data showing the results and achievements of business ideas that have been commercialized to date.

[0404] "Means of learning" refers to the function of training an AI model using collected data.

[0405] "AI technology" refers to artificial intelligence technology in general, and particularly includes machine learning and natural language processing models.

[0406] "Evaluation criteria" refers to the metrics or scoring rules used to evaluate business ideas.

[0407] "Means of analysis" refers to the function of analyzing and evaluating data using AI technology.

[0408] "Means of quantification" refers to the function of quantifying the probability of success of a business idea.

[0409] "Enterprise" refers to a legal entity that has the ability and desire to commercialize a business idea.

[0410] An "auction" refers to the process of bidding on business ideas and the highest bidder wins the right to purchase them.

[0411] "Assignment process" refers to the process by which the rights to an idea are officially transferred to the highest bidding company.

[0412] The present invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The details of the implementation of this system and the operation of the program are described below.

[0413] Idea collection

[0414] User

[0415] Users log in to the platform and access the form for submitting ideas. Here, they enter a title, summary, and detailed description in the form. Furthermore, an emotion engine runs in the background, capturing emotional data in real time as the user types. Once users have completed entering information and pressed the submit button, this information is sent to the server.

[0416] server

[0417] The server receives the idea and emotion data sent by the user and stores this information in a database. After storing the information, it sends a data reception confirmation notice to the user. The database used is, for example, MySQL or PostgreSQL.

[0418] Collecting and learning from past data

[0419] server

[0420] The server collects data on past business ideas and their success (e.g., target market, revenue, implementation technology, etc.), as well as past sentiment data. This data is then prepared for input into an AI model (e.g., TensorFlow or PyTorch).

[0421] The server inputs the collected data into the AI ​​model, which then learns to generate evaluation criteria, which are then stored in a database.

[0422] Idea Evaluation

[0423] server

[0424] The server analyzes new business ideas and emotional data received from users using evaluation criteria based on past data. Using AI technology (natural language processing models and machine learning algorithms), it quantifies the idea's probability of commercial success as a score, which also reflects the emotional data. The evaluation results are stored in a database and the user is notified of the results.

[0425] Selection of companies suitable for commercialization and holding an auction

[0426] server

[0427] Based on the evaluation results, ideas deemed to have a high probability of commercialization will be listed, and companies suitable for commercialization will be selected. Selected companies will be invited to participate in the auction via email or notification.

[0428] Corporate Users

[0429] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to win the right to purchase the idea.

[0430] Auction Results and Transfer of Rights

[0431] server

[0432] At the end of the auction, the highest bidder will be identified and the process of transferring the idea rights will begin, which will then be recorded in the database as a completed transfer and notify the relevant parties.

[0433] Corporate Users

[0434] The corporate user receives the successful bid notification and proceeds with the procedures for acquiring the idea rights.

[0435] Specific examples

[0436] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[0437] User

[0438] Users access the platform and enter the title "AI-based personalized content suggestion system." They then enter a summary and detailed description, and emotional data is collected in real time as they enter the information. All information and emotional data is then sent.

[0439] server

[0440] The server stores the received ideas and emotional data and analyzes them using AI technology. If the idea is deemed to have a high probability of commercialization, it selects appropriate content distribution service companies and invites them to participate in the auction.

[0441] Corporate Users

[0442] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[0443] This system allows for the evaluation and commercialization of new business ideas that take into account the emotional value of users, resulting in more accurate evaluation and improved likelihood of commercialization.

[0444] Prompt Sentence Examples

[0445] Please tell us the details of the implementation of a system that will be offered to companies in an auction format to evaluate a new business idea called "a personalized content suggestion system using AI" and collect emotional data to increase the probability of commercialization success.

[0446] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0447] Step 1:

[0448] User: Platform login

[0449] A user accesses the platform and logs in by entering their authentication information (user ID, password) on the login screen. The authentication information is sent to the server, which then collates it with the database to authenticate the user. After successful authentication, a form screen for submitting ideas is displayed on the user's device. Input data: user ID, password. Output data: idea submission form.

[0450] Step 2:

[0451] User: Fill out the idea submission form

[0452] The user enters a title, summary, and detailed description into the submission form. While the user is entering data, the emotion engine runs in the background and collects emotional data in real time as the user enters the information. Emotional data is collected using, for example, a webcam or microphone. Input data: Title, summary, detailed description. Output data: Emotional data as the user enters the information.

[0453] Step 3:

[0454] User: Submit information

[0455] When the user presses the send button, the title, summary, detailed description, and emotion data are sent to the server. The server temporarily stores the received information in memory and begins the database storage process. Input data: title, summary, detailed description, emotion data. Output data: Data sent to the server completed.

[0456] Step 4:

[0457] Server: Data storage

[0458] The server stores the received idea information and emotion data in a database. Once the database storage is complete, a data reception confirmation notification is sent to the user. Input data: idea information, emotion data. Output data: data storage completion notification.

[0459] Step 5:

[0460] Server: Collection of historical data

[0461] The server collects past business ideas, commercial success data, and emotional data from a database. The collected data is preprocessed to train the AI ​​model. Input data: past business ideas, commercial success data, and emotional data. Output data: preprocessed training data.

[0462] Step 6:

[0463] Server: Preparing training data

[0464] The server converts the preprocessed data into a format appropriate for the AI ​​model (e.g., TensorFlow or PyTorch). Data processing is performed to convert it into the appropriate format. Input data: Preprocessed training data. Output data: Data in the AI ​​model input format.

[0465] Step 7:

[0466] Server: AI model training

[0467] The server inputs data into the AI ​​model and performs learning to generate evaluation criteria. The evaluation criteria generated through learning are stored in a database. Input data: Data in the AI ​​model input format. Output data: Evaluation criteria.

[0468] Step 8:

[0469] Server: Evaluating ideas

[0470] The server analyzes the new business idea and sentiment data received from the user based on the generated evaluation criteria. Natural language processing models and machine learning algorithms are used for the analysis. Input data: new business idea, sentiment data, evaluation criteria. Output data: score of the probability of commercialization success.

[0471] Step 9:

[0472] Server: Evaluation result storage and notification

[0473] The server stores the evaluation results of the probability of commercial success in a database and notifies the user of the evaluation results of the idea. Input data: Score of the probability of commercial success. Output data: Notification of evaluation results.

[0474] Step 10:

[0475] Server: Company Selection

[0476] The server lists ideas with a high probability of commercialization success and selects suitable companies. Selected companies are then invited to participate in the auction via email or notification. Input data: Ideas with a high probability of commercialization success. Output data: List of selected companies, invitation email.

[0477] Step 11:

[0478] Corporate users: Participating in auctions

[0479] Corporate users receive an invitation email and log in to the auction platform. They then participate in the auction from their own accounts and place bids to obtain the right to purchase ideas. Input data: invitation email, account information. Output data: auction participation, bid.

[0480] Step 12:

[0481] Server: Confirmation of auction results and transfer of rights

[0482] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. The transfer completion information is recorded in the database and notified to the relevant parties. Input data: Auction results. Output data: Notification of transfer procedure completion.

[0483] Step 13:

[0484] Corporate users: Rights acquisition procedure

[0485] The corporate user receives the successful bid notification and proceeds with the procedures to acquire the idea rights. Finally, a new service is developed based on the acquired rights and released to the market. Input data: successful bid notification. Output data: Rights acquired, new service developed.

[0486] (Application example 2)

[0487] 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."

[0488] Conventional business idea evaluation systems fail to consider user emotions or intuitive values ​​when quantitatively assessing the probability of an idea's commercialization success. This can result in the idea's true value being overlooked, hindering its commercialization. Furthermore, the process of selecting appropriate companies and holding auctions based on the evaluation results is inefficient. An effective system is needed to collect user emotion data and evaluate ideas based on it.

[0489] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0490] In this invention, the server includes means for receiving and storing new business ideas from individuals or corporations, means for collecting and learning data on past business ideas and their successful commercialization, means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success, means for collecting emotional data when the idea is submitted and reflecting this in the evaluation, means for selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas, and means for transferring the idea rights to the company with the highest bid in the auction. This makes it possible to more accurately evaluate the value of business ideas while taking user emotions into consideration and improve the probability of successful commercialization.

[0491] 1. A "business idea" is a creative concept or proposal for a new product, service, process, or business model, originating from an individual or legal entity.

[0492] 2. "Emotional Data" refers to data that quantifies or categorizes the emotional reactions or states that users show when submitting ideas.

[0493] 3. "Evaluation Criteria" means indicators or standards based on AI technology that use historical and sentiment data to measure the value of new business ideas and the probability of commercial success.

[0494] 4. "Probability of commercial success" is the statistical probability that a particular business idea will be successful and profitable when brought to market.

[0495] 5. "AI technology" refers to a group of technologies that use advanced algorithms such as machine learning and deep learning to analyze data and make predictions and decisions.

[0496] 6. "Enterprise" means a legal entity or organization that has the ability to purchase and implement business ideas for commercialization.

[0497] 7. An "auction" is a process in which participating companies compete for the right to purchase an idea, with the highest bidder winning the right.

[0498] 8. "Transfer Procedure" refers to the process of transferring the rights to an idea to a company that has won the right to purchase the idea in an auction, by carrying out the necessary legal and contractual procedures.

[0499] This invention is a system that collects new business ideas from users, evaluates them, and provides them to companies suitable for commercialization. The core of this system involves evaluating business ideas including emotional data, and transferring idea rights through an auction format.

[0500] System configuration

[0501] 1. User Device:

[0502] Users submit new business ideas using a smartphone application. As they submit their ideas, an emotion engine collects emotional data in real time as they type. Emotional data is obtained from the user's facial expressions, voice, and tone of voice as they type.

[0503] 2. Server:

[0504] The server has the following main functions:

[0505] Data reception and storage: Receive business ideas and sentiment data sent by users and store them in a database.

[0506] Evaluation by AI model: The AI ​​model is trained using collected data on past business ideas and sentiment data. It analyzes new business ideas based on evaluation criteria and quantifies their probability of commercialization.

[0507] Auction management: Select suitable companies based on the probability of commercialization success, hold an auction, and manage the process of transferring idea rights to the highest bidder.

[0508] Hardware and software used

[0509] Hardware:

[0510] Server: A high-performance server for storing data, running AI models, and managing auctions.

[0511] User device: Smartphone, tablet, etc.

[0512] software:

[0513] Flask: A framework for providing APIs and receiving requests from users.

[0514] EmotionEngine: A library for collecting and analyzing user emotion data.

[0515] AI Model: Uses machine learning algorithms to learn from historical data and evaluate new business ideas.

[0516] Database: A relational database for storing ideas, sentiment data, and evaluation results.

[0517] Specific examples

[0518] As a concrete example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI." A user uses the system as follows:

[0519] 1. User Action:

[0520] The user launches the smartphone app and accesses a form to submit a business idea. They enter "AI-based personalized content suggestion system" as the title, and then fill in a summary and detailed description. During this process, the emotion engine collects emotion data in real time. All information and emotion data is sent.

[0521] 2. Server processing:

[0522] The server stores and analyzes the received ideas and sentiment data. The AI ​​model evaluates them and calculates the probability of commercialization success. Based on the evaluation results, suitable content distribution service companies are selected and invited to participate in the auction.

[0523] 3. Enterprise operations:

[0524] Invited companies log in to the auction platform and make bids to win the right to purchase the idea. The highest bidder will acquire the rights to the idea and develop and deploy a new service.

[0525] Prompt Sentence Examples

[0526] The prompt that users use to submit their ideas is as follows:

[0527] Title: "AI-based personalized content suggestion system"

[0528] Summary: "This system is a service that suggests individually optimized content based on the user's emotional data."

[0529] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0530] Step 1:

[0531] Submit your business idea

[0532] User input: A user launches a smartphone application and inputs a new business idea. They fill out a form with a title, summary, and detailed description. During this process, the emotion engine collects emotional data in real time from the user's facial expressions, voice, and tone of voice.

[0533] Data processing and data calculation: The text data entered by the user and the emotion data collected by the emotion engine are organized into JSON format data and sent to the server.

[0534] Output: The server receives the idea data and emotion data sent by the user.

[0535] Step 2:

[0536] Data storage

[0537] Server input: Business idea data and sentiment data received in step 1.

[0538] Data processing and data calculation: The server connects to the database and stores the received idea data and emotion data in the database in an appropriate format. The data is stored in the form of ID, user ID, title, summary, details, emotion data, etc.

[0539] Output: A message is generated to confirm the data save and notify the user.

[0540] Step 3:

[0541] Evaluation preparation using AI models

[0542] Server input: Past business idea data, commercial success data, and sentiment data obtained from the database.

[0543] Data processing and data calculation: The server inputs past business idea data and its sentiment data into the AI ​​model for learning. The AI ​​model generates evaluation criteria based on this data and prepares to evaluate new business ideas.

[0544] Output: A generative AI model with updated evaluation metrics.

[0545] Step 4:

[0546] Evaluating new ideas

[0547] Server input: new business idea data and sentiment data received from users, and the updated generative AI model.

[0548] Data processing and calculation: The AI ​​model analyzes new business ideas submitted by users based on evaluation criteria. The evaluation, including emotional data, quantifies the probability of commercialization success.

[0549] Output: A score indicating the probability of commercial success is generated and stored in a database. The user is notified of the evaluation result.

[0550] Step 5:

[0551] Holding an auction

[0552] Server input: Evaluated business idea data and their commercial success probability scores.

[0553] Data processing and data calculation: The server selects companies that are likely to commercialize the idea based on the probability of commercialization success, and sends an invitation to participate in the auction to the selected companies via email or notification.

[0554] Output: The companies participating in the auction are determined and the auction platform is set up.

[0555] Step 6:

[0556] Auction execution and notification of results

[0557] Server input: Bid data of companies participating in the auction.

[0558] Data processing and data calculation: The server collects and analyzes the bidding data during the auction period and determines the highest bidder.

[0559] Output: The company selected as the highest bidder at the end of the auction will begin the process of transferring the idea rights. The auction results will be notified to the user and participating companies.

[0560] Step 7:

[0561] Completion of the transfer of rights

[0562] Server input: Data of the highest bidding company and business idea rights information.

[0563] Data processing and data operation: The server will carry out the transfer procedures for the idea rights in accordance with the law and contract, record the completion of the transfer in the database, and notify the relevant parties.

[0564] Output: Record and notification of completed title transfer.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] [Second embodiment]

[0569] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0570] 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.

[0571] 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).

[0572] 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.

[0573] 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.

[0574] 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).

[0575] 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. 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.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] In the smart glasses 214, 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.

[0580] 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."

[0581] This invention is a system that uses AI technology to evaluate new business ideas collected from individuals and corporations, and provides the rights to these ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[0582] 1. Idea collection

[0583] User

[0584] Users log in to the platform and enter the required information in the idea submission form. Required information includes a title, summary, and detailed description. When users press the submit button, this information is sent to the server.

[0585] server

[0586] The submitted ideas are received and stored in the database. Once the storage is complete, a data reception confirmation notice is sent to the user.

[0587] 2. Collecting and learning from past data

[0588] server

[0589] Collect data on the business idea's past success, including target market, revenue, implementation technology, etc.

[0590] This data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[0591] 3. Evaluating ideas

[0592] server

[0593] The collected new business ideas are analyzed based on evaluation criteria, and AI technology is used to quantify the probability of each idea being successfully commercialized.

[0594] The evaluation results are stored in a database and notified to the user.

[0595] 4. Selection of companies suitable for commercialization and holding an auction

[0596] server

[0597] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select suitable companies to hold an auction for these ideas.

[0598] Selected companies will be sent an invitation to participate in the auction via email and notification.

[0599] Corporate Users

[0600] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[0601] 5. Auction Results and Transfer of Rights

[0602] server

[0603] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[0604] Corporate Users

[0605] Once you receive confirmation of your successful bid, you can begin the process of transferring the rights to your idea.

[0606] Specific examples

[0607] As an example, consider the idea of ​​a new content distribution method: "A personalized content suggestion system using AI."

[0608] User

[0609] Access the platform, fill in the form with specific details, and submit it.

[0610] server

[0611] The received ideas are stored and analyzed based on evaluation criteria. If an idea is deemed to have a high probability of commercialization, suitable content distribution service companies will be selected and invited to participate in the auction.

[0612] Corporate Users

[0613] Companies participate in the auction, and the highest bidder acquires the rights to the idea. They then develop new services based on the acquired rights and bring them to market.

[0614] In this way, the present invention realizes a system that utilizes AI technology to appropriately evaluate many business ideas and provide them to companies that can make the most use of them.

[0615] The processing flow will be explained below.

[0616] Step 1:

[0617] User: Log in to the platform, access the idea submission form, enter the required information (title, summary, detailed description), and click the submit button.

[0618] Step 2:

[0619] Server: Receives ideas sent by users via the REST API, saves the received data in a database, and notifies the user when the data has been saved.

[0620] Step 3:

[0621] Server: Collects data on past business ideas and their success (target market, revenue, implementation technology, etc.).

[0622] Step 4:

[0623] Server: Inputs the collected data into the AI ​​model, allowing it to learn, then generates criteria for evaluating new business ideas and stores those criteria in a database.

[0624] Step 5:

[0625] Server: Analyzes new business ideas received from users based on evaluation criteria, and uses AI technology to score the probability of commercialization success for each idea.

