system

Abstract

We provide the system. [Solution] A means of collecting publicly available intellectual property information and summarizing this intellectual property information using a generative model, A means of analyzing summarized intellectual property information and exploring the possibility of applying its technical content to other industrial fields, A means of generating new business proposals based on the analysis results, A means of quantitatively evaluating and visually displaying the generated business proposals, A means to share evaluated business proposals with other users and provide a platform to support their commercialization, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a 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's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a current situation where many intellectual properties are not fully utilized after acquisition, missing opportunities for new business creation. As a result, enterprises may lose the opportunity to maximize profits, and the economic development may be stagnant. Furthermore, with existing information processing technologies, it is difficult to efficiently analyze extensive intellectual property information and automatically create new business ideas applicable across multiple industrial fields. Also, there is a need for comprehensive means to evaluate the feasibility of the generated ideas and find the path to commercialization.

Means for Solving the Problems

[0005] This invention provides a means for collecting publicly available intellectual property information, summarizing it using a generative model, and exploring its potential applications in other industrial fields based on this summary. Furthermore, it constructs a system that includes means for generating new business proposals from the information obtained through this exploration, quantitatively evaluating these proposals, and visually displaying them. The evaluated business proposals can be shared among users, and concrete commercialization is supported through discussions on a secure platform. In addition, a function is incorporated in which an artificial intelligence virtual advisor supports the concretization of business plans. This helps transform previously unused intellectual property into new businesses.

[0006] "Publicly available intellectual property information" refers to patents, copyrights, and other intellectual property information that is made publicly available by public institutions such as the Japan Patent Office and is accessible to anyone.

[0007] A "generative model" is an artificial intelligence or machine learning algorithm that learns from data and generates new information or content.

[0008] "Methods of summarization" refer to methods and techniques for presenting information clearly and concisely, reducing the amount of information while preserving the original content.

[0009] "Means of exploring applicability to other industrial fields" refers to analytical methods and processes for determining whether patented technology can be applied to various industries.

[0010] "Methods for generating new business proposals" refer to methodologies and technologies for creating new business ideas based on market needs and technological backgrounds.

[0011] "Means of quantitative evaluation and visual display" refers to methods and tools for quantifying and evaluating information and data, and then visualizing that evaluation using graphs, charts, and other means.

[0012] A "secure infrastructure" refers to a system environment where the safety of data and communications is ensured, and it encompasses the technologies and fundamental structures necessary to prevent unauthorized access to information.

[0013] A "virtual advisor AI" is an artificial intelligence program designed to support the user's decision-making process, acting as a virtual advisor. [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 Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the 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, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the 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, the 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 disk (e.g., hard disk), or magnetic tape, 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 system that supports the creation of new businesses by utilizing publicly available intellectual property information. This system collects intellectual property information from publicly available patent databases and provides a series of processes to promote the user's business development based on that information.

[0036] Collection and summarization of intellectual property information

[0037] Server: Regularly accesses publicly available patent databases to retrieve new intellectual property information. The retrieved information includes patent numbers, technical summaries, and patent classification information. A generative model is used to automatically summarize the obtained information and extract key technical elements and features.

[0038] Exploring and analyzing the potential applications of the technology.

[0039] AI agent (server): Analyzes summarized patent information. Utilizes natural language processing technology to evaluate whether the technical details can be applied to other industrial fields.

[0040] Generation and evaluation of new business proposals

[0041] AI Agent: Integrates potential technological applications across multiple industrial sectors and generates new business proposals by referencing existing market trend data and past business models. The generated proposals are quantitatively evaluated by the AI ​​model from the perspectives of novelty, marketability, and technical feasibility. The results are visually displayed on a dashboard, allowing users to understand the strengths and weaknesses of the proposals at a glance.

[0042] Collaboration and business development support

[0043] Terminal (User): Based on visualized business proposals, users engage in discussions with other users and industry expert AI. Collaboration on the platform takes place in a secure environment, enhancing the safety of information.

[0044] Users can develop concrete business plans with advice from a strategic consultant AI. This includes resource allocation, partner identification, and risk analysis. By using this system, companies can effectively utilize untapped intellectual property and quickly seize new business opportunities.

[0045] Specific example

[0046] Terminal (User): For example, a user working at an electronics manufacturer checks patent information for a new battery technology on the platform. This patent is applied and evaluated as a power-saving technology for portable devices. An AI agent considers market data and generates a business proposal for energy-saving batteries for home appliances, displaying it on a dashboard along with an evaluation score.

[0047] User: Receive assistance in exploring the feasibility of commercializing this proposal and creating an actionable business plan, while communicating with other stakeholders through the system.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server accesses publicly available patent databases and collects new and updated intellectual property information. This collection includes basic information such as patent number, invention summary, and technical field.

[0051] Step 2:

[0052] The server inputs collected intellectual property information into a generative model to automatically generate patent summaries. These summaries concisely summarize the key technological elements and their potential applications.

[0053] Step 3:

[0054] An AI agent (server) analyzes the summary and uses natural language processing technology to analyze the technical elements in order to identify which other industrial fields the patented technology can be applied to.

[0055] Step 4:

[0056] The AI ​​agent integrates the potential applications of technologies from multiple fields based on the analysis results and generates new business proposals. Market trends and data from past success stories are also referenced in this process.

[0057] Step 5:

[0058] The server uses an AI model to quantitatively evaluate the novelty, market potential, and feasibility of the generated business proposals. The evaluation results are summarized as a score.

[0059] Step 6:

[0060] The server visualizes the evaluation results in graphs and charts, generating a dashboard that allows users to view detailed evaluation information through an interface.

[0061] Step 7:

[0062] The user interacts with other team members and industry experts on the platform based on evaluation results, discussing how to refine and improve business proposals.

[0063] Step 8:

[0064] Users receive support from a strategic consultant AI to create concrete business plans, including resource allocation and risk analysis. This prepares the platform for increasing the feasibility of the business.

[0065] (Example 1)

[0066] 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."

[0067] In today's highly information-driven society, the effective utilization of knowledge asset information is crucial for creating new businesses and innovating existing ones. However, collecting information from vast amounts of publicly available databases and using it to make quick and accurate business proposals requires considerable effort and knowledge. Furthermore, analyzing this information for application in other fields demands advanced technology. Against this backdrop, there is a need for systems that can efficiently collect, analyze, and utilize knowledge asset information.

[0068] 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.

[0069] In this invention, the server includes means for collecting knowledge property information from a publicly available database, means for summarizing the information using a generative model, and means for analyzing the information using natural language processing technology and exploring its potential applications in other fields. This enables the rapid and efficient generation of new business proposals and the formulation of business strategies based on them.

[0070] "Intellectual property information" is a general term for information concerning creations and inventions that are protected by law, such as patents, copyrights, and trademarks.

[0071] A "generative model" is a computational model that uses artificial intelligence algorithms to generate a specific output from input data.

[0072] "Natural language processing technology" refers to a set of technologies that enable computers to understand, interpret, and generate human language.

[0073] "Analysis" is the process of breaking down information and data into its details in order to understand its structure and content.

[0074] A "business proposal" is a plan or proposal created to present the concept and direction of a new business.

[0075] "Quantitative evaluation" refers to conducting a concrete evaluation using numerical values, with the aim of making an objective judgment based on various indicators and criteria.

[0076] "Visualized format" refers to a method of making information easier to understand by representing it in a visual form such as graphs or diagrams.

[0077] "Sharing" means making information and data available for use and access by multiple stakeholders.

[0078] In order to implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together.

[0079] server

[0080] The server collects the latest intellectual property information by periodically accessing publicly available databases. This process utilizes internet-connected computers and API technology to retrieve data. The obtained information, including patent numbers, technical summaries, and patent classifications, is stored in a local database on the server. Next, a generative AI model is used to summarize this information and extract key technical elements and features. Specifically, the AI ​​model is provided with prompts such as, "List three key technical elements of this patent."

[0081] terminal

[0082] The terminal provides an environment where users can view generated business proposals and discuss them with other users and industry expert AI. On the terminal, visualized business proposals provided by the server are displayed in a dashboard format, making it easy to understand evaluation scores, proposal strengths, and areas for improvement. The platform is equipped with security measures to ensure the safety of information.

[0083] User

[0084] Through their devices, users develop concrete business plans while receiving advice from a strategic consultant AI. At this stage, they devise specific strategies such as resource allocation, risk assessment, and partner identification to increase the feasibility of business opportunities. An example of a prompt might be, "Please suggest what new businesses could be conceived using this technology." This system enables users to rationally and effectively generate new business ideas from a vast amount of knowledge and develop them quickly and safely.

[0085] The form for implementing the invention, through the integration of these processes and technical elements, provides comprehensive support for users to leverage intellectual property information to build new businesses.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The server accesses publicly available databases to collect intellectual property information. It uses patent numbers, technology summaries, and patent classification information obtained via an API as input. The server collects large amounts of this data and stores it in a local database. The output of this step is intellectual property information organized in a structured format.

[0089] Step 2:

[0090] The server uses a generative AI model to summarize the collected knowledge property information. It uses the patent data obtained in Step 1 as input. Specifically, the server provides the AI ​​model with prompts such as "List three key technical elements of this patent," and extracts the main technical elements from the data. The output is data containing the summarized technical elements and features.

[0091] Step 3:

[0092] The server's AI agent analyzes the summarized patent information and explores its potential applications in other fields. It uses the technical information summarized in step 2 as input and leverages natural language processing techniques. The server compares the information against datasets and industry trend information to evaluate which industries the technology is applicable to. The output is the analysis results, including potential application areas.

[0093] Step 4:

[0094] The server generates new business proposals using an AI model based on the analysis results. The analysis data from step 3 and market trend data are used as input. The server activates the AI ​​model through the prompt, "Please suggest what new businesses can be conceived using this technology," and generates proposals. The output is a business proposal containing new business ideas.

[0095] Step 5:

[0096] The server quantitatively evaluates the generated business proposals and displays them in a visualized format on a dashboard. It uses new business proposals as input and calculates evaluation metrics using an AI model. Specifically, it scores novelty, market potential, and technical feasibility. The output is business proposal information with visualized evaluation scores.

[0097] Step 6:

[0098] The terminal provides an environment where users can view visualized business proposals and discuss them with other users and industry expert AI. The evaluated business proposals generated in step 5 are used as input. The terminal displays this data in a secure environment, enabling safe information sharing among users. The output is feedback on commercialization through collaborative discussion.

