system

Abstract

We provide the system. [Solution] A profiling method that analyzes information from users to identify user characteristics, Market analysis tools that collect market data and identify growth markets, An idea generation method that integrates user characteristics and growth market information to generate business ideas, A validation method to verify the generated business idea and provide areas for improvement, A means of formulating an action plan that provides the optimal steps for commercialization, A system that includes this.

Description

Technical Field

[0004] , ,

[0005] , ,

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

Background Art

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

Prior Art Documents

[0006] "User information" refers to the personal information, skill data, and interest information of users who input information into the platform.

[0007] "Profiling tools" refer to functions that analyze information provided by users to identify the characteristics of individual users and appropriate business areas.

[0008] "Market data" refers to information about the market, including economic trends, consumer behavior, and competitive landscapes in specific industries or regions.

[0009] "Market analysis tools" refer to functions where different AI agents collect and analyze market data to identify growth markets.

[0010] A "growth market" refers to a market that has future potential and has been identified as having significant room for development in its current state.

[0011] "Idea generation means" refers to a function that integrates user characteristics and growth market information to generate new business ideas.

[0012] "Verification means" refers to a function that evaluates the feasibility and marketability of generated business ideas and provides suggestions for improvement.

[0013] "Action plan formulation tools" refer to the function of providing a plan to translate a business idea into concrete steps for commercialization. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

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

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

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

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0035] This invention is a comprehensive business idea creation and verification system utilizing an autonomous AI agent. This system generates appropriate business ideas based on user information and evaluates the feasibility of the proposed ideas using market data. The system's operation is described in detail below.

[0036] First, the user logs into the system via a terminal and enters information such as their work history, skills, and interests. The server receives this information and analyzes it using a deep learning algorithm. This analysis generates a profile of the user's characteristics, and the server then suggests the most suitable business areas for the user. For example, if the user is proficient in the IT field, areas such as cloud computing or cybersecurity can be recommended.

[0037] Next, the server performs market analysis. Multiple AI agents analyze market data obtained from the internet to detect untapped markets with growth potential. Based on this, the server identifies promising business opportunities and presents them to the user.

[0038] Next, the server uses an idea generation tool to combine user profiles and market data to generate specific business ideas. The generated ideas take into account the user's strengths and market opportunities, and the server provides these ideas to the user in detail. For example, if the user's characteristics include digital marketing and there is high demand for smart devices in a particular region, the development of a new advertising platform might be proposed.

[0039] Subsequently, the user receives the suggested ideas via their device and provides feedback. Based on this feedback, the server uses an AI agent to analyze market viability and the competitive landscape, identifying areas for further improvement. For example, it can analyze competitor trends and recommend differentiation strategies.

[0040] Ultimately, the server develops an action plan and presents the user with steps toward commercialization. This plan includes necessary resources and potential challenges, helping the user create a concrete implementation plan. In this way, the user can quickly turn their business idea into a feasible one and aim for success.

[0041] Thus, the present invention utilizes user input and market data to consistently support the process from generating innovative business ideas to their implementation.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users log in to the platform using their device and enter basic information such as work history, skills, and interests through the portal interface.

[0045] Step 2:

[0046] The server receives information sent by the user and securely stores it in a database. Then, it analyzes this information using a deep learning model to generate a user profile. The user profile includes characteristics and strengths based on the user's skills and experience.

[0047] Step 3:

[0048] The server activates AI agents to acquire market data. This data includes information from the internet and partner data providers, and is used to analyze market trends, consumer behavior, and the competitive landscape. Each AI agent specializes in data for a specific industry or region.

[0049] Step 4:

[0050] Based on the collected market data, the server identifies untapped markets with growth potential. This information is integrated with user profiles to create a list of suggested business opportunities for the user. The user is then presented with attractive business area options to pursue.

[0051] Step 5:

[0052] The server uses an idea generation engine to combine user profile information with insights from market data to create concrete business ideas. These ideas reflect the individual user's strengths and market needs, and their feasibility is evaluated.

[0053] Step 6:

[0054] Users can review proposed business ideas from their devices and provide feedback. This feedback is sent to the system and used to further improve the ideas.

[0055] Step 7:

[0056] The server incorporates user feedback and uses automatically generated AI models to conduct competitive analysis and market evaluation, identifying the feasibility and areas for improvement of ideas. The results are presented to the user, and further actions are recommended if necessary.

[0057] Step 8:

[0058] Ultimately, the server uses action plan development tools to create an implementation plan from the business idea. This plan includes necessary resources, personnel, budget, and potential risks. The user can then use this information to proceed with specific business implementation.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] In today's business environment, it is difficult to quickly generate optimal business ideas that maximize the skills and interests of individual users while considering market growth potential. Furthermore, providing concrete steps and improvements to enhance the feasibility of the generated ideas is currently not sufficiently achieved. This hinders small and medium-sized enterprises and entrepreneurs from creating and rapidly implementing innovative business models.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes an information analysis means that analyzes information from the user to identify the user's characteristics, a proposal means that suggests the optimal business area based on the information, and a market data analysis means that collects market data using multiple AI agents to identify growth areas. This makes it possible to generate individual business ideas that reflect the user's skills and interests, and to formulate concrete action plans based on those ideas.

[0064] "Information analysis means" refers to methods for processing information provided by users and identifying individual characteristics.

[0065] "Proposal methods" refer to techniques for suggesting the most suitable business areas based on analyzed user information.

[0066] "Market data analysis methods" refer to techniques that use multiple AI agents to collect data from the market and identify areas with growth potential.

[0067] "Concept generation methods" refer to techniques for formulating specific business models by combining user characteristics and market information.

[0068] "Verification methods" refer to techniques for evaluating the generated business model and providing additional information and areas for improvement.

[0069] "Planning methods" refer to techniques for presenting concrete action plans for implementing an idea.

[0070] This invention is a system that generates optimal business ideas based on user information and supports their steady commercialization. Users access the system using a terminal. The terminal is provided with an interface for inputting the user's work history, skills, interests, etc. This information is sent to a server. The server receives this information and analyzes the user's characteristics using information analysis means. Generative AI models and deep learning algorithms are used for information analysis. As a result, a user profile is generated, and the optimal business area is presented to the user through a suggestion means.

[0071] The server also uses multiple AI agents to collect market data and identify markets with growth potential. Big data analytics and time series analysis are employed for market data analysis, which helps detect promising market opportunities.

[0072] Furthermore, the server combines user profiles and market data to generate concrete business concepts. In this process, a generative AI model is utilized to propose business models that consider user characteristics and market opportunities. The generated business concepts are evaluated using validation tools, and improvements are provided as needed. Finally, the server presents a detailed action plan using planning tools. This plan includes specific steps and resources for implementing the idea.

[0073] For example, if the information provided by the user relates to "eco-friendly product development," the system can analyze market data, identify the growing market for renewable energy, and specifically propose the development of new products utilizing solar panels.

[0074] An example of a prompt to input into a generative AI model would be text such as, "The user's area of ​​interest is eco-products. Based on current market information and user characteristics, please propose appropriate business ideas."

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] Users log in to the system using their terminal and enter information such as their work history, skills, and interests. This information is received via forms on the terminal. The entered data is then transferred to the server via the internet.

[0078] Step 2:

[0079] The server processes the received user information using information analysis tools. This process utilizes a generative AI model and deep learning algorithms for data processing. As output, a profile defining the user's characteristics is generated. This profile is then used for subsequent business area proposals.

[0080] Step 3:

[0081] The server suggests the most suitable business domain based on the profile. At this stage, suggestion tools are used to analyze the entity and select a specific industry domain that matches the user's interests and skills. The output is a recommended domain, such as "IT services" or "eco-products."

[0082] Step 4:

[0083] The server uses multiple AI agents to collect market data from external data sources. Inputs include publicly available data on the internet and commercial databases, accessed through data acquisition protocols. Outputs include information on collected market trends and growth forecasts.

[0084] Step 5:

[0085] The server analyzes market information collected using market data analysis tools. Big data analysis techniques and time-series analysis are used to identify markets with growth potential and output the detected growth areas. This process utilizes data pattern recognition and clustering technologies.

[0086] Step 6:

[0087] The server integrates user profiles and market data, and generates concrete business concepts using concept generation tools. Data calculations are performed by a generation AI model, and specific business ideas are proposed as output. These ideas might include, for example, "the development of an eco-friendly new product and its market strategy."

[0088] Step 7:

[0089] The server validates the generated business concept and provides suggestions for improvement as needed. At this stage, validation tools are used, and competitive analysis and risk assessment are performed. The output is feedback on the idea's evaluation and areas for improvement.

[0090] Step 8:

[0091] The server ultimately uses planning tools to present the user with a detailed action plan. The output includes specific steps for commercialization and the necessary resources. Based on this information, the user can put their business idea into action.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] The process of generating new business ideas and evaluating their potential in the actual market is time-consuming and resource-intensive for companies and individuals. In particular, identifying the optimal business area based on user characteristics and developing concrete plans based on growth market data is complex. Therefore, a system is needed that efficiently and comprehensively generates and evaluates business ideas and provides clear implementation steps.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes profiling means for analyzing information from users and identifying their characteristics, market analysis means for collecting market data and identifying growth markets, and information presentation means for providing various technical ideas related to the business domain. This enables the efficient generation and evaluation of business ideas based on user characteristics and market data.

[0097] "Profiling methods" are means of analyzing information provided by users to identify their characteristics.

[0098] "Market analysis tools" are means of collecting data from the market to identify markets that are expected to grow.

[0099] An "idea generation method" is a means of creating new business ideas based on user characteristics and information on growing markets.

[0100] "Verification methods" are means for evaluating the feasibility of a generated business idea and identifying areas for improvement.

[0101] "Information presentation methods" refer to means of providing various technical ideas relevant to the business domain.

[0102] An "action plan formulation tool" is a means of providing the optimal steps for realizing a business idea.

[0103] This invention can be implemented using a system centered around a server. The server is equipped with multiple data processing means and operates in cooperation with a user terminal. The user accesses the system through the terminal and starts the business idea generation process by inputting the necessary information.

[0104] Specifically, when a user inputs their work history, skills, and interests using a terminal, the server receives this information and performs analysis using profiling tools. These profiling tools use software such as Python and TENSORFLOW® to identify characteristics based on the user's information using deep learning algorithms.

[0105] Next, the server's market analysis tool identifies markets with growth potential based on data collected from the internet. This analysis utilizes multiple AI agents. For example, data management using Firebase could be considered.

[0106] Following this, the server uses an idea generation mechanism to combine user characteristics obtained through profiling with market analysis data to create new business ideas. The generated ideas are then provided to the user via an application using an information presentation mechanism. At this stage, for example, new approaches related to energy-saving technologies or data management efficiency may be proposed to the user.

[0107] Furthermore, users can provide feedback on the generated business ideas, which the server then uses to conduct more detailed market analysis and competitor research. This leads to the development of a concrete action plan for the business idea, and users are shown actionable steps.

[0108] For example, if a user expresses interest in energy conservation in data centers, the system will generate a prompt message such as, "Please propose a new approach to energy conservation technologies in data centers. Specifically, please describe what kind of energy management systems are conceivable, taking future market trends into consideration."

[0109] This system allows users to efficiently generate new business ideas and ultimately build actionable plans in a short period of time.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] Users input information about their work history, skills, and interests using a terminal. The terminal then transmits this information as digital data to a server. The input data serves as foundational information to reveal the user's characteristics.

[0113] Step 2:

[0114] The server analyzes the received digital data using profiling techniques. This analysis utilizes a deep learning algorithm based on TensorFlow. As a result of the analysis, profile data indicating the user's characteristics is generated. This profile data serves as an indicator of which business areas the user is best suited for.

[0115] Step 3:

[0116] The server collects market data from the internet using market analysis tools and analyzes it. The collected data is processed by an AI agent, and market segments with expected growth potential are identified using a predictive analytics model. The output of this step is a list of markets with potential for development.

[0117] Step 4:

[0118] The server combines profile data and market data, and uses an idea generation tool to create new business ideas. Here, Python is used to programmatically generate ideas that consider the user's strengths and market opportunities. A list of the generated business ideas is output, and this list forms the basis for the next step.

[0119] Step 5:

[0120] Users receive the generated business ideas on their devices and provide feedback. This feedback is then sent back to the server and used for further analysis of the idea's marketability and competitive landscape. The feedback data reflects human intuition and market trends.