[0626] Step 6:

[0627] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[0628] Step 7:

[0629] Server: Based on the evaluation results, it lists ideas with a high probability of commercialization success and selects companies that can easily commercialize those ideas.

[0630] Step 8:

[0631] Server: Sends invitations to selected companies to participate in the auction via email or notification.

[0632] Step 9:

[0633] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[0634] Step 10:

[0635] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[0636] Step 11:

[0637] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[0638] Step 12:

[0639] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[0640] Example 1

[0641] 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."

[0642] In conventional business idea evaluation systems, ideas collected from individuals and corporations are often not properly evaluated, resulting in ideas being left unattended without sufficient consideration of their commercialization potential. Furthermore, the evaluation criteria are inconsistent, leading to unreliable evaluation results. Furthermore, the process for effectively selecting companies suitable for commercialization and holding auctions is insufficient, resulting in delays in the realization of ideas.

[0643] 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.

[0644] In this invention, the server includes a means for receiving and storing new business ideas from individuals or corporations, a means for collecting and learning from past data on business ideas and their commercialization success records, and a means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success. This enables a consistent and efficient process for evaluating and commercializing new business ideas. Furthermore, users can log in to the platform and submit their ideas, making the system easy to use. Furthermore, the AI ​​model is used to generate evaluation criteria and quantify the probability of commercialization success, improving the reliability of the evaluation results. Selected companies are invited to participate in an auction, and a means for companies to participate in the auction and acquire ideas allows for the rapid realization of business ideas.

[0645] "Individual or Legal Entity" means the entity that creates and submits a business idea to the system.

[0646] A "new business idea" is an innovative business concept or technology that has not yet appeared on the market.

[0647] "Means for receiving and storing" refers to the mechanism by which the system receives business ideas sent by users and stores them in a database or storage.

[0648] "Past data on business ideas" refers to information about previously submitted business ideas, including data on past successes and market trends.

[0649] "Commercialization success data" is information indicating whether past business ideas have actually been brought to market and achieved success.

[0650] "Means of collecting and learning" refers to the process of statistically analyzing past business ideas and their success stories, inputting them into an AI model, and having it learn.

[0651] "AI technology" refers to artificial intelligence technology that can mimic human judgment and analyze large data sets. Typical examples include machine learning and deep learning.

[0652] "Evaluation criteria" are indicators used to analyze new business ideas and evaluate the probability of commercialization success.

[0653] "Means of analysis and quantification" refers to a method of using AI technology to evaluate business ideas as a numerical score.

[0654] The "evaluation result" is a score that indicates the probability of successful commercialization after analyzing a business idea using AI technology.

[0655] "Companies suitable for commercialization" are those that are judged based on the evaluation results to have a high probability of realizing new business ideas in the market.

[0656] An "idea purchase rights auction" is a process in which companies bid for the rights to a new business idea, and the highest bidder acquires the rights.

[0657] An "Invitation to Auction" is an official communication offering selected companies the opportunity to acquire the idea rights.

[0658] The "Transfer of Rights Process" is a set of legal and business procedures for formally transferring ownership of a business idea to the highest bidder after the auction ends.

[0659] "Means for logging into the platform" means the authentication mechanism by which a user accesses the system and logs into their account.

[0660] "Means for submitting ideas by entering necessary information" is a function for entering information such as a title, summary, detailed description, etc. and sending it to the server.

[0661] "Means of inputting past data and data on successful performance into an AI model, allowing it to learn and generate" refers to a function that inputs collected data into an AI model to generate evaluation criteria and automatically updates the evaluation criteria.

[0662] "Method of analyzing new business ideas using AI technology and quantifying the probability of commercialization success" is a method of analyzing business ideas using AI technology and expressing the probability of commercialization success as a score.

[0663] The "means for inviting participants to participate in the auction" is a function for sending invitations to selected companies to participate in the auction of idea rights.

[0664] "A process by which companies participating in an auction bid for the right to purchase an idea" is a process by which selected companies compete in an auction for the right to purchase an idea.

[0665] This invention is a system for evaluating new business ideas submitted by individuals or corporations and providing them to companies suitable for commercialization. This system is composed of a server, terminals, and users.

[0666] 1. Idea collection

[0667] User:

[0668] First, users access the platform and are authenticated by entering their username and password on the login screen. After successfully logging in, they proceed to the idea submission form from the dashboard, enter the title, summary, and detailed description, and submit.

[0669] server:

[0670] The server receives the idea information sent by the user and stores it in a database. Once the data has been saved, it sends a notification to the user confirming receipt of the data. The platform's authentication and data storage functions are implemented using standard web servers (e.g., Apache or Nginx) and database servers (e.g., MySQL or PostgreSQL).

[0671] 2. Collecting and learning from past data

[0672] server:

[0673] The server collects past data on business ideas and commercial success data from external APIs or internal databases. The server inputs the collected data into an AI model and performs learning to generate evaluation criteria. Specifically, the AI ​​model is trained using frameworks such as TensorFlow and PyTorch. The training progress is displayed to the administrator in real time on the terminal.

[0674] 3. Evaluating ideas

[0675] server:

[0676] The server reads new business ideas collected from the database and analyzes them based on evaluation criteria using AI technology. The probability of commercialization success is quantified as a score and the evaluation results are saved in the database. After the evaluation results are generated, they are notified to the user.

[0677] 4. Selection of companies suitable for commercialization and holding an auction

[0678] server:

[0679] Based on the evaluation results, the server creates a list of business ideas with a high probability of commercialization success and selects the most suitable companies. The server determines suitability using past transaction data and company profiles. Selected companies are notified by email with an invitation to participate in the auction.

[0680] Corporate users:

[0681] Selected corporate users will receive an invitation email and log in to the auction platform to bid for the right to purchase the business idea. The server updates the bidding information in real time and monitors the auction status.

[0682] 5. Auction Results and Transfer of Rights

[0683] server:

[0684] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. Once the transfer procedure is complete, the server records the information in a database and notifies the parties involved.

[0685] Corporate users:

[0686] The highest bidder, the corporate user, will receive a notice of successful bid and proceed with the idea rights transfer procedure, allowing the company to develop a new service based on the purchased business idea and bring it to market.

[0687] Examples and prompts

[0688] As a concrete example, let's take a business idea called "a system for proposing personalized content using AI." When this idea is submitted, the user logs into the platform, enters the title and details of the idea into a form, and submits it. The server receives the idea, evaluates it using an AI model, and calculates a score representing the probability of commercialization success. If the score is high, suitable companies are invited to participate in the auction. Corporate users then participate in the auction and acquire the rights to the idea.

[0689] Examples of prompts include:

[0690] "What information do I need in a dataset to train an AI model that will assess the success probability of a new business idea?"

[0691] "How can I provide a business idea with potential for commercialization to the right company?"

[0692] Using such prompts increases the accuracy and efficiency of the system, which leverages AI technology to quickly and accurately evaluate business ideas and provide them to the right companies, facilitating their realization.

[0693] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0694] Step 1:

[0695] User accesses the platform

[0696] Input: Username, Password

[0697] How it works: A user accesses the platform's login screen and enters their username and password.

[0698] Output: Sending authentication information

[0699] The server performs authentication

[0700] Input: Username, Password

[0701] Data calculation: The server checks the entered username and password against the credentials stored in the database.

[0702] Output: Authentication result

[0703] The device displays the dashboard

[0704] Input: Authentication result

[0705] Behavior: If authentication is successful, the user's dashboard screen is displayed on the device.

[0706] Output: Dashboard screen

[0707] Step 2:

[0708] User proceeds to idea submission form

[0709] Input: User actions

[0710] How it works: A user navigates to the idea submission form from the dashboard and fills in the fields, specifically the title, summary, and description.

[0711] Output: Idea information

[0712] The device temporarily stores and transmits the idea information

[0713] Input: Idea information

[0714] Data processing: Idea information is temporarily stored in cache memory.

[0715] Behavior: When the user presses the submit button, the idea information is sent to the server as a POST request.

[0716] Output: POST request

[0717] The server receives and stores the idea information

[0718] Input: POST request

[0719] Data processing: idea information is stored in a database.

[0720] Behavior: Once the data has been saved, the server will send a confirmation to the user.

[0721] Output: Save completion notification

[0722] Step 3:

[0723] The server collects past data

[0724] Input: Request to external API or internal database

[0725] Data collection: The server collects historical data on business ideas and their commercial success.

[0726] Output: Historical data

[0727] The server inputs data into the AI ​​model and it learns

[0728] Input: Historical data

[0729] Data calculation: The data collected by the server is input into an AI model (e.g., TensorFlow or PyTorch) and trained to generate evaluation criteria.

[0730] Output: Evaluation criteria

[0731] Your device displays your learning progress

[0732] Input: Learning progress

[0733] What it does: Shows learning progress to administrators in real time.

[0734] Output: progress indicator

[0735] Step 4:

[0736] Servers evaluate new ideas

[0737] Input: New business idea, evaluation criteria

[0738] Data calculation: The server analyzes new business ideas based on evaluation criteria and quantifies the probability of commercial success.

[0739] Output: Probability of commercial success score

[0740] The server saves the evaluation results and notifies you.

[0741] Input: Probability of commercial success score

[0742] Data processing: Save the scores to a database.

[0743] Action: Sends the user a notification of the evaluation results.

[0744] Output: Notification

[0745] Step 5:

[0746] Select a company suitable for commercialization of the server

[0747] Input: Evaluation results, company profile data

[0748] Data calculation: Based on the evaluation results and company profile data, companies with a high probability of commercialization success are selected.

[0749] Output: Selection result

[0750] The server sends the invitation to the company

[0751] Input: Selection result

[0752] How it works: The server sends email invitations to selected companies to participate in the auction.

[0753] Output: Invitation email

[0754] Corporate users participate in the auction and bid

[0755] Input: Invitation email

[0756] How it works: A corporate user receives an invitation email, logs into the auction platform, and places a bid for the right to purchase an idea from their account.

[0757] Output: Bid information

[0758] The server checks the auction results and starts the process

[0759] Input: Bid Information

[0760] Data calculation: Identify the highest bidder and initiate the idea rights transfer process.

[0761] Output: Notification of start of transfer procedure

[0762] Corporate users proceed with the rights transfer procedure

[0763] Input: Notice of commencement of transfer procedure

[0764] How it works: A corporate user goes through the transfer of rights process and prepares and completes the necessary paperwork.

[0765] Output: Completion report

[0766] The server records and notifies the completion of the transfer

[0767] Input: Completion report

[0768] Data processing: Record the transfer completion information in the database.

[0769] What it does: Sends notification to the parties involved that the transfer is complete.

[0770] Output: Completion notification

[0771] (Application example 1)

[0772] 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."

[0773] Previous business idea evaluation systems had unclear criteria for increasing the probability of commercialization success, and the evaluations were not always accurate. Furthermore, the process for providing evaluated business ideas to the most suitable companies was unclear, which could result in missed business opportunities. Furthermore, the means for participating in auctions for evaluated ideas were limited, making it inconvenient for companies.

[0774] 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.

[0775] In this invention, the server includes: means for receiving and storing new business proposals from individuals or corporations; means for collecting and learning data on past business proposals and their commercial success; means for using AI technology to analyze new business proposals based on evaluation criteria and quantify their commercialization success rates; means for selecting companies suitable for commercializing the evaluated business proposals and holding an auction for the right to purchase the proposals; means for transferring the proposal rights to the highest bidder in the auction; and, in the case of proposals related to content distribution services, means for companies to participate in the auction via a smartphone application for proposals that receive an evaluation score above a certain level. This enables accurate evaluation of business proposals and prompt provision of the proposals to the most suitable companies. Furthermore, companies can easily participate in the auction via the smartphone application, greatly improving convenience.

[0776] A "new business idea" is a proposal or concept for a new business devised by an individual or corporation.

[0777] "Past business proposals" are business proposals or ideas that have been proposed and implemented in some form.

[0778] "Commercialization success data" refers to data on the track record and results of business ideas that have been commercialized in the past.

[0779] "AI technology" refers to technology that uses artificial intelligence and makes decisions and predictions through machine learning and data analysis.

[0780] "Evaluation criteria" are standards for evaluating new business ideas, and include factors such as probability of success and market adaptability.

[0781] "Quantification" means expressing the evaluation of the target business proposal in concrete numerical terms.

[0782] An "auction" is a trading method in which multiple companies participate and bid for the right to purchase a target business proposal.

[0783] "Proposal Purchase Rights" means the right of the highest bidder in an auction to purchase a particular business proposal.

[0784] The "proposal rights transfer procedure" refers to the procedure for officially transferring the rights of a business proposal that has been won in an auction to the bidding company.

[0785] "Content distribution service" is a general term for services that distribute digital content to users.

[0786] A "smartphone application" is a software program that runs on a smartphone.

[0787] An "evaluation score" is a numerical representation of the evaluation result of a business proposal, and indicates the value and probability of success of the proposal.

[0788] An "enterprise" is a legal entity that operates with a specific business purpose.

[0789] The present invention is a system that uses AI technology to evaluate new business ideas collected from individuals or corporations and provides the rights to companies for commercialization. The following describes the details of the embodiment of this system and the operation of the program.

[0790] 1. Idea collection

[0791] User

[0792] Users log in to the platform and enter the necessary information (title, summary, detailed description) into the business proposal submission form. When the submit button is pressed, the information is sent to the server.

[0793] server

[0794] The server receives the business proposal and stores it in the database. Once the storage is complete, it sends a data reception confirmation notice to the user.

[0795] 2. Collecting and learning from past data

[0796] server

[0797] The server collects data on past business proposals and successful commercialization, including information on target markets, revenue, and implementation technologies. This data is input into an AI model, which learns to generate evaluation criteria. The generated evaluation criteria are stored in a database.

[0798] 3. Evaluating ideas

[0799] server

[0800] The server analyzes the collected new business ideas based on the evaluation criteria. At this time, AI technology is used to quantify the probability of commercialization success for each idea. The evaluation results are stored in a database and notified to the user.

[0801] 4. Selection of companies suitable for commercialization and holding an auction

[0802] server

[0803] Based on the evaluation results, the server will create a list of business proposals with a high probability of commercialization success. It will then select suitable companies to hold an auction for these proposals. It will then send invitations to the selected companies to participate in the auction via email and notifications.

[0804] Corporate Users

[0805] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to acquire the right to purchase the proposal.

[0806] 5. Auction Results and Transfer of Rights

[0807] server

[0808] At the end of the auction, the server identifies the highest bidder, initiates the transfer of the rights, records the completion of the transfer in the database, and notifies the parties involved.

[0809] Corporate Users

[0810] The corporate user receives a confirmation of the successful bid and proceeds with the proposal rights transfer procedure.

[0811] Example

[0812] Consider a business proposal called "a new personalized content proposal system." Users access the platform, enter specific details into a form, and submit it. The server saves the received proposal and analyzes it based on evaluation criteria. If the proposal is deemed to have a high probability of commercial success, a suitable content distribution service company is selected and invited to participate in an auction. The company participates in the auction and, as the highest bidder, acquires the rights to the proposal. A new service is developed based on the acquired rights and launched in the market.

[0813] Hardware and software used

[0814] Server: AWS EC2 (server hosting)

[0815] Database: AWS RDS (database management)

[0816] AI technology: scikit-learn (machine learning library)

[0817] Web framework: Flask (Python web framework)

[0818] API documentation: Swagger

[0819] Prompt Sentence Examples

[0820] Post a new personalized content suggestion system.

[0821] example:

[0822] Title: AI-powered personalized content suggestion system

[0823] What it is: AI suggests the best content based on a customer's browsing history.

[0824] Description: The system analyzes users' past browsing history and suggests content that best suits their interests.

[0825] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0826] Step 1:

[0827] Users log in to the platform, enter the required information (title, summary, detailed description) in the business proposal submission form, and submit it.

[0828] Input: Title, summary, detailed description

[0829] Output: Send data to the server

[0830] Specific operations: The user uses a web browser or smartphone application to access the platform's business proposal submission page, enter the required information, and press the submit button.

[0831] Step 2:

[0832] The server receives the submitted business proposal, stores it in a database, and sends a data reception confirmation notice to the user once the saving is complete.

[0833] Input: Business proposal data submitted by the user

[0834] Output: Save to database and confirmation notification

[0835] Specific operation: The server receives the sent data, stores it in the AWS RDS database, and sends a notification to the user after the data is saved.

[0836] Step 3:

[0837] The server collects data on past business proposals and successful commercializations to create a learning dataset.

[0838] Input: Existing business plan data and its commercial success record data

[0839] Output: Training dataset

[0840] Specific operation: The server collects past business plans and their performance data from the Internet and internal databases, and uses this to generate a learning dataset.

[0841] Step 4:

[0842] The server uses a generative AI model to learn the training dataset and generate evaluation criteria.

[0843] Input: Training dataset

[0844] Output: Evaluation criteria

[0845] Specific operation: The server uses the scikit-learn library to input the training dataset into the model, generate evaluation criteria, and store them in the database.

[0846] Step 5:

[0847] The server analyzes new business ideas sent by users based on evaluation criteria and quantifies the probability of commercial success as a score.

[0848] Input: New business idea data, evaluation criteria

[0849] Output: Probability of commercial success score

[0850] Specific operation: The server analyzes new business idea data based on the evaluation criteria and calculates the probability of commercial success as a score using a random forest model.