[0099] Step 7:

[0100] The user receives advice from a strategic consultant AI via their device and develops a concrete business plan. The feedback and suggestions obtained in step 6 are used as input. The user then performs specific actions such as resource allocation, risk assessment, and partner selection to build the business plan. The output is an actionable business plan.

[0101] (Application Example 1)

[0102] 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."

[0103] In today's business environment, there is a demand for the rapid and efficient utilization of existing knowledge assets. However, extracting useful information from vast amounts of knowledge asset data and applying it to new businesses is not easy. In particular, the process of applying technical information such as patent information to other industrial fields to create new business opportunities is complex and time-consuming. Against this backdrop, there is a need for methods to effectively analyze knowledge asset information and rapidly generate and share new business ideas.

[0104] 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.

[0105] In this invention, the server includes means for collecting publicly available knowledge asset information and summarizing the generated knowledge asset information; means for analyzing the summarized knowledge asset information and exploring the possibility of applying the technical information to other domains; and means for generating innovative business proposals based on the analysis results. This makes it possible to manage knowledge asset data and visualize new business ideas on the user's device.

[0106] "Publicly available knowledge asset information" refers to the collection of knowledge and information contained in patents, technical documents, etc., that have been made publicly available in a format that is accessible to the general public.

[0107] The "function for summarizing generated knowledge asset information" refers to the process or means of scrutinizing collected knowledge asset information and concisely summarizing important technical elements.

[0108] The "function to analyze and explore the possibility of applying that technical information to other fields" refers to a means of analyzing summarized technical information in detail and investigating how it can be applied to other industrial fields.

[0109] The "function for generating innovative business proposals" refers to the process of identifying new business opportunities based on analyzed information and developing them into concrete proposals.

[0110] "A means of managing knowledge asset data and visualizing new business ideas on users' devices" refers to a method of effectively organizing data related to knowledge assets and displaying analysis results and generated business proposals in an easy-to-understand manner on the user's device.

[0111] The server has a pipeline for collecting publicly available knowledge asset information, and it regularly accesses numerous patent databases to obtain new information. This information is stored on the server as knowledge asset data, including patent numbers, technical summaries, and classification information. Based on the collected information, a generative AI model is used to automatically summarize the data and extract important technical elements.

[0112] This system operates in a data center and is built using Python and the Flask framework on the backend. It also utilizes libraries such as spaCy and NLTK for natural language processing. PostgreSQL is used as the database for centralized management of patent information summaries.

[0113] The terminal (user) is provided with the ability to explore technological applications in other industrial fields based on the summary information provided by this server. The generated new business proposals are visualized on the user's device, allowing the user to efficiently evaluate business ideas and take the first step towards realization.

[0114] As a concrete example, if a user views patent information related to a new data storage technology in the app, the AI ​​will analyze this patent and generate a business proposal for an efficient storage solution for big data. This provides the user with an environment to plan projects. An example of a prompt message could be, "Based on this patent information, please generate a proposal for a new storage solution for data centers."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server periodically accesses publicly available patent databases to collect knowledge asset information, including patent numbers, technical summaries, and patent classification information. The input is new patent data retrieved from the patent database, and the output is structured data stored within the server. This data is then organized for subsequent summarization processing.

[0118] Step 2:

[0119] The server summarizes the collected knowledge asset information using a generative AI model. The input is raw patent information obtained from a patent database, and the output is summarized information with key technological elements extracted. This summarization process utilizes natural language processing techniques to significantly reduce the amount of information while retaining the important points.

[0120] Step 3:

[0121] The server analyzes summarized technical information and explores its potential applications in other industrial fields. It takes summarized information as input and generates a list of potential technology candidates as output. This analysis uses an algorithm that finds correlations with known technology databases.

[0122] Step 4:

[0123] The server generates new business proposals based on the analysis results. Here, a list of potential technologies is used as input, and innovative business proposals are generated as output. This process also relies on a generation AI model, which designs realistic proposals by referencing market trend data.

[0124] Step 5:

[0125] The terminal (user) receives output from the server and visualizes the generated new business proposal on the device. The input is detailed plan data as a business proposal, and the output is an interface that the user can view and evaluate. The specific operation here is to provide the user with an easy-to-understand UI and to interactively evaluate the business feasibility.

[0126] Step 6:

[0127] The user carries out project planning based on a visualized business proposal. Here, the system receives output from the terminal and uses the provided prompt text as input to support strategic decision-making. This process enables the user to formulate a concrete business strategy.

[0128] 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.

[0129] This invention combines a system that supports the creation of new businesses by utilizing intellectual property information with an emotion engine that recognizes user emotions. This system collects intellectual property information from patent databases and can easily develop new businesses based on that information.

[0130] Collection and summarization of intellectual property information

[0131] Server: Accesses publicly available patent databases and regularly collects the latest intellectual property information. The collected information includes patent numbers, technical summaries, and patent classification information. Using a generative model, this information is concisely summarized and stored in the database.

[0132] Exploring the potential applications of technology

[0133] AI Agent (Server): Analyzes summarized information and uses natural language processing technology to evaluate its applicability in various industrial fields. Based on this information, it generates new business proposals.

[0134] Interface adjustment using an emotion engine

[0135] Terminal (User): The emotion engine analyzes the user's facial expressions and tone of voice in real time and dynamically adjusts the user interface. If the user shows interest, it highlights details of the suggestion and guidance on the next steps.

[0136] Evaluation and sharing of business proposals

[0137] Server: Evaluates generated business proposals using an AI model from the perspectives of novelty, marketability, and technical feasibility, and displays the results visually. Based on feedback from the emotion engine, it optimizes the method and order in which proposals are displayed.

[0138] Business development support through a collaboration platform

[0139] User (device): Share evaluated proposals with other users and experts on a shared platform and engage in discussions while utilizing emotion sensor data. This secure platform allows for rapid improvement of ideas and development of new proposals.

[0140] Specific example

[0141] Terminal (User): A user from a pharmaceutical company searches for patents related to new synthetic substances through the platform. This patent is analyzed, and its potential application as a new material in medical devices is proposed. If the user shows a positive reaction to this proposal, the emotion engine recognizes this and displays further information such as specific application examples and market data.

[0142] Users: Through group discussions, they will explore the potential for commercializing this application and formulate concrete actions for its realization together with a strategic consultant AI.

[0143] In this way, the present invention supports the efficient implementation of new businesses while increasing user interest through a system design that utilizes an emotion engine.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The server accesses publicly available patent databases to collect the latest intellectual property information. The collected information consists of patent numbers, a summary of the technology, and patent classifications.

[0147] Step 2:

[0148] The server collects intellectual property information and summarizes it using a generative model. The summary is created in a way that concisely explains the key elements of the technology and its potential applications.

[0149] Step 3:

[0150] An AI agent (server) analyzes the summarized information and uses natural language processing technology to identify potential applications in other industrial fields. This lays the foundation for generating new business proposals.

[0151] Step 4:

[0152] The server evaluates the generated business proposals. An AI model quantifies the novelty, marketability, and technical feasibility of the proposals, and records the results in a database.

[0153] Step 5:

[0154] The server generates a dashboard on the user's terminal to visually display the evaluation results. The graphical interface allows users to easily understand the details of the recommendations.

[0155] Step 6:

[0156] An emotion engine built into the device (user) analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time. The user interface is then dynamically adjusted according to the recognized emotion.

[0157] Step 7:

[0158] When the sentiment engine detects a positive response while a user is viewing suggestions, detailed information and relevant data are highlighted on the interface, and the next action step is displayed at the top.

[0159] Step 8:

[0160] Users share evaluated business proposals with other team members and experts through the system. The collaboration platform is used to improve and refine ideas based on emotional feedback.

[0161] Step 9:

[0162] Users develop detailed plans for commercialization by considering feedback from an emotional engine and receiving advice from a strategic consultant AI. This increases the likelihood of new business ventures becoming feasible.

[0163] (Example 2)

[0164] 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".

[0165] In today's diverse economic activity landscape, there is a need for efficient methods to generate highly innovative proposals. However, the process of extracting useful knowledge from vast information resources and translating it into concrete proposals is complex and time-consuming. Furthermore, adjusting the interface to suit user emotions is necessary to enhance the acceptability of proposals, but effective means of achieving this are lacking. As a result, supporting the efficient and effective integration of these proposals into economic activity remains a challenging issue.

[0166] 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.

[0167] In this invention, the server includes means for collecting publicly available information resources and summarizing them using a generative model; means for analyzing the summarized information resources and exploring the possibility of applying their technological content to other areas of economic activity; and means for dynamically adjusting the user interface using an engine that analyzes user emotions. This seamlessly integrates information extraction, proposal generation, and emotion-based interface optimization, enabling the efficient and effective creation and realization of new economic activities.

[0168] "Information resources" refer to a collection of diverse information, such as publicly available patents, papers, and databases, which are used for analyzing technical content and discovering new knowledge.

[0169] A "generative model" is a technology that uses machine learning and natural language processing algorithms to summarize, generate, and analyze input data, enabling the acquisition of new insights from information resources.

[0170] The term "economic activity domain" encompasses diverse fields and cross-sectoral activities within industry and business, representing areas where the application of technologies and products can be considered.

[0171] A "user interface" is the interface through which information is exchanged between the user and the system, and its design must take into account ease of use and usability.

[0172] An "emotion engine" is a technology for analyzing a user's emotional state, particularly through facial recognition and voice analysis, to understand the user's reactions and dynamically optimize the interface.

[0173] This invention provides a system for extracting useful knowledge from publicly available information resources and creating new economic activities based on that knowledge. This system is realized through the interaction of a server, a terminal, and a user.

[0174] The server collects information resources such as patents and databases, and summarizes this information using a generative AI model. For example, it periodically searches for the latest patent information, retrieves patent numbers, technical summaries, and patent classification information, and then summarizes it. This summarized information is stored in the server's database and used for subsequent analysis.

[0175] The device interacts with the user through its user interface. Equipped with an emotion engine, it dynamically adjusts the interface by analyzing the user's facial expressions and voice tone using devices such as the camera and microphone. For example, it has a function that emphasizes the display of relevant information when the user shows interest.

[0176] Users can explore the possibilities of specific economic activities based on the information and suggestions provided. This system allows users to select information in areas of interest and evaluate its applicability. Furthermore, users can share suggestions with each other and engage in collaborative discussions toward commercialization. A shared platform is provided as the foundation for this, enabling efficient discussions utilizing emotion sensor data.

[0177] For example, if a user belongs to the pharmaceutical industry, they can search and analyze patent information on new synthetic substances and propose their application to medical devices. When the emotion engine determines that the user's response is positive, it displays more specific application examples and market data, providing guidance for the next action.