[0121] Step 6:

[0122] The server uses verification methods based on user feedback to identify areas for improvement. It conducts competitive analysis and proposes differentiation strategies. Here, AI-powered market viability assessments are performed, and data necessary for the next action plan is output.

[0123] Step 7:

[0124] The server uses action planning tools to provide users with concrete, actionable steps. This plan includes necessary resources and potential challenges. Ultimately, users receive an actionable business plan.

[0125] Step 8:

[0126] Users can review and implement the final business plan on their devices. A specific example is "developing a new business entry strategy utilizing market trend forecasting with a generative AI model."

[0127] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0128] This invention is a system that generates and validates business ideas through user profiling and market analysis, combining an emotion engine that recognizes user emotions. This system analyzes user information from multiple perspectives and proposes flexible business strategies that take emotional states into account. Specific embodiments are described below.

[0129] First, the user logs into the system via a terminal and inputs their work history, skills, interests, and real-time emotional data. Emotional data is collected through text analysis and voice input. Upon receiving this information, the server uses an emotional engine to recognize the user's emotional state. It then generates a detailed user profile by combining the user's skill data and emotional data, and the server suggests the most suitable business areas for the user.

[0130] Next, the server launches multiple AI agents to collect market data. Each AI agent focuses on a specific industry or region, analyzing market trends and consumer behavior. This identifies untapped markets with growth potential and presents business opportunities based on user profiles and market data.

[0131] Subsequently, the server uses an idea generation mechanism to generate business ideas that reflect the user's emotional information. The user's emotional state is considered as a factor influencing the creativity and direction of the ideas; if the user is in a positive emotional state, bolder business strategies may be proposed.

[0132] The generated business ideas are presented to the user, and feedback is collected from the user via the device. The server incorporates this feedback and user sentiment information to examine the feasibility and market suitability of the ideas in detail. Furthermore, the server uses verification tools to perform comparative analysis with other competing ideas based on sentiment information, and provides the user with a refined idea.

[0133] Finally, the server uses an action plan development tool to create an optimized execution plan for the user. This plan includes specific commercialization steps that take emotional information into account, necessary resources, and risk management measures. Based on this action plan, the user can effectively move towards realizing their business idea.

[0134] Thus, the present invention provides a more personalized and highly successful business plan by incorporating the user's emotional state.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] Users log in to the platform using their devices and enter their work history, skills, and interests, as well as sentiment data in real time. Sentiment data is provided via text input and voice.

[0138] Step 2:

[0139] The server securely stores information received from the user in a database and profiles the user's characteristics using deep learning algorithms. In addition, it activates an emotion engine to analyze the provided emotion data and identify the user's current emotional state.

[0140] Step 3:

[0141] The server activates AI agents to collect and analyze market data from diverse sources. The AI ​​agents focus on specific industries and regions, investigating market trends, consumer behavior, and competitive landscapes to identify untapped markets with growth potential.

[0142] Step 4:

[0143] The server integrates user profiles, emotional state information, and market data, and uses an idea generation engine to create business ideas. The server proposes flexible ideas based on the user's emotional state; for example, it might suggest a risky business approach in a positive emotional state.

[0144] Step 5:

[0145] Users can review business ideas presented by the server via their devices and provide feedback. This user feedback, along with sentiment information, is used in the next analysis step.

[0146] Step 6:

[0147] The server validates business ideas generated using AI models, taking into account user feedback and emotional information. The server performs market and competitive analysis, identifies necessary improvements, and presents them to the user again.

[0148] Step 7:

[0149] Ultimately, the server uses action planning tools to create a feasible business plan adapted to the emotional state. This plan includes specific implementation steps, necessary resources, and risk management measures. Based on this plan, the user can effectively carry out their activities.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] Traditional user profiling and market analysis systems only analyze user information in general terms and have the problem of not being able to propose business ideas that take into account the emotional state of users. Furthermore, they struggle to quickly and accurately identify growth markets in a dynamic market environment. Therefore, there is a need to provide flexible business strategies based on the individual emotional state and skills of users.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes profiling means for analyzing information from the user to identify user characteristics and recognize emotional states, market analysis means for collecting market data using multiple intelligent agents and identifying growth markets, and idea generation means for integrating user characteristics, emotional states, and growth market information to generate business ideas. This makes it possible to quickly and effectively provide personalized business strategies that reflect the user's emotions.

[0155] "Profiling tools" are devices or software used to analyze information collected from users and identify their characteristics and emotional states.

[0156] "Market analysis tools" refer to devices or software that use multiple intelligent agents to collect market data and identify markets with growth potential.

[0157] An "idea generation tool" is a device or software that integrates user characteristics, emotional states, and market information to generate new business ideas.

[0158] A "verification tool" is a device or software used to evaluate a generated business idea and provide improvements based on user feedback.

[0159] An "action plan formulation tool" is a device or software that takes into account the user's emotional information and provides the user with optimized business development steps.

[0160] An "intelligent agent" is a program or system that autonomously collects and analyzes market data, focusing on specific industries or regions.

[0161] This invention is a system for generating personalized business strategies that take user emotions into consideration. Specific embodiments are shown below.

[0162] Users access the system using a terminal and input their work history, skills, interests, and real-time sentiment data. Sentiment data is acquired using sentiment analysis technology via voice or text input. The software used includes sentiment analysis algorithms.

[0163] After receiving this information, the server uses profiling techniques to identify user characteristics and emotional states. Profiling is performed using machine learning models, and database software manages the user profiles.

[0164] Next, the server activates multiple intelligent agents through market analysis tools to collect market data. These intelligent agents focus on collecting and analyzing data for specific industries and regions. This utilizes web scraping techniques and API-based data integration. The analysis results help identify markets with growth potential.

[0165] Based on these analysis results, the server uses a generative AI model to generate business ideas integrated with the user's emotional state. The generated ideas are then creatively refined based on the user's emotional information and presented to the user's device. The user provides feedback on the proposed ideas, and the server uses this information to validate and optimize them.

[0166] For example, if a user is passionate about cooking as a hobby and the emotion engine recognizes that excitement, the system might suggest business ideas such as "online cooking classes" or "developing new menus using local ingredients."

[0167] An example of a prompt message is as follows: "The user's work experience is as a marketing specialist, their interest is cooking, and their current mood is elevated. Based on their skill set, please propose a suitable business idea."

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] Users log in to the system via their device and enter profile information, including work history, skills, and interests, as well as real-time sentiment data. This sentiment data is obtained through text analysis and voice input. The device then sends this data to the server.

[0171] Step 2:

[0172] The server analyzes the profile information and emotional data received from the user using profiling tools. By applying the input data to an emotional analysis algorithm, the user's emotional state is identified. This generates a detailed user profile.

[0173] Step 3:

[0174] The server uses market analysis tools to activate multiple intelligent agents to collect market data. Input consists of search criteria based on industry and region. Data is obtained through web scraping techniques and APIs, and output as market information indicating promising growth.

[0175] Step 4:

[0176] The server uses a generative AI model to integrate user characteristics, emotional states, and market information to generate business ideas. Based on the input, the idea generation algorithm processes the data and outputs new business ideas.

[0177] Step 5:

[0178] The generated business ideas are sent from the server to the user's terminal and presented to the user. The user provides feedback on the proposed ideas, and this information is sent back to the server via the terminal.

[0179] Step 6:

[0180] The server analyzes user feedback and sentiment information using verification tools to identify the feasibility and areas for improvement of the idea. A competitive analysis algorithm compares the idea with other ideas and outputs an optimized idea.

[0181] Step 7:

[0182] Ultimately, the server uses action planning tools to develop a concrete action plan, taking into account the user's emotional information. This plan includes necessary resources and risk management measures and is provided to the user via the terminal. Based on this plan, the user moves on to implementing their business idea.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0185] In today's business environment, uniform product recommendations that ignore consumers' emotional states can negatively impact purchasing intent. Traditional methods make it difficult to capture user emotions in real time and quickly propose products and services that respond accordingly. This creates a challenge in providing more personalized user experiences.

[0186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0187] In this invention, the server includes profiling means for analyzing user information to identify user characteristics, market analysis means for collecting market data to identify growth markets, and emotion recognition means for recognizing the user's emotional state in real time and optimizing information provision. This makes it possible to dynamically adjust product suggestions based on the user's emotional information and provide a more personalized user experience that enhances purchasing intent.

[0188] A "user" is an individual who uses a system to provide information.

[0189] "Profiling techniques" are technologies used to analyze information provided by users and identify their individual characteristics and attributes.

[0190] "Market analysis tools" are techniques that analyze market data collected from external sources to identify markets and trends that are expected to grow.

[0191] An "idea generation method" is a technique for devising new business ideas by integrating user characteristics and market data.

[0192] "Verification methods" are techniques for evaluating the feasibility and market suitability of generated business ideas and identifying necessary improvements.

[0193] "Action plan formulation tools" are technologies that create optimal business development steps and plans for users and provide concrete action guidelines.

[0194] "Emotion recognition means" refers to technology that recognizes the user's real-time emotional state and adjusts the content of information provided based on that.

[0195] A "product suggestion method" is a technology for dynamically adjusting the products and services suggested according to the user's emotional state.

[0196] The system for implementing this invention mainly consists of a server and a user terminal. The server is equipped with profiling means for analyzing information provided by the user, mainly skill and interest information, and real-time sentiment data. The profiling means collects sentiment data using voice input and text analysis, and uses this to generate individual user profiles. Google® Cloud Speech-to-Text API and Amazon Rekognition are used to collect sentiment data.

[0197] Furthermore, the server possesses market analysis capabilities, using different AI agents to collect and analyze data focused on specific industries and regions, identifying promising market trends. This utilizes advanced machine learning algorithms, which are integrated with user profiles to generate business ideas.

[0198] The user's device has an emotion recognition mechanism that grasps the user's emotional state in real time. This data is sent to a server, and a product suggestion mechanism dynamically suggests products and services that correspond to the user's emotional state. For example, if the user is in a positive emotional state, new products or bold suggestions are made, while if they are in a negative emotional state, relaxation products or sales information are provided.

[0199] As a concrete example, a user browsing an online shopping site on their device during their commute will receive different suggestions depending on their emotional tone when performing a voice search using their smartphone's microphone. An example of a prompt would be, "Please tell me how to analyze my current emotional state and suggest products that match it." Based on this prompt, a generative AI model can generate and present the most suitable suggestions to the user.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] Users log in to the system via their device and input skill data, interest information, and emotion data. The input data is sent from the device to the server. The server receives this data and analyzes the emotional state using an emotion engine. The data is processed through text analysis and voice input, and the emotion recognition model determines the type and intensity of the emotion.

[0203] Step 2:

[0204] The server uses profiling techniques to analyze the received user data. The input consists of user characteristics and attributes, and the output is a detailed user profile. This process integrates skill data and interest information, resulting in a comprehensive user analysis.

[0205] Step 3:

[0206] Based on user profiles, the server activates market analysis tools and uses different AI agents to collect market data specific to a particular industry or region. The input is market data, and the output is trend information for growing markets. Data analysis by the AI ​​agents identifies potential markets.

[0207] Step 4:

[0208] The server uses a generative AI model to integrate user profiles and market trend information to generate business ideas. The inputs are user profiles and market information, and the output is the generated business idea. In this process, the generative AI model evaluates the novelty and relevance of the proposal and refines the idea.

[0209] Step 5:

[0210] The server uses validation tools to evaluate the feasibility of the generated business ideas, based on user feedback and sentiment data. The inputs are the business ideas and user feedback, while the output is an improved idea, including suggested enhancements.

[0211] Step 6:

[0212] The server generates optimized business steps using an action plan development tool. The input is an improved business idea, and the output is an implementation plan. The server designs specific action procedures and resource allocations and provides them to the user.

[0213] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0229] This invention is a comprehensive business idea creation and verification system utilizing an autonomous AI agent. This system generates appropriate business ideas based on user information and evaluates the feasibility of the proposed ideas using market data. The system's operation is described in detail below.

[0230] First, the user logs into the system via a terminal and enters information such as their work history, skills, and interests. The server receives this information and analyzes it using a deep learning algorithm. This analysis generates a profile of the user's characteristics, and the server then suggests the most suitable business areas for the user. For example, if the user is proficient in the IT field, areas such as cloud computing or cybersecurity can be recommended.