[0851] Step 6:

[0852] The server selects corporate users suitable for commercialization based on the scores of the evaluated business proposals and holds an auction for the right to purchase the proposals.

[0853] Input: Probability of commercial success score

[0854] Output: Selection and notification of auction participants

[0855] Specific operation: The server selects suitable corporate users for business proposals with high evaluation scores and sends them invitation emails containing a link to the auction platform.

[0856] Step 7:

[0857] Corporate users receive an invitation email, log in to the auction platform, and place a bid to win the right to purchase the proposal.

[0858] Input: Corporate user bid amount

[0859] Output: Record of bidding results

[0860] Specific operation: The corporate user clicks the link in the invitation email, logs in to the auction platform, enters the bid amount, and presses the bid button. The bid results are recorded on the server.

[0861] Step 8:

[0862] At the end of the auction, the server identifies the highest bidder and initiates the process of transferring the business proposal rights.

[0863] Input: Auction bid results

[0864] Output: Initiation and notification of transfer procedure

[0865] Specific operation: After the auction ends, the server checks the highest bid and notifies the bidding company of the details of the procedure for transferring the bid rights.

[0866] Step 9:

[0867] The corporate user will receive a confirmation of the successful bid and proceed with the rights transfer procedure for the business proposal.

[0868] Input: Notification of details of rights transfer procedure

[0869] Output: Transfer of rights completed

[0870] Specific operation: The corporate user provides the necessary information for the rights transfer according to the notified procedure, and the rights transfer is finally completed.

[0871] 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.

[0872] This invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[0873] 1. Idea collection

[0874] User

[0875] Log in to the platform and access the idea submission form. When entering the required information (title, summary, detailed description), the emotion engine is also used to obtain the user's emotional data at the time of entry. When the user presses the submit button, this information is sent to the server.

[0876] server

[0877] The submitted idea and emotion data is received and stored in the database. Once the data is stored, a data reception confirmation notification is sent to the user.

[0878] 2. Collecting and learning from past data

[0879] server

[0880] Collect historical data on business ideas and their success (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[0881] The collected data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[0882] 3. Evaluating ideas

[0883] server

[0884] The emotional data obtained by the emotion engine, along with new business ideas received from users, is analyzed based on evaluation criteria. Using AI technology, the emotional data is reflected when quantifying the probability of commercialization success for each idea.

[0885] The evaluation results are stored in a database, and the user is notified of the evaluation results of the idea.

[0886] 4. Selection of companies suitable for commercialization and holding an auction

[0887] server

[0888] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select companies that can easily commercialize these ideas.

[0889] Selected companies will be sent an invitation to participate in the auction via email or notification.

[0890] Corporate Users

[0891] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[0892] 5. Auction Results and Transfer of Rights

[0893] server

[0894] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[0895] Corporate Users

[0896] Once you receive the successful bid, you will proceed with the procedures to acquire the idea rights.

[0897] Specific examples

[0898] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[0899] User

[0900] Access the platform and enter "AI-based personalized content suggestion system" as the title. Enter a summary and detailed description, and emotional data will be collected in real time as you enter it. Send all information and emotional data.

[0901] server

[0902] The received ideas and sentiment data are stored and analyzed. If the idea is deemed to have a high probability of commercialization, a suitable content distribution service company will be selected and invited to participate in the auction.

[0903] Corporate Users

[0904] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[0905] Through the above process, the present invention provides a system that utilizes an emotion engine to evaluate and commercialize new business ideas while taking into account the emotional value of users. This system improves the accuracy of evaluation and the likelihood of commercialization.

[0906] The processing flow will be explained below.

[0907] Step 1:

[0908] User: Logs in to the platform and accesses the idea submission form. While entering the title, summary, and detailed description, the emotion engine also collects the user's emotion data in real time. After entering all the information and emotion data, the user clicks the submit button.

[0909] Step 2:

[0910] Server: Receives business ideas and sentiment data sent by users via REST API, saves the data in the database, and notifies the user that the data has been saved.

[0911] Step 3:

[0912] Server: Collects historical data on business ideas and their success stories (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[0913] Step 4:

[0914] Server: The collected data is input into the AI ​​model and it learns, generating evaluation criteria for new business ideas and saving them in a database.

[0915] Step 5:

[0916] Server: Analyzes new business ideas received from users and the emotional data acquired by the emotion engine based on evaluation criteria. AI technology is used to quantify the probability of commercialization success for each idea, and the emotional data is reflected in the score.

[0917] Step 6:

[0918] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[0919] Step 7:

[0920] Server: Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success. We will then select companies that can easily commercialize these ideas.

[0921] Step 8:

[0922] Server: Sends emails or notifications to selected companies inviting them to participate in the auction.

[0923] Step 9:

[0924] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[0925] Step 10:

[0926] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[0927] Step 11:

[0928] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[0929] Step 12:

[0930] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[0931] Example 2

[0932] 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."

[0933] Conventional systems evaluate new business ideas without considering their emotional value, which means they cannot accurately reflect the true potential of the ideas submitted by users. Furthermore, they lack important information, such as emotional data, in the idea evaluation and commercialization process, which reduces the accuracy of predicting the probability of success.

[0934] 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.

[0935] In this invention, the server includes a means for receiving new business ideas from individuals or corporations and storing them together with emotional data, a means for collecting and learning data on past business ideas and their commercial successes, as well as past emotional data, and a means for using AI technology to analyze new business ideas based on evaluation criteria and taking the emotional data into account when quantifying the probability of their commercial success. This enables more accurate evaluation of business ideas and prediction of the probability of commercial success by taking the emotional data into account.

[0936] "Individual or Legal Entity" refers to a user as an individual or a legal entity such as a company or organization.

[0937] "Business ideas" refer to business proposals and plans for new products, services, business models, etc.

[0938] "Emotion data" refers to data that expresses the user's emotional state in the form of numbers, text, or the like.

[0939] "Means for storing" refers to the function of storing received information in a database or storage.

[0940] "Past business ideas" refers to historical data on business ideas that have been submitted to date.

[0941] "Commercialization success data" refers to data showing the results and achievements of business ideas that have been commercialized to date.

[0942] "Means of learning" refers to the function of training an AI model using collected data.

[0943] "AI technology" refers to artificial intelligence technology in general, and particularly includes machine learning and natural language processing models.

[0944] "Evaluation criteria" refers to the metrics or scoring rules used to evaluate business ideas.

[0945] "Means of analysis" refers to the function of analyzing and evaluating data using AI technology.

[0946] "Means of quantification" refers to the function of quantifying the probability of success of a business idea.

[0947] "Enterprise" refers to a legal entity that has the ability and desire to commercialize a business idea.

[0948] An "auction" refers to the process of bidding on business ideas and the highest bidder wins the right to purchase them.

[0949] "Assignment process" refers to the process by which the rights to an idea are officially transferred to the highest bidding company.

[0950] The present invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The details of the implementation of this system and the operation of the program are described below.

[0951] Idea collection

[0952] User

[0953] Users log in to the platform and access the form for submitting ideas. Here, they enter a title, summary, and detailed description in the form. Furthermore, an emotion engine runs in the background, capturing emotional data in real time as the user types. Once users have completed entering information and pressed the submit button, this information is sent to the server.

[0954] server

[0955] The server receives the idea and emotion data sent by the user and stores this information in a database. After storing the information, it sends a data reception confirmation notice to the user. The database used is, for example, MySQL or PostgreSQL.

[0956] Collecting and learning from past data

[0957] server

[0958] The server collects data on past business ideas and their success (e.g., target market, revenue, implementation technology, etc.), as well as past sentiment data. This data is then prepared for input into an AI model (e.g., TensorFlow or PyTorch).

[0959] The server inputs the collected data into the AI ​​model, which then learns to generate evaluation criteria, which are then stored in a database.

[0960] Idea Evaluation

[0961] server

[0962] The server analyzes new business ideas and emotional data received from users using evaluation criteria based on past data. Using AI technology (natural language processing models and machine learning algorithms), it quantifies the idea's probability of commercial success as a score, which also reflects the emotional data. The evaluation results are stored in a database and the user is notified of the results.

[0963] Selection of companies suitable for commercialization and holding an auction

[0964] server

[0965] Based on the evaluation results, ideas deemed to have a high probability of commercialization will be listed, and companies suitable for commercialization will be selected. Selected companies will be invited to participate in the auction via email or notification.

[0966] Corporate Users

[0967] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to win the right to purchase the idea.

[0968] Auction Results and Transfer of Rights

[0969] server

[0970] At the end of the auction, the highest bidder will be identified and the process of transferring the idea rights will begin, which will then be recorded in the database as a completed transfer and notify the relevant parties.

[0971] Corporate Users

[0972] The corporate user receives the successful bid notification and proceeds with the procedures for acquiring the idea rights.

[0973] Specific examples

[0974] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[0975] User

[0976] Users access the platform and enter the title "AI-based personalized content suggestion system." They then enter a summary and detailed description, and emotional data is collected in real time as they enter the information. All information and emotional data is then sent.

[0977] server

[0978] The server stores the received ideas and emotional data and analyzes them using AI technology. If the idea is deemed to have a high probability of commercialization, it selects appropriate content distribution service companies and invites them to participate in the auction.

[0979] Corporate Users

[0980] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[0981] This system allows for the evaluation and commercialization of new business ideas that take into account the emotional value of users, resulting in more accurate evaluation and improved likelihood of commercialization.

[0982] Prompt Sentence Examples

[0983] Please tell us the details of the implementation of a system that will be offered to companies in an auction format to evaluate a new business idea called "a personalized content suggestion system using AI" and collect emotional data to increase the probability of commercialization success.

[0984] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0985] Step 1:

[0986] User: Platform login

[0987] A user accesses the platform and logs in by entering their authentication information (user ID, password) on the login screen. The authentication information is sent to the server, which then collates it with the database to authenticate the user. After successful authentication, a form screen for submitting ideas is displayed on the user's device. Input data: user ID, password. Output data: idea submission form.

[0988] Step 2:

[0989] User: Fill out the idea submission form

[0990] The user enters a title, summary, and detailed description into the submission form. While the user is entering data, the emotion engine runs in the background and collects emotional data in real time as the user enters the information. Emotional data is collected using, for example, a webcam or microphone. Input data: Title, summary, detailed description. Output data: Emotional data as the user enters the information.

[0991] Step 3:

[0992] User: Submit information

[0993] When the user presses the send button, the title, summary, detailed description, and emotion data are sent to the server. The server temporarily stores the received information in memory and begins the database storage process. Input data: title, summary, detailed description, emotion data. Output data: Data sent to the server completed.

[0994] Step 4:

[0995] Server: Data storage

[0996] The server stores the received idea information and emotion data in a database. Once the database storage is complete, a data reception confirmation notification is sent to the user. Input data: idea information, emotion data. Output data: data storage completion notification.

[0997] Step 5:

[0998] Server: Collection of historical data

[0999] The server collects past business ideas, commercial success data, and emotional data from a database. The collected data is preprocessed to train the AI ​​model. Input data: past business ideas, commercial success data, and emotional data. Output data: preprocessed training data.

[1000] Step 6:

[1001] Server: Preparing training data

[1002] The server converts the preprocessed data into a format appropriate for the AI ​​model (e.g., TensorFlow or PyTorch). Data processing is performed to convert it into the appropriate format. Input data: Preprocessed training data. Output data: Data in the AI ​​model input format.

[1003] Step 7:

[1004] Server: AI model training

[1005] The server inputs data into the AI ​​model and performs learning to generate evaluation criteria. The evaluation criteria generated through learning are stored in a database. Input data: Data in the AI ​​model input format. Output data: Evaluation criteria.

[1006] Step 8:

[1007] Server: Evaluating ideas

[1008] The server analyzes the new business idea and sentiment data received from the user based on the generated evaluation criteria. Natural language processing models and machine learning algorithms are used for the analysis. Input data: new business idea, sentiment data, evaluation criteria. Output data: score of the probability of commercialization success.

[1009] Step 9:

[1010] Server: Evaluation result storage and notification

[1011] The server stores the evaluation results of the probability of commercial success in a database and notifies the user of the evaluation results of the idea. Input data: Score of the probability of commercial success. Output data: Notification of evaluation results.

[1012] Step 10:

[1013] Server: Company Selection

[1014] The server lists ideas with a high probability of commercialization success and selects suitable companies. Selected companies are then invited to participate in the auction via email or notification. Input data: Ideas with a high probability of commercialization success. Output data: List of selected companies, invitation email.

[1015] Step 11:

[1016] Corporate users: Participating in auctions

[1017] Corporate users receive an invitation email and log in to the auction platform. They then participate in the auction from their own accounts and place bids to obtain the right to purchase ideas. Input data: invitation email, account information. Output data: auction participation, bid.

[1018] Step 12:

[1019] Server: Confirmation of auction results and transfer of rights

[1020] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. The transfer completion information is recorded in the database and notified to the relevant parties. Input data: Auction results. Output data: Notification of transfer procedure completion.

[1021] Step 13:

[1022] Corporate users: Rights acquisition procedure

[1023] The corporate user receives the successful bid notification and proceeds with the procedures to acquire the idea rights. Finally, a new service is developed based on the acquired rights and released to the market. Input data: successful bid notification. Output data: Rights acquired, new service developed.

[1024] (Application example 2)

[1025] 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."

[1026] Conventional business idea evaluation systems fail to consider user emotions or intuitive values ​​when quantitatively assessing the probability of an idea's commercialization success. This can result in the idea's true value being overlooked, hindering its commercialization. Furthermore, the process of selecting appropriate companies and holding auctions based on the evaluation results is inefficient. An effective system is needed to collect user emotion data and evaluate ideas based on it.

[1027] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1028] In this invention, the server includes means for receiving and storing new business ideas from individuals or corporations, means for collecting and learning data on past business ideas and their successful commercialization, means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success, means for collecting emotional data when the idea is submitted and reflecting this in the evaluation, means for selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas, and means for transferring the idea rights to the company with the highest bid in the auction. This makes it possible to more accurately evaluate the value of business ideas while taking user emotions into consideration and improve the probability of successful commercialization.

[1029] 1. A "business idea" is a creative concept or proposal for a new product, service, process, or business model, originating from an individual or legal entity.

[1030] 2. "Emotional Data" refers to data that quantifies or categorizes the emotional reactions or states that users show when submitting ideas.

[1031] 3. "Evaluation Criteria" means indicators or standards based on AI technology that use historical and sentiment data to measure the value of new business ideas and the probability of commercial success.

[1032] 4. "Probability of commercial success" is the statistical probability that a particular business idea will be successful and profitable when brought to market.

[1033] 5. "AI technology" refers to a group of technologies that use advanced algorithms such as machine learning and deep learning to analyze data and make predictions and decisions.

[1034] 6. "Enterprise" means a legal entity or organization that has the ability to purchase and implement business ideas for commercialization.

[1035] 7. An "auction" is a process in which participating companies compete for the right to purchase an idea, with the highest bidder winning the right.

[1036] 8. "Transfer Procedure" refers to the process of transferring the rights to an idea to a company that has won the right to purchase the idea in an auction, by carrying out the necessary legal and contractual procedures.

[1037] This invention is a system that collects new business ideas from users, evaluates them, and provides them to companies suitable for commercialization. The core of this system involves evaluating business ideas including emotional data, and transferring idea rights through an auction format.

[1038] System configuration

[1039] 1. User Device:

[1040] Users submit new business ideas using a smartphone application. As they submit their ideas, an emotion engine collects emotional data in real time as they type. Emotional data is obtained from the user's facial expressions, voice, and tone of voice as they type.

[1041] 2. Server:

[1042] The server has the following main functions:

[1043] Data reception and storage: Receive business ideas and sentiment data sent by users and store them in a database.

[1044] Evaluation by AI model: The AI ​​model is trained using collected data on past business ideas and sentiment data. It analyzes new business ideas based on evaluation criteria and quantifies their probability of commercialization.

[1045] Auction management: Select suitable companies based on the probability of commercialization success, hold an auction, and manage the process of transferring idea rights to the highest bidder.

[1046] Hardware and software used

[1047] Hardware:

[1048] Server: A high-performance server for storing data, running AI models, and managing auctions.

[1049] User device: Smartphone, tablet, etc.

[1050] software:

[1051] Flask: A framework for providing APIs and receiving requests from users.

[1052] EmotionEngine: A library for collecting and analyzing user emotion data.

[1053] AI Model: Uses machine learning algorithms to learn from historical data and evaluate new business ideas.

[1054] Database: A relational database for storing ideas, sentiment data, and evaluation results.

[1055] Specific examples

[1056] As a concrete example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI." A user uses the system as follows:

[1057] 1. User Action:

[1058] The user launches the smartphone app and accesses a form to submit a business idea. They enter "AI-based personalized content suggestion system" as the title, and then fill in a summary and detailed description. During this process, the emotion engine collects emotion data in real time. All information and emotion data is sent.

[1059] 2. Server processing:

[1060] The server stores and analyzes the received ideas and sentiment data. The AI ​​model evaluates them and calculates the probability of commercialization success. Based on the evaluation results, suitable content distribution service companies are selected and invited to participate in the auction.

[1061] 3. Enterprise operations:

[1062] Invited companies log in to the auction platform and make bids to win the right to purchase the idea. The highest bidder will acquire the rights to the idea and develop and deploy a new service.

[1063] Prompt Sentence Examples

[1064] The prompt that users use to submit their ideas is as follows:

[1065] Title: "AI-based personalized content suggestion system"

[1066] Summary: "This system is a service that suggests individually optimized content based on the user's emotional data."