[0178] Examples of prompts include specific instructions such as, "Generate proposals to evaluate the potential of new businesses based on the latest patent information," or "Explain the interface adjustment function that responds to user emotions."

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The server collects patent and database information from publicly available information resources. This collection is performed by inputting search prompt sentences using specific keywords and conditions into an AI model. The collected data includes patent numbers, technology summaries, and patent classification information. This data is temporarily stored on the server.

[0182] Step 2:

[0183] The server summarizes the collected information using a generative AI model. This summarization process uses natural language processing techniques to shorten long texts and extract key elements. The input is detailed patent information, and the output is summarized short text. This summarized information is stored in a database.

[0184] Step 3:

[0185] The server evaluates applicability based on the summarized information. Using natural language processing techniques, it analyzes the applicability of the technology across different industrial sectors. This analysis also considers market trends and past case studies. The input is summarized information, and the output is a list of potential industrial sectors and specific suggestions. These suggestions are stored in a database and can be accessed by users later.

[0186] Step 4:

[0187] The device uses an emotion engine to analyze facial expressions and tone of voice to understand the user's emotions. This analysis dynamically adjusts the information displayed on the interface. The input is real-time user behavior data, and the output is the adjusted interface display. Specifically, information that is of interest to the user is highlighted.

[0188] Step 5:

[0189] The server quantitatively evaluates the generated economic activity proposals and displays them visually on a screen. Artificial intelligence uses novelty, marketability, and technical feasibility as evaluation criteria. The input to this process is the proposal content, and the output is the evaluation results represented in graphs and charts. This information is transmitted to the user terminal.

[0190] Step 6:

[0191] Users utilize the platform to share information with other users based on their evaluated suggestions. This sharing platform allows for discussions while referencing emotion sensor data. Inputs are evaluated suggestions, and outputs are comments and feedback. One specific function is the ability to send notifications to other users.

[0192] (Application Example 2)

[0193] 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".

[0194] In today's complex industrial environment, creating new businesses requires the effective use of intellectual property information and the provision of dynamic interfaces based on user emotions. However, conventional systems have limitations in analyzing intellectual property information and generating business proposals, and are insufficient in adjusting interfaces to leverage user emotions. This also makes it difficult to quickly assess the marketability and feasibility of new businesses and to promote collaboration with other users.

[0195] 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.

[0196] This invention includes a server that collects publicly available intellectual property information and summarizes this intellectual property information using a generative model; a server that analyzes the summarized intellectual property information and explores the possibility of applying its technical content to other industrial fields; and a server that generates new business proposals based on the analysis results. This enables an efficient and dynamic business creation process based on intellectual property information, and by allowing interface adjustments that respond to user emotions, it becomes possible to quickly determine the marketability and feasibility of new businesses and promote collaboration with other users.

[0197] "Intellectual property information" refers to legally protected technical information and ideas, such as publicly available patents and trademarks.

[0198] A "generative model" is a computer program that automatically generates text and data using deep learning or machine learning algorithms.

[0199] "Methods of summarization" are techniques for extracting large amounts of information, summarizing the key points concisely, and presenting them in an easy-to-understand format.

[0200] "Natural language processing technology" is a technique for processing human language into a form that is easy for computers to handle and for analyzing its meaning.

[0201] "Means of recognizing emotions" refers to technologies that detect a user's facial expressions, voice, and other actions to determine their emotional state.

[0202] "Means of adjusting the interface" refers to technologies that adaptively change the displayed content and usability based on user responses.

[0203] "Means of visual display" refers to technologies that show analysis results and evaluation content to users in an easy-to-understand format, such as graphs and charts.

[0204] A "user" is an individual or organization that uses this system to obtain intellectual property information or business proposals.

[0205] This invention embodies a system that effectively supports the creation of new businesses by utilizing intellectual property information. The system's operation and necessary technical elements are described in detail below.

[0206] The server is responsible for periodically collecting publicly available patent information. This patent information mainly includes patent numbers, technical summaries, and patent classification information. The collected data is automatically summarized by a generative model using the machine learning library TENSORFLOW® and stored in a database.

[0207] Subsequently, the server uses natural language processing technology to analyze how patent information can be applied to various industrial fields. This makes it possible to generate new business proposals that meet the needs of the industry. The proposed businesses are then visualized using a visual evaluation tool, based on their marketability and feasibility.

[0208] The user terminal uses emotion recognition software installed on a smartphone or smart glasses (for example, Microsoft® Azure® Emotion API). This allows for real-time analysis of the user's facial expressions and tone of voice, and dynamic adjustments to the user interface. Detailed information is highlighted when the user shows interest.

[0209] As a concrete example, imagine a user working at a startup company with new technology, and they search for new home automation technology patents through the platform. They can then receive suggestions on potential new applications of this patent as a smart home technology. If the user responds positively to a suggestion, the emotion engine recognizes this and provides more detailed market data and competitor information.

[0210] An example of a prompt for the generating AI model is: "Generate proposals for home automation utilizing new technologies in smart cities. In particular, output specific ideas based on recent patent information."

[0211] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0212] Step 1:

[0213] The server accesses the patent database to collect publicly available intellectual property information. This information includes patent numbers, technical summaries, and patent classification information. The collected data is stored directly in the database.

[0214] Step 2:

[0215] The server summarizes the collected intellectual property information using a generative AI model. The summarization process converts the information into a compact and easily understandable format. This output summary is then stored again in the database.

[0216] Step 3:

[0217] The server analyzes the summarized intellectual property information and uses natural language processing technology to process the data to identify which industrial sectors it can be applied to. Based on the analysis results, new business proposals are generated, and these generated proposals become the output.

[0218] Step 4:

[0219] The generated business proposals are quantitatively evaluated using AI-powered visualization tools, and the results are visually displayed to the user. Focusing on marketability and technical feasibility, the analysis results are presented in figures and charts.

[0220] Step 5:

[0221] On the user's device, emotion recognition software installed on the smartphone or smart glasses analyzes the user's facial expressions and tone of voice in real time. This allows the user interface to dynamically adjust based on emotional changes, highlighting relevant suggestions based on their interest.

[0222] Step 6:

[0223] Users can share evaluated suggestions with other users and engage in discussions within the system. Users can also input prompts as needed and use the AI ​​generation model to obtain further, more specific idea outputs.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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".

[0240] This invention is a system that supports the creation of new businesses by utilizing publicly available intellectual property information. This system collects intellectual property information from publicly available patent databases and provides a series of processes to promote the user's business development based on that information.

[0241] Collection and summarization of intellectual property information

[0242] Server: Regularly accesses publicly available patent databases to retrieve new intellectual property information. The retrieved information includes patent numbers, technical summaries, and patent classification information. A generative model is used to automatically summarize the obtained information and extract key technical elements and features.

[0243] Exploring and analyzing the potential applications of the technology.

[0244] AI agent (server): Analyzes summarized patent information. Utilizes natural language processing technology to evaluate whether the technical details can be applied to other industrial fields.

[0245] Generation and evaluation of new business proposals

[0246] AI Agent: Integrates potential technological applications across multiple industrial sectors and generates new business proposals by referencing existing market trend data and past business models. The generated proposals are quantitatively evaluated by the AI ​​model from the perspectives of novelty, marketability, and technical feasibility. The results are visually displayed on a dashboard, allowing users to understand the strengths and weaknesses of the proposals at a glance.

[0247] Collaboration and business development support

[0248] Terminal (User): Based on visualized business proposals, users engage in discussions with other users and industry expert AI. Collaboration on the platform takes place in a secure environment, enhancing the safety of information.

[0249] Users can develop concrete business plans with advice from a strategic consultant AI. This includes resource allocation, partner identification, and risk analysis. By using this system, companies can effectively utilize untapped intellectual property and quickly seize new business opportunities.

[0250] Specific example

[0251] Terminal (User): For example, a user working at an electronics manufacturer checks patent information for a new battery technology on the platform. This patent is applied and evaluated as a power-saving technology for portable devices. An AI agent considers market data and generates a business proposal for energy-saving batteries for home appliances, displaying it on a dashboard along with an evaluation score.

[0252] User: Receive assistance in exploring the feasibility of commercializing this proposal and creating an actionable business plan, while communicating with other stakeholders through the system.

[0253] The following describes the processing flow.

[0254] Step 1:

[0255] The server accesses publicly available patent databases and collects new and updated intellectual property information. This collection includes basic information such as patent number, invention summary, and technical field.

[0256] Step 2:

[0257] The server inputs collected intellectual property information into a generative model to automatically generate patent summaries. These summaries concisely summarize the key technological elements and their potential applications.

[0258] Step 3:

[0259] An AI agent (server) analyzes the summary and uses natural language processing technology to analyze the technical elements in order to identify which other industrial fields the patented technology can be applied to.

[0260] Step 4:

[0261] The AI ​​agent integrates the potential applications of technologies from multiple fields based on the analysis results and generates new business proposals. Market trends and data from past success stories are also referenced in this process.

[0262] Step 5:

[0263] The server uses an AI model to quantitatively evaluate the novelty, market potential, and feasibility of the generated business proposals. The evaluation results are summarized as a score.

[0264] Step 6:

[0265] The server visualizes the evaluation results in graphs and charts, generating a dashboard that allows users to view detailed evaluation information through an interface.

[0266] Step 7:

[0267] The user interacts with other team members and industry experts on the platform based on evaluation results, discussing how to refine and improve business proposals.

[0268] Step 8:

[0269] Users receive support from a strategic consultant AI to create concrete business plans, including resource allocation and risk analysis. This prepares the platform for increasing the feasibility of the business.

[0270] (Example 1)

[0271] 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."

[0272] In today's highly information-driven society, the effective utilization of knowledge asset information is crucial for creating new businesses and innovating existing ones. However, collecting information from vast amounts of publicly available databases and using it to make quick and accurate business proposals requires considerable effort and knowledge. Furthermore, analyzing this information for application in other fields demands advanced technology. Against this backdrop, there is a need for systems that can efficiently collect, analyze, and utilize knowledge asset information.

[0273] 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.

[0274] In this invention, the server includes means for collecting knowledge property information from a publicly available database, means for summarizing the information using a generative model, and means for analyzing the information using natural language processing technology and exploring its potential applications in other fields. This enables the rapid and efficient generation of new business proposals and the formulation of business strategies based on them.

[0275] "Intellectual property information" is a general term for information concerning creations and inventions that are protected by law, such as patents, copyrights, and trademarks.