[0231] Next, the server performs market analysis. Multiple AI agents analyze market data obtained from the internet to detect untapped markets with growth potential. Based on this, the server identifies promising business opportunities and presents them to the user.

[0232] Next, the server uses an idea generation tool to combine user profiles and market data to generate specific business ideas. The generated ideas take into account the user's strengths and market opportunities, and the server provides these ideas to the user in detail. For example, if the user's characteristics include digital marketing and there is high demand for smart devices in a particular region, the development of a new advertising platform might be proposed.

[0233] Subsequently, the user receives the suggested ideas via their device and provides feedback. Based on this feedback, the server uses an AI agent to analyze market viability and the competitive landscape, identifying areas for further improvement. For example, it can analyze competitor trends and recommend differentiation strategies.

[0234] Ultimately, the server develops an action plan and presents the user with steps toward commercialization. This plan includes necessary resources and potential challenges, helping the user create a concrete implementation plan. In this way, the user can quickly turn their business idea into a feasible one and aim for success.

[0235] Thus, the present invention utilizes user input and market data to consistently support the process from generating innovative business ideas to their implementation.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] Users log in to the platform using their device and enter basic information such as work history, skills, and interests through the portal interface.

[0239] Step 2:

[0240] The server receives information sent by the user and securely stores it in a database. Then, it analyzes this information using a deep learning model to generate a user profile. The user profile includes characteristics and strengths based on the user's skills and experience.

[0241] Step 3:

[0242] The server activates AI agents to acquire market data. This data includes information from the internet and partner data providers, and is used to analyze market trends, consumer behavior, and the competitive landscape. Each AI agent specializes in data for a specific industry or region.

[0243] Step 4:

[0244] Based on the collected market data, the server identifies untapped markets with growth potential. This information is integrated with user profiles to create a list of suggested business opportunities for the user. The user is then presented with attractive business area options to pursue.

[0245] Step 5:

[0246] The server uses an idea generation engine to combine user profile information with insights from market data to create concrete business ideas. These ideas reflect the individual user's strengths and market needs, and their feasibility is evaluated.

[0247] Step 6:

[0248] Users can review proposed business ideas from their devices and provide feedback. This feedback is sent to the system and used to further improve the ideas.

[0249] Step 7:

[0250] The server incorporates user feedback and uses automatically generated AI models to conduct competitive analysis and market evaluation, identifying the feasibility and areas for improvement of ideas. The results are presented to the user, and further actions are recommended if necessary.

[0251] Step 8:

[0252] Ultimately, the server uses action plan development tools to create an implementation plan from the business idea. This plan includes necessary resources, personnel, budget, and potential risks. The user can then use this information to proceed with specific business implementation.

[0253] (Example 1)

[0254] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0255] In today's business environment, it is difficult to quickly generate optimal business ideas that maximize the skills and interests of individual users while considering market growth potential. Furthermore, providing concrete steps and improvements to enhance the feasibility of the generated ideas is currently not sufficiently achieved. This hinders small and medium-sized enterprises and entrepreneurs from creating and rapidly implementing innovative business models.

[0256] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0257] In this invention, the server includes an information analysis means that analyzes information from the user to identify the user's characteristics, a proposal means that suggests the optimal business area based on the information, and a market data analysis means that collects market data using multiple AI agents to identify growth areas. This makes it possible to generate individual business ideas that reflect the user's skills and interests, and to formulate concrete action plans based on those ideas.

[0258] "Information analysis means" refers to methods for processing information provided by users and identifying individual characteristics.

[0259] "Proposal methods" refer to techniques for suggesting the most suitable business areas based on analyzed user information.

[0260] "Market data analysis methods" refer to techniques that use multiple AI agents to collect data from the market and identify areas with growth potential.

[0261] "Concept generation methods" refer to techniques for formulating specific business models by combining user characteristics and market information.

[0262] "Verification methods" refer to techniques for evaluating the generated business model and providing additional information and areas for improvement.

[0263] "Planning methods" refer to techniques for presenting concrete action plans for implementing an idea.

[0264] This invention is a system that generates optimal business ideas based on user information and supports their steady commercialization. Users access the system using a terminal. The terminal is provided with an interface for inputting the user's work history, skills, interests, etc. This information is sent to a server. The server receives this information and analyzes the user's characteristics using information analysis means. Generative AI models and deep learning algorithms are used for information analysis. As a result, a user profile is generated, and the optimal business area is presented to the user through a suggestion means.

[0265] The server also uses multiple AI agents to collect market data and identify markets with growth potential. Big data analytics and time series analysis are employed for market data analysis, which helps detect promising market opportunities.

[0266] Furthermore, the server combines user profiles and market data to generate concrete business concepts. In this process, a generative AI model is utilized to propose business models that consider user characteristics and market opportunities. The generated business concepts are evaluated using validation tools, and improvements are provided as needed. Finally, the server presents a detailed action plan using planning tools. This plan includes specific steps and resources for implementing the idea.

[0267] For example, if the information provided by the user relates to "eco-friendly product development," the system can analyze market data, identify the growing market for renewable energy, and specifically propose the development of new products utilizing solar panels.

[0268] An example of a prompt to input into a generative AI model would be text such as, "The user's area of ​​interest is eco-products. Based on current market information and user characteristics, please propose appropriate business ideas."

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] Users log in to the system using their terminal and enter information such as their work history, skills, and interests. This information is received via forms on the terminal. The entered data is then transferred to the server via the internet.

[0272] Step 2:

[0273] The server processes the received user information using information analysis tools. This process utilizes a generative AI model and deep learning algorithms for data processing. As output, a profile defining the user's characteristics is generated. This profile is then used for subsequent business area proposals.

[0274] Step 3:

[0275] The server suggests the most suitable business domain based on the profile. At this stage, suggestion tools are used to analyze the entity and select a specific industry domain that matches the user's interests and skills. The output is a recommended domain, such as "IT services" or "eco-products."

[0276] Step 4:

[0277] The server uses multiple AI agents to collect market data from external data sources. Inputs include publicly available data on the internet and commercial databases, accessed through data acquisition protocols. Outputs include information on collected market trends and growth forecasts.

[0278] Step 5:

[0279] The server analyzes the market information collected using the market data analysis means. By using big data analysis methods and time series analysis, it identifies the markets with expected growth and outputs the detected growth areas. In this process, data pattern recognition and clustering techniques are used.

[0280] Step 6:

[0281] The server integrates the user's profile and market data and generates specific business ideas using the idea generation means. Data calculations are performed by the generated AI model, and specific business ideas are proposed as the output. This idea could be, for example, "the development of an eco-friendly new product and its market strategy".

[0282] Step 7:

[0283] The server verifies the generated business ideas and provides improvement points if necessary. At this stage, verification means are used, and competitive analysis and risk assessment are carried out. The output is the evaluation result of the idea and feedback on the points that need improvement.

[0284] Step 8:

[0285] The server finally uses the planning means to present a detailed action plan to the user. The output includes specific steps for commercialization and the necessary resources. The user can then move forward with implementing the business idea based on this information.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] The process of generating new business ideas and evaluating their potential in the actual market is time-consuming and resource-intensive for companies and individuals. In particular, identifying the optimal business area based on user characteristics and developing concrete plans based on growth market data is complex. Therefore, a system is needed that efficiently and comprehensively generates and evaluates business ideas and provides clear implementation steps.

[0289] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0290] In this invention, the server includes profiling means for analyzing information from users and identifying their characteristics, market analysis means for collecting market data and identifying growth markets, and information presentation means for providing various technical ideas related to the business domain. This enables the efficient generation and evaluation of business ideas based on user characteristics and market data.

[0291] "Profiling methods" are means of analyzing information provided by users to identify their characteristics.

[0292] "Market analysis tools" are means of collecting data from the market to identify markets that are expected to grow.

[0293] An "idea generation method" is a means of creating new business ideas based on user characteristics and information on growing markets.

[0294] "Verification methods" are means for evaluating the feasibility of a generated business idea and identifying areas for improvement.

[0295] "Information presentation methods" refer to means of providing various technical ideas relevant to the business domain.

[0296] An "action plan formulation tool" is a means of providing the optimal steps for realizing a business idea.

[0297] This invention can be implemented using a system centered around a server. The server is equipped with multiple data processing means and operates in cooperation with a user terminal. The user accesses the system through the terminal and starts the business idea generation process by inputting the necessary information.

[0298] Specifically, when a user inputs their work history, skills, and interests using a terminal, the server receives this information and performs analysis using profiling tools. These profiling tools use software such as Python and TensorFlow to identify characteristics based on the user's information using deep learning algorithms.

[0299] Next, the server's market analysis tool identifies markets with growth potential based on data collected from the internet. This analysis utilizes multiple AI agents. For example, data management using Firebase could be considered.

[0300] Following this, the server uses an idea generation mechanism to combine user characteristics obtained through profiling with market analysis data to create new business ideas. The generated ideas are then provided to the user via an application using an information presentation mechanism. At this stage, for example, new approaches related to energy-saving technologies or data management efficiency may be proposed to the user.

[0301] Furthermore, users can provide feedback on the generated business ideas, which the server then uses to conduct more detailed market analysis and competitor research. This leads to the development of a concrete action plan for the business idea, and users are shown actionable steps.

[0302] For example, when a user shows interest in energy conservation in a data center, the system generates a prompt sentence: "Please propose a new approach to energy conservation technology in the data center. Specifically, please show what kind of energy management system can be considered, taking into account future market trends."

[0303] With this system, users can efficiently generate new business ideas and ultimately construct executable plans in a short period of time.

[0304] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0305] Step 1:

[0306] The user uses a terminal to input information regarding work history, skills, and interests. At this time, the terminal transmits the input information to the server as digital data. The data to be input is basic information for clarifying the user's characteristics.

[0307] Step 2:

[0308] The server analyzes the received digital data using profiling means. For this analysis, a deep learning algorithm using TensorFlow is utilized. As a result of the analysis, profile data indicating the user's characteristics is generated. The profile data serves as an indicator showing which business areas the user is suitable for.

[0309] Step 3:

[0310] The server collects market data from the Internet using market analysis means and analyzes it. The collected data is processed by an AI agent, and market segments expected to grow are identified using a predictive analysis model. The output of this step is a list of markets with expected growth.

[0311] Step 4:

[0312] The server combines profile data and market data, and uses an idea generation tool to create new business ideas. Here, Python is used to programmatically generate ideas that consider the user's strengths and market opportunities. A list of the generated business ideas is output, and this list forms the basis for the next step.

[0313] Step 5:

[0314] Users receive the generated business ideas on their devices and provide feedback. This feedback is then sent back to the server and used for further analysis of the idea's marketability and competitive landscape. The feedback data reflects human intuition and market trends.

[0315] Step 6:

[0316] The server uses verification methods based on user feedback to identify areas for improvement. It conducts competitive analysis and proposes differentiation strategies. Here, AI-powered market viability assessments are performed, and data necessary for the next action plan is output.

[0317] Step 7:

[0318] The server uses action planning tools to provide users with concrete, actionable steps. This plan includes necessary resources and potential challenges. Ultimately, users receive an actionable business plan.

[0319] Step 8:

[0320] Users can review and implement the final business plan on their devices. A specific example is "developing a new business entry strategy utilizing market trend forecasting with a generative AI model."

[0321] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0322] This invention is a system that generates and validates business ideas through user profiling and market analysis, combining an emotion engine that recognizes user emotions. This system analyzes user information from multiple perspectives and proposes flexible business strategies that take emotional states into account. Specific embodiments are described below.

[0323] First, the user logs into the system via a terminal and inputs their work history, skills, interests, and real-time emotional data. Emotional data is collected through text analysis and voice input. Upon receiving this information, the server uses an emotional engine to recognize the user's emotional state. It then generates a detailed user profile by combining the user's skill data and emotional data, and the server suggests the most suitable business areas for the user.

[0324] Next, the server launches multiple AI agents to collect market data. Each AI agent focuses on a specific industry or region, analyzing market trends and consumer behavior. This identifies untapped markets with growth potential and presents business opportunities based on user profiles and market data.

[0325] Subsequently, the server uses an idea generation mechanism to generate business ideas that reflect the user's emotional information. The user's emotional state is considered as a factor influencing the creativity and direction of the ideas; if the user is in a positive emotional state, bolder business strategies may be proposed.