[1067] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1068] Step 1:

[1069] Submit your business idea

[1070] User input: A user launches a smartphone application and inputs a new business idea. They fill out a form with a title, summary, and detailed description. During this process, the emotion engine collects emotional data in real time from the user's facial expressions, voice, and tone of voice.

[1071] Data processing and data calculation: The text data entered by the user and the emotion data collected by the emotion engine are organized into JSON format data and sent to the server.

[1072] Output: The server receives the idea data and emotion data sent by the user.

[1073] Step 2:

[1074] Data storage

[1075] Server input: Business idea data and sentiment data received in step 1.

[1076] Data processing and data calculation: The server connects to the database and stores the received idea data and emotion data in the database in an appropriate format. The data is stored in the form of ID, user ID, title, summary, details, emotion data, etc.

[1077] Output: A message is generated to confirm the data save and notify the user.

[1078] Step 3:

[1079] Evaluation preparation using AI models

[1080] Server input: Past business idea data, commercial success data, and sentiment data obtained from the database.

[1081] Data processing and data calculation: The server inputs past business idea data and its sentiment data into the AI ​​model for learning. The AI ​​model generates evaluation criteria based on this data and prepares to evaluate new business ideas.

[1082] Output: A generative AI model with updated evaluation metrics.

[1083] Step 4:

[1084] Evaluating new ideas

[1085] Server input: new business idea data and sentiment data received from users, and the updated generative AI model.

[1086] Data processing and calculation: The AI ​​model analyzes new business ideas submitted by users based on evaluation criteria. The evaluation, including emotional data, quantifies the probability of commercialization success.

[1087] Output: A score indicating the probability of commercial success is generated and stored in a database. The user is notified of the evaluation result.

[1088] Step 5:

[1089] Holding an auction

[1090] Server input: Evaluated business idea data and their commercial success probability scores.

[1091] Data processing and data calculation: The server selects companies that are likely to commercialize the idea based on the probability of commercialization success, and sends an invitation to participate in the auction to the selected companies via email or notification.

[1092] Output: The companies participating in the auction are determined and the auction platform is set up.

[1093] Step 6:

[1094] Auction execution and notification of results

[1095] Server input: Bid data of companies participating in the auction.

[1096] Data processing and data calculation: The server collects and analyzes the bidding data during the auction period and determines the highest bidder.

[1097] Output: The company selected as the highest bidder at the end of the auction will begin the process of transferring the idea rights. The auction results will be notified to the user and participating companies.

[1098] Step 7:

[1099] Completion of the transfer of rights

[1100] Server input: Data of the highest bidding company and business idea rights information.

[1101] Data processing and data operation: The server will carry out the transfer procedures for the idea rights in accordance with the law and contract, record the completion of the transfer in the database, and notify the relevant parties.

[1102] Output: Record and notification of completed title transfer.

[1103] 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.

[1104] 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.

[1105] 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.

[1106] [Third embodiment]

[1107] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1108] 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.

[1109] 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).

[1110] 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.

[1111] 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.

[1112] 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).

[1113] 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. 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.

[1114] 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.

[1115] 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.

[1116] 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.

[1117] 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.

[1118] 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."

[1119] This invention is a system that uses AI technology to evaluate new business ideas collected from individuals and corporations, and provides the rights to these ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[1120] 1. Idea collection

[1121] User

[1122] Users log in to the platform and enter the required information in the idea submission form. Required information includes a title, summary, and detailed description. When users press the submit button, this information is sent to the server.

[1123] server

[1124] The submitted ideas are received and stored in the database. Once the storage is complete, a data reception confirmation notice is sent to the user.

[1125] 2. Collecting and learning from past data

[1126] server

[1127] Collect data on the business idea's past success, including target market, revenue, implementation technology, etc.

[1128] This data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[1129] 3. Evaluating ideas

[1130] server

[1131] The collected new business ideas are analyzed based on evaluation criteria, and AI technology is used to quantify the probability of each idea being successfully commercialized.

[1132] The evaluation results are stored in a database and notified to the user.

[1133] 4. Selection of companies suitable for commercialization and holding an auction

[1134] server

[1135] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select suitable companies to hold an auction for these ideas.

[1136] Selected companies will be sent an invitation to participate in the auction via email and notification.

[1137] Corporate Users

[1138] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[1139] 5. Auction Results and Transfer of Rights

[1140] server

[1141] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[1142] Corporate Users

[1143] Once you receive confirmation of your successful bid, you can begin the process of transferring the rights to your idea.

[1144] Specific examples

[1145] As an example, consider the idea of ​​a new content distribution method: "A personalized content suggestion system using AI."

[1146] User

[1147] Access the platform, fill in the form with specific details, and submit it.

[1148] server

[1149] The received ideas are stored and analyzed based on evaluation criteria. If an idea is deemed to have a high probability of commercialization, suitable content distribution service companies will be selected and invited to participate in the auction.

[1150] Corporate Users

[1151] Companies participate in the auction, and the highest bidder acquires the rights to the idea. They then develop new services based on the acquired rights and bring them to market.

[1152] In this way, the present invention realizes a system that utilizes AI technology to appropriately evaluate many business ideas and provide them to companies that can make the most use of them.

[1153] The processing flow will be explained below.

[1154] Step 1:

[1155] User: Log in to the platform, access the idea submission form, enter the required information (title, summary, detailed description), and click the submit button.

[1156] Step 2:

[1157] Server: Receives ideas sent by users via the REST API, saves the received data in a database, and notifies the user when the data has been saved.

[1158] Step 3:

[1159] Server: Collects data on past business ideas and their success (target market, revenue, implementation technology, etc.).

[1160] Step 4:

[1161] Server: Inputs the collected data into the AI ​​model, allowing it to learn, then generates criteria for evaluating new business ideas and stores those criteria in a database.

[1162] Step 5:

[1163] Server: Analyzes new business ideas received from users based on evaluation criteria, and uses AI technology to score the probability of commercialization success for each idea.

[1164] Step 6:

[1165] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[1166] Step 7:

[1167] Server: Based on the evaluation results, it lists ideas with a high probability of commercialization success and selects companies that can easily commercialize those ideas.

[1168] Step 8:

[1169] Server: Sends invitations to selected companies to participate in the auction via email or notification.

[1170] Step 9:

[1171] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[1172] Step 10:

[1173] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[1174] Step 11:

[1175] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[1176] Step 12:

[1177] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[1178] Example 1

[1179] 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."

[1180] In conventional business idea evaluation systems, ideas collected from individuals and corporations are often not properly evaluated, resulting in ideas being left unattended without sufficient consideration of their commercialization potential. Furthermore, the evaluation criteria are inconsistent, leading to unreliable evaluation results. Furthermore, the process for effectively selecting companies suitable for commercialization and holding auctions is insufficient, resulting in delays in the realization of ideas.

[1181] 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.

[1182] In this invention, the server includes a means for receiving and storing new business ideas from individuals or corporations, a means for collecting and learning from past data on business ideas and their commercialization success records, and a means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success. This enables a consistent and efficient process for evaluating and commercializing new business ideas. Furthermore, users can log in to the platform and submit their ideas, making the system easy to use. Furthermore, the AI ​​model is used to generate evaluation criteria and quantify the probability of commercialization success, improving the reliability of the evaluation results. Selected companies are invited to participate in an auction, and a means for companies to participate in the auction and acquire ideas allows for the rapid realization of business ideas.

[1183] "Individual or Legal Entity" means the entity that creates and submits a business idea to the system.

[1184] A "new business idea" is an innovative business concept or technology that has not yet appeared on the market.

[1185] "Means for receiving and storing" refers to the mechanism by which the system receives business ideas sent by users and stores them in a database or storage.

[1186] "Past data on business ideas" refers to information about previously submitted business ideas, including data on past successes and market trends.

[1187] "Commercialization success data" is information indicating whether past business ideas have actually been brought to market and achieved success.

[1188] "Means of collecting and learning" refers to the process of statistically analyzing past business ideas and their success stories, inputting them into an AI model, and having it learn.

[1189] "AI technology" refers to artificial intelligence technology that can mimic human judgment and analyze large data sets. Typical examples include machine learning and deep learning.

[1190] "Evaluation criteria" are indicators used to analyze new business ideas and evaluate the probability of commercialization success.

[1191] "Means of analysis and quantification" refers to a method of using AI technology to evaluate business ideas as a numerical score.

[1192] The "evaluation result" is a score that indicates the probability of successful commercialization after analyzing a business idea using AI technology.

[1193] "Companies suitable for commercialization" are those that are judged based on the evaluation results to have a high probability of realizing new business ideas in the market.

[1194] An "idea purchase rights auction" is a process in which companies bid for the rights to a new business idea, and the highest bidder acquires the rights.

[1195] An "Invitation to Auction" is an official communication offering selected companies the opportunity to acquire the idea rights.

[1196] The "Transfer of Rights Process" is a set of legal and business procedures for formally transferring ownership of a business idea to the highest bidder after the auction ends.

[1197] "Means for logging into the platform" means the authentication mechanism by which a user accesses the system and logs into their account.

[1198] "Means for submitting ideas by entering necessary information" is a function for entering information such as a title, summary, detailed description, etc. and sending it to the server.

[1199] "Means of inputting past data and data on successful performance into an AI model, allowing it to learn and generate" refers to a function that inputs collected data into an AI model to generate evaluation criteria and automatically updates the evaluation criteria.

[1200] "Method of analyzing new business ideas using AI technology and quantifying the probability of commercialization success" is a method of analyzing business ideas using AI technology and expressing the probability of commercialization success as a score.

[1201] The "means for inviting participants to participate in the auction" is a function for sending invitations to selected companies to participate in the auction of idea rights.

[1202] "A process by which companies participating in an auction bid for the right to purchase an idea" is a process by which selected companies compete in an auction for the right to purchase an idea.

[1203] This invention is a system for evaluating new business ideas submitted by individuals or corporations and providing them to companies suitable for commercialization. This system is composed of a server, terminals, and users.

[1204] 1. Idea collection

[1205] User:

[1206] First, users access the platform and are authenticated by entering their username and password on the login screen. After successfully logging in, they proceed to the idea submission form from the dashboard, enter the title, summary, and detailed description, and submit.

[1207] server:

[1208] The server receives the idea information sent by the user and stores it in a database. Once the data has been saved, it sends a notification to the user confirming receipt of the data. The platform's authentication and data storage functions are implemented using standard web servers (e.g., Apache or Nginx) and database servers (e.g., MySQL or PostgreSQL).

[1209] 2. Collecting and learning from past data

[1210] server:

[1211] The server collects past data on business ideas and commercial success data from external APIs or internal databases. The server inputs the collected data into an AI model and performs learning to generate evaluation criteria. Specifically, the AI ​​model is trained using frameworks such as TensorFlow and PyTorch. The training progress is displayed to the administrator in real time on the terminal.

[1212] 3. Evaluating ideas

[1213] server:

[1214] The server reads new business ideas collected from the database and analyzes them based on evaluation criteria using AI technology. The probability of commercialization success is quantified as a score and the evaluation results are saved in the database. After the evaluation results are generated, they are notified to the user.

[1215] 4. Selection of companies suitable for commercialization and holding an auction

[1216] server:

[1217] Based on the evaluation results, the server creates a list of business ideas with a high probability of commercialization success and selects the most suitable companies. The server determines suitability using past transaction data and company profiles. Selected companies are notified by email with an invitation to participate in the auction.

[1218] Corporate users:

[1219] Selected corporate users will receive an invitation email and log in to the auction platform to bid for the right to purchase the business idea. The server updates the bidding information in real time and monitors the auction status.

[1220] 5. Auction Results and Transfer of Rights

[1221] server:

[1222] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. Once the transfer procedure is complete, the server records the information in a database and notifies the parties involved.

[1223] Corporate users:

[1224] The highest bidder, the corporate user, will receive a notice of successful bid and proceed with the idea rights transfer procedure, allowing the company to develop a new service based on the purchased business idea and bring it to market.

[1225] Examples and prompts

[1226] As a concrete example, let's take a business idea called "a system for proposing personalized content using AI." When this idea is submitted, the user logs into the platform, enters the title and details of the idea into a form, and submits it. The server receives the idea, evaluates it using an AI model, and calculates a score representing the probability of commercialization success. If the score is high, suitable companies are invited to participate in the auction. Corporate users then participate in the auction and acquire the rights to the idea.

[1227] Examples of prompts include:

[1228] "What information do I need in a dataset to train an AI model that will assess the success probability of a new business idea?"

[1229] "How can I provide a business idea with potential for commercialization to the right company?"

[1230] Using such prompts increases the accuracy and efficiency of the system, which leverages AI technology to quickly and accurately evaluate business ideas and provide them to the right companies, facilitating their realization.

[1231] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1232] Step 1:

[1233] User accesses the platform

[1234] Input: Username, Password

[1235] How it works: A user accesses the platform's login screen and enters their username and password.

[1236] Output: Sending authentication information

[1237] The server performs authentication

[1238] Input: Username, Password

[1239] Data calculation: The server checks the entered username and password against the credentials stored in the database.

[1240] Output: Authentication result

[1241] The device displays the dashboard

[1242] Input: Authentication result

[1243] Behavior: If authentication is successful, the user's dashboard screen is displayed on the device.

[1244] Output: Dashboard screen

[1245] Step 2:

[1246] User proceeds to idea submission form

[1247] Input: User actions

[1248] How it works: A user navigates to the idea submission form from the dashboard and fills in the fields, specifically the title, summary, and description.

[1249] Output: Idea information

[1250] The device temporarily stores and transmits the idea information

[1251] Input: Idea information

[1252] Data processing: Idea information is temporarily stored in cache memory.

[1253] Behavior: When the user presses the submit button, the idea information is sent to the server as a POST request.

[1254] Output: POST request

[1255] The server receives and stores the idea information

[1256] Input: POST request

[1257] Data processing: idea information is stored in a database.

[1258] Behavior: Once the data has been saved, the server will send a confirmation to the user.

[1259] Output: Save completion notification

[1260] Step 3:

[1261] The server collects past data

[1262] Input: Request to external API or internal database

[1263] Data collection: The server collects historical data on business ideas and their commercial success.

[1264] Output: Historical data

[1265] The server inputs data into the AI ​​model and it learns

[1266] Input: Historical data

[1267] Data calculation: The data collected by the server is input into an AI model (e.g., TensorFlow or PyTorch) and trained to generate evaluation criteria.

[1268] Output: Evaluation criteria

[1269] Your device displays your learning progress

[1270] Input: Learning progress

[1271] What it does: Shows learning progress to administrators in real time.

[1272] Output: progress indicator

[1273] Step 4:

[1274] Servers evaluate new ideas

[1275] Input: New business idea, evaluation criteria

[1276] Data calculation: The server analyzes new business ideas based on evaluation criteria and quantifies the probability of commercial success.

[1277] Output: Probability of commercial success score

[1278] The server saves the evaluation results and notifies you.

[1279] Input: Probability of commercial success score

[1280] Data processing: Save the scores to a database.

[1281] Action: Sends the user a notification of the evaluation results.

[1282] Output: Notification

[1283] Step 5:

[1284] Select a company suitable for commercialization of the server

[1285] Input: Evaluation results, company profile data

[1286] Data calculation: Based on the evaluation results and company profile data, companies with a high probability of commercialization success are selected.

[1287] Output: Selection result

[1288] The server sends the invitation to the company

[1289] Input: Selection result

[1290] How it works: The server sends email invitations to selected companies to participate in the auction.

[1291] Output: Invitation email

[1292] Corporate users participate in the auction and bid

[1293] Input: Invitation email

[1294] How it works: A corporate user receives an invitation email, logs into the auction platform, and places a bid for the right to purchase an idea from their account.

[1295] Output: Bid information

[1296] The server checks the auction results and starts the process

[1297] Input: Bid Information

[1298] Data calculation: Identify the highest bidder and initiate the idea rights transfer process.

[1299] Output: Notification of start of transfer procedure

[1300] Corporate users proceed with the rights transfer procedure

[1301] Input: Notice of commencement of transfer procedure

[1302] How it works: A corporate user goes through the transfer of rights process and prepares and completes the necessary paperwork.

[1303] Output: Completion report

[1304] The server records and notifies the completion of the transfer

[1305] Input: Completion report

[1306] Data processing: Record the transfer completion information in the database.

[1307] What it does: Sends notification to the parties involved that the transfer is complete.

[1308] Output: Completion notification

[1309] (Application example 1)

[1310] 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."

[1311] Previous business idea evaluation systems had unclear criteria for increasing the probability of commercialization success, and the evaluations were not always accurate. Furthermore, the process for providing evaluated business ideas to the most suitable companies was unclear, which could result in missed business opportunities. Furthermore, the means for participating in auctions for evaluated ideas were limited, making it inconvenient for companies.

[1312] 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.

[1313] In this invention, the server includes: means for receiving and storing new business proposals from individuals or corporations; means for collecting and learning data on past business proposals and their commercial success; means for using AI technology to analyze new business proposals based on evaluation criteria and quantify their commercialization success rates; means for selecting companies suitable for commercializing the evaluated business proposals and holding an auction for the right to purchase the proposals; means for transferring the proposal rights to the highest bidder in the auction; and, in the case of proposals related to content distribution services, means for companies to participate in the auction via a smartphone application for proposals that receive an evaluation score above a certain level. This enables accurate evaluation of business proposals and prompt provision of the proposals to the most suitable companies. Furthermore, companies can easily participate in the auction via the smartphone application, greatly improving convenience.