[0276] A "generative model" is a computational model that uses artificial intelligence algorithms to generate a specific output from input data.

[0277] "Natural language processing technology" refers to a set of technologies that enable computers to understand, interpret, and generate human language.

[0278] "Analysis" is the process of breaking down information and data into its details in order to understand its structure and content.

[0279] A "business proposal" is a plan or proposal created to present the concept and direction of a new business.

[0280] "Quantitative evaluation" refers to conducting a concrete evaluation using numerical values, with the aim of making an objective judgment based on various indicators and criteria.

[0281] "Visualized format" refers to a method of making information easier to understand by representing it in a visual form such as graphs or diagrams.

[0282] "Sharing" means making information and data available for use and access by multiple stakeholders.

[0283] To implement this invention, it is necessary to construct a system in which the server, terminal, and user cooperate and operate.

[0284] Server

[0285] The server collects the latest intellectual property information by periodically accessing a publicly available database. In this process, the API technology is utilized to obtain data using a computer device connected to the Internet. The obtained information includes patent numbers, technical summaries, and patent classification information, and is stored in a local database within the server. Next, a generative AI model is used to summarize this information and extract the main technical elements and features. Specifically, a prompt sentence such as "Please list three important technical elements of this patent" is supplied to the AI model.

[0286] Terminal

[0287] The terminal provides an environment for the user to view the generated business proposals and conduct discussions with other users and industry expert AIs. On the terminal, the visualized business proposals provided by the server are displayed in a dashboard format, making it easier to understand the evaluation scores, strengths, and issues of the proposals. Security measures are implemented on the platform to ensure the security of information.

[0288] User

[0289] The user formulates a specific business plan through the terminal while receiving advice from the strategic consultant AI. At this stage, specific strategies such as resource allocation, risk assessment, and identification of partners are considered to enhance the feasibility of realizing business opportunities. An example of a prompt sentence is "Please propose what new businesses can be considered using this technology." With this system, the user can rationally and effectively generate new business ideas from a vast amount of intellectual property information and develop them quickly and securely.

[0290] The form for implementing the invention, through the integration of these processes and technical elements, provides comprehensive support for users to leverage intellectual property information to build new businesses.

[0291] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0292] Step 1:

[0293] The server accesses publicly available databases to collect intellectual property information. It uses patent numbers, technology summaries, and patent classification information obtained via an API as input. The server collects large amounts of this data and stores it in a local database. The output of this step is intellectual property information organized in a structured format.

[0294] Step 2:

[0295] The server uses a generative AI model to summarize the collected knowledge property information. It uses the patent data obtained in Step 1 as input. Specifically, the server provides the AI ​​model with prompts such as "List three key technical elements of this patent," and extracts the main technical elements from the data. The output is data containing the summarized technical elements and features.

[0296] Step 3:

[0297] The server's AI agent analyzes the summarized patent information and explores its potential applications in other fields. It uses the technical information summarized in step 2 as input and leverages natural language processing techniques. The server compares the information against datasets and industry trend information to evaluate which industries the technology is applicable to. The output is the analysis results, including potential application areas.

[0298] Step 4:

[0299] The server generates new business proposals using an AI model based on the analysis results. The analysis data from step 3 and market trend data are used as input. The server activates the AI ​​model through the prompt, "Please suggest what new businesses can be conceived using this technology," and generates proposals. The output is a business proposal containing new business ideas.

[0300] Step 5:

[0301] The server quantitatively evaluates the generated business proposals and displays them in a visualized format on a dashboard. It uses new business proposals as input and calculates evaluation metrics using an AI model. Specifically, it scores novelty, market potential, and technical feasibility. The output is business proposal information with visualized evaluation scores.

[0302] Step 6:

[0303] The terminal provides an environment where users can view visualized business proposals and discuss them with other users and industry expert AI. The evaluated business proposals generated in step 5 are used as input. The terminal displays this data in a secure environment, enabling safe information sharing among users. The output is feedback on commercialization through collaborative discussion.

[0304] Step 7:

[0305] The user receives advice from a strategic consultant AI via their device and develops a concrete business plan. The feedback and suggestions obtained in step 6 are used as input. The user then performs specific actions such as resource allocation, risk assessment, and partner selection to build the business plan. The output is an actionable business plan.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0308] In a modern business environment, it is required to utilize existing intellectual property assets quickly and efficiently. However, it is not easy to extract useful information from a vast amount of intellectual property asset information and apply it to new businesses. In particular, the process of applying technical information such as patent information to other industrial fields to create new business opportunities is complex and time-consuming. Against this backdrop, there is a need for a method to effectively analyze intellectual property asset information and quickly generate and share new business ideas.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0310] In this invention, the server includes means for collecting publicly available intellectual property asset information and summarizing the generated intellectual property asset information, means for analyzing the summarized intellectual property asset information and exploring the possibility of adapting the technical information to other fields, and means for generating innovative business proposals based on the analysis results. As a result, it becomes possible to manage intellectual property data and visualize new business ideas on the user's device.

[0311] "Publicly available intellectual property asset information" is an accumulation of knowledge and information included in patents, technical documents, etc. that are publicly available in a generally usable form.

[0312] The "function of summarizing the generated intellectual property asset information" is a process or means for examining the collected intellectual property asset information and shortening and summarizing important technical elements.

[0313] The "function of analyzing and exploring the possibility of adapting the technical information to other fields" is a means for analyzing the summarized technical information in detail and investigating how it can be applied to other industrial fields.

[0314] The "function for generating innovative business proposals" refers to the process of identifying new business opportunities based on analyzed information and developing them into concrete proposals.

[0315] "A means of managing knowledge asset data and visualizing new business ideas on users' devices" refers to a method of effectively organizing data related to knowledge assets and displaying analysis results and generated business proposals in an easy-to-understand manner on the user's device.

[0316] The server has a pipeline for collecting publicly available knowledge asset information, and it regularly accesses numerous patent databases to obtain new information. This information is stored on the server as knowledge asset data, including patent numbers, technical summaries, and classification information. Based on the collected information, a generative AI model is used to automatically summarize the data and extract important technical elements.

[0317] This system operates in a data center and is built using Python and the Flask framework on the backend. It also utilizes libraries such as spaCy and NLTK for natural language processing. PostgreSQL is used as the database for centralized management of patent information summaries.

[0318] The terminal (user) is provided with the ability to explore technological applications in other industrial fields based on the summary information provided by this server. The generated new business proposals are visualized on the user's device, allowing the user to efficiently evaluate business ideas and take the first step towards realization.

[0319] As a concrete example, if a user views patent information related to a new data storage technology in the app, the AI ​​will analyze this patent and generate a business proposal for an efficient storage solution for big data. This provides the user with an environment to plan projects. An example of a prompt message could be, "Based on this patent information, please generate a proposal for a new storage solution for data centers."

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] The server periodically accesses publicly available patent databases to collect knowledge asset information, including patent numbers, technical summaries, and patent classification information. The input is new patent data retrieved from the patent database, and the output is structured data stored within the server. This data is then organized for subsequent summarization processing.

[0323] Step 2:

[0324] The server summarizes the collected knowledge asset information using a generative AI model. The input is raw patent information obtained from a patent database, and the output is summarized information with key technological elements extracted. This summarization process utilizes natural language processing techniques to significantly reduce the amount of information while retaining the important points.

[0325] Step 3:

[0326] The server analyzes summarized technical information and explores its potential applications in other industrial fields. It takes summarized information as input and generates a list of potential technology candidates as output. This analysis uses an algorithm that finds correlations with known technology databases.

[0327] Step 4:

[0328] The server generates new business proposals based on the analysis results. Here, a list of potential technologies is used as input, and innovative business proposals are generated as output. This process also relies on a generation AI model, which designs realistic proposals by referencing market trend data.

[0329] Step 5:

[0330] The terminal (user) receives output from the server and visualizes the generated new business proposal on the device. The input is detailed plan data as a business proposal, and the output is an interface that the user can view and evaluate. The specific operation here is to provide the user with an easy-to-understand UI and to interactively evaluate the business feasibility.

[0331] Step 6:

[0332] The user carries out project planning based on a visualized business proposal. Here, the system receives output from the terminal and uses the provided prompt text as input to support strategic decision-making. This process enables the user to formulate a concrete business strategy.

[0333] 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.

[0334] This invention combines a system that supports the creation of new businesses by utilizing intellectual property information with an emotion engine that recognizes user emotions. This system collects intellectual property information from patent databases and can easily develop new businesses based on that information.

[0335] Collection and summarization of intellectual property information

[0336] Server: Accesses publicly available patent databases and regularly collects the latest intellectual property information. The collected information includes patent numbers, technical summaries, and patent classification information. Using a generative model, this information is concisely summarized and stored in the database.

[0337] Exploring the potential applications of technology

[0338] AI Agent (Server): Analyzes summarized information and uses natural language processing technology to evaluate its applicability in various industrial fields. Based on this information, it generates new business proposals.

[0339] Interface adjustment using an emotion engine

[0340] Terminal (User): The emotion engine analyzes the user's facial expressions and tone of voice in real time and dynamically adjusts the user interface. If the user shows interest, it highlights details of the suggestion and guidance on the next steps.

[0341] Evaluation and sharing of business proposals

[0342] Server: Evaluates generated business proposals using an AI model from the perspectives of novelty, marketability, and technical feasibility, and displays the results visually. Based on feedback from the emotion engine, it optimizes the method and order in which proposals are displayed.

[0343] Business development support through a collaboration platform

[0344] User (device): Share evaluated proposals with other users and experts on a shared platform and engage in discussions while utilizing emotion sensor data. This secure platform allows for rapid improvement of ideas and development of new proposals.

[0345] Specific example

[0346] Terminal (User): A user from a pharmaceutical company searches for patents related to new synthetic substances through the platform. This patent is analyzed, and its potential application as a new material in medical devices is proposed. If the user shows a positive reaction to this proposal, the emotion engine recognizes this and displays further information such as specific application examples and market data.

[0347] Users: Through group discussions, they will explore the potential for commercializing this application and formulate concrete actions for its realization together with a strategic consultant AI.

[0348] In this way, the present invention supports the efficient implementation of new businesses while increasing user interest through a system design that utilizes an emotion engine.

[0349] The following describes the processing flow.

[0350] Step 1:

[0351] The server accesses publicly available patent databases to collect the latest intellectual property information. The collected information consists of patent numbers, a summary of the technology, and patent classifications.

[0352] Step 2:

[0353] The server collects intellectual property information and summarizes it using a generative model. The summary is created in a way that concisely explains the key elements of the technology and its potential applications.