[0326] The generated business ideas are presented to the user, and feedback is collected from the user via the device. The server incorporates this feedback and user sentiment information to examine the feasibility and market suitability of the ideas in detail. Furthermore, the server uses verification tools to perform comparative analysis with other competing ideas based on sentiment information, and provides the user with a refined idea.

[0327] Finally, the server uses an action plan development tool to create an optimized execution plan for the user. This plan includes specific commercialization steps that take emotional information into account, necessary resources, and risk management measures. Based on this action plan, the user can effectively move towards realizing their business idea.

[0328] Thus, the present invention provides a more personalized and highly successful business plan by incorporating the user's emotional state.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] Users log in to the platform using their devices and enter their work history, skills, and interests, as well as sentiment data in real time. Sentiment data is provided via text input and voice.

[0332] Step 2:

[0333] The server securely stores information received from the user in a database and profiles the user's characteristics using deep learning algorithms. In addition, it activates an emotion engine to analyze the provided emotion data and identify the user's current emotional state.

[0334] Step 3:

[0335] The server activates AI agents to collect and analyze market data from diverse sources. The AI ​​agents focus on specific industries and regions, investigating market trends, consumer behavior, and competitive landscapes to identify untapped markets with growth potential.

[0336] Step 4:

[0337] The server integrates user profiles, emotional state information, and market data, and uses an idea generation engine to create business ideas. The server proposes flexible ideas based on the user's emotional state; for example, it might suggest a risky business approach in a positive emotional state.

[0338] Step 5:

[0339] Users can review business ideas presented by the server via their devices and provide feedback. This user feedback, along with sentiment information, is used in the next analysis step.

[0340] Step 6:

[0341] The server validates business ideas generated using AI models, taking into account user feedback and emotional information. The server performs market and competitive analysis, identifies necessary improvements, and presents them to the user again.

[0342] Step 7:

[0343] Ultimately, the server uses action planning tools to create a feasible business plan adapted to the emotional state. This plan includes specific implementation steps, necessary resources, and risk management measures. Based on this plan, the user can effectively carry out their activities.

[0344] (Example 2)

[0345] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0346] Traditional user profiling and market analysis systems only analyze user information in general terms and have the problem of not being able to propose business ideas that take into account the emotional state of users. Furthermore, they struggle to quickly and accurately identify growth markets in a dynamic market environment. Therefore, there is a need to provide flexible business strategies based on the individual emotional state and skills of users.

[0347] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0348] In this invention, the server includes profiling means for analyzing information from the user to identify user characteristics and recognize emotional states, market analysis means for collecting market data using multiple intelligent agents and identifying growth markets, and idea generation means for integrating user characteristics, emotional states, and growth market information to generate business ideas. This makes it possible to quickly and effectively provide personalized business strategies that reflect the user's emotions.

[0349] "Profiling tools" are devices or software used to analyze information collected from users and identify their characteristics and emotional states.

[0350] "Market analysis tools" refer to devices or software that use multiple intelligent agents to collect market data and identify markets with growth potential.

[0351] An "idea generation tool" is a device or software that integrates user characteristics, emotional states, and market information to generate new business ideas.

[0352] A "verification tool" is a device or software used to evaluate a generated business idea and provide improvements based on user feedback.

[0353] An "action plan formulation tool" is a device or software that takes into account the user's emotional information and provides the user with optimized business development steps.

[0354] An "intelligent agent" is a program or system that autonomously collects and analyzes market data, focusing on specific industries or regions.

[0355] This invention is a system for generating personalized business strategies that take user emotions into consideration. Specific embodiments are shown below.

[0356] Users access the system using a terminal and input their work history, skills, interests, and real-time sentiment data. Sentiment data is acquired using sentiment analysis technology via voice or text input. The software used includes sentiment analysis algorithms.

[0357] After receiving this information, the server uses profiling techniques to identify user characteristics and emotional states. Profiling is performed using machine learning models, and database software manages the user profiles.

[0358] Next, the server activates multiple intelligent agents through market analysis tools to collect market data. These intelligent agents focus on collecting and analyzing data for specific industries and regions. This utilizes web scraping techniques and API-based data integration. The analysis results help identify markets with growth potential.

[0359] Based on these analysis results, the server uses a generative AI model to generate business ideas integrated with the user's emotional state. The generated ideas are then creatively refined based on the user's emotional information and presented to the user's device. The user provides feedback on the proposed ideas, and the server uses this information to validate and optimize them.

[0360] For example, if a user is passionate about cooking as a hobby and the emotion engine recognizes that excitement, the system might suggest business ideas such as "online cooking classes" or "developing new menus using local ingredients."

[0361] An example of a prompt message is as follows: "The user's work experience is as a marketing specialist, their interest is cooking, and their current mood is elevated. Based on their skill set, please propose a suitable business idea."

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] Users log in to the system via their device and enter profile information, including work history, skills, and interests, as well as real-time sentiment data. This sentiment data is obtained through text analysis and voice input. The device then sends this data to the server.

[0365] Step 2:

[0366] The server analyzes the profile information and emotional data received from the user using profiling tools. By applying the input data to an emotional analysis algorithm, the user's emotional state is identified. This generates a detailed user profile.

[0367] Step 3:

[0368] The server uses market analysis tools to activate multiple intelligent agents to collect market data. Input consists of search criteria based on industry and region. Data is obtained through web scraping techniques and APIs, and output as market information indicating promising growth.

[0369] Step 4:

[0370] The server uses a generative AI model to integrate user characteristics, emotional states, and market information to generate business ideas. Based on the input, the idea generation algorithm processes the data and outputs new business ideas.

[0371] Step 5:

[0372] The generated business ideas are sent from the server to the user's terminal and presented to the user. The user provides feedback on the proposed ideas, and this information is sent back to the server via the terminal.

[0373] Step 6:

[0374] The server analyzes user feedback and sentiment information using verification tools to identify the feasibility and areas for improvement of the idea. A competitive analysis algorithm compares the idea with other ideas and outputs an optimized idea.

[0375] Step 7:

[0376] Ultimately, the server uses action planning tools to develop a concrete action plan, taking into account the user's emotional information. This plan includes necessary resources and risk management measures and is provided to the user via the terminal. Based on this plan, the user moves on to implementing their business idea.

[0377] (Application Example 2)

[0378] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0379] In today's business environment, uniform product recommendations that ignore consumers' emotional states can negatively impact purchasing intent. Traditional methods make it difficult to capture user emotions in real time and quickly propose products and services that respond accordingly. This creates a challenge in providing more personalized user experiences.

[0380] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0381] In this invention, the server includes profiling means for analyzing user information to identify user characteristics, market analysis means for collecting market data to identify growth markets, and emotion recognition means for recognizing the user's emotional state in real time and optimizing information provision. This makes it possible to dynamically adjust product suggestions based on the user's emotional information and provide a more personalized user experience that enhances purchasing intent.

[0382] A "user" is an individual who uses a system to provide information.

[0383] "Profiling techniques" are technologies used to analyze information provided by users and identify their individual characteristics and attributes.

[0384] "Market analysis tools" are techniques that analyze market data collected from external sources to identify markets and trends that are expected to grow.

[0385] An "idea generation method" is a technique for devising new business ideas by integrating user characteristics and market data.

[0386] "Verification methods" are techniques for evaluating the feasibility and market suitability of generated business ideas and identifying necessary improvements.

[0387] "Action plan formulation tools" are technologies that create optimal business development steps and plans for users and provide concrete action guidelines.

[0388] "Emotion recognition means" refers to technology that recognizes the user's real-time emotional state and adjusts the content of information provided based on that.

[0389] A "product suggestion method" is a technology for dynamically adjusting the products and services suggested according to the user's emotional state.

[0390] The system for implementing this invention mainly consists of a server and a user terminal. The server is equipped with profiling means for analyzing information provided by the user, mainly skill and interest information, and real-time sentiment data. The profiling means collects sentiment data using voice input and text analysis, and uses this to generate individual user profiles. Google Cloud Speech-to-Text API and Amazon Rekognition are used to collect sentiment data.

[0391] Furthermore, the server possesses market analysis capabilities, using different AI agents to collect and analyze data focused on specific industries and regions, identifying promising market trends. This utilizes advanced machine learning algorithms, which are integrated with user profiles to generate business ideas.

[0392] The user's device has an emotion recognition mechanism that grasps the user's emotional state in real time. This data is sent to a server, and a product suggestion mechanism dynamically suggests products and services that correspond to the user's emotional state. For example, if the user is in a positive emotional state, new products or bold suggestions are made, while if they are in a negative emotional state, relaxation products or sales information are provided.

[0393] As a concrete example, a user browsing an online shopping site on their device during their commute will receive different suggestions depending on their emotional tone when performing a voice search using their smartphone's microphone. An example of a prompt would be, "Please tell me how to analyze my current emotional state and suggest products that match it." Based on this prompt, a generative AI model can generate and present the most suitable suggestions to the user.

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] Users log in to the system via their device and input skill data, interest information, and emotion data. The input data is sent from the device to the server. The server receives this data and analyzes the emotional state using an emotion engine. The data is processed through text analysis and voice input, and the emotion recognition model determines the type and intensity of the emotion.

[0397] Step 2:

[0398] The server uses profiling techniques to analyze the received user data. The input consists of user characteristics and attributes, and the output is a detailed user profile. This process integrates skill data and interest information, resulting in a comprehensive user analysis.

[0399] Step 3:

[0400] Based on user profiles, the server activates market analysis tools and uses different AI agents to collect market data specific to a particular industry or region. The input is market data, and the output is trend information for growing markets. Data analysis by the AI ​​agents identifies potential markets.

[0401] Step 4:

[0402] The server uses a generative AI model to integrate user profiles and market trend information to generate business ideas. The inputs are user profiles and market information, and the output is the generated business idea. In this process, the generative AI model evaluates the novelty and relevance of the proposal and refines the idea.

[0403] Step 5:

[0404] The server uses validation tools to evaluate the feasibility of the generated business ideas, based on user feedback and sentiment data. The inputs are the business ideas and user feedback, while the output is an improved idea, including suggested enhancements.

[0405] Step 6:

[0406] The server generates optimized business steps using an action plan development tool. The input is an improved business idea, and the output is an implementation plan. The server designs specific action procedures and resource allocations and provides them to the user.

[0407] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0408] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0409] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0410] [Third Embodiment]

[0411] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0412] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0413] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0414] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0415] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0416] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0417] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0418] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0419] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0420] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0421] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0422] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0423] This invention is a comprehensive business idea creation and verification system utilizing an autonomous AI agent. This system generates appropriate business ideas based on user information and evaluates the feasibility of the proposed ideas using market data. The system's operation is described in detail below.

[0424] First, the user logs into the system via a terminal and enters information such as their work history, skills, and interests. The server receives this information and analyzes it using a deep learning algorithm. This analysis generates a profile of the user's characteristics, and the server then suggests the most suitable business areas for the user. For example, if the user is proficient in the IT field, areas such as cloud computing or cybersecurity can be recommended.

[0425] Next, the server performs market analysis. Multiple AI agents analyze market data obtained from the internet to detect untapped markets with growth potential. Based on this, the server identifies promising business opportunities and presents them to the user.

[0426] Next, the server uses an idea generation tool to combine user profiles and market data to generate specific business ideas. The generated ideas take into account the user's strengths and market opportunities, and the server provides these ideas to the user in detail. For example, if the user's characteristics include digital marketing and there is high demand for smart devices in a particular region, the development of a new advertising platform might be proposed.

[0427] Subsequently, the user receives the suggested ideas via their device and provides feedback. Based on this feedback, the server uses an AI agent to analyze market viability and the competitive landscape, identifying areas for further improvement. For example, it can analyze competitor trends and recommend differentiation strategies.

[0428] Ultimately, the server develops an action plan and presents the user with steps toward commercialization. This plan includes necessary resources and potential challenges, helping the user create a concrete implementation plan. In this way, the user can quickly turn their business idea into a feasible one and aim for success.

[0429] Thus, the present invention utilizes user input and market data to consistently support the process from generating innovative business ideas to their implementation.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] Users log in to the platform using their device and enter basic information such as work history, skills, and interests through the portal interface.