[1314] A "new business idea" is a proposal or concept for a new business devised by an individual or corporation.

[1315] "Past business proposals" are business proposals or ideas that have been proposed and implemented in some form.

[1316] "Commercialization success data" refers to data on the track record and results of business ideas that have been commercialized in the past.

[1317] "AI technology" refers to technology that uses artificial intelligence and makes decisions and predictions through machine learning and data analysis.

[1318] "Evaluation criteria" are standards for evaluating new business ideas, and include factors such as probability of success and market adaptability.

[1319] "Quantification" means expressing the evaluation of the target business proposal in concrete numerical terms.

[1320] An "auction" is a trading method in which multiple companies participate and bid for the right to purchase a target business proposal.

[1321] "Proposal Purchase Rights" means the right of the highest bidder in an auction to purchase a particular business proposal.

[1322] The "proposal rights transfer procedure" refers to the procedure for officially transferring the rights of a business proposal that has been won in an auction to the bidding company.

[1323] "Content distribution service" is a general term for services that distribute digital content to users.

[1324] A "smartphone application" is a software program that runs on a smartphone.

[1325] An "evaluation score" is a numerical representation of the evaluation result of a business proposal, and indicates the value and probability of success of the proposal.

[1326] An "enterprise" is a legal entity that operates with a specific business purpose.

[1327] The present invention is a system that uses AI technology to evaluate new business ideas collected from individuals or corporations and provides the rights to companies for commercialization. The following describes the details of the embodiment of this system and the operation of the program.

[1328] 1. Idea collection

[1329] User

[1330] Users log in to the platform and enter the necessary information (title, summary, detailed description) into the business proposal submission form. When the submit button is pressed, the information is sent to the server.

[1331] server

[1332] The server receives the business proposal and stores it in the database. Once the storage is complete, it sends a data reception confirmation notice to the user.

[1333] 2. Collecting and learning from past data

[1334] server

[1335] The server collects data on past business proposals and successful commercialization, including information on target markets, revenue, and implementation technologies. This data is input into an AI model, which learns to generate evaluation criteria. The generated evaluation criteria are stored in a database.

[1336] 3. Evaluating ideas

[1337] server

[1338] The server analyzes the collected new business ideas based on the evaluation criteria. At this time, AI technology is used to quantify the probability of commercialization success for each idea. The evaluation results are stored in a database and notified to the user.

[1339] 4. Selection of companies suitable for commercialization and holding an auction

[1340] server

[1341] Based on the evaluation results, the server will create a list of business proposals with a high probability of commercialization success. It will then select suitable companies to hold an auction for these proposals. It will then send invitations to the selected companies to participate in the auction via email and notifications.

[1342] Corporate Users

[1343] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to acquire the right to purchase the proposal.

[1344] 5. Auction Results and Transfer of Rights

[1345] server

[1346] At the end of the auction, the server identifies the highest bidder, initiates the transfer of the rights, records the completion of the transfer in the database, and notifies the parties involved.

[1347] Corporate Users

[1348] The corporate user receives a confirmation of the successful bid and proceeds with the proposal rights transfer procedure.

[1349] Example

[1350] Consider a business proposal called "a new personalized content proposal system." Users access the platform, enter specific details into a form, and submit it. The server saves the received proposal and analyzes it based on evaluation criteria. If the proposal is deemed to have a high probability of commercial success, a suitable content distribution service company is selected and invited to participate in an auction. The company participates in the auction and, as the highest bidder, acquires the rights to the proposal. A new service is developed based on the acquired rights and launched in the market.

[1351] Hardware and software used

[1352] Server: AWS EC2 (server hosting)

[1353] Database: AWS RDS (database management)

[1354] AI technology: scikit-learn (machine learning library)

[1355] Web framework: Flask (Python web framework)

[1356] API documentation: Swagger

[1357] Prompt Sentence Examples

[1358] Post a new personalized content suggestion system.

[1359] example:

[1360] Title: AI-powered personalized content suggestion system

[1361] What it is: AI suggests the best content based on a customer's browsing history.

[1362] Description: The system analyzes users' past browsing history and suggests content that best suits their interests.

[1363] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1364] Step 1:

[1365] Users log in to the platform, enter the required information (title, summary, detailed description) in the business proposal submission form, and submit it.

[1366] Input: Title, summary, detailed description

[1367] Output: Send data to the server

[1368] Specific operations: The user uses a web browser or smartphone application to access the platform's business proposal submission page, enter the required information, and press the submit button.

[1369] Step 2:

[1370] The server receives the submitted business proposal, stores it in a database, and sends a data reception confirmation notice to the user once the saving is complete.

[1371] Input: Business proposal data submitted by the user

[1372] Output: Save to database and confirmation notification

[1373] Specific operation: The server receives the sent data, stores it in the AWS RDS database, and sends a notification to the user after the data is saved.

[1374] Step 3:

[1375] The server collects data on past business proposals and successful commercializations to create a learning dataset.

[1376] Input: Existing business plan data and its commercial success record data

[1377] Output: Training dataset

[1378] Specific operation: The server collects past business plans and their performance data from the Internet and internal databases, and uses this to generate a learning dataset.

[1379] Step 4:

[1380] The server uses a generative AI model to learn the training dataset and generate evaluation criteria.

[1381] Input: Training dataset

[1382] Output: Evaluation criteria

[1383] Specific operation: The server uses the scikit-learn library to input the training dataset into the model, generate evaluation criteria, and store them in the database.

[1384] Step 5:

[1385] The server analyzes new business ideas sent by users based on evaluation criteria and quantifies the probability of commercial success as a score.

[1386] Input: New business idea data, evaluation criteria

[1387] Output: Probability of commercial success score

[1388] Specific operation: The server analyzes new business idea data based on the evaluation criteria and calculates the probability of commercial success as a score using a random forest model.

[1389] Step 6:

[1390] The server selects corporate users suitable for commercialization based on the scores of the evaluated business proposals and holds an auction for the right to purchase the proposals.

[1391] Input: Probability of commercial success score

[1392] Output: Selection and notification of auction participants

[1393] Specific operation: The server selects suitable corporate users for business proposals with high evaluation scores and sends them invitation emails containing a link to the auction platform.

[1394] Step 7:

[1395] Corporate users receive an invitation email, log in to the auction platform, and place a bid to win the right to purchase the proposal.

[1396] Input: Corporate user bid amount

[1397] Output: Record of bidding results

[1398] Specific operation: The corporate user clicks the link in the invitation email, logs in to the auction platform, enters the bid amount, and presses the bid button. The bid results are recorded on the server.

[1399] Step 8:

[1400] At the end of the auction, the server identifies the highest bidder and initiates the process of transferring the business proposal rights.

[1401] Input: Auction bid results

[1402] Output: Initiation and notification of transfer procedure

[1403] Specific operation: After the auction ends, the server checks the highest bid and notifies the bidding company of the details of the procedure for transferring the bid rights.

[1404] Step 9:

[1405] The corporate user will receive a confirmation of the successful bid and proceed with the rights transfer procedure for the business proposal.

[1406] Input: Notification of details of rights transfer procedure

[1407] Output: Transfer of rights completed

[1408] Specific operation: The corporate user provides the necessary information for the rights transfer according to the notified procedure, and the rights transfer is finally completed.

[1409] 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.

[1410] This invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[1411] 1. Idea collection

[1412] User

[1413] Log in to the platform and access the idea submission form. When entering the required information (title, summary, detailed description), the emotion engine is also used to obtain the user's emotional data at the time of entry. When the user presses the submit button, this information is sent to the server.

[1414] server

[1415] The submitted idea and emotion data is received and stored in the database. Once the data is stored, a data reception confirmation notification is sent to the user.

[1416] 2. Collecting and learning from past data

[1417] server

[1418] Collect historical data on business ideas and their success (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[1419] The collected data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[1420] 3. Evaluating ideas

[1421] server

[1422] The emotional data obtained by the emotion engine, along with new business ideas received from users, is analyzed based on evaluation criteria. Using AI technology, the emotional data is reflected when quantifying the probability of commercialization success for each idea.

[1423] The evaluation results are stored in a database, and the user is notified of the evaluation results of the idea.

[1424] 4. Selection of companies suitable for commercialization and holding an auction

[1425] server

[1426] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select companies that can easily commercialize these ideas.

[1427] Selected companies will be sent an invitation to participate in the auction via email or notification.

[1428] Corporate Users

[1429] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[1430] 5. Auction Results and Transfer of Rights

[1431] server

[1432] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[1433] Corporate Users

[1434] Once you receive the successful bid, you will proceed with the procedures to acquire the idea rights.

[1435] Specific examples

[1436] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[1437] User

[1438] Access the platform and enter "AI-based personalized content suggestion system" as the title. Enter a summary and detailed description, and emotional data will be collected in real time as you enter it. Send all information and emotional data.

[1439] server

[1440] The received ideas and sentiment data are stored and analyzed. If the idea is deemed to have a high probability of commercialization, a suitable content distribution service company will be selected and invited to participate in the auction.

[1441] Corporate Users

[1442] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[1443] Through the above process, the present invention provides a system that utilizes an emotion engine to evaluate and commercialize new business ideas while taking into account the emotional value of users. This system improves the accuracy of evaluation and the likelihood of commercialization.

[1444] The processing flow will be explained below.

[1445] Step 1:

[1446] User: Logs in to the platform and accesses the idea submission form. While entering the title, summary, and detailed description, the emotion engine also collects the user's emotion data in real time. After entering all the information and emotion data, the user clicks the submit button.

[1447] Step 2:

[1448] Server: Receives business ideas and sentiment data sent by users via REST API, saves the data in the database, and notifies the user that the data has been saved.

[1449] Step 3:

[1450] Server: Collects historical data on business ideas and their success stories (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[1451] Step 4:

[1452] Server: The collected data is input into the AI ​​model and it learns, generating evaluation criteria for new business ideas and saving them in a database.

[1453] Step 5:

[1454] Server: Analyzes new business ideas received from users and the emotional data acquired by the emotion engine based on evaluation criteria. AI technology is used to quantify the probability of commercialization success for each idea, and the emotional data is reflected in the score.

[1455] Step 6:

[1456] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[1457] Step 7:

[1458] Server: Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success. We will then select companies that can easily commercialize these ideas.

[1459] Step 8:

[1460] Server: Sends emails or notifications to selected companies inviting them to participate in the auction.

[1461] Step 9:

[1462] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[1463] Step 10:

[1464] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[1465] Step 11:

[1466] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[1467] Step 12:

[1468] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[1469] Example 2

[1470] 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."

[1471] Conventional systems evaluate new business ideas without considering their emotional value, which means they cannot accurately reflect the true potential of the ideas submitted by users. Furthermore, they lack important information, such as emotional data, in the idea evaluation and commercialization process, which reduces the accuracy of predicting the probability of success.

[1472] 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.

[1473] In this invention, the server includes a means for receiving new business ideas from individuals or corporations and storing them together with emotional data, a means for collecting and learning data on past business ideas and their commercial successes, as well as past emotional data, and a means for using AI technology to analyze new business ideas based on evaluation criteria and taking the emotional data into account when quantifying the probability of their commercial success. This enables more accurate evaluation of business ideas and prediction of the probability of commercial success by taking the emotional data into account.

[1474] "Individual or Legal Entity" refers to a user as an individual or a legal entity such as a company or organization.

[1475] "Business ideas" refer to business proposals and plans for new products, services, business models, etc.

[1476] "Emotion data" refers to data that expresses the user's emotional state in the form of numbers, text, or the like.

[1477] "Means for storing" refers to the function of storing received information in a database or storage.

[1478] "Past business ideas" refers to historical data on business ideas that have been submitted to date.

[1479] "Commercialization success data" refers to data showing the results and achievements of business ideas that have been commercialized to date.

[1480] "Means of learning" refers to the function of training an AI model using collected data.

[1481] "AI technology" refers to artificial intelligence technology in general, and particularly includes machine learning and natural language processing models.

[1482] "Evaluation criteria" refers to the metrics or scoring rules used to evaluate business ideas.

[1483] "Means of analysis" refers to the function of analyzing and evaluating data using AI technology.

[1484] "Means of quantification" refers to the function of quantifying the probability of success of a business idea.

[1485] "Enterprise" refers to a legal entity that has the ability and desire to commercialize a business idea.

[1486] An "auction" refers to the process of bidding on business ideas and the highest bidder wins the right to purchase them.

[1487] "Assignment process" refers to the process by which the rights to an idea are officially transferred to the highest bidding company.

[1488] The present invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The details of the implementation of this system and the operation of the program are described below.

[1489] Idea collection

[1490] User

[1491] Users log in to the platform and access the form for submitting ideas. Here, they enter a title, summary, and detailed description in the form. Furthermore, an emotion engine runs in the background, capturing emotional data in real time as the user types. Once users have completed entering information and pressed the submit button, this information is sent to the server.

[1492] server

[1493] The server receives the idea and emotion data sent by the user and stores this information in a database. After storing the information, it sends a data reception confirmation notice to the user. The database used is, for example, MySQL or PostgreSQL.

[1494] Collecting and learning from past data

[1495] server

[1496] The server collects data on past business ideas and their success (e.g., target market, revenue, implementation technology, etc.), as well as past sentiment data. This data is then prepared for input into an AI model (e.g., TensorFlow or PyTorch).

[1497] The server inputs the collected data into the AI ​​model, which then learns to generate evaluation criteria, which are then stored in a database.

[1498] Idea Evaluation

[1499] server

[1500] The server analyzes new business ideas and emotional data received from users using evaluation criteria based on past data. Using AI technology (natural language processing models and machine learning algorithms), it quantifies the idea's probability of commercial success as a score, which also reflects the emotional data. The evaluation results are stored in a database and the user is notified of the results.

[1501] Selection of companies suitable for commercialization and holding an auction

[1502] server

[1503] Based on the evaluation results, ideas deemed to have a high probability of commercialization will be listed, and companies suitable for commercialization will be selected. Selected companies will be invited to participate in the auction via email or notification.

[1504] Corporate Users

[1505] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to win the right to purchase the idea.

[1506] Auction Results and Transfer of Rights

[1507] server

[1508] At the end of the auction, the highest bidder will be identified and the process of transferring the idea rights will begin, which will then be recorded in the database as a completed transfer and notify the relevant parties.

[1509] Corporate Users

[1510] The corporate user receives the successful bid notification and proceeds with the procedures for acquiring the idea rights.

[1511] Specific examples

[1512] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[1513] User

[1514] Users access the platform and enter the title "AI-based personalized content suggestion system." They then enter a summary and detailed description, and emotional data is collected in real time as they enter the information. All information and emotional data is then sent.

[1515] server

[1516] The server stores the received ideas and emotional data and analyzes them using AI technology. If the idea is deemed to have a high probability of commercialization, it selects appropriate content distribution service companies and invites them to participate in the auction.

[1517] Corporate Users

[1518] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[1519] This system allows for the evaluation and commercialization of new business ideas that take into account the emotional value of users, resulting in more accurate evaluation and improved likelihood of commercialization.

[1520] Prompt Sentence Examples

[1521] Please tell us the details of the implementation of a system that will be offered to companies in an auction format to evaluate a new business idea called "a personalized content suggestion system using AI" and collect emotional data to increase the probability of commercialization success.

[1522] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1523] Step 1:

[1524] User: Platform login

[1525] A user accesses the platform and logs in by entering their authentication information (user ID, password) on the login screen. The authentication information is sent to the server, which then collates it with the database to authenticate the user. After successful authentication, a form screen for submitting ideas is displayed on the user's device. Input data: user ID, password. Output data: idea submission form.

[1526] Step 2:

[1527] User: Fill out the idea submission form

[1528] The user enters a title, summary, and detailed description into the submission form. While the user is entering data, the emotion engine runs in the background and collects emotional data in real time as the user enters the information. Emotional data is collected using, for example, a webcam or microphone. Input data: Title, summary, detailed description. Output data: Emotional data as the user enters the information.

[1529] Step 3:

[1530] User: Submit information

[1531] When the user presses the send button, the title, summary, detailed description, and emotion data are sent to the server. The server temporarily stores the received information in memory and begins the database storage process. Input data: title, summary, detailed description, emotion data. Output data: Data sent to the server completed.

[1532] Step 4:

[1533] Server: Data storage

[1534] The server stores the received idea information and emotion data in a database. Once the database storage is complete, a data reception confirmation notification is sent to the user. Input data: idea information, emotion data. Output data: data storage completion notification.

[1535] Step 5:

[1536] Server: Collection of historical data

[1537] The server collects past business ideas, commercial success data, and emotional data from a database. The collected data is preprocessed to train the AI ​​model. Input data: past business ideas, commercial success data, and emotional data. Output data: preprocessed training data.

[1538] Step 6:

[1539] Server: Preparing training data

[1540] The server converts the preprocessed data into a format appropriate for the AI ​​model (e.g., TensorFlow or PyTorch). Data processing is performed to convert it into the appropriate format. Input data: Preprocessed training data. Output data: Data in the AI ​​model input format.

[1541] Step 7:

[1542] Server: AI model training

[1543] The server inputs data into the AI ​​model and performs learning to generate evaluation criteria. The evaluation criteria generated through learning are stored in a database. Input data: Data in the AI ​​model input format. Output data: Evaluation criteria.