[0354] Step 3:

[0355] An AI agent (server) analyzes the summarized information and uses natural language processing technology to identify potential applications in other industrial fields. This lays the foundation for generating new business proposals.

[0356] Step 4:

[0357] The server evaluates the generated business proposals. An AI model quantifies the novelty, marketability, and technical feasibility of the proposals, and records the results in a database.

[0358] Step 5:

[0359] The server generates a dashboard on the user's terminal to visually display the evaluation results. The graphical interface allows users to easily understand the details of the recommendations.

[0360] Step 6:

[0361] An emotion engine built into the device (user) analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time. The user interface is then dynamically adjusted according to the recognized emotion.

[0362] Step 7:

[0363] When the sentiment engine detects a positive response while a user is viewing suggestions, detailed information and relevant data are highlighted on the interface, and the next action step is displayed at the top.

[0364] Step 8:

[0365] Users share evaluated business proposals with other team members and experts through the system. The collaboration platform is used to improve and refine ideas based on emotional feedback.

[0366] Step 9:

[0367] Users develop detailed plans for commercialization by considering feedback from an emotional engine and receiving advice from a strategic consultant AI. This increases the likelihood of new business ventures becoming feasible.

[0368] (Example 2)

[0369] 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".

[0370] In today's diverse economic activity landscape, there is a need for efficient methods to generate highly innovative proposals. However, the process of extracting useful knowledge from vast information resources and translating it into concrete proposals is complex and time-consuming. Furthermore, adjusting the interface to suit user emotions is necessary to enhance the acceptability of proposals, but effective means of achieving this are lacking. As a result, supporting the efficient and effective integration of these proposals into economic activity remains a challenging issue.

[0371] 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.

[0372] In this invention, the server includes means for collecting publicly available information resources and summarizing them using a generative model; means for analyzing the summarized information resources and exploring the possibility of applying their technological content to other areas of economic activity; and means for dynamically adjusting the user interface using an engine that analyzes user emotions. This seamlessly integrates information extraction, proposal generation, and emotion-based interface optimization, enabling the efficient and effective creation and realization of new economic activities.

[0373] "Information resources" refer to a collection of diverse information, such as publicly available patents, papers, and databases, which are used for analyzing technical content and discovering new knowledge.

[0374] A "generative model" is a technology that uses machine learning and natural language processing algorithms to summarize, generate, and analyze input data, enabling the acquisition of new insights from information resources.

[0375] The term "economic activity domain" encompasses diverse fields and cross-sectoral activities within industry and business, representing areas where the application of technologies and products can be considered.

[0376] A "user interface" is the interface through which information is exchanged between the user and the system, and its design must take into account ease of use and usability.

[0377] An "emotion engine" is a technology for analyzing a user's emotional state, particularly through facial recognition and voice analysis, to understand the user's reactions and dynamically optimize the interface.

[0378] This invention provides a system for extracting useful knowledge from publicly available information resources and creating new economic activities based on that knowledge. This system is realized through the interaction of a server, a terminal, and a user.

[0379] The server collects information resources such as patents and databases, and summarizes this information using a generative AI model. For example, it periodically searches for the latest patent information, retrieves patent numbers, technical summaries, and patent classification information, and then summarizes it. This summarized information is stored in the server's database and used for subsequent analysis.

[0380] The device interacts with the user through its user interface. Equipped with an emotion engine, it dynamically adjusts the interface by analyzing the user's facial expressions and voice tone using devices such as the camera and microphone. For example, it has a function that emphasizes the display of relevant information when the user shows interest.

[0381] Users can explore the possibilities of specific economic activities based on the information and suggestions provided. This system allows users to select information in areas of interest and evaluate its applicability. Furthermore, users can share suggestions with each other and engage in collaborative discussions toward commercialization. A shared platform is provided as the foundation for this, enabling efficient discussions utilizing emotion sensor data.

[0382] For example, if a user belongs to the pharmaceutical industry, they can search and analyze patent information on new synthetic substances and propose their application to medical devices. When the emotion engine determines that the user's response is positive, it displays more specific application examples and market data, providing guidance for the next action.

[0383] Examples of prompts include specific instructions such as, "Generate proposals to evaluate the potential of new businesses based on the latest patent information," or "Explain the interface adjustment function that responds to user emotions."

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1:

[0386] The server collects patent and database information from publicly available information resources. This collection is performed by inputting search prompt sentences using specific keywords and conditions into an AI model. The collected data includes patent numbers, technology summaries, and patent classification information. This data is temporarily stored on the server.

[0387] Step 2:

[0388] The server summarizes the collected information using a generative AI model. This summarization process uses natural language processing techniques to shorten long texts and extract key elements. The input is detailed patent information, and the output is summarized short text. This summarized information is stored in a database.

[0389] Step 3:

[0390] The server evaluates applicability based on the summarized information. Using natural language processing techniques, it analyzes the applicability of the technology across different industrial sectors. This analysis also considers market trends and past case studies. The input is summarized information, and the output is a list of potential industrial sectors and specific suggestions. These suggestions are stored in a database and can be accessed by users later.

[0391] Step 4:

[0392] The device uses an emotion engine to analyze facial expressions and tone of voice to understand the user's emotions. This analysis dynamically adjusts the information displayed on the interface. The input is real-time user behavior data, and the output is the adjusted interface display. Specifically, information that is of interest to the user is highlighted.

[0393] Step 5:

[0394] The server quantitatively evaluates the generated economic activity proposals and displays them visually on a screen. Artificial intelligence uses novelty, marketability, and technical feasibility as evaluation criteria. The input to this process is the proposal content, and the output is the evaluation results represented in graphs and charts. This information is transmitted to the user terminal.

[0395] Step 6:

[0396] Users utilize the platform to share information with other users based on their evaluated suggestions. This sharing platform allows for discussions while referencing emotion sensor data. Inputs are evaluated suggestions, and outputs are comments and feedback. One specific function is the ability to send notifications to other users.

[0397] (Application Example 2)

[0398] 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."

[0399] In today's complex industrial environment, creating new businesses requires the effective use of intellectual property information and the provision of dynamic interfaces based on user emotions. However, conventional systems have limitations in analyzing intellectual property information and generating business proposals, and are insufficient in adjusting interfaces to leverage user emotions. This also makes it difficult to quickly assess the marketability and feasibility of new businesses and to promote collaboration with other users.

[0400] 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.

[0401] This invention includes a server that collects publicly available intellectual property information and summarizes this intellectual property information using a generative model; a server that analyzes the summarized intellectual property information and explores the possibility of applying its technical content to other industrial fields; and a server that generates new business proposals based on the analysis results. This enables an efficient and dynamic business creation process based on intellectual property information, and by allowing interface adjustments that respond to user emotions, it becomes possible to quickly determine the marketability and feasibility of new businesses and promote collaboration with other users.

[0402] "Intellectual property information" refers to legally protected technical information and ideas, such as publicly available patents and trademarks.

[0403] A "generative model" is a computer program that automatically generates text and data using deep learning or machine learning algorithms.

[0404] "Methods of summarization" are techniques for extracting large amounts of information, summarizing the key points concisely, and presenting them in an easy-to-understand format.

[0405] "Natural language processing technology" is a technique for processing human language into a form that is easy for computers to handle and for analyzing its meaning.

[0406] "Means of recognizing emotions" refers to technologies that detect a user's facial expressions, voice, and other actions to determine their emotional state.

[0407] "Means of adjusting the interface" refers to technologies that adaptively change the displayed content and usability based on user responses.

[0408] "Means of visual display" refers to technologies that show analysis results and evaluation content to users in an easy-to-understand format, such as graphs and charts.

[0409] A "user" is an individual or organization that uses this system to obtain intellectual property information or business proposals.

[0410] This invention embodies a system that effectively supports the creation of new businesses by utilizing intellectual property information. The system's operation and necessary technical elements are described in detail below.

[0411] The server is responsible for periodically collecting publicly available patent information. This patent information mainly includes patent numbers, technical summaries, and patent classification information. The collected data is automatically summarized by a generative model using TensorFlow as a machine learning library and stored in a database.

[0412] Subsequently, the server uses natural language processing technology to analyze how patent information can be applied to various industrial fields. This makes it possible to generate new business proposals that meet the needs of the industry. The proposed businesses are then visualized using a visual evaluation tool, based on their marketability and feasibility.

[0413] The user device utilizes emotion recognition software (such as Microsoft Azure Emotion API) installed on smartphones or smart glasses. This allows for real-time analysis of the user's facial expressions and tone of voice, dynamically adjusting the user interface. Detailed information is highlighted when the user shows interest.

[0414] As a concrete example, imagine a user working at a startup company with new technology, and they search for new home automation technology patents through the platform. They can then receive suggestions on potential new applications of this patent as a smart home technology. If the user responds positively to a suggestion, the emotion engine recognizes this and provides more detailed market data and competitor information.

[0415] An example of a prompt for the generating AI model is: "Generate proposals for home automation utilizing new technologies in smart cities. In particular, output specific ideas based on recent patent information."

[0416] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0417] Step 1:

[0418] The server accesses the patent database to collect publicly available intellectual property information. This information includes patent numbers, technical summaries, and patent classification information. The collected data is stored directly in the database.

[0419] Step 2:

[0420] The server summarizes the collected intellectual property information using a generative AI model. The summarization process converts the information into a compact and easily understandable format. This output summary is then stored again in the database.

[0421] Step 3:

[0422] The server analyzes the summarized intellectual property information and uses natural language processing technology to process the data to identify which industrial sectors it can be applied to. Based on the analysis results, new business proposals are generated, and these generated proposals become the output.

[0423] Step 4:

[0424] The generated business proposals are quantitatively evaluated using AI-powered visualization tools, and the results are visually displayed to the user. Focusing on marketability and technical feasibility, the analysis results are presented in figures and charts.

[0425] Step 5:

[0426] On the user's device, emotion recognition software installed on the smartphone or smart glasses analyzes the user's facial expressions and tone of voice in real time. This allows the user interface to dynamically adjust based on emotional changes, highlighting relevant suggestions based on their interest.

[0427] Step 6:

[0428] Users can share evaluated suggestions with other users and engage in discussions within the system. Users can also input prompts as needed and use the AI ​​generation model to obtain further, more specific idea outputs.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] [Third Embodiment]

[0433] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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).

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] 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".

[0445] This invention is a system that supports the creation of new businesses by utilizing publicly available intellectual property information. This system collects intellectual property information from publicly available patent databases and provides a series of processes to promote the user's business development based on that information.