[0433] Step 2:

[0434] The server receives information sent by the user and securely stores it in a database. Then, it analyzes this information using a deep learning model to generate a user profile. The user profile includes characteristics and strengths based on the user's skills and experience.

[0435] Step 3:

[0436] The server activates AI agents to acquire market data. This data includes information from the internet and partner data providers, and is used to analyze market trends, consumer behavior, and the competitive landscape. Each AI agent specializes in data for a specific industry or region.

[0437] Step 4:

[0438] Based on the collected market data, the server identifies untapped markets with growth potential. This information is integrated with user profiles to create a list of suggested business opportunities for the user. The user is then presented with attractive business area options to pursue.

[0439] Step 5:

[0440] The server uses an idea generation engine to combine user profile information with insights from market data to create concrete business ideas. These ideas reflect the individual user's strengths and market needs, and their feasibility is evaluated.

[0441] Step 6:

[0442] Users can review proposed business ideas from their devices and provide feedback. This feedback is sent to the system and used to further improve the ideas.

[0443] Step 7:

[0444] The server incorporates user feedback and uses automatically generated AI models to conduct competitive analysis and market evaluation, identifying the feasibility and areas for improvement of ideas. The results are presented to the user, and further actions are recommended if necessary.

[0445] Step 8:

[0446] Ultimately, the server uses action plan development tools to create an implementation plan from the business idea. This plan includes necessary resources, personnel, budget, and potential risks. The user can then use this information to proceed with specific business implementation.

[0447] (Example 1)

[0448] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0449] In today's business environment, it is difficult to quickly generate optimal business ideas that maximize the skills and interests of individual users while considering market growth potential. Furthermore, providing concrete steps and improvements to enhance the feasibility of the generated ideas is currently not sufficiently achieved. This hinders small and medium-sized enterprises and entrepreneurs from creating and rapidly implementing innovative business models.

[0450] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0451] In this invention, the server includes an information analysis means that analyzes information from the user to identify the user's characteristics, a proposal means that suggests the optimal business area based on the information, and a market data analysis means that collects market data using multiple AI agents to identify growth areas. This makes it possible to generate individual business ideas that reflect the user's skills and interests, and to formulate concrete action plans based on those ideas.

[0452] "Information analysis means" refers to methods for processing information provided by users and identifying individual characteristics.

[0453] "Proposal methods" refer to techniques for suggesting the most suitable business areas based on analyzed user information.

[0454] "Market data analysis methods" refer to techniques that use multiple AI agents to collect data from the market and identify areas with growth potential.

[0455] "Concept generation methods" refer to techniques for formulating specific business models by combining user characteristics and market information.

[0456] "Verification methods" refer to techniques for evaluating the generated business model and providing additional information and areas for improvement.

[0457] "Planning methods" refer to techniques for presenting concrete action plans for implementing an idea.

[0458] This invention is a system that generates optimal business ideas based on user information and supports their steady commercialization. Users access the system using a terminal. The terminal is provided with an interface for inputting the user's work history, skills, interests, etc. This information is sent to a server. The server receives this information and analyzes the user's characteristics using information analysis means. Generative AI models and deep learning algorithms are used for information analysis. As a result, a user profile is generated, and the optimal business area is presented to the user through a suggestion means.

[0459] The server also uses multiple AI agents to collect market data and identify markets with growth potential. Big data analytics and time series analysis are employed for market data analysis, which helps detect promising market opportunities.

[0460] Furthermore, the server combines user profiles and market data to generate concrete business concepts. In this process, a generative AI model is utilized to propose business models that consider user characteristics and market opportunities. The generated business concepts are evaluated using validation tools, and improvements are provided as needed. Finally, the server presents a detailed action plan using planning tools. This plan includes specific steps and resources for implementing the idea.

[0461] For example, if the information provided by the user relates to "eco-friendly product development," the system can analyze market data, identify the growing market for renewable energy, and specifically propose the development of new products utilizing solar panels.

[0462] An example of a prompt to input into a generative AI model would be text such as, "The user's area of ​​interest is eco-products. Based on current market information and user characteristics, please propose appropriate business ideas."

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] Users log in to the system using their terminal and enter information such as their work history, skills, and interests. This information is received via forms on the terminal. The entered data is then transferred to the server via the internet.

[0466] Step 2:

[0467] The server processes the received user information using information analysis tools. This process utilizes a generative AI model and deep learning algorithms for data processing. As output, a profile defining the user's characteristics is generated. This profile is then used for subsequent business area proposals.

[0468] Step 3:

[0469] The server suggests the most suitable business domain based on the profile. At this stage, suggestion tools are used to analyze the entity and select a specific industry domain that matches the user's interests and skills. The output is a recommended domain, such as "IT services" or "eco-products."

[0470] Step 4:

[0471] The server uses multiple AI agents to collect market data from external data sources. Inputs include publicly available data on the internet and commercial databases, accessed through data acquisition protocols. Outputs include information on collected market trends and growth forecasts.

[0472] Step 5:

[0473] The server analyzes market information collected using market data analysis tools. Big data analysis techniques and time-series analysis are used to identify markets with growth potential and output the detected growth areas. This process utilizes data pattern recognition and clustering technologies.

[0474] Step 6:

[0475] The server integrates user profiles and market data, and generates concrete business concepts using concept generation tools. Data calculations are performed by a generation AI model, and specific business ideas are proposed as output. These ideas might include, for example, "the development of an eco-friendly new product and its market strategy."

[0476] Step 7:

[0477] The server validates the generated business concept and provides suggestions for improvement as needed. At this stage, validation tools are used, and competitive analysis and risk assessment are performed. The output is feedback on the idea's evaluation and areas for improvement.

[0478] Step 8:

[0479] The server ultimately uses planning tools to present the user with a detailed action plan. The output includes specific steps for commercialization and the necessary resources. Based on this information, the user can put their business idea into action.

[0480] (Application Example 1)

[0481] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0482] The process of generating new business ideas and evaluating their potential in the actual market is time-consuming and resource-intensive for companies and individuals. In particular, identifying the optimal business area based on user characteristics and developing concrete plans based on growth market data is complex. Therefore, a system is needed that efficiently and comprehensively generates and evaluates business ideas and provides clear implementation steps.

[0483] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0484] In this invention, the server includes profiling means for analyzing information from users and identifying their characteristics, market analysis means for collecting market data and identifying growth markets, and information presentation means for providing various technical ideas related to the business domain. This enables the efficient generation and evaluation of business ideas based on user characteristics and market data.

[0485] "Profiling methods" are means of analyzing information provided by users to identify their characteristics.

[0486] "Market analysis tools" are means of collecting data from the market to identify markets that are expected to grow.

[0487] An "idea generation method" is a means of creating new business ideas based on user characteristics and information on growing markets.

[0488] "Verification methods" are means for evaluating the feasibility of a generated business idea and identifying areas for improvement.

[0489] "Information presentation methods" refer to means of providing various technical ideas relevant to the business domain.

[0490] An "action plan formulation tool" is a means of providing the optimal steps for realizing a business idea.

[0491] This invention can be implemented using a system centered around a server. The server is equipped with multiple data processing means and operates in cooperation with a user terminal. The user accesses the system through the terminal and starts the business idea generation process by inputting the necessary information.

[0492] Specifically, when a user inputs their work history, skills, and interests using a terminal, the server receives this information and performs analysis using profiling tools. These profiling tools use software such as Python and TensorFlow to identify characteristics based on the user's information using deep learning algorithms.

[0493] Next, the server's market analysis tool identifies markets with growth potential based on data collected from the internet. This analysis utilizes multiple AI agents. For example, data management using Firebase could be considered.

[0494] Following this, the server uses an idea generation mechanism to combine user characteristics obtained through profiling with market analysis data to create new business ideas. The generated ideas are then provided to the user via an application using an information presentation mechanism. At this stage, for example, new approaches related to energy-saving technologies or data management efficiency may be proposed to the user.

[0495] Furthermore, users can provide feedback on the generated business ideas, which the server then uses to conduct more detailed market analysis and competitor research. This leads to the development of a concrete action plan for the business idea, and users are shown actionable steps.

[0496] For example, if a user expresses interest in energy conservation in data centers, the system will generate a prompt message such as, "Please propose a new approach to energy conservation technologies in data centers. Specifically, please describe what kind of energy management systems are conceivable, taking future market trends into consideration."

[0497] This system allows users to efficiently generate new business ideas and ultimately build actionable plans in a short period of time.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] Users input information about their work history, skills, and interests using a terminal. The terminal then transmits this information as digital data to a server. The input data serves as foundational information to reveal the user's characteristics.

[0501] Step 2:

[0502] The server analyzes the received digital data using profiling techniques. This analysis utilizes a deep learning algorithm based on TensorFlow. As a result of the analysis, profile data indicating the user's characteristics is generated. This profile data serves as an indicator of which business areas the user is best suited for.

[0503] Step 3:

[0504] The server collects market data from the internet using market analysis tools and analyzes it. The collected data is processed by an AI agent, and market segments with expected growth potential are identified using a predictive analytics model. The output of this step is a list of markets with potential for development.

[0505] Step 4:

[0506] The server combines profile data and market data, and uses an idea generation tool to create new business ideas. Here, Python is used to programmatically generate ideas that consider the user's strengths and market opportunities. A list of the generated business ideas is output, and this list forms the basis for the next step.

[0507] Step 5:

[0508] Users receive the generated business ideas on their devices and provide feedback. This feedback is then sent back to the server and used for further analysis of the idea's marketability and competitive landscape. The feedback data reflects human intuition and market trends.

[0509] Step 6:

[0510] The server uses verification methods based on user feedback to identify areas for improvement. It conducts competitive analysis and proposes differentiation strategies. Here, AI-powered market viability assessments are performed, and data necessary for the next action plan is output.

[0511] Step 7:

[0512] The server uses action planning tools to provide users with concrete, actionable steps. This plan includes necessary resources and potential challenges. Ultimately, users receive an actionable business plan.

[0513] Step 8:

[0514] Users can review and implement the final business plan on their devices. A specific example is "developing a new business entry strategy utilizing market trend forecasting with a generative AI model."

[0515] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0516] This invention is a system that generates and validates business ideas through user profiling and market analysis, combining an emotion engine that recognizes user emotions. This system analyzes user information from multiple perspectives and proposes flexible business strategies that take emotional states into account. Specific embodiments are described below.

[0517] First, the user logs into the system via a terminal and inputs their work history, skills, interests, and real-time emotional data. Emotional data is collected through text analysis and voice input. Upon receiving this information, the server uses an emotional engine to recognize the user's emotional state. It then generates a detailed user profile by combining the user's skill data and emotional data, and the server suggests the most suitable business areas for the user.

[0518] Next, the server launches multiple AI agents to collect market data. Each AI agent focuses on a specific industry or region, analyzing market trends and consumer behavior. This identifies untapped markets with growth potential and presents business opportunities based on user profiles and market data.

[0519] Subsequently, the server uses an idea generation mechanism to generate business ideas that reflect the user's emotional information. The user's emotional state is considered as a factor influencing the creativity and direction of the ideas; if the user is in a positive emotional state, bolder business strategies may be proposed.

[0520] The generated business ideas are presented to the user, and feedback is collected from the user via the device. The server incorporates this feedback and user sentiment information to examine the feasibility and market suitability of the ideas in detail. Furthermore, the server uses verification tools to perform comparative analysis with other competing ideas based on sentiment information, and provides the user with a refined idea.

[0521] Finally, the server uses an action plan development tool to create an optimized execution plan for the user. This plan includes specific commercialization steps that take emotional information into account, necessary resources, and risk management measures. Based on this action plan, the user can effectively move towards realizing their business idea.

[0522] Thus, the present invention provides a more personalized and highly successful business plan by incorporating the user's emotional state.

[0523] The following describes the processing flow.

[0524] Step 1:

[0525] Users log in to the platform using their devices and enter their work history, skills, and interests, as well as sentiment data in real time. Sentiment data is provided via text input and voice.

[0526] Step 2:

[0527] The server securely stores information received from the user in a database and profiles the user's characteristics using deep learning algorithms. In addition, it activates an emotion engine to analyze the provided emotion data and identify the user's current emotional state.

[0528] Step 3:

[0529] The server activates AI agents to collect and analyze market data from diverse sources. The AI ​​agents focus on specific industries and regions, investigating market trends, consumer behavior, and competitive landscapes to identify untapped markets with growth potential.