[1544] Step 8:

[1545] Server: Evaluating ideas

[1546] The server analyzes the new business idea and sentiment data received from the user based on the generated evaluation criteria. Natural language processing models and machine learning algorithms are used for the analysis. Input data: new business idea, sentiment data, evaluation criteria. Output data: score of the probability of commercialization success.

[1547] Step 9:

[1548] Server: Evaluation result storage and notification

[1549] The server stores the evaluation results of the probability of commercial success in a database and notifies the user of the evaluation results of the idea. Input data: Score of the probability of commercial success. Output data: Notification of evaluation results.

[1550] Step 10:

[1551] Server: Company Selection

[1552] The server lists ideas with a high probability of commercialization success and selects suitable companies. Selected companies are then invited to participate in the auction via email or notification. Input data: Ideas with a high probability of commercialization success. Output data: List of selected companies, invitation email.

[1553] Step 11:

[1554] Corporate users: Participating in auctions

[1555] Corporate users receive an invitation email and log in to the auction platform. They then participate in the auction from their own accounts and place bids to obtain the right to purchase ideas. Input data: invitation email, account information. Output data: auction participation, bid.

[1556] Step 12:

[1557] Server: Confirmation of auction results and transfer of rights

[1558] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. The transfer completion information is recorded in the database and notified to the relevant parties. Input data: Auction results. Output data: Notification of transfer procedure completion.

[1559] Step 13:

[1560] Corporate users: Rights acquisition procedure

[1561] The corporate user receives the successful bid notification and proceeds with the procedures to acquire the idea rights. Finally, a new service is developed based on the acquired rights and released to the market. Input data: successful bid notification. Output data: Rights acquired, new service developed.

[1562] (Application example 2)

[1563] 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."

[1564] Conventional business idea evaluation systems fail to consider user emotions or intuitive values ​​when quantitatively assessing the probability of an idea's commercialization success. This can result in the idea's true value being overlooked, hindering its commercialization. Furthermore, the process of selecting appropriate companies and holding auctions based on the evaluation results is inefficient. An effective system is needed to collect user emotion data and evaluate ideas based on it.

[1565] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1566] In this invention, the server includes means for receiving and storing new business ideas from individuals or corporations, means for collecting and learning data on past business ideas and their successful commercialization, means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success, means for collecting emotional data when the idea is submitted and reflecting this in the evaluation, means for selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas, and means for transferring the idea rights to the company with the highest bid in the auction. This makes it possible to more accurately evaluate the value of business ideas while taking user emotions into consideration and improve the probability of successful commercialization.

[1567] 1. A "business idea" is a creative concept or proposal for a new product, service, process, or business model, originating from an individual or legal entity.

[1568] 2. "Emotional Data" refers to data that quantifies or categorizes the emotional reactions or states that users show when submitting ideas.

[1569] 3. "Evaluation Criteria" means indicators or standards based on AI technology that use historical and sentiment data to measure the value of new business ideas and the probability of commercial success.

[1570] 4. "Probability of commercial success" is the statistical probability that a particular business idea will be successful and profitable when brought to market.

[1571] 5. "AI technology" refers to a group of technologies that use advanced algorithms such as machine learning and deep learning to analyze data and make predictions and decisions.

[1572] 6. "Enterprise" means a legal entity or organization that has the ability to purchase and implement business ideas for commercialization.

[1573] 7. An "auction" is a process in which participating companies compete for the right to purchase an idea, with the highest bidder winning the right.

[1574] 8. "Transfer Procedure" refers to the process of transferring the rights to an idea to a company that has won the right to purchase the idea in an auction, by carrying out the necessary legal and contractual procedures.

[1575] This invention is a system that collects new business ideas from users, evaluates them, and provides them to companies suitable for commercialization. The core of this system involves evaluating business ideas including emotional data, and transferring idea rights through an auction format.

[1576] System configuration

[1577] 1. User Device:

[1578] Users submit new business ideas using a smartphone application. As they submit their ideas, an emotion engine collects emotional data in real time as they type. Emotional data is obtained from the user's facial expressions, voice, and tone of voice as they type.

[1579] 2. Server:

[1580] The server has the following main functions:

[1581] Data reception and storage: Receive business ideas and sentiment data sent by users and store them in a database.

[1582] Evaluation by AI model: The AI ​​model is trained using collected data on past business ideas and sentiment data. It analyzes new business ideas based on evaluation criteria and quantifies their probability of commercialization.

[1583] Auction management: Select suitable companies based on the probability of commercialization success, hold an auction, and manage the process of transferring idea rights to the highest bidder.

[1584] Hardware and software used

[1585] Hardware:

[1586] Server: A high-performance server for storing data, running AI models, and managing auctions.

[1587] User device: Smartphone, tablet, etc.

[1588] software:

[1589] Flask: A framework for providing APIs and receiving requests from users.

[1590] EmotionEngine: A library for collecting and analyzing user emotion data.

[1591] AI Model: Uses machine learning algorithms to learn from historical data and evaluate new business ideas.

[1592] Database: A relational database for storing ideas, sentiment data, and evaluation results.

[1593] Specific examples

[1594] As a concrete example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI." A user uses the system as follows:

[1595] 1. User Action:

[1596] The user launches the smartphone app and accesses a form to submit a business idea. They enter "AI-based personalized content suggestion system" as the title, and then fill in a summary and detailed description. During this process, the emotion engine collects emotion data in real time. All information and emotion data is sent.

[1597] 2. Server processing:

[1598] The server stores and analyzes the received ideas and sentiment data. The AI ​​model evaluates them and calculates the probability of commercialization success. Based on the evaluation results, suitable content distribution service companies are selected and invited to participate in the auction.

[1599] 3. Enterprise operations:

[1600] Invited companies log in to the auction platform and make bids to win the right to purchase the idea. The highest bidder will acquire the rights to the idea and develop and deploy a new service.

[1601] Prompt Sentence Examples

[1602] The prompt that users use to submit their ideas is as follows:

[1603] Title: "AI-based personalized content suggestion system"

[1604] Summary: "This system is a service that suggests individually optimized content based on the user's emotional data."

[1605] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1606] Step 1:

[1607] Submit your business idea

[1608] User input: A user launches a smartphone application and inputs a new business idea. They fill out a form with a title, summary, and detailed description. During this process, the emotion engine collects emotional data in real time from the user's facial expressions, voice, and tone of voice.

[1609] Data processing and data calculation: The text data entered by the user and the emotion data collected by the emotion engine are organized into JSON format data and sent to the server.

[1610] Output: The server receives the idea data and emotion data sent by the user.

[1611] Step 2:

[1612] Data storage

[1613] Server input: Business idea data and sentiment data received in step 1.

[1614] Data processing and data calculation: The server connects to the database and stores the received idea data and emotion data in the database in an appropriate format. The data is stored in the form of ID, user ID, title, summary, details, emotion data, etc.

[1615] Output: A message is generated to confirm the data save and notify the user.

[1616] Step 3:

[1617] Evaluation preparation using AI models

[1618] Server input: Past business idea data, commercial success data, and sentiment data obtained from the database.

[1619] Data processing and data calculation: The server inputs past business idea data and its sentiment data into the AI ​​model for learning. The AI ​​model generates evaluation criteria based on this data and prepares to evaluate new business ideas.

[1620] Output: A generative AI model with updated evaluation metrics.

[1621] Step 4:

[1622] Evaluating new ideas

[1623] Server input: new business idea data and sentiment data received from users, and the updated generative AI model.

[1624] Data processing and calculation: The AI ​​model analyzes new business ideas submitted by users based on evaluation criteria. The evaluation, including emotional data, quantifies the probability of commercialization success.

[1625] Output: A score indicating the probability of commercial success is generated and stored in a database. The user is notified of the evaluation result.

[1626] Step 5:

[1627] Holding an auction

[1628] Server input: Evaluated business idea data and their commercial success probability scores.

[1629] Data processing and data calculation: The server selects companies that are likely to commercialize the idea based on the probability of commercialization success, and sends an invitation to participate in the auction to the selected companies via email or notification.

[1630] Output: The companies participating in the auction are determined and the auction platform is set up.

[1631] Step 6:

[1632] Auction execution and notification of results

[1633] Server input: Bid data of companies participating in the auction.

[1634] Data processing and data calculation: The server collects and analyzes the bidding data during the auction period and determines the highest bidder.

[1635] Output: The company selected as the highest bidder at the end of the auction will begin the process of transferring the idea rights. The auction results will be notified to the user and participating companies.

[1636] Step 7:

[1637] Completion of the transfer of rights

[1638] Server input: Data of the highest bidding company and business idea rights information.

[1639] Data processing and data operation: The server will carry out the transfer procedures for the idea rights in accordance with the law and contract, record the completion of the transfer in the database, and notify the relevant parties.

[1640] Output: Record and notification of completed title transfer.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] [Fourth embodiment]

[1645] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1646] 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.

[1647] 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).

[1648] 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.

[1649] 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.

[1650] 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).

[1651] 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. 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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."

[1658] This invention is a system that uses AI technology to evaluate new business ideas collected from individuals and corporations, and provides the rights to these ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[1659] 1. Idea collection

[1660] User

[1661] Users log in to the platform and enter the required information in the idea submission form. Required information includes a title, summary, and detailed description. When users press the submit button, this information is sent to the server.

[1662] server

[1663] The submitted ideas are received and stored in the database. Once the storage is complete, a data reception confirmation notice is sent to the user.

[1664] 2. Collecting and learning from past data

[1665] server

[1666] Collect data on the business idea's past success, including target market, revenue, implementation technology, etc.

[1667] This data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[1668] 3. Evaluating ideas

[1669] server

[1670] The collected new business ideas are analyzed based on evaluation criteria, and AI technology is used to quantify the probability of each idea being successfully commercialized.

[1671] The evaluation results are stored in a database and notified to the user.

[1672] 4. Selection of companies suitable for commercialization and holding an auction

[1673] server

[1674] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select suitable companies to hold an auction for these ideas.

[1675] Selected companies will be sent an invitation to participate in the auction via email and notification.

[1676] Corporate Users

[1677] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[1678] 5. Auction Results and Transfer of Rights

[1679] server

[1680] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[1681] Corporate Users

[1682] Once you receive confirmation of your successful bid, you can begin the process of transferring the rights to your idea.

[1683] Specific examples

[1684] As an example, consider the idea of ​​a new content distribution method: "A personalized content suggestion system using AI."

[1685] User

[1686] Access the platform, fill in the form with specific details, and submit it.

[1687] server

[1688] The received ideas are stored and analyzed based on evaluation criteria. If an idea is deemed to have a high probability of commercialization, suitable content distribution service companies will be selected and invited to participate in the auction.

[1689] Corporate Users

[1690] Companies participate in the auction, and the highest bidder acquires the rights to the idea. They then develop new services based on the acquired rights and bring them to market.

[1691] In this way, the present invention realizes a system that utilizes AI technology to appropriately evaluate many business ideas and provide them to companies that can make the most use of them.

[1692] The processing flow will be explained below.

[1693] Step 1:

[1694] User: Log in to the platform, access the idea submission form, enter the required information (title, summary, detailed description), and click the submit button.

[1695] Step 2:

[1696] Server: Receives ideas sent by users via the REST API, saves the received data in a database, and notifies the user when the data has been saved.

[1697] Step 3:

[1698] Server: Collects data on past business ideas and their success (target market, revenue, implementation technology, etc.).

[1699] Step 4:

[1700] Server: Inputs the collected data into the AI ​​model, allowing it to learn, then generates criteria for evaluating new business ideas and stores those criteria in a database.

[1701] Step 5:

[1702] Server: Analyzes new business ideas received from users based on evaluation criteria, and uses AI technology to score the probability of commercialization success for each idea.

[1703] Step 6:

[1704] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[1705] Step 7:

[1706] Server: Based on the evaluation results, it lists ideas with a high probability of commercialization success and selects companies that can easily commercialize those ideas.

[1707] Step 8:

[1708] Server: Sends invitations to selected companies to participate in the auction via email or notification.

[1709] Step 9:

[1710] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[1711] Step 10:

[1712] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[1713] Step 11:

[1714] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[1715] Step 12:

[1716] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[1717] Example 1

[1718] 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."

[1719] In conventional business idea evaluation systems, ideas collected from individuals and corporations are often not properly evaluated, resulting in ideas being left unattended without sufficient consideration of their commercialization potential. Furthermore, the evaluation criteria are inconsistent, leading to unreliable evaluation results. Furthermore, the process for effectively selecting companies suitable for commercialization and holding auctions is insufficient, resulting in delays in the realization of ideas.

[1720] 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.

[1721] In this invention, the server includes a means for receiving and storing new business ideas from individuals or corporations, a means for collecting and learning from past data on business ideas and their commercialization success records, and a means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success. This enables a consistent and efficient process for evaluating and commercializing new business ideas. Furthermore, users can log in to the platform and submit their ideas, making the system easy to use. Furthermore, the AI ​​model is used to generate evaluation criteria and quantify the probability of commercialization success, improving the reliability of the evaluation results. Selected companies are invited to participate in an auction, and a means for companies to participate in the auction and acquire ideas allows for the rapid realization of business ideas.

[1722] "Individual or Legal Entity" means the entity that creates and submits a business idea to the system.

[1723] A "new business idea" is an innovative business concept or technology that has not yet appeared on the market.

[1724] "Means for receiving and storing" refers to the mechanism by which the system receives business ideas sent by users and stores them in a database or storage.

[1725] "Past data on business ideas" refers to information about previously submitted business ideas, including data on past successes and market trends.

[1726] "Commercialization success data" is information indicating whether past business ideas have actually been brought to market and achieved success.

[1727] "Means of collecting and learning" refers to the process of statistically analyzing past business ideas and their success stories, inputting them into an AI model, and having it learn.

[1728] "AI technology" refers to artificial intelligence technology that can mimic human judgment and analyze large data sets. Typical examples include machine learning and deep learning.

[1729] "Evaluation criteria" are indicators used to analyze new business ideas and evaluate the probability of commercialization success.

[1730] "Means of analysis and quantification" refers to a method of using AI technology to evaluate business ideas as a numerical score.

[1731] The "evaluation result" is a score that indicates the probability of successful commercialization after analyzing a business idea using AI technology.

[1732] "Companies suitable for commercialization" are those that are judged based on the evaluation results to have a high probability of realizing new business ideas in the market.

[1733] An "idea purchase rights auction" is a process in which companies bid for the rights to a new business idea, and the highest bidder acquires the rights.

[1734] An "Invitation to Auction" is an official communication offering selected companies the opportunity to acquire the idea rights.

[1735] The "Transfer of Rights Process" is a set of legal and business procedures for formally transferring ownership of a business idea to the highest bidder after the auction ends.

[1736] "Means for logging into the platform" means the authentication mechanism by which a user accesses the system and logs into their account.

[1737] "Means for submitting ideas by entering necessary information" is a function for entering information such as a title, summary, detailed description, etc. and sending it to the server.

[1738] "Means of inputting past data and data on successful performance into an AI model, allowing it to learn and generate" refers to a function that inputs collected data into an AI model to generate evaluation criteria and automatically updates the evaluation criteria.

[1739] "Method of analyzing new business ideas using AI technology and quantifying the probability of commercialization success" is a method of analyzing business ideas using AI technology and expressing the probability of commercialization success as a score.

[1740] The "means for inviting participants to participate in the auction" is a function for sending invitations to selected companies to participate in the auction of idea rights.

[1741] "A process by which companies participating in an auction bid for the right to purchase an idea" is a process by which selected companies compete in an auction for the right to purchase an idea.

[1742] This invention is a system for evaluating new business ideas submitted by individuals or corporations and providing them to companies suitable for commercialization. This system is composed of a server, terminals, and users.

[1743] 1. Idea collection

[1744] User:

[1745] First, users access the platform and are authenticated by entering their username and password on the login screen. After successfully logging in, they proceed to the idea submission form from the dashboard, enter the title, summary, and detailed description, and submit.

[1746] server:

[1747] The server receives the idea information sent by the user and stores it in a database. Once the data has been saved, it sends a notification to the user confirming receipt of the data. The platform's authentication and data storage functions are implemented using standard web servers (e.g., Apache or Nginx) and database servers (e.g., MySQL or PostgreSQL).

[1748] 2. Collecting and learning from past data

[1749] server:

[1750] The server collects past data on business ideas and commercial success data from external APIs or internal databases. The server inputs the collected data into an AI model and performs learning to generate evaluation criteria. Specifically, the AI ​​model is trained using frameworks such as TensorFlow and PyTorch. The training progress is displayed to the administrator in real time on the terminal.

[1751] 3. Evaluating ideas

[1752] server:

[1753] The server reads new business ideas collected from the database and analyzes them based on evaluation criteria using AI technology. The probability of commercialization success is quantified as a score and the evaluation results are saved in the database. After the evaluation results are generated, they are notified to the user.

[1754] 4. Selection of companies suitable for commercialization and holding an auction

[1755] server:

[1756] Based on the evaluation results, the server creates a list of business ideas with a high probability of commercialization success and selects the most suitable companies. The server determines suitability using past transaction data and company profiles. Selected companies are notified by email with an invitation to participate in the auction.

[1757] Corporate users:

[1758] Selected corporate users will receive an invitation email and log in to the auction platform to bid for the right to purchase the business idea. The server updates the bidding information in real time and monitors the auction status.