[0446] Collection and summarization of intellectual property information

[0447] Server: Regularly accesses publicly available patent databases to retrieve new intellectual property information. The retrieved information includes patent numbers, technical summaries, and patent classification information. A generative model is used to automatically summarize the obtained information and extract key technical elements and features.

[0448] Exploring and analyzing the potential applications of the technology.

[0449] AI agent (server): Analyzes summarized patent information. Utilizes natural language processing technology to evaluate whether the technical details can be applied to other industrial fields.

[0450] Generation and evaluation of new business proposals

[0451] AI Agent: Integrates potential technological applications across multiple industrial sectors and generates new business proposals by referencing existing market trend data and past business models. The generated proposals are quantitatively evaluated by the AI ​​model from the perspectives of novelty, marketability, and technical feasibility. The results are visually displayed on a dashboard, allowing users to understand the strengths and weaknesses of the proposals at a glance.

[0452] Collaboration and business development support

[0453] Terminal (User): Based on visualized business proposals, users engage in discussions with other users and industry expert AI. Collaboration on the platform takes place in a secure environment, enhancing the safety of information.

[0454] Users can develop concrete business plans with advice from a strategic consultant AI. This includes resource allocation, partner identification, and risk analysis. By using this system, companies can effectively utilize untapped intellectual property and quickly seize new business opportunities.

[0455] Specific example

[0456] Terminal (User): For example, a user working at an electronics manufacturer checks patent information for a new battery technology on the platform. This patent is applied and evaluated as a power-saving technology for portable devices. An AI agent considers market data and generates a business proposal for energy-saving batteries for home appliances, displaying it on a dashboard along with an evaluation score.

[0457] User: Receive assistance in exploring the feasibility of commercializing this proposal and creating an actionable business plan, while communicating with other stakeholders through the system.

[0458] The following describes the processing flow.

[0459] Step 1:

[0460] The server accesses publicly available patent databases and collects new and updated intellectual property information. This collection includes basic information such as patent number, invention summary, and technical field.

[0461] Step 2:

[0462] The server inputs collected intellectual property information into a generative model to automatically generate patent summaries. These summaries concisely summarize the key technological elements and their potential applications.

[0463] Step 3:

[0464] An AI agent (server) analyzes the summary and uses natural language processing technology to analyze the technical elements in order to identify which other industrial fields the patented technology can be applied to.

[0465] Step 4:

[0466] The AI ​​agent integrates the potential applications of technologies from multiple fields based on the analysis results and generates new business proposals. Market trends and data from past success stories are also referenced in this process.

[0467] Step 5:

[0468] The server uses an AI model to quantitatively evaluate the novelty, market potential, and feasibility of the generated business proposals. The evaluation results are summarized as a score.

[0469] Step 6:

[0470] The server visualizes the evaluation results in graphs and charts, generating a dashboard that allows users to view detailed evaluation information through an interface.

[0471] Step 7:

[0472] The user interacts with other team members and industry experts on the platform based on evaluation results, discussing how to refine and improve business proposals.

[0473] Step 8:

[0474] Users receive support from a strategic consultant AI to create concrete business plans, including resource allocation and risk analysis. This prepares the platform for increasing the feasibility of the business.

[0475] (Example 1)

[0476] 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."

[0477] In today's highly information-driven society, the effective utilization of knowledge asset information is crucial for creating new businesses and innovating existing ones. However, collecting information from vast amounts of publicly available databases and using it to make quick and accurate business proposals requires considerable effort and knowledge. Furthermore, analyzing this information for application in other fields demands advanced technology. Against this backdrop, there is a need for systems that can efficiently collect, analyze, and utilize knowledge asset information.

[0478] 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.

[0479] In this invention, the server includes means for collecting knowledge property information from a publicly available database, means for summarizing the information using a generative model, and means for analyzing the information using natural language processing technology and exploring its potential applications in other fields. This enables the rapid and efficient generation of new business proposals and the formulation of business strategies based on them.

[0480] "Intellectual property information" is a general term for information concerning creations and inventions that are protected by law, such as patents, copyrights, and trademarks.

[0481] A "generative model" is a computational model that uses artificial intelligence algorithms to generate a specific output from input data.

[0482] "Natural language processing technology" refers to a set of technologies that enable computers to understand, interpret, and generate human language.

[0483] "Analysis" is the process of breaking down information and data into its details in order to understand its structure and content.

[0484] A "business proposal" is a plan or proposal created to present the concept and direction of a new business.

[0485] "Quantitative evaluation" refers to conducting a concrete evaluation using numerical values, with the aim of making an objective judgment based on various indicators and criteria.

[0486] "Visualized format" refers to a method of making information easier to understand by representing it in a visual form such as graphs or diagrams.

[0487] "Sharing" means making information and data available for use and access by multiple stakeholders.

[0488] In order to implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together.

[0489] server

[0490] The server collects the latest intellectual property information by periodically accessing publicly available databases. This process utilizes internet-connected computers and API technology to retrieve data. The obtained information, including patent numbers, technical summaries, and patent classifications, is stored in a local database on the server. Next, a generative AI model is used to summarize this information and extract key technical elements and features. Specifically, the AI ​​model is provided with prompts such as, "List three key technical elements of this patent."

[0491] terminal

[0492] The terminal provides an environment where users can view generated business proposals and discuss them with other users and industry expert AI. On the terminal, visualized business proposals provided by the server are displayed in a dashboard format, making it easy to understand evaluation scores, proposal strengths, and areas for improvement. The platform is equipped with security measures to ensure the safety of information.

[0493] User

[0494] Through their devices, users develop concrete business plans while receiving advice from a strategic consultant AI. At this stage, they devise specific strategies such as resource allocation, risk assessment, and partner identification to increase the feasibility of business opportunities. An example of a prompt might be, "Please suggest what new businesses could be conceived using this technology." This system enables users to rationally and effectively generate new business ideas from a vast amount of knowledge and develop them quickly and safely.

[0495] The form for implementing the invention, through the integration of these processes and technical elements, provides comprehensive support for users to leverage intellectual property information to build new businesses.

[0496] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0497] Step 1:

[0498] The server accesses publicly available databases to collect intellectual property information. It uses patent numbers, technology summaries, and patent classification information obtained via an API as input. The server collects large amounts of this data and stores it in a local database. The output of this step is intellectual property information organized in a structured format.

[0499] Step 2:

[0500] The server uses a generative AI model to summarize the collected knowledge property information. It uses the patent data obtained in Step 1 as input. Specifically, the server provides the AI ​​model with prompts such as "List three key technical elements of this patent," and extracts the main technical elements from the data. The output is data containing the summarized technical elements and features.

[0501] Step 3:

[0502] The server's AI agent analyzes the summarized patent information and explores its potential applications in other fields. It uses the technical information summarized in step 2 as input and leverages natural language processing techniques. The server compares the information against datasets and industry trend information to evaluate which industries the technology is applicable to. The output is the analysis results, including potential application areas.

[0503] Step 4:

[0504] The server generates new business proposals using an AI model based on the analysis results. The analysis data from step 3 and market trend data are used as input. The server activates the AI ​​model through the prompt, "Please suggest what new businesses can be conceived using this technology," and generates proposals. The output is a business proposal containing new business ideas.

[0505] Step 5:

[0506] The server quantitatively evaluates the generated business proposals and displays them in a visualized format on a dashboard. It uses new business proposals as input and calculates evaluation metrics using an AI model. Specifically, it scores novelty, market potential, and technical feasibility. The output is business proposal information with visualized evaluation scores.

[0507] Step 6:

[0508] The terminal provides an environment where users can view visualized business proposals and discuss them with other users and industry expert AI. The evaluated business proposals generated in step 5 are used as input. The terminal displays this data in a secure environment, enabling safe information sharing among users. The output is feedback on commercialization through collaborative discussion.

[0509] Step 7:

[0510] The user receives advice from a strategic consultant AI via their device and develops a concrete business plan. The feedback and suggestions obtained in step 6 are used as input. The user then performs specific actions such as resource allocation, risk assessment, and partner selection to build the business plan. The output is an actionable business plan.

[0511] (Application Example 1)

[0512] 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."

[0513] In today's business environment, there is a demand for the rapid and efficient utilization of existing knowledge assets. However, extracting useful information from vast amounts of knowledge asset data and applying it to new businesses is not easy. In particular, the process of applying technical information such as patent information to other industrial fields to create new business opportunities is complex and time-consuming. Against this backdrop, there is a need for methods to effectively analyze knowledge asset information and rapidly generate and share new business ideas.

[0514] 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.

[0515] In this invention, the server includes means for collecting publicly available knowledge asset information and summarizing the generated knowledge asset information; means for analyzing the summarized knowledge asset information and exploring the possibility of applying the technical information to other domains; and means for generating innovative business proposals based on the analysis results. This makes it possible to manage knowledge asset data and visualize new business ideas on the user's device.

[0516] "Publicly available knowledge asset information" refers to the collection of knowledge and information contained in patents, technical documents, etc., that have been made publicly available in a format that is accessible to the general public.

[0517] The "function for summarizing generated knowledge asset information" refers to the process or means of scrutinizing collected knowledge asset information and concisely summarizing important technical elements.

[0518] The "function to analyze and explore the possibility of applying that technical information to other fields" refers to a means of analyzing summarized technical information in detail and investigating how it can be applied to other industrial fields.

[0519] The "function for generating innovative business proposals" refers to the process of identifying new business opportunities based on analyzed information and developing them into concrete proposals.

[0520] "A means of managing knowledge asset data and visualizing new business ideas on users' devices" refers to a method of effectively organizing data related to knowledge assets and displaying analysis results and generated business proposals in an easy-to-understand manner on the user's device.

[0521] The server has a pipeline for collecting publicly available knowledge asset information, and it regularly accesses numerous patent databases to obtain new information. This information is stored on the server as knowledge asset data, including patent numbers, technical summaries, and classification information. Based on the collected information, a generative AI model is used to automatically summarize the data and extract important technical elements.

[0522] This system operates in a data center and is built using Python and the Flask framework on the backend. It also utilizes libraries such as spaCy and NLTK for natural language processing. PostgreSQL is used as the database for centralized management of patent information summaries.

[0523] The terminal (user) is provided with the ability to explore technological applications in other industrial fields based on the summary information provided by this server. The generated new business proposals are visualized on the user's device, allowing the user to efficiently evaluate business ideas and take the first step towards realization.