[0530] Step 4:

[0531] The server integrates user profiles, emotional state information, and market data, and uses an idea generation engine to create business ideas. The server proposes flexible ideas based on the user's emotional state; for example, it might suggest a risky business approach in a positive emotional state.

[0532] Step 5:

[0533] Users can review business ideas presented by the server via their devices and provide feedback. This user feedback, along with sentiment information, is used in the next analysis step.

[0534] Step 6:

[0535] The server validates business ideas generated using AI models, taking into account user feedback and emotional information. The server performs market and competitive analysis, identifies necessary improvements, and presents them to the user again.

[0536] Step 7:

[0537] Ultimately, the server uses action planning tools to create a feasible business plan adapted to the emotional state. This plan includes specific implementation steps, necessary resources, and risk management measures. Based on this plan, the user can effectively carry out their activities.

[0538] (Example 2)

[0539] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] Traditional user profiling and market analysis systems only analyze user information in general terms and have the problem of not being able to propose business ideas that take into account the emotional state of users. Furthermore, they struggle to quickly and accurately identify growth markets in a dynamic market environment. Therefore, there is a need to provide flexible business strategies based on the individual emotional state and skills of users.

[0541] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0542] In this invention, the server includes profiling means for analyzing information from the user to identify user characteristics and recognize emotional states, market analysis means for collecting market data using multiple intelligent agents and identifying growth markets, and idea generation means for integrating user characteristics, emotional states, and growth market information to generate business ideas. This makes it possible to quickly and effectively provide personalized business strategies that reflect the user's emotions.

[0543] "Profiling tools" are devices or software used to analyze information collected from users and identify their characteristics and emotional states.

[0544] "Market analysis tools" refer to devices or software that use multiple intelligent agents to collect market data and identify markets with growth potential.

[0545] An "idea generation tool" is a device or software that integrates user characteristics, emotional states, and market information to generate new business ideas.

[0546] A "verification tool" is a device or software used to evaluate a generated business idea and provide improvements based on user feedback.

[0547] An "action plan formulation tool" is a device or software that takes into account the user's emotional information and provides the user with optimized business development steps.

[0548] An "intelligent agent" is a program or system that autonomously collects and analyzes market data, focusing on specific industries or regions.

[0549] This invention is a system for generating personalized business strategies that take user emotions into consideration. Specific embodiments are shown below.

[0550] Users access the system using a terminal and input their work history, skills, interests, and real-time sentiment data. Sentiment data is acquired using sentiment analysis technology via voice or text input. The software used includes sentiment analysis algorithms.

[0551] After receiving this information, the server uses profiling techniques to identify user characteristics and emotional states. Profiling is performed using machine learning models, and database software manages the user profiles.

[0552] Next, the server activates multiple intelligent agents through market analysis tools to collect market data. These intelligent agents focus on collecting and analyzing data for specific industries and regions. This utilizes web scraping techniques and API-based data integration. The analysis results help identify markets with growth potential.

[0553] Based on these analysis results, the server uses a generative AI model to generate business ideas integrated with the user's emotional state. The generated ideas are then creatively refined based on the user's emotional information and presented to the user's device. The user provides feedback on the proposed ideas, and the server uses this information to validate and optimize them.

[0554] For example, if a user is passionate about cooking as a hobby and the emotion engine recognizes that excitement, the system might suggest business ideas such as "online cooking classes" or "developing new menus using local ingredients."

[0555] An example of a prompt message is as follows: "The user's work experience is as a marketing specialist, their interest is cooking, and their current mood is elevated. Based on their skill set, please propose a suitable business idea."

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] Users log in to the system via their device and enter profile information, including work history, skills, and interests, as well as real-time sentiment data. This sentiment data is obtained through text analysis and voice input. The device then sends this data to the server.

[0559] Step 2:

[0560] The server analyzes the profile information and emotional data received from the user using profiling tools. By applying the input data to an emotional analysis algorithm, the user's emotional state is identified. This generates a detailed user profile.

[0561] Step 3:

[0562] The server uses market analysis tools to activate multiple intelligent agents to collect market data. Input consists of search criteria based on industry and region. Data is obtained through web scraping techniques and APIs, and output as market information indicating promising growth.

[0563] Step 4:

[0564] The server uses a generative AI model to integrate user characteristics, emotional states, and market information to generate business ideas. Based on the input, the idea generation algorithm processes the data and outputs new business ideas.

[0565] Step 5:

[0566] The generated business ideas are sent from the server to the user's terminal and presented to the user. The user provides feedback on the proposed ideas, and this information is sent back to the server via the terminal.

[0567] Step 6:

[0568] The server analyzes user feedback and sentiment information using verification tools to identify the feasibility and areas for improvement of the idea. A competitive analysis algorithm compares the idea with other ideas and outputs an optimized idea.

[0569] Step 7:

[0570] Ultimately, the server uses action planning tools to develop a concrete action plan, taking into account the user's emotional information. This plan includes necessary resources and risk management measures and is provided to the user via the terminal. Based on this plan, the user moves on to implementing their business idea.

[0571] (Application Example 2)

[0572] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0573] In today's business environment, uniform product recommendations that ignore consumers' emotional states can negatively impact purchasing intent. Traditional methods make it difficult to capture user emotions in real time and quickly propose products and services that respond accordingly. This creates a challenge in providing more personalized user experiences.

[0574] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0575] In this invention, the server includes profiling means for analyzing user information to identify user characteristics, market analysis means for collecting market data to identify growth markets, and emotion recognition means for recognizing the user's emotional state in real time and optimizing information provision. This makes it possible to dynamically adjust product suggestions based on the user's emotional information and provide a more personalized user experience that enhances purchasing intent.

[0576] A "user" is an individual who uses a system to provide information.

[0577] "Profiling techniques" are technologies used to analyze information provided by users and identify their individual characteristics and attributes.

[0578] "Market analysis tools" are techniques that analyze market data collected from external sources to identify markets and trends that are expected to grow.

[0579] An "idea generation method" is a technique for devising new business ideas by integrating user characteristics and market data.

[0580] "Verification methods" are techniques for evaluating the feasibility and market suitability of generated business ideas and identifying necessary improvements.

[0581] "Action plan formulation tools" are technologies that create optimal business development steps and plans for users and provide concrete action guidelines.

[0582] "Emotion recognition means" refers to technology that recognizes the user's real-time emotional state and adjusts the content of information provided based on that.

[0583] A "product suggestion method" is a technology for dynamically adjusting the products and services suggested according to the user's emotional state.

[0584] The system for implementing this invention mainly consists of a server and a user terminal. The server is equipped with profiling means for analyzing information provided by the user, mainly skill and interest information, and real-time sentiment data. The profiling means collects sentiment data using voice input and text analysis, and uses this to generate individual user profiles. Google Cloud Speech-to-Text API and Amazon Rekognition are used to collect sentiment data.

[0585] Furthermore, the server possesses market analysis capabilities, using different AI agents to collect and analyze data focused on specific industries and regions, identifying promising market trends. This utilizes advanced machine learning algorithms, which are integrated with user profiles to generate business ideas.

[0586] The user's device has an emotion recognition mechanism that grasps the user's emotional state in real time. This data is sent to a server, and a product suggestion mechanism dynamically suggests products and services that correspond to the user's emotional state. For example, if the user is in a positive emotional state, new products or bold suggestions are made, while if they are in a negative emotional state, relaxation products or sales information are provided.

[0587] As a concrete example, a user browsing an online shopping site on their device during their commute will receive different suggestions depending on their emotional tone when performing a voice search using their smartphone's microphone. An example of a prompt would be, "Please tell me how to analyze my current emotional state and suggest products that match it." Based on this prompt, a generative AI model can generate and present the most suitable suggestions to the user.

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] Users log in to the system via their device and input skill data, interest information, and emotion data. The input data is sent from the device to the server. The server receives this data and analyzes the emotional state using an emotion engine. The data is processed through text analysis and voice input, and the emotion recognition model determines the type and intensity of the emotion.

[0591] Step 2:

[0592] The server uses profiling techniques to analyze the received user data. The input consists of user characteristics and attributes, and the output is a detailed user profile. This process integrates skill data and interest information, resulting in a comprehensive user analysis.

[0593] Step 3:

[0594] Based on user profiles, the server activates market analysis tools and uses different AI agents to collect market data specific to a particular industry or region. The input is market data, and the output is trend information for growing markets. Data analysis by the AI ​​agents identifies potential markets.

[0595] Step 4:

[0596] The server uses a generative AI model to integrate user profiles and market trend information to generate business ideas. The inputs are user profiles and market information, and the output is the generated business idea. In this process, the generative AI model evaluates the novelty and relevance of the proposal and refines the idea.

[0597] Step 5:

[0598] The server uses validation tools to evaluate the feasibility of the generated business ideas, based on user feedback and sentiment data. The inputs are the business ideas and user feedback, while the output is an improved idea, including suggested enhancements.

[0599] Step 6:

[0600] The server generates optimized business steps using an action plan development tool. The input is an improved business idea, and the output is an implementation plan. The server designs specific action procedures and resource allocations and provides them to the user.

[0601] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0602] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0603] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0604] [Fourth Embodiment]

[0605] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0606] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0607] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0608] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0609] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0610] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0611] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0612] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0613] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0614] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0615] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0616] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0617] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0618] This invention is a comprehensive business idea creation and verification system utilizing an autonomous AI agent. This system generates appropriate business ideas based on user information and evaluates the feasibility of the proposed ideas using market data. The system's operation is described in detail below.

[0619] First, the user logs into the system via a terminal and enters information such as their work history, skills, and interests. The server receives this information and analyzes it using a deep learning algorithm. This analysis generates a profile of the user's characteristics, and the server then suggests the most suitable business areas for the user. For example, if the user is proficient in the IT field, areas such as cloud computing or cybersecurity can be recommended.

[0620] Next, the server performs market analysis. Multiple AI agents analyze market data obtained from the internet to detect untapped markets with growth potential. Based on this, the server identifies promising business opportunities and presents them to the user.

[0621] Next, the server uses an idea generation tool to combine user profiles and market data to generate specific business ideas. The generated ideas take into account the user's strengths and market opportunities, and the server provides these ideas to the user in detail. For example, if the user's characteristics include digital marketing and there is high demand for smart devices in a particular region, the development of a new advertising platform might be proposed.

[0622] Subsequently, the user receives the suggested ideas via their device and provides feedback. Based on this feedback, the server uses an AI agent to analyze market viability and the competitive landscape, identifying areas for further improvement. For example, it can analyze competitor trends and recommend differentiation strategies.

[0623] Ultimately, the server develops an action plan and presents the user with steps toward commercialization. This plan includes necessary resources and potential challenges, helping the user create a concrete implementation plan. In this way, the user can quickly turn their business idea into a feasible one and aim for success.

[0624] Thus, the present invention utilizes user input and market data to consistently support the process from generating innovative business ideas to their implementation.

[0625] The following describes the processing flow.

[0626] Step 1:

[0627] Users log in to the platform using their device and enter basic information such as work history, skills, and interests through the portal interface.

[0628] Step 2:

[0629] The server receives information sent by the user and securely stores it in a database. Then, it analyzes this information using a deep learning model to generate a user profile. The user profile includes characteristics and strengths based on the user's skills and experience.

[0630] Step 3:

[0631] The server activates AI agents to acquire market data. This data includes information from the internet and partner data providers, and is used to analyze market trends, consumer behavior, and the competitive landscape. Each AI agent specializes in data for a specific industry or region.

[0632] Step 4:

[0633] Based on the collected market data, the server identifies untapped markets with growth potential. This information is integrated with user profiles to create a list of suggested business opportunities for the user. The user is then presented with attractive business area options to pursue.

[0634] Step 5:

[0635] The server uses an idea generation engine to combine user profile information with insights from market data to create concrete business ideas. These ideas reflect the individual user's strengths and market needs, and their feasibility is evaluated.

[0636] Step 6:

[0637] Users can review proposed business ideas from their devices and provide feedback. This feedback is sent to the system and used to further improve the ideas.

[0638] Step 7:

[0639] The server incorporates user feedback and uses automatically generated AI models to conduct competitive analysis and market evaluation, identifying the feasibility and areas for improvement of ideas. The results are presented to the user, and further actions are recommended if necessary.