[1759] 5. Auction Results and Transfer of Rights

[1760] server:

[1761] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. Once the transfer procedure is complete, the server records the information in a database and notifies the parties involved.

[1762] Corporate users:

[1763] The highest bidder, the corporate user, will receive a notice of successful bid and proceed with the idea rights transfer procedure, allowing the company to develop a new service based on the purchased business idea and bring it to market.

[1764] Examples and prompts

[1765] As a concrete example, let's take a business idea called "a system for proposing personalized content using AI." When this idea is submitted, the user logs into the platform, enters the title and details of the idea into a form, and submits it. The server receives the idea, evaluates it using an AI model, and calculates a score representing the probability of commercialization success. If the score is high, suitable companies are invited to participate in the auction. Corporate users then participate in the auction and acquire the rights to the idea.

[1766] Examples of prompts include:

[1767] "What information do I need in a dataset to train an AI model that will assess the success probability of a new business idea?"

[1768] "How can I provide a business idea with potential for commercialization to the right company?"

[1769] Using such prompts increases the accuracy and efficiency of the system, which leverages AI technology to quickly and accurately evaluate business ideas and provide them to the right companies, facilitating their realization.

[1770] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1771] Step 1:

[1772] User accesses the platform

[1773] Input: Username, Password

[1774] How it works: A user accesses the platform's login screen and enters their username and password.

[1775] Output: Sending authentication information

[1776] The server performs authentication

[1777] Input: Username, Password

[1778] Data calculation: The server checks the entered username and password against the credentials stored in the database.

[1779] Output: Authentication result

[1780] The device displays the dashboard

[1781] Input: Authentication result

[1782] Behavior: If authentication is successful, the user's dashboard screen is displayed on the device.

[1783] Output: Dashboard screen

[1784] Step 2:

[1785] User proceeds to idea submission form

[1786] Input: User actions

[1787] How it works: A user navigates to the idea submission form from the dashboard and fills in the fields, specifically the title, summary, and description.

[1788] Output: Idea information

[1789] The device temporarily stores and transmits the idea information

[1790] Input: Idea information

[1791] Data processing: Idea information is temporarily stored in cache memory.

[1792] Behavior: When the user presses the submit button, the idea information is sent to the server as a POST request.

[1793] Output: POST request

[1794] The server receives and stores the idea information

[1795] Input: POST request

[1796] Data processing: idea information is stored in a database.

[1797] Behavior: Once the data has been saved, the server will send a confirmation to the user.

[1798] Output: Save completion notification

[1799] Step 3:

[1800] The server collects past data

[1801] Input: Request to external API or internal database

[1802] Data collection: The server collects historical data on business ideas and their commercial success.

[1803] Output: Historical data

[1804] The server inputs data into the AI ​​model and it learns

[1805] Input: Historical data

[1806] Data calculation: The data collected by the server is input into an AI model (e.g., TensorFlow or PyTorch) and trained to generate evaluation criteria.

[1807] Output: Evaluation criteria

[1808] Your device displays your learning progress

[1809] Input: Learning progress

[1810] What it does: Shows learning progress to administrators in real time.

[1811] Output: progress indicator

[1812] Step 4:

[1813] Servers evaluate new ideas

[1814] Input: New business idea, evaluation criteria

[1815] Data calculation: The server analyzes new business ideas based on evaluation criteria and quantifies the probability of commercial success.

[1816] Output: Probability of commercial success score

[1817] The server saves the evaluation results and notifies you.

[1818] Input: Probability of commercial success score

[1819] Data processing: Save the scores to a database.

[1820] Action: Sends the user a notification of the evaluation results.

[1821] Output: Notification

[1822] Step 5:

[1823] Select a company suitable for commercialization of the server

[1824] Input: Evaluation results, company profile data

[1825] Data calculation: Based on the evaluation results and company profile data, companies with a high probability of commercialization success are selected.

[1826] Output: Selection result

[1827] The server sends the invitation to the company

[1828] Input: Selection result

[1829] How it works: The server sends email invitations to selected companies to participate in the auction.

[1830] Output: Invitation email

[1831] Corporate users participate in the auction and bid

[1832] Input: Invitation email

[1833] How it works: A corporate user receives an invitation email, logs into the auction platform, and places a bid for the right to purchase an idea from their account.

[1834] Output: Bid information

[1835] The server checks the auction results and starts the process

[1836] Input: Bid Information

[1837] Data calculation: Identify the highest bidder and initiate the idea rights transfer process.

[1838] Output: Notification of start of transfer procedure

[1839] Corporate users proceed with the rights transfer procedure

[1840] Input: Notice of commencement of transfer procedure

[1841] How it works: A corporate user goes through the transfer of rights process and prepares and completes the necessary paperwork.

[1842] Output: Completion report

[1843] The server records and notifies the completion of the transfer

[1844] Input: Completion report

[1845] Data processing: Record the transfer completion information in the database.

[1846] What it does: Sends notification to the parties involved that the transfer is complete.

[1847] Output: Completion notification

[1848] (Application example 1)

[1849] 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."

[1850] Previous business idea evaluation systems had unclear criteria for increasing the probability of commercialization success, and the evaluations were not always accurate. Furthermore, the process for providing evaluated business ideas to the most suitable companies was unclear, which could result in missed business opportunities. Furthermore, the means for participating in auctions for evaluated ideas were limited, making it inconvenient for companies.

[1851] 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.

[1852] In this invention, the server includes: means for receiving and storing new business proposals from individuals or corporations; means for collecting and learning data on past business proposals and their commercial success; means for using AI technology to analyze new business proposals based on evaluation criteria and quantify their commercialization success rates; means for selecting companies suitable for commercializing the evaluated business proposals and holding an auction for the right to purchase the proposals; means for transferring the proposal rights to the highest bidder in the auction; and, in the case of proposals related to content distribution services, means for companies to participate in the auction via a smartphone application for proposals that receive an evaluation score above a certain level. This enables accurate evaluation of business proposals and prompt provision of the proposals to the most suitable companies. Furthermore, companies can easily participate in the auction via the smartphone application, greatly improving convenience.

[1853] A "new business idea" is a proposal or concept for a new business devised by an individual or corporation.

[1854] "Past business proposals" are business proposals or ideas that have been proposed and implemented in some form.

[1855] "Commercialization success data" refers to data on the track record and results of business ideas that have been commercialized in the past.

[1856] "AI technology" refers to technology that uses artificial intelligence and makes decisions and predictions through machine learning and data analysis.

[1857] "Evaluation criteria" are standards for evaluating new business ideas, and include factors such as probability of success and market adaptability.

[1858] "Quantification" means expressing the evaluation of the target business proposal in concrete numerical terms.

[1859] An "auction" is a trading method in which multiple companies participate and bid for the right to purchase a target business proposal.

[1860] "Proposal Purchase Rights" means the right of the highest bidder in an auction to purchase a particular business proposal.

[1861] The "proposal rights transfer procedure" refers to the procedure for officially transferring the rights of a business proposal that has been won in an auction to the bidding company.

[1862] "Content distribution service" is a general term for services that distribute digital content to users.

[1863] A "smartphone application" is a software program that runs on a smartphone.

[1864] An "evaluation score" is a numerical representation of the evaluation result of a business proposal, and indicates the value and probability of success of the proposal.

[1865] An "enterprise" is a legal entity that operates with a specific business purpose.

[1866] The present invention is a system that uses AI technology to evaluate new business ideas collected from individuals or corporations and provides the rights to companies for commercialization. The following describes the details of the embodiment of this system and the operation of the program.

[1867] 1. Idea collection

[1868] User

[1869] Users log in to the platform and enter the necessary information (title, summary, detailed description) into the business proposal submission form. When the submit button is pressed, the information is sent to the server.

[1870] server

[1871] The server receives the business proposal and stores it in the database. Once the storage is complete, it sends a data reception confirmation notice to the user.

[1872] 2. Collecting and learning from past data

[1873] server

[1874] The server collects data on past business proposals and successful commercialization, including information on target markets, revenue, and implementation technologies. This data is input into an AI model, which learns to generate evaluation criteria. The generated evaluation criteria are stored in a database.

[1875] 3. Evaluating ideas

[1876] server

[1877] The server analyzes the collected new business ideas based on the evaluation criteria. At this time, AI technology is used to quantify the probability of commercialization success for each idea. The evaluation results are stored in a database and notified to the user.

[1878] 4. Selection of companies suitable for commercialization and holding an auction

[1879] server

[1880] Based on the evaluation results, the server will create a list of business proposals with a high probability of commercialization success. It will then select suitable companies to hold an auction for these proposals. It will then send invitations to the selected companies to participate in the auction via email and notifications.

[1881] Corporate Users

[1882] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to acquire the right to purchase the proposal.

[1883] 5. Auction Results and Transfer of Rights

[1884] server

[1885] At the end of the auction, the server identifies the highest bidder, initiates the transfer of the rights, records the completion of the transfer in the database, and notifies the parties involved.

[1886] Corporate Users

[1887] The corporate user receives a confirmation of the successful bid and proceeds with the proposal rights transfer procedure.

[1888] Example

[1889] Consider a business proposal called "a new personalized content proposal system." Users access the platform, enter specific details into a form, and submit it. The server saves the received proposal and analyzes it based on evaluation criteria. If the proposal is deemed to have a high probability of commercial success, a suitable content distribution service company is selected and invited to participate in an auction. The company participates in the auction and, as the highest bidder, acquires the rights to the proposal. A new service is developed based on the acquired rights and launched in the market.

[1890] Hardware and software used

[1891] Server: AWS EC2 (server hosting)

[1892] Database: AWS RDS (database management)

[1893] AI technology: scikit-learn (machine learning library)

[1894] Web framework: Flask (Python web framework)

[1895] API documentation: Swagger

[1896] Prompt Sentence Examples

[1897] Post a new personalized content suggestion system.

[1898] example:

[1899] Title: AI-powered personalized content suggestion system

[1900] What it is: AI suggests the best content based on a customer's browsing history.

[1901] Description: The system analyzes users' past browsing history and suggests content that best suits their interests.

[1902] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1903] Step 1:

[1904] Users log in to the platform, enter the required information (title, summary, detailed description) in the business proposal submission form, and submit it.

[1905] Input: Title, summary, detailed description

[1906] Output: Send data to the server

[1907] Specific operations: The user uses a web browser or smartphone application to access the platform's business proposal submission page, enter the required information, and press the submit button.

[1908] Step 2:

[1909] The server receives the submitted business proposal, stores it in a database, and sends a data reception confirmation notice to the user once the saving is complete.

[1910] Input: Business proposal data submitted by the user

[1911] Output: Save to database and confirmation notification

[1912] Specific operation: The server receives the sent data, stores it in the AWS RDS database, and sends a notification to the user after the data is saved.

[1913] Step 3:

[1914] The server collects data on past business proposals and successful commercializations to create a learning dataset.

[1915] Input: Existing business plan data and its commercial success record data

[1916] Output: Training dataset

[1917] Specific operation: The server collects past business plans and their performance data from the Internet and internal databases, and uses this to generate a learning dataset.

[1918] Step 4:

[1919] The server uses a generative AI model to learn the training dataset and generate evaluation criteria.

[1920] Input: Training dataset

[1921] Output: Evaluation criteria

[1922] Specific operation: The server uses the scikit-learn library to input the training dataset into the model, generate evaluation criteria, and store them in the database.

[1923] Step 5:

[1924] The server analyzes new business ideas sent by users based on evaluation criteria and quantifies the probability of commercial success as a score.

[1925] Input: New business idea data, evaluation criteria

[1926] Output: Probability of commercial success score

[1927] Specific operation: The server analyzes new business idea data based on the evaluation criteria and calculates the probability of commercial success as a score using a random forest model.

[1928] Step 6:

[1929] The server selects corporate users suitable for commercialization based on the scores of the evaluated business proposals and holds an auction for the right to purchase the proposals.

[1930] Input: Probability of commercial success score

[1931] Output: Selection and notification of auction participants

[1932] Specific operation: The server selects suitable corporate users for business proposals with high evaluation scores and sends them invitation emails containing a link to the auction platform.

[1933] Step 7:

[1934] Corporate users receive an invitation email, log in to the auction platform, and place a bid to win the right to purchase the proposal.

[1935] Input: Corporate user bid amount

[1936] Output: Record of bidding results

[1937] Specific operation: The corporate user clicks the link in the invitation email, logs in to the auction platform, enters the bid amount, and presses the bid button. The bid results are recorded on the server.

[1938] Step 8:

[1939] At the end of the auction, the server identifies the highest bidder and initiates the process of transferring the business proposal rights.

[1940] Input: Auction bid results

[1941] Output: Initiation and notification of transfer procedure

[1942] Specific operation: After the auction ends, the server checks the highest bid and notifies the bidding company of the details of the procedure for transferring the bid rights.

[1943] Step 9:

[1944] The corporate user will receive a confirmation of the successful bid and proceed with the rights transfer procedure for the business proposal.

[1945] Input: Notification of details of rights transfer procedure

[1946] Output: Transfer of rights completed

[1947] Specific operation: The corporate user provides the necessary information for the rights transfer according to the notified procedure, and the rights transfer is finally completed.

[1948] 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.

[1949] This invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The following describes the details of the implementation of this system and the operation of the program.

[1950] 1. Idea collection

[1951] User

[1952] Log in to the platform and access the idea submission form. When entering the required information (title, summary, detailed description), the emotion engine is also used to obtain the user's emotional data at the time of entry. When the user presses the submit button, this information is sent to the server.

[1953] server

[1954] The submitted idea and emotion data is received and stored in the database. Once the data is stored, a data reception confirmation notification is sent to the user.

[1955] 2. Collecting and learning from past data

[1956] server

[1957] Collect historical data on business ideas and their success (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[1958] The collected data is input into an AI model, which learns to generate evaluation criteria, which are then stored in a database.

[1959] 3. Evaluating ideas

[1960] server

[1961] The emotional data obtained by the emotion engine, along with new business ideas received from users, is analyzed based on evaluation criteria. Using AI technology, the emotional data is reflected when quantifying the probability of commercialization success for each idea.

[1962] The evaluation results are stored in a database, and the user is notified of the evaluation results of the idea.

[1963] 4. Selection of companies suitable for commercialization and holding an auction

[1964] server

[1965] Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success, and select companies that can easily commercialize these ideas.

[1966] Selected companies will be sent an invitation to participate in the auction via email or notification.

[1967] Corporate Users

[1968] After receiving the invitation email, you will log in to the auction platform, participate in the auction from your account, and make a bid to win the right to purchase the idea.

[1969] 5. Auction Results and Transfer of Rights

[1970] server

[1971] At the end of the auction, the highest bidder is identified, the process of transferring the idea rights is initiated, the completion of the transfer is recorded in the database, and the relevant parties are notified.

[1972] Corporate Users

[1973] Once you receive the successful bid, you will proceed with the procedures to acquire the idea rights.

[1974] Specific examples

[1975] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[1976] User

[1977] Access the platform and enter "AI-based personalized content suggestion system" as the title. Enter a summary and detailed description, and emotional data will be collected in real time as you enter it. Send all information and emotional data.

[1978] server

[1979] The received ideas and sentiment data are stored and analyzed. If the idea is deemed to have a high probability of commercialization, a suitable content distribution service company will be selected and invited to participate in the auction.

[1980] Corporate Users

[1981] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[1982] Through the above process, the present invention provides a system that utilizes an emotion engine to evaluate and commercialize new business ideas while taking into account the emotional value of users. This system improves the accuracy of evaluation and the likelihood of commercialization.

[1983] The processing flow will be explained below.

[1984] Step 1:

[1985] User: Logs in to the platform and accesses the idea submission form. While entering the title, summary, and detailed description, the emotion engine also collects the user's emotion data in real time. After entering all the information and emotion data, the user clicks the submit button.

[1986] Step 2:

[1987] Server: Receives business ideas and sentiment data sent by users via REST API, saves the data in the database, and notifies the user that the data has been saved.

[1988] Step 3:

[1989] Server: Collects historical data on business ideas and their success stories (target market, revenue, implementation technology, etc.), as well as historical sentiment data.

[1990] Step 4:

[1991] Server: The collected data is input into the AI ​​model and it learns, generating evaluation criteria for new business ideas and saving them in a database.

[1992] Step 5:

[1993] Server: Analyzes new business ideas received from users and the emotional data acquired by the emotion engine based on evaluation criteria. AI technology is used to quantify the probability of commercialization success for each idea, and the emotional data is reflected in the score.

[1994] Step 6:

[1995] Server: Stores the evaluation results in a database and notifies the user of the idea evaluation results.

[1996] Step 7:

[1997] Server: Based on the evaluation results, we will create a list of ideas with a high probability of commercialization success. We will then select companies that can easily commercialize these ideas.

[1998] Step 8:

[1999] Server: Sends emails or notifications to selected companies inviting them to participate in the auction.

[2000] Step 9:

[2001] Corporate users: receive an invitation email and log in to the auction platform. They can then participate in the auction from their own account and make a bid to win the right to purchase the idea.

[2002] Step 10:

[2003] Server: At the end of the auction, the highest bidder is identified and the idea rights transfer procedure is initiated.

[2004] Step 11:

[2005] Corporate users: Receive notification of successful bid and proceed with the procedures to acquire the idea rights.