[0524] As a concrete example, if a user views patent information related to a new data storage technology in the app, the AI ​​will analyze this patent and generate a business proposal for an efficient storage solution for big data. This provides the user with an environment to plan projects. An example of a prompt message could be, "Based on this patent information, please generate a proposal for a new storage solution for data centers."

[0525] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0526] Step 1:

[0527] The server periodically accesses publicly available patent databases to collect knowledge asset information, including patent numbers, technical summaries, and patent classification information. The input is new patent data retrieved from the patent database, and the output is structured data stored within the server. This data is then organized for subsequent summarization processing.

[0528] Step 2:

[0529] The server summarizes the collected knowledge asset information using a generative AI model. The input is raw patent information obtained from a patent database, and the output is summarized information with key technological elements extracted. This summarization process utilizes natural language processing techniques to significantly reduce the amount of information while retaining the important points.

[0530] Step 3:

[0531] The server analyzes summarized technical information and explores its potential applications in other industrial fields. It takes summarized information as input and generates a list of potential technology candidates as output. This analysis uses an algorithm that finds correlations with known technology databases.

[0532] Step 4:

[0533] The server generates new business proposals based on the analysis results. Here, a list of potential technologies is used as input, and innovative business proposals are generated as output. This process also relies on a generation AI model, which designs realistic proposals by referencing market trend data.

[0534] Step 5:

[0535] The terminal (user) receives output from the server and visualizes the generated new business proposal on the device. The input is detailed plan data as a business proposal, and the output is an interface that the user can view and evaluate. The specific operation here is to provide the user with an easy-to-understand UI and to interactively evaluate the business feasibility.

[0536] Step 6:

[0537] The user carries out project planning based on a visualized business proposal. Here, the system receives output from the terminal and uses the provided prompt text as input to support strategic decision-making. This process enables the user to formulate a concrete business strategy.

[0538] 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.

[0539] This invention combines a system that supports the creation of new businesses by utilizing intellectual property information with an emotion engine that recognizes user emotions. This system collects intellectual property information from patent databases and can easily develop new businesses based on that information.

[0540] Collection and summarization of intellectual property information

[0541] Server: Accesses publicly available patent databases and regularly collects the latest intellectual property information. The collected information includes patent numbers, technical summaries, and patent classification information. Using a generative model, this information is concisely summarized and stored in the database.

[0542] Exploring the potential applications of technology

[0543] AI Agent (Server): Analyzes summarized information and uses natural language processing technology to evaluate its applicability in various industrial fields. Based on this information, it generates new business proposals.

[0544] Interface adjustment using an emotion engine

[0545] Terminal (User): The emotion engine analyzes the user's facial expressions and tone of voice in real time and dynamically adjusts the user interface. If the user shows interest, it highlights details of the suggestion and guidance on the next steps.

[0546] Evaluation and sharing of business proposals

[0547] Server: Evaluates generated business proposals using an AI model from the perspectives of novelty, marketability, and technical feasibility, and displays the results visually. Based on feedback from the emotion engine, it optimizes the method and order in which proposals are displayed.

[0548] Business development support through a collaboration platform

[0549] User (device): Share evaluated proposals with other users and experts on a shared platform and engage in discussions while utilizing emotion sensor data. This secure platform allows for rapid improvement of ideas and development of new proposals.

[0550] Specific example

[0551] Terminal (User): A user from a pharmaceutical company searches for patents related to new synthetic substances through the platform. This patent is analyzed, and its potential application as a new material in medical devices is proposed. If the user shows a positive reaction to this proposal, the emotion engine recognizes this and displays further information such as specific application examples and market data.

[0552] Users: Through group discussions, they will explore the potential for commercializing this application and formulate concrete actions for its realization together with a strategic consultant AI.

[0553] In this way, the present invention supports the efficient implementation of new businesses while increasing user interest through a system design that utilizes an emotion engine.

[0554] The following describes the processing flow.

[0555] Step 1:

[0556] The server accesses publicly available patent databases to collect the latest intellectual property information. The collected information consists of patent numbers, a summary of the technology, and patent classifications.

[0557] Step 2:

[0558] The server collects intellectual property information and summarizes it using a generative model. The summary is created in a way that concisely explains the key elements of the technology and its potential applications.

[0559] Step 3:

[0560] An AI agent (server) analyzes the summarized information and uses natural language processing technology to identify potential applications in other industrial fields. This lays the foundation for generating new business proposals.

[0561] Step 4:

[0562] The server evaluates the generated business proposals. An AI model quantifies the novelty, marketability, and technical feasibility of the proposals, and records the results in a database.

[0563] Step 5:

[0564] The server generates a dashboard on the user's terminal to visually display the evaluation results. The graphical interface allows users to easily understand the details of the recommendations.

[0565] Step 6:

[0566] An emotion engine built into the device (user) analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time. The user interface is then dynamically adjusted according to the recognized emotion.

[0567] Step 7:

[0568] When the sentiment engine detects a positive response while a user is viewing suggestions, detailed information and relevant data are highlighted on the interface, and the next action step is displayed at the top.

[0569] Step 8:

[0570] Users share evaluated business proposals with other team members and experts through the system. The collaboration platform is used to improve and refine ideas based on emotional feedback.

[0571] Step 9:

[0572] Users develop detailed plans for commercialization by considering feedback from an emotional engine and receiving advice from a strategic consultant AI. This increases the likelihood of new business ventures becoming feasible.

[0573] (Example 2)

[0574] 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."

[0575] In today's diverse economic activity landscape, there is a need for efficient methods to generate highly innovative proposals. However, the process of extracting useful knowledge from vast information resources and translating it into concrete proposals is complex and time-consuming. Furthermore, adjusting the interface to suit user emotions is necessary to enhance the acceptability of proposals, but effective means of achieving this are lacking. As a result, supporting the efficient and effective integration of these proposals into economic activity remains a challenging issue.

[0576] 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.

[0577] In this invention, the server includes means for collecting publicly available information resources and summarizing them using a generative model; means for analyzing the summarized information resources and exploring the possibility of applying their technological content to other areas of economic activity; and means for dynamically adjusting the user interface using an engine that analyzes user emotions. This seamlessly integrates information extraction, proposal generation, and emotion-based interface optimization, enabling the efficient and effective creation and realization of new economic activities.

[0578] "Information resources" refer to a collection of diverse information, such as publicly available patents, papers, and databases, which are used for analyzing technical content and discovering new knowledge.

[0579] A "generative model" is a technology that uses machine learning and natural language processing algorithms to summarize, generate, and analyze input data, enabling the acquisition of new insights from information resources.

[0580] The term "economic activity domain" encompasses diverse fields and cross-sectoral activities within industry and business, representing areas where the application of technologies and products can be considered.

[0581] A "user interface" is the interface through which information is exchanged between the user and the system, and its design must take into account ease of use and usability.

[0582] An "emotion engine" is a technology for analyzing a user's emotional state, particularly through facial recognition and voice analysis, to understand the user's reactions and dynamically optimize the interface.

[0583] This invention provides a system for extracting useful knowledge from publicly available information resources and creating new economic activities based on that knowledge. This system is realized through the interaction of a server, a terminal, and a user.

[0584] The server collects information resources such as patents and databases, and summarizes this information using a generative AI model. For example, it periodically searches for the latest patent information, retrieves patent numbers, technical summaries, and patent classification information, and then summarizes it. This summarized information is stored in the server's database and used for subsequent analysis.

[0585] The device interacts with the user through its user interface. Equipped with an emotion engine, it dynamically adjusts the interface by analyzing the user's facial expressions and voice tone using devices such as the camera and microphone. For example, it has a function that emphasizes the display of relevant information when the user shows interest.

[0586] Users can explore the possibilities of specific economic activities based on the information and suggestions provided. This system allows users to select information in areas of interest and evaluate its applicability. Furthermore, users can share suggestions with each other and engage in collaborative discussions toward commercialization. A shared platform is provided as the foundation for this, enabling efficient discussions utilizing emotion sensor data.

[0587] For example, if a user belongs to the pharmaceutical industry, they can search and analyze patent information on new synthetic substances and propose their application to medical devices. When the emotion engine determines that the user's response is positive, it displays more specific application examples and market data, providing guidance for the next action.

[0588] Examples of prompts include specific instructions such as, "Generate proposals to evaluate the potential of new businesses based on the latest patent information," or "Explain the interface adjustment function that responds to user emotions."

[0589] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0590] Step 1:

[0591] The server collects patent and database information from publicly available information resources. This collection is performed by inputting search prompt sentences using specific keywords and conditions into an AI model. The collected data includes patent numbers, technology summaries, and patent classification information. This data is temporarily stored on the server.

[0592] Step 2:

[0593] The server summarizes the collected information using a generative AI model. This summarization process uses natural language processing techniques to shorten long texts and extract key elements. The input is detailed patent information, and the output is summarized short text. This summarized information is stored in a database.

[0594] Step 3:

[0595] The server evaluates applicability based on the summarized information. Using natural language processing techniques, it analyzes the applicability of the technology across different industrial sectors. This analysis also considers market trends and past case studies. The input is summarized information, and the output is a list of potential industrial sectors and specific suggestions. These suggestions are stored in a database and can be accessed by users later.

[0596] Step 4:

[0597] The device uses an emotion engine to analyze facial expressions and tone of voice to understand the user's emotions. This analysis dynamically adjusts the information displayed on the interface. The input is real-time user behavior data, and the output is the adjusted interface display. Specifically, information that is of interest to the user is highlighted.

[0598] Step 5:

[0599] The server quantitatively evaluates the generated economic activity proposals and displays them visually on a screen. Artificial intelligence uses novelty, marketability, and technical feasibility as evaluation criteria. The input to this process is the proposal content, and the output is the evaluation results represented in graphs and charts. This information is transmitted to the user terminal.

[0600] Step 6:

[0601] Users utilize the platform to share information with other users based on their evaluated suggestions. This sharing platform allows for discussions while referencing emotion sensor data. Inputs are evaluated suggestions, and outputs are comments and feedback. One specific function is the ability to send notifications to other users.

[0602] (Application Example 2)

[0603] 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."

[0604] In today's complex industrial environment, creating new businesses requires the effective use of intellectual property information and the provision of dynamic interfaces based on user emotions. However, conventional systems have limitations in analyzing intellectual property information and generating business proposals, and are insufficient in adjusting interfaces to leverage user emotions. This also makes it difficult to quickly assess the marketability and feasibility of new businesses and to promote collaboration with other users.

[0605] 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.