[0640] Step 8:

[0641] Ultimately, the server uses action plan development tools to create an implementation plan from the business idea. This plan includes necessary resources, personnel, budget, and potential risks. The user can then use this information to proceed with specific business implementation.

[0642] (Example 1)

[0643] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0644] In today's business environment, it is difficult to quickly generate optimal business ideas that maximize the skills and interests of individual users while considering market growth potential. Furthermore, providing concrete steps and improvements to enhance the feasibility of the generated ideas is currently not sufficiently achieved. This hinders small and medium-sized enterprises and entrepreneurs from creating and rapidly implementing innovative business models.

[0645] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0646] In this invention, the server includes an information analysis means that analyzes information from the user to identify the user's characteristics, a proposal means that suggests the optimal business area based on the information, and a market data analysis means that collects market data using multiple AI agents to identify growth areas. This makes it possible to generate individual business ideas that reflect the user's skills and interests, and to formulate concrete action plans based on those ideas.

[0647] "Information analysis means" refers to methods for processing information provided by users and identifying individual characteristics.

[0648] "Proposal methods" refer to techniques for suggesting the most suitable business areas based on analyzed user information.

[0649] "Market data analysis methods" refer to techniques that use multiple AI agents to collect data from the market and identify areas with growth potential.

[0650] "Concept generation methods" refer to techniques for formulating specific business models by combining user characteristics and market information.

[0651] "Verification methods" refer to techniques for evaluating the generated business model and providing additional information and areas for improvement.

[0652] "Planning methods" refer to techniques for presenting concrete action plans for implementing an idea.

[0653] This invention is a system that generates optimal business ideas based on user information and supports their steady commercialization. Users access the system using a terminal. The terminal is provided with an interface for inputting the user's work history, skills, interests, etc. This information is sent to a server. The server receives this information and analyzes the user's characteristics using information analysis means. Generative AI models and deep learning algorithms are used for information analysis. As a result, a user profile is generated, and the optimal business area is presented to the user through a suggestion means.

[0654] The server also uses multiple AI agents to collect market data and identify markets with growth potential. Big data analytics and time series analysis are employed for market data analysis, which helps detect promising market opportunities.

[0655] Furthermore, the server combines user profiles and market data to generate concrete business concepts. In this process, a generative AI model is utilized to propose business models that consider user characteristics and market opportunities. The generated business concepts are evaluated using validation tools, and improvements are provided as needed. Finally, the server presents a detailed action plan using planning tools. This plan includes specific steps and resources for implementing the idea.

[0656] For example, if the information provided by the user relates to "eco-friendly product development," the system can analyze market data, identify the growing market for renewable energy, and specifically propose the development of new products utilizing solar panels.

[0657] An example of a prompt to input into a generative AI model would be text such as, "The user's area of ​​interest is eco-products. Based on current market information and user characteristics, please propose appropriate business ideas."

[0658] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0659] Step 1:

[0660] Users log in to the system using their terminal and enter information such as their work history, skills, and interests. This information is received via forms on the terminal. The entered data is then transferred to the server via the internet.

[0661] Step 2:

[0662] The server processes the received user information using information analysis tools. This process utilizes a generative AI model and deep learning algorithms for data processing. As output, a profile defining the user's characteristics is generated. This profile is then used for subsequent business area proposals.

[0663] Step 3:

[0664] The server suggests the most suitable business domain based on the profile. At this stage, suggestion tools are used to analyze the entity and select a specific industry domain that matches the user's interests and skills. The output is a recommended domain, such as "IT services" or "eco-products."

[0665] Step 4:

[0666] The server uses multiple AI agents to collect market data from external data sources. Inputs include publicly available data on the internet and commercial databases, accessed through data acquisition protocols. Outputs include information on collected market trends and growth forecasts.

[0667] Step 5:

[0668] The server analyzes market information collected using market data analysis tools. Big data analysis techniques and time-series analysis are used to identify markets with growth potential and output the detected growth areas. This process utilizes data pattern recognition and clustering technologies.

[0669] Step 6:

[0670] The server integrates user profiles and market data, and generates concrete business concepts using concept generation tools. Data calculations are performed by a generation AI model, and specific business ideas are proposed as output. These ideas might include, for example, "the development of an eco-friendly new product and its market strategy."

[0671] Step 7:

[0672] The server validates the generated business concept and provides suggestions for improvement as needed. At this stage, validation tools are used, and competitive analysis and risk assessment are performed. The output is feedback on the idea's evaluation and areas for improvement.

[0673] Step 8:

[0674] The server ultimately uses planning tools to present the user with a detailed action plan. The output includes specific steps for commercialization and the necessary resources. Based on this information, the user can put their business idea into action.

[0675] (Application Example 1)

[0676] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] The process of generating new business ideas and evaluating their potential in the actual market is time-consuming and resource-intensive for companies and individuals. In particular, identifying the optimal business area based on user characteristics and developing concrete plans based on growth market data is complex. Therefore, a system is needed that efficiently and comprehensively generates and evaluates business ideas and provides clear implementation steps.

[0678] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0679] In this invention, the server includes profiling means for analyzing information from users and identifying their characteristics, market analysis means for collecting market data and identifying growth markets, and information presentation means for providing various technical ideas related to the business domain. This enables the efficient generation and evaluation of business ideas based on user characteristics and market data.

[0680] "Profiling methods" are means of analyzing information provided by users to identify their characteristics.

[0681] "Market analysis tools" are means of collecting data from the market to identify markets that are expected to grow.

[0682] An "idea generation method" is a means of creating new business ideas based on user characteristics and information on growing markets.

[0683] "Verification methods" are means for evaluating the feasibility of a generated business idea and identifying areas for improvement.

[0684] "Information presentation methods" refer to means of providing various technical ideas relevant to the business domain.

[0685] An "action plan formulation tool" is a means of providing the optimal steps for realizing a business idea.

[0686] This invention can be implemented using a system centered around a server. The server is equipped with multiple data processing means and operates in cooperation with a user terminal. The user accesses the system through the terminal and starts the business idea generation process by inputting the necessary information.

[0687] Specifically, when a user inputs their work history, skills, and interests using a terminal, the server receives this information and performs analysis using profiling tools. These profiling tools use software such as Python and TensorFlow to identify characteristics based on the user's information using deep learning algorithms.

[0688] Next, the server's market analysis tool identifies markets with growth potential based on data collected from the internet. This analysis utilizes multiple AI agents. For example, data management using Firebase could be considered.

[0689] Following this, the server uses an idea generation mechanism to combine user characteristics obtained through profiling with market analysis data to create new business ideas. The generated ideas are then provided to the user via an application using an information presentation mechanism. At this stage, for example, new approaches related to energy-saving technologies or data management efficiency may be proposed to the user.

[0690] Furthermore, users can provide feedback on the generated business ideas, which the server then uses to conduct more detailed market analysis and competitor research. This leads to the development of a concrete action plan for the business idea, and users are shown actionable steps.

[0691] For example, if a user expresses interest in energy conservation in data centers, the system will generate a prompt message such as, "Please propose a new approach to energy conservation technologies in data centers. Specifically, please describe what kind of energy management systems are conceivable, taking future market trends into consideration."

[0692] This system allows users to efficiently generate new business ideas and ultimately build actionable plans in a short period of time.

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] Users input information about their work history, skills, and interests using a terminal. The terminal then transmits this information as digital data to a server. The input data serves as foundational information to reveal the user's characteristics.

[0696] Step 2:

[0697] The server analyzes the received digital data using profiling techniques. This analysis utilizes a deep learning algorithm based on TensorFlow. As a result of the analysis, profile data indicating the user's characteristics is generated. This profile data serves as an indicator of which business areas the user is best suited for.

[0698] Step 3:

[0699] The server collects market data from the internet using market analysis tools and analyzes it. The collected data is processed by an AI agent, and market segments with expected growth potential are identified using a predictive analytics model. The output of this step is a list of markets with potential for development.

[0700] Step 4:

[0701] The server combines profile data and market data, and uses an idea generation tool to create new business ideas. Here, Python is used to programmatically generate ideas that consider the user's strengths and market opportunities. A list of the generated business ideas is output, and this list forms the basis for the next step.

[0702] Step 5:

[0703] Users receive the generated business ideas on their devices and provide feedback. This feedback is then sent back to the server and used for further analysis of the idea's marketability and competitive landscape. The feedback data reflects human intuition and market trends.

[0704] Step 6:

[0705] The server uses verification methods based on user feedback to identify areas for improvement. It conducts competitive analysis and proposes differentiation strategies. Here, AI-powered market viability assessments are performed, and data necessary for the next action plan is output.

[0706] Step 7:

[0707] The server uses action planning tools to provide users with concrete, actionable steps. This plan includes necessary resources and potential challenges. Ultimately, users receive an actionable business plan.

[0708] Step 8:

[0709] Users can review and implement the final business plan on their devices. A specific example is "developing a new business entry strategy utilizing market trend forecasting with a generative AI model."

[0710] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0711] This invention is a system that generates and validates business ideas through user profiling and market analysis, combining an emotion engine that recognizes user emotions. This system analyzes user information from multiple perspectives and proposes flexible business strategies that take emotional states into account. Specific embodiments are described below.

[0712] First, the user logs into the system via a terminal and inputs their work history, skills, interests, and real-time emotional data. Emotional data is collected through text analysis and voice input. Upon receiving this information, the server uses an emotional engine to recognize the user's emotional state. It then generates a detailed user profile by combining the user's skill data and emotional data, and the server suggests the most suitable business areas for the user.

[0713] Next, the server launches multiple AI agents to collect market data. Each AI agent focuses on a specific industry or region, analyzing market trends and consumer behavior. This identifies untapped markets with growth potential and presents business opportunities based on user profiles and market data.

[0714] Subsequently, the server uses an idea generation mechanism to generate business ideas that reflect the user's emotional information. The user's emotional state is considered as a factor influencing the creativity and direction of the ideas; if the user is in a positive emotional state, bolder business strategies may be proposed.

[0715] The generated business ideas are presented to the user, and feedback is collected from the user via the device. The server incorporates this feedback and user sentiment information to examine the feasibility and market suitability of the ideas in detail. Furthermore, the server uses verification tools to perform comparative analysis with other competing ideas based on sentiment information, and provides the user with a refined idea.

[0716] Finally, the server uses an action plan development tool to create an optimized execution plan for the user. This plan includes specific commercialization steps that take emotional information into account, necessary resources, and risk management measures. Based on this action plan, the user can effectively move towards realizing their business idea.

[0717] Thus, the present invention provides a more personalized and highly successful business plan by incorporating the user's emotional state.

[0718] The following describes the processing flow.

[0719] Step 1:

[0720] Users log in to the platform using their devices and enter their work history, skills, and interests, as well as sentiment data in real time. Sentiment data is provided via text input and voice.

[0721] Step 2:

[0722] The server securely stores information received from the user in a database and profiles the user's characteristics using deep learning algorithms. In addition, it activates an emotion engine to analyze the provided emotion data and identify the user's current emotional state.

[0723] Step 3:

[0724] The server activates AI agents to collect and analyze market data from diverse sources. The AI ​​agents focus on specific industries and regions, investigating market trends, consumer behavior, and competitive landscapes to identify untapped markets with growth potential.

[0725] Step 4:

[0726] The server integrates user profiles, emotional state information, and market data, and uses an idea generation engine to create business ideas. The server proposes flexible ideas based on the user's emotional state; for example, it might suggest a risky business approach in a positive emotional state.

[0727] Step 5:

[0728] Users can review business ideas presented by the server via their devices and provide feedback. This user feedback, along with sentiment information, is used in the next analysis step.

[0729] Step 6:

[0730] The server validates business ideas generated using AI models, taking into account user feedback and emotional information. The server performs market and competitive analysis, identifies necessary improvements, and presents them to the user again.

[0731] Step 7:

[0732] Ultimately, the server uses action planning tools to create a feasible business plan adapted to the emotional state. This plan includes specific implementation steps, necessary resources, and risk management measures. Based on this plan, the user can effectively carry out their activities.

[0733] (Example 2)

[0734] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0735] Traditional user profiling and market analysis systems only analyze user information in general terms and have the problem of not being able to propose business ideas that take into account the emotional state of users. Furthermore, they struggle to quickly and accurately identify growth markets in a dynamic market environment. Therefore, there is a need to provide flexible business strategies based on the individual emotional state and skills of users.