[2006] Step 12:

[2007] Server: Completes the rights transfer procedure, updates the database, and sends a transfer completion notification to the relevant parties.

[2008] Example 2

[2009] 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."

[2010] Conventional systems evaluate new business ideas without considering their emotional value, which means they cannot accurately reflect the true potential of the ideas submitted by users. Furthermore, they lack important information, such as emotional data, in the idea evaluation and commercialization process, which reduces the accuracy of predicting the probability of success.

[2011] 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.

[2012] In this invention, the server includes a means for receiving new business ideas from individuals or corporations and storing them together with emotional data, a means for collecting and learning data on past business ideas and their commercial successes, as well as past emotional data, and a means for using AI technology to analyze new business ideas based on evaluation criteria and taking the emotional data into account when quantifying the probability of their commercial success. This enables more accurate evaluation of business ideas and prediction of the probability of commercial success by taking the emotional data into account.

[2013] "Individual or Legal Entity" refers to a user as an individual or a legal entity such as a company or organization.

[2014] "Business ideas" refer to business proposals and plans for new products, services, business models, etc.

[2015] "Emotion data" refers to data that expresses the user's emotional state in the form of numbers, text, or the like.

[2016] "Means for storing" refers to the function of storing received information in a database or storage.

[2017] "Past business ideas" refers to historical data on business ideas that have been submitted to date.

[2018] "Commercialization success data" refers to data showing the results and achievements of business ideas that have been commercialized to date.

[2019] "Means of learning" refers to the function of training an AI model using collected data.

[2020] "AI technology" refers to artificial intelligence technology in general, and particularly includes machine learning and natural language processing models.

[2021] "Evaluation criteria" refers to the metrics or scoring rules used to evaluate business ideas.

[2022] "Means of analysis" refers to the function of analyzing and evaluating data using AI technology.

[2023] "Means of quantification" refers to the function of quantifying the probability of success of a business idea.

[2024] "Enterprise" refers to a legal entity that has the ability and desire to commercialize a business idea.

[2025] An "auction" refers to the process of bidding on business ideas and the highest bidder wins the right to purchase them.

[2026] "Assignment process" refers to the process by which the rights to an idea are officially transferred to the highest bidding company.

[2027] The present invention combines an emotion engine with a system that uses AI technology to evaluate new business ideas collected from individuals and corporations and provides the rights to those ideas to companies for commercialization. The details of the implementation of this system and the operation of the program are described below.

[2028] Idea collection

[2029] User

[2030] Users log in to the platform and access the form for submitting ideas. Here, they enter a title, summary, and detailed description in the form. Furthermore, an emotion engine runs in the background, capturing emotional data in real time as the user types. Once users have completed entering information and pressed the submit button, this information is sent to the server.

[2031] server

[2032] The server receives the idea and emotion data sent by the user and stores this information in a database. After storing the information, it sends a data reception confirmation notice to the user. The database used is, for example, MySQL or PostgreSQL.

[2033] Collecting and learning from past data

[2034] server

[2035] The server collects data on past business ideas and their success (e.g., target market, revenue, implementation technology, etc.), as well as past sentiment data. This data is then prepared for input into an AI model (e.g., TensorFlow or PyTorch).

[2036] The server inputs the collected data into the AI ​​model, which then learns to generate evaluation criteria, which are then stored in a database.

[2037] Idea Evaluation

[2038] server

[2039] The server analyzes new business ideas and emotional data received from users using evaluation criteria based on past data. Using AI technology (natural language processing models and machine learning algorithms), it quantifies the idea's probability of commercial success as a score, which also reflects the emotional data. The evaluation results are stored in a database and the user is notified of the results.

[2040] Selection of companies suitable for commercialization and holding an auction

[2041] server

[2042] Based on the evaluation results, ideas deemed to have a high probability of commercialization will be listed, and companies suitable for commercialization will be selected. Selected companies will be invited to participate in the auction via email or notification.

[2043] Corporate Users

[2044] Corporate users receive an invitation email and log in to the auction platform, participate in the auction from their own account, and make a bid to win the right to purchase the idea.

[2045] Auction Results and Transfer of Rights

[2046] server

[2047] At the end of the auction, the highest bidder will be identified and the process of transferring the idea rights will begin, which will then be recorded in the database as a completed transfer and notify the relevant parties.

[2048] Corporate Users

[2049] The corporate user receives the successful bid notification and proceeds with the procedures for acquiring the idea rights.

[2050] Specific examples

[2051] As an example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI."

[2052] User

[2053] Users access the platform and enter the title "AI-based personalized content suggestion system." They then enter a summary and detailed description, and emotional data is collected in real time as they enter the information. All information and emotional data is then sent.

[2054] server

[2055] The server stores the received ideas and emotional data and analyzes them using AI technology. If the idea is deemed to have a high probability of commercialization, it selects appropriate content distribution service companies and invites them to participate in the auction.

[2056] Corporate Users

[2057] Receive an invitation to participate in an auction, become the highest bidder and acquire the rights to the idea. Use the acquired rights to develop a new service and bring it to market.

[2058] This system allows for the evaluation and commercialization of new business ideas that take into account the emotional value of users, resulting in more accurate evaluation and improved likelihood of commercialization.

[2059] Prompt Sentence Examples

[2060] Please tell us the details of the implementation of a system that will be offered to companies in an auction format to evaluate a new business idea called "a personalized content suggestion system using AI" and collect emotional data to increase the probability of commercialization success.

[2061] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2062] Step 1:

[2063] User: Platform login

[2064] A user accesses the platform and logs in by entering their authentication information (user ID, password) on the login screen. The authentication information is sent to the server, which then collates it with the database to authenticate the user. After successful authentication, a form screen for submitting ideas is displayed on the user's device. Input data: user ID, password. Output data: idea submission form.

[2065] Step 2:

[2066] User: Fill out the idea submission form

[2067] The user enters a title, summary, and detailed description into the submission form. While the user is entering data, the emotion engine runs in the background and collects emotional data in real time as the user enters the information. Emotional data is collected using, for example, a webcam or microphone. Input data: Title, summary, detailed description. Output data: Emotional data as the user enters the information.

[2068] Step 3:

[2069] User: Submit information

[2070] When the user presses the send button, the title, summary, detailed description, and emotion data are sent to the server. The server temporarily stores the received information in memory and begins the database storage process. Input data: title, summary, detailed description, emotion data. Output data: Data sent to the server completed.

[2071] Step 4:

[2072] Server: Data storage

[2073] The server stores the received idea information and emotion data in a database. Once the database storage is complete, a data reception confirmation notification is sent to the user. Input data: idea information, emotion data. Output data: data storage completion notification.

[2074] Step 5:

[2075] Server: Collection of historical data

[2076] The server collects past business ideas, commercial success data, and emotional data from a database. The collected data is preprocessed to train the AI ​​model. Input data: past business ideas, commercial success data, and emotional data. Output data: preprocessed training data.

[2077] Step 6:

[2078] Server: Preparing training data

[2079] The server converts the preprocessed data into a format appropriate for the AI ​​model (e.g., TensorFlow or PyTorch). Data processing is performed to convert it into the appropriate format. Input data: Preprocessed training data. Output data: Data in the AI ​​model input format.

[2080] Step 7:

[2081] Server: AI model training

[2082] The server inputs data into the AI ​​model and performs learning to generate evaluation criteria. The evaluation criteria generated through learning are stored in a database. Input data: Data in the AI ​​model input format. Output data: Evaluation criteria.

[2083] Step 8:

[2084] Server: Evaluating ideas

[2085] The server analyzes the new business idea and sentiment data received from the user based on the generated evaluation criteria. Natural language processing models and machine learning algorithms are used for the analysis. Input data: new business idea, sentiment data, evaluation criteria. Output data: score of the probability of commercialization success.

[2086] Step 9:

[2087] Server: Evaluation result storage and notification

[2088] The server stores the evaluation results of the probability of commercial success in a database and notifies the user of the evaluation results of the idea. Input data: Score of the probability of commercial success. Output data: Notification of evaluation results.

[2089] Step 10:

[2090] Server: Company Selection

[2091] The server lists ideas with a high probability of commercialization success and selects suitable companies. Selected companies are then invited to participate in the auction via email or notification. Input data: Ideas with a high probability of commercialization success. Output data: List of selected companies, invitation email.

[2092] Step 11:

[2093] Corporate users: Participating in auctions

[2094] Corporate users receive an invitation email and log in to the auction platform. They then participate in the auction from their own accounts and place bids to obtain the right to purchase ideas. Input data: invitation email, account information. Output data: auction participation, bid.

[2095] Step 12:

[2096] Server: Confirmation of auction results and transfer of rights

[2097] When the auction ends, the server identifies the highest bidder and initiates the transfer procedure for the idea rights. The transfer completion information is recorded in the database and notified to the relevant parties. Input data: Auction results. Output data: Notification of transfer procedure completion.

[2098] Step 13:

[2099] Corporate users: Rights acquisition procedure

[2100] The corporate user receives the successful bid notification and proceeds with the procedures to acquire the idea rights. Finally, a new service is developed based on the acquired rights and released to the market. Input data: successful bid notification. Output data: Rights acquired, new service developed.

[2101] (Application example 2)

[2102] 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."

[2103] Conventional business idea evaluation systems fail to consider user emotions or intuitive values ​​when quantitatively assessing the probability of an idea's commercialization success. This can result in the idea's true value being overlooked, hindering its commercialization. Furthermore, the process of selecting appropriate companies and holding auctions based on the evaluation results is inefficient. An effective system is needed to collect user emotion data and evaluate ideas based on it.

[2104] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2105] In this invention, the server includes means for receiving and storing new business ideas from individuals or corporations, means for collecting and learning data on past business ideas and their successful commercialization, means for analyzing new business ideas based on evaluation criteria using AI technology and quantifying the probability of their commercialization success, means for collecting emotional data when the idea is submitted and reflecting this in the evaluation, means for selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas, and means for transferring the idea rights to the company with the highest bid in the auction. This makes it possible to more accurately evaluate the value of business ideas while taking user emotions into consideration and improve the probability of successful commercialization.

[2106] 1. A "business idea" is a creative concept or proposal for a new product, service, process, or business model, originating from an individual or legal entity.

[2107] 2. "Emotional Data" refers to data that quantifies or categorizes the emotional reactions or states that users show when submitting ideas.

[2108] 3. "Evaluation Criteria" means indicators or standards based on AI technology that use historical and sentiment data to measure the value of new business ideas and the probability of commercial success.

[2109] 4. "Probability of commercial success" is the statistical probability that a particular business idea will be successful and profitable when brought to market.

[2110] 5. "AI technology" refers to a group of technologies that use advanced algorithms such as machine learning and deep learning to analyze data and make predictions and decisions.

[2111] 6. "Enterprise" means a legal entity or organization that has the ability to purchase and implement business ideas for commercialization.

[2112] 7. An "auction" is a process in which participating companies compete for the right to purchase an idea, with the highest bidder winning the right.

[2113] 8. "Transfer Procedure" refers to the process of transferring the rights to an idea to a company that has won the right to purchase the idea in an auction, by carrying out the necessary legal and contractual procedures.

[2114] This invention is a system that collects new business ideas from users, evaluates them, and provides them to companies suitable for commercialization. The core of this system involves evaluating business ideas including emotional data, and transferring idea rights through an auction format.

[2115] System configuration

[2116] 1. User Device:

[2117] Users submit new business ideas using a smartphone application. As they submit their ideas, an emotion engine collects emotional data in real time as they type. Emotional data is obtained from the user's facial expressions, voice, and tone of voice as they type.

[2118] 2. Server:

[2119] The server has the following main functions:

[2120] Data reception and storage: Receive business ideas and sentiment data sent by users and store them in a database.

[2121] Evaluation by AI model: The AI ​​model is trained using collected data on past business ideas and sentiment data. It analyzes new business ideas based on evaluation criteria and quantifies their probability of commercialization.

[2122] Auction management: Select suitable companies based on the probability of commercialization success, hold an auction, and manage the process of transferring idea rights to the highest bidder.

[2123] Hardware and software used

[2124] Hardware:

[2125] Server: A high-performance server for storing data, running AI models, and managing auctions.

[2126] User device: Smartphone, tablet, etc.

[2127] software:

[2128] Flask: A framework for providing APIs and receiving requests from users.

[2129] EmotionEngine: A library for collecting and analyzing user emotion data.

[2130] AI Model: Uses machine learning algorithms to learn from historical data and evaluate new business ideas.

[2131] Database: A relational database for storing ideas, sentiment data, and evaluation results.

[2132] Specific examples

[2133] As a concrete example, let's consider the idea of ​​a new content distribution method called "a personalized content suggestion system using AI." A user uses the system as follows:

[2134] 1. User Action:

[2135] The user launches the smartphone app and accesses a form to submit a business idea. They enter "AI-based personalized content suggestion system" as the title, and then fill in a summary and detailed description. During this process, the emotion engine collects emotion data in real time. All information and emotion data is sent.

[2136] 2. Server processing:

[2137] The server stores and analyzes the received ideas and sentiment data. The AI ​​model evaluates them and calculates the probability of commercialization success. Based on the evaluation results, suitable content distribution service companies are selected and invited to participate in the auction.

[2138] 3. Enterprise operations:

[2139] Invited companies log in to the auction platform and make bids to win the right to purchase the idea. The highest bidder will acquire the rights to the idea and develop and deploy a new service.

[2140] Prompt Sentence Examples

[2141] The prompt that users use to submit their ideas is as follows:

[2142] Title: "AI-based personalized content suggestion system"

[2143] Summary: "This system is a service that suggests individually optimized content based on the user's emotional data."

[2144] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2145] Step 1:

[2146] Submit your business idea

[2147] User input: A user launches a smartphone application and inputs a new business idea. They fill out a form with a title, summary, and detailed description. During this process, the emotion engine collects emotional data in real time from the user's facial expressions, voice, and tone of voice.

[2148] Data processing and data calculation: The text data entered by the user and the emotion data collected by the emotion engine are organized into JSON format data and sent to the server.

[2149] Output: The server receives the idea data and emotion data sent by the user.

[2150] Step 2:

[2151] Data storage

[2152] Server input: Business idea data and sentiment data received in step 1.

[2153] Data processing and data calculation: The server connects to the database and stores the received idea data and emotion data in the database in an appropriate format. The data is stored in the form of ID, user ID, title, summary, details, emotion data, etc.

[2154] Output: A message is generated to confirm the data save and notify the user.

[2155] Step 3:

[2156] Evaluation preparation using AI models

[2157] Server input: Past business idea data, commercial success data, and sentiment data obtained from the database.

[2158] Data processing and data calculation: The server inputs past business idea data and its sentiment data into the AI ​​model for learning. The AI ​​model generates evaluation criteria based on this data and prepares to evaluate new business ideas.

[2159] Output: A generative AI model with updated evaluation metrics.

[2160] Step 4:

[2161] Evaluating new ideas

[2162] Server input: new business idea data and sentiment data received from users, and the updated generative AI model.

[2163] Data processing and calculation: The AI ​​model analyzes new business ideas submitted by users based on evaluation criteria. The evaluation, including emotional data, quantifies the probability of commercialization success.

[2164] Output: A score indicating the probability of commercial success is generated and stored in a database. The user is notified of the evaluation result.

[2165] Step 5:

[2166] Holding an auction

[2167] Server input: Evaluated business idea data and their commercial success probability scores.

[2168] Data processing and data calculation: The server selects companies that are likely to commercialize the idea based on the probability of commercialization success, and sends an invitation to participate in the auction to the selected companies via email or notification.

[2169] Output: The companies participating in the auction are determined and the auction platform is set up.

[2170] Step 6:

[2171] Auction execution and notification of results

[2172] Server input: Bid data of companies participating in the auction.

[2173] Data processing and data calculation: The server collects and analyzes the bidding data during the auction period and determines the highest bidder.

[2174] Output: The company selected as the highest bidder at the end of the auction will begin the process of transferring the idea rights. The auction results will be notified to the user and participating companies.

[2175] Step 7:

[2176] Completion of the transfer of rights

[2177] Server input: Data of the highest bidding company and business idea rights information.

[2178] Data processing and data operation: The server will carry out the transfer procedures for the idea rights in accordance with the law and contract, record the completion of the transfer in the database, and notify the relevant parties.

[2179] Output: Record and notification of completed title transfer.

[2180] 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.

[2181] 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.

[2182] 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 robot 414.

[2183] 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.

[2184] 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.

[2185] 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.

[2186] 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).

[2187] 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.

[2188] 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."

[2189] 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.

[2190] 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).

[2191] 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.

[2192] 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.

[2193] 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.

[2194] 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.

[2195] 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.

[2196] 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.

[2197] 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 ...

Claims

1. A means for receiving and storing new business ideas from individuals or entities; A means of collecting and learning from data on past business ideas and their successful commercialization; A method to use AI technology to analyze new business ideas based on evaluation criteria and quantify the probability of their commercialization success. A means of selecting companies suitable for commercializing the evaluated business ideas and holding an auction for the right to purchase the ideas; a means for carrying out the process of transferring the idea rights to the highest bidder in the auction; A system including:

2. The system according to claim 1, further comprising a means for generating evaluation criteria using AI technology based on actual data on success when quantifying the probability of commercialization success of an idea.

3. 2. The system of claim 1, further comprising means for calculating a score for the idea based on the evaluation criteria, and for targeting and inviting companies to participate in the auction according to the score.

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