[0736] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0737] In this invention, the server includes profiling means for analyzing information from the user to identify user characteristics and recognize emotional states, market analysis means for collecting market data using multiple intelligent agents and identifying growth markets, and idea generation means for integrating user characteristics, emotional states, and growth market information to generate business ideas. This makes it possible to quickly and effectively provide personalized business strategies that reflect the user's emotions.

[0738] "Profiling tools" are devices or software used to analyze information collected from users and identify their characteristics and emotional states.

[0739] "Market analysis tools" refer to devices or software that use multiple intelligent agents to collect market data and identify markets with growth potential.

[0740] An "idea generation tool" is a device or software that integrates user characteristics, emotional states, and market information to generate new business ideas.

[0741] A "verification tool" is a device or software used to evaluate a generated business idea and provide improvements based on user feedback.

[0742] An "action plan formulation tool" is a device or software that takes into account the user's emotional information and provides the user with optimized business development steps.

[0743] An "intelligent agent" is a program or system that autonomously collects and analyzes market data, focusing on specific industries or regions.

[0744] This invention is a system for generating personalized business strategies that take user emotions into consideration. Specific embodiments are shown below.

[0745] Users access the system using a terminal and input their work history, skills, interests, and real-time sentiment data. Sentiment data is acquired using sentiment analysis technology via voice or text input. The software used includes sentiment analysis algorithms.

[0746] After receiving this information, the server uses profiling techniques to identify user characteristics and emotional states. Profiling is performed using machine learning models, and database software manages the user profiles.

[0747] Next, the server activates multiple intelligent agents through market analysis tools to collect market data. These intelligent agents focus on collecting and analyzing data for specific industries and regions. This utilizes web scraping techniques and API-based data integration. The analysis results help identify markets with growth potential.

[0748] Based on these analysis results, the server uses a generative AI model to generate business ideas integrated with the user's emotional state. The generated ideas are then creatively refined based on the user's emotional information and presented to the user's device. The user provides feedback on the proposed ideas, and the server uses this information to validate and optimize them.

[0749] For example, if a user is passionate about cooking as a hobby and the emotion engine recognizes that excitement, the system might suggest business ideas such as "online cooking classes" or "developing new menus using local ingredients."

[0750] An example of a prompt message is as follows: "The user's work experience is as a marketing specialist, their interest is cooking, and their current mood is elevated. Based on their skill set, please propose a suitable business idea."

[0751] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0752] Step 1:

[0753] Users log in to the system via their device and enter profile information, including work history, skills, and interests, as well as real-time sentiment data. This sentiment data is obtained through text analysis and voice input. The device then sends this data to the server.

[0754] Step 2:

[0755] The server analyzes the profile information and emotional data received from the user using profiling tools. By applying the input data to an emotional analysis algorithm, the user's emotional state is identified. This generates a detailed user profile.

[0756] Step 3:

[0757] The server uses market analysis tools to activate multiple intelligent agents to collect market data. Input consists of search criteria based on industry and region. Data is obtained through web scraping techniques and APIs, and output as market information indicating promising growth.

[0758] Step 4:

[0759] The server uses a generative AI model to integrate user characteristics, emotional states, and market information to generate business ideas. Based on the input, the idea generation algorithm processes the data and outputs new business ideas.

[0760] Step 5:

[0761] The generated business ideas are sent from the server to the user's terminal and presented to the user. The user provides feedback on the proposed ideas, and this information is sent back to the server via the terminal.

[0762] Step 6:

[0763] The server analyzes user feedback and sentiment information using verification tools to identify the feasibility and areas for improvement of the idea. A competitive analysis algorithm compares the idea with other ideas and outputs an optimized idea.

[0764] Step 7:

[0765] Ultimately, the server uses action planning tools to develop a concrete action plan, taking into account the user's emotional information. This plan includes necessary resources and risk management measures and is provided to the user via the terminal. Based on this plan, the user moves on to implementing their business idea.

[0766] (Application Example 2)

[0767] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] In today's business environment, uniform product recommendations that ignore consumers' emotional states can negatively impact purchasing intent. Traditional methods make it difficult to capture user emotions in real time and quickly propose products and services that respond accordingly. This creates a challenge in providing more personalized user experiences.

[0769] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0770] In this invention, the server includes profiling means for analyzing user information to identify user characteristics, market analysis means for collecting market data to identify growth markets, and emotion recognition means for recognizing the user's emotional state in real time and optimizing information provision. This makes it possible to dynamically adjust product suggestions based on the user's emotional information and provide a more personalized user experience that enhances purchasing intent.

[0771] A "user" is an individual who uses a system to provide information.

[0772] "Profiling techniques" are technologies used to analyze information provided by users and identify their individual characteristics and attributes.

[0773] "Market analysis tools" are techniques that analyze market data collected from external sources to identify markets and trends that are expected to grow.

[0774] An "idea generation method" is a technique for devising new business ideas by integrating user characteristics and market data.

[0775] "Verification methods" are techniques for evaluating the feasibility and market suitability of generated business ideas and identifying necessary improvements.

[0776] "Action plan formulation tools" are technologies that create optimal business development steps and plans for users and provide concrete action guidelines.

[0777] "Emotion recognition means" refers to technology that recognizes the user's real-time emotional state and adjusts the content of information provided based on that.

[0778] A "product suggestion method" is a technology for dynamically adjusting the products and services suggested according to the user's emotional state.

[0779] The system for implementing this invention mainly consists of a server and a user terminal. The server is equipped with profiling means for analyzing information provided by the user, mainly skill and interest information, and real-time sentiment data. The profiling means collects sentiment data using voice input and text analysis, and uses this to generate individual user profiles. Google Cloud Speech-to-Text API and Amazon Rekognition are used to collect sentiment data.

[0780] Furthermore, the server possesses market analysis capabilities, using different AI agents to collect and analyze data focused on specific industries and regions, identifying promising market trends. This utilizes advanced machine learning algorithms, which are integrated with user profiles to generate business ideas.

[0781] The user's device has an emotion recognition mechanism that grasps the user's emotional state in real time. This data is sent to a server, and a product suggestion mechanism dynamically suggests products and services that correspond to the user's emotional state. For example, if the user is in a positive emotional state, new products or bold suggestions are made, while if they are in a negative emotional state, relaxation products or sales information are provided.

[0782] As a concrete example, a user browsing an online shopping site on their device during their commute will receive different suggestions depending on their emotional tone when performing a voice search using their smartphone's microphone. An example of a prompt would be, "Please tell me how to analyze my current emotional state and suggest products that match it." Based on this prompt, a generative AI model can generate and present the most suitable suggestions to the user.

[0783] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0784] Step 1:

[0785] Users log in to the system via their device and input skill data, interest information, and emotion data. The input data is sent from the device to the server. The server receives this data and analyzes the emotional state using an emotion engine. The data is processed through text analysis and voice input, and the emotion recognition model determines the type and intensity of the emotion.

[0786] Step 2:

[0787] The server uses profiling techniques to analyze the received user data. The input consists of user characteristics and attributes, and the output is a detailed user profile. This process integrates skill data and interest information, resulting in a comprehensive user analysis.

[0788] Step 3:

[0789] Based on user profiles, the server activates market analysis tools and uses different AI agents to collect market data specific to a particular industry or region. The input is market data, and the output is trend information for growing markets. Data analysis by the AI ​​agents identifies potential markets.

[0790] Step 4:

[0791] The server uses a generative AI model to integrate user profiles and market trend information to generate business ideas. The inputs are user profiles and market information, and the output is the generated business idea. In this process, the generative AI model evaluates the novelty and relevance of the proposal and refines the idea.

[0792] Step 5:

[0793] The server uses validation tools to evaluate the feasibility of the generated business ideas, based on user feedback and sentiment data. The inputs are the business ideas and user feedback, while the output is an improved idea, including suggested enhancements.

[0794] Step 6:

[0795] The server generates optimized business steps using an action plan development tool. The input is an improved business idea, and the output is an implementation plan. The server designs specific action procedures and resource allocations and provides them to the user.

[0796] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0797] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0798] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0799] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0800] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0801] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0802] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0803] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0804] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0805] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0806] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0807] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0808] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0809] 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.

[0810] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0811] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0812] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0813] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0814] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0815] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0816] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A profiling method that analyzes information from users to identify user characteristics,

[0820] Market analysis tools that collect market data and identify growth markets,

[0821] An idea generation method that integrates user characteristics and growth market information to generate business ideas,

[0822] A validation method to verify the generated business idea and provide areas for improvement,

[0823] A means of formulating an action plan that provides the optimal steps for commercialization,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, wherein the profiling means analyzes the skill data and interest information provided by the user.

[0827] (Claim 3)

[0828] The system according to claim 1, wherein the market analysis means analyzes data specific to a particular industry or region using different AI agents.

[0829] "Example 1"

[0830] (Claim 1)

[0831] An information analysis method that analyzes information from users to identify user characteristics,

[0832] A proposal method that suggests the most suitable business area based on information,

[0833] A market data analysis method that collects market data using multiple AI agents and identifies growth areas,

[0834] A concept generation method that combines user characteristics and market information to generate concrete business concepts,

[0835] A verification mechanism to verify the generated business concept and provide additional information,

[0836] A planning tool that provides an optimal business development plan,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, wherein the information analysis means analyzes the skill data and interest information provided by the user.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein the market data analysis means analyzes data specific to a particular industry or region using different artificial intelligence agents.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] A profiling method that analyzes information from users to identify user characteristics,

[0845] Market analysis tools that collect market data and identify growth markets,

[0846] An idea generation method that integrates user characteristics and growth market information to generate business ideas,

[0847] A validation method to verify the generated business idea and provide areas for improvement,

[0848] An information presentation tool that provides various technical ideas related to the business domain,

[0849] A means of formulating an action plan that provides the optimal steps for commercialization,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, wherein the profiling means analyzes the skill data and interest information provided by the user.

[0853] (Claim 3)

[0854] The system according to claim 1, wherein the market analysis means analyzes data specific to a particular industry or region using different AI agents.

[0855] "Example 2 of combining an emotion engine"

[0856] (Claim 1)

[0857] A profiling method that analyzes user information to identify user characteristics and recognize emotional states,

[0858] A market analysis method that collects market data using multiple intelligent agents and identifies growth markets,

[0859] An idea generation method that integrates user characteristics, emotional states, and growth market information to generate business ideas,

[0860] A validation method for verifying generated business ideas, collecting feedback, and providing areas for improvement,

[0861] A means of formulating an action plan that provides the optimal business development steps considering user sentiment information,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, wherein the profiling means analyzes the user's provided skill data and interest information, as well as real-time sentiment data through text analysis and voice analysis.

[0865] (Claim 3)

[0866] The system according to claim 1, wherein the market analysis means analyzes data specific to a particular industry or region using different intelligent agents and performs trend analysis.

[0867] "Application example 2 when combining with an emotional engine"

[0868] (Claim 1)

[0869] A profiling method that analyzes information from users to identify user characteristics,

[0870] Market analysis tools that collect market data and identify growth markets,

[0871] An idea generation method that integrates user characteristics and growth market information to generate business ideas,

[0872] A validation method to verify the generated business idea and provide areas for improvement,

[0873] A means of formulating an action plan that provides the optimal steps for commercialization,

[0874] A means of recognizing the user's emotional state in real time and optimizing information provision,

[0875] A product suggestion method that dynamically adjusts the suggested content based on the user's emotional information,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, wherein the profiling means analyzes the skill data and interest information provided by the user.

[0879] (Claim 3)

[0880] The system according to claim 1, wherein the market analysis means analyzes data specific to a particular industry or region using different AI agents. [Explanation of symbols]

[0881] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A profiling method that analyzes information from users to identify user characteristics, Market analysis tools that collect market data and identify growth markets, An idea generation method that integrates user characteristics and growth market information to generate business ideas, A validation method to verify the generated business idea and provide areas for improvement, A means of formulating an action plan that provides the optimal steps for commercialization, A system that includes this.

2. The system according to claim 1, wherein the profiling means analyzes the skill data and interest information provided by the user.

3. The system according to claim 1, wherein the market analysis means analyzes data specific to a particular industry or region using different AI agents.

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