[0606] This invention includes a server that collects publicly available intellectual property information and summarizes this intellectual property information using a generative model; a server that analyzes the summarized intellectual property information and explores the possibility of applying its technical content to other industrial fields; and a server that generates new business proposals based on the analysis results. This enables an efficient and dynamic business creation process based on intellectual property information, and by allowing interface adjustments that respond to user emotions, it becomes possible to quickly determine the marketability and feasibility of new businesses and promote collaboration with other users.

[0607] "Intellectual property information" refers to legally protected technical information and ideas, such as publicly available patents and trademarks.

[0608] A "generative model" is a computer program that automatically generates text and data using deep learning or machine learning algorithms.

[0609] "Methods of summarization" are techniques for extracting large amounts of information, summarizing the key points concisely, and presenting them in an easy-to-understand format.

[0610] "Natural language processing technology" is a technique for processing human language into a form that is easy for computers to handle and for analyzing its meaning.

[0611] "Means of recognizing emotions" refers to technologies that detect a user's facial expressions, voice, and other actions to determine their emotional state.

[0612] "Means of adjusting the interface" refers to technologies that adaptively change the displayed content and usability based on user responses.

[0613] "Means of visual display" refers to technologies that show analysis results and evaluation content to users in an easy-to-understand format, such as graphs and charts.

[0614] A "user" is an individual or organization that uses this system to obtain intellectual property information or business proposals.

[0615] This invention embodies a system that effectively supports the creation of new businesses by utilizing intellectual property information. The system's operation and necessary technical elements are described in detail below.

[0616] The server is responsible for periodically collecting publicly available patent information. This patent information mainly includes patent numbers, technical summaries, and patent classification information. The collected data is automatically summarized by a generative model using TensorFlow as a machine learning library and stored in a database.

[0617] Subsequently, the server uses natural language processing technology to analyze how patent information can be applied to various industrial fields. This makes it possible to generate new business proposals that meet the needs of the industry. The proposed businesses are then visualized using a visual evaluation tool, based on their marketability and feasibility.

[0618] The user device utilizes emotion recognition software (such as Microsoft Azure Emotion API) installed on smartphones or smart glasses. This allows for real-time analysis of the user's facial expressions and tone of voice, dynamically adjusting the user interface. Detailed information is highlighted when the user shows interest.

[0619] As a concrete example, imagine a user working at a startup company with new technology, and they search for new home automation technology patents through the platform. They can then receive suggestions on potential new applications of this patent as a smart home technology. If the user responds positively to a suggestion, the emotion engine recognizes this and provides more detailed market data and competitor information.

[0620] An example of a prompt for the generating AI model is: "Generate proposals for home automation utilizing new technologies in smart cities. In particular, output specific ideas based on recent patent information."

[0621] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0622] Step 1:

[0623] The server accesses the patent database to collect publicly available intellectual property information. This information includes patent numbers, technical summaries, and patent classification information. The collected data is stored directly in the database.

[0624] Step 2:

[0625] The server summarizes the collected intellectual property information using a generative AI model. The summarization process converts the information into a compact and easily understandable format. This output summary is then stored again in the database.

[0626] Step 3:

[0627] The server analyzes the summarized intellectual property information and uses natural language processing technology to process the data to identify which industrial sectors it can be applied to. Based on the analysis results, new business proposals are generated, and these generated proposals become the output.

[0628] Step 4:

[0629] The generated business proposals are quantitatively evaluated using AI-powered visualization tools, and the results are visually displayed to the user. Focusing on marketability and technical feasibility, the analysis results are presented in figures and charts.

[0630] Step 5:

[0631] On the user's device, emotion recognition software installed on the smartphone or smart glasses analyzes the user's facial expressions and tone of voice in real time. This allows the user interface to dynamically adjust based on emotional changes, highlighting relevant suggestions based on their interest.

[0632] Step 6:

[0633] Users can share evaluated suggestions with other users and engage in discussions within the system. Users can also input prompts as needed and use the AI ​​generation model to obtain further, more specific idea outputs.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] [Fourth Embodiment]

[0638] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0639] 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.

[0640] 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).

[0641] 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.

[0642] 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.

[0643] 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).

[0644] 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.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] 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".

[0651] This invention is a system that supports the creation of new businesses by utilizing publicly available intellectual property information. This system collects intellectual property information from publicly available patent databases and provides a series of processes to promote the user's business development based on that information.

[0652] Collection and summarization of intellectual property information

[0653] Server: Regularly accesses publicly available patent databases to retrieve new intellectual property information. The retrieved information includes patent numbers, technical summaries, and patent classification information. A generative model is used to automatically summarize the obtained information and extract key technical elements and features.

[0654] Exploring and analyzing the potential applications of the technology.

[0655] AI agent (server): Analyzes summarized patent information. Utilizes natural language processing technology to evaluate whether the technical details can be applied to other industrial fields.

[0656] Generation and evaluation of new business proposals

[0657] AI Agent: Integrates potential technological applications across multiple industrial sectors and generates new business proposals by referencing existing market trend data and past business models. The generated proposals are quantitatively evaluated by the AI ​​model from the perspectives of novelty, marketability, and technical feasibility. The results are visually displayed on a dashboard, allowing users to understand the strengths and weaknesses of the proposals at a glance.

[0658] Collaboration and business development support

[0659] Terminal (User): Based on visualized business proposals, users engage in discussions with other users and industry expert AI. Collaboration on the platform takes place in a secure environment, enhancing the safety of information.

[0660] Users can develop concrete business plans with advice from a strategic consultant AI. This includes resource allocation, partner identification, and risk analysis. By using this system, companies can effectively utilize untapped intellectual property and quickly seize new business opportunities.

[0661] Specific example

[0662] Terminal (User): For example, a user working at an electronics manufacturer checks patent information for a new battery technology on the platform. This patent is applied and evaluated as a power-saving technology for portable devices. An AI agent considers market data and generates a business proposal for energy-saving batteries for home appliances, displaying it on a dashboard along with an evaluation score.

[0663] User: Receive assistance in exploring the feasibility of commercializing this proposal and creating an actionable business plan, while communicating with other stakeholders through the system.

[0664] The following describes the processing flow.

[0665] Step 1:

[0666] The server accesses publicly available patent databases and collects new and updated intellectual property information. This collection includes basic information such as patent number, invention summary, and technical field.

[0667] Step 2:

[0668] The server inputs collected intellectual property information into a generative model to automatically generate patent summaries. These summaries concisely summarize the key technological elements and their potential applications.

[0669] Step 3:

[0670] An AI agent (server) analyzes the summary and uses natural language processing technology to analyze the technical elements in order to identify which other industrial fields the patented technology can be applied to.

[0671] Step 4:

[0672] The AI ​​agent integrates the potential applications of technologies from multiple fields based on the analysis results and generates new business proposals. Market trends and data from past success stories are also referenced in this process.

[0673] Step 5:

[0674] The server uses an AI model to quantitatively evaluate the novelty, market potential, and feasibility of the generated business proposals. The evaluation results are summarized as a score.

[0675] Step 6:

[0676] The server visualizes the evaluation results in graphs and charts, generating a dashboard that allows users to view detailed evaluation information through an interface.

[0677] Step 7:

[0678] The user interacts with other team members and industry experts on the platform based on evaluation results, discussing how to refine and improve business proposals.

[0679] Step 8:

[0680] Users receive support from a strategic consultant AI to create concrete business plans, including resource allocation and risk analysis. This prepares the platform for increasing the feasibility of the business.

[0681] (Example 1)

[0682] 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".

[0683] In today's highly information-driven society, the effective utilization of knowledge asset information is crucial for creating new businesses and innovating existing ones. However, collecting information from vast amounts of publicly available databases and using it to make quick and accurate business proposals requires considerable effort and knowledge. Furthermore, analyzing this information for application in other fields demands advanced technology. Against this backdrop, there is a need for systems that can efficiently collect, analyze, and utilize knowledge asset information.

[0684] 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.

[0685] In this invention, the server includes means for collecting knowledge property information from a publicly available database, means for summarizing the information using a generative model, and means for analyzing the information using natural language processing technology and exploring its potential applications in other fields. This enables the rapid and efficient generation of new business proposals and the formulation of business strategies based on them.

[0686] "Intellectual property information" is a general term for information concerning creations and inventions that are protected by law, such as patents, copyrights, and trademarks.

[0687] A "generative model" is a computational model that uses artificial intelligence algorithms to generate a specific output from input data.

[0688] "Natural language processing technology" refers to a set of technologies that enable computers to understand, interpret, and generate human language.

[0689] "Analysis" is the process of breaking down information and data into its details in order to understand its structure and content.

[0690] A "business proposal" is a plan or proposal created to present the concept and direction of a new business.

[0691] "Quantitative evaluation" refers to conducting a concrete evaluation using numerical values, with the aim of making an objective judgment based on various indicators and criteria.

[0692] "Visualized format" refers to a method of making information easier to understand by representing it in a visual form such as graphs or diagrams.

[0693] "Sharing" means making information and data available for use and access by multiple stakeholders.

[0694] In order to implement this invention, it is necessary to build a system in which a server, a terminal, and a user work together.

[0695] server

[0696] The server collects the latest intellectual property information by periodically accessing publicly available databases. This process utilizes internet-connected computers and API technology to retrieve data. The obtained information, including patent numbers, technical summaries, and patent classifications, is stored in a local database on the server. Next, a generative AI model is used to summarize this information and extract key technical elements and features. Specifically, the AI ​​model is provided with prompts such as, "List three key technical elements of this patent."

[0697] terminal

[0698] The terminal provides an environment where users can view generated business proposals and discuss them with other users and industry expert AI. On the terminal, visualized business proposals provided by the server are displayed in a dashboard format, making it easy to understand evaluation scores, proposal strengths, and areas for improvement. The platform is equipped with security measures to ensure the safety of information.

[0699] User

[0700] Through their devices, users develop concrete business plans while receiving advice from a strategic consultant AI. At this stage, they devise specific strategies such as resource allocation, risk assessment, and partner identification to increase the feasibility of business opportunities. An example of a prompt might be, "Please suggest what new businesses could be conceived using this technology." This system enables users to rationally and effectively generate new business ideas from a vast amount of knowledge and develop them quickly and safely.

[0701] The form for implementing the invention, through the integration of these processes and technical elements, provides comprehensive support for users to leverage intellectual property information to build new businesses.

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] The server accesses publicly available databases to collect intellectual property information. It uses patent numbers, technology summaries, and patent classification information obtained via an API as input. The server collects large amounts of this data and stores it in a local database. The output of this step is intellectual property information organized in a structured format.

[0705] Step 2:

[0706] The server uses a generative AI model to summarize the collected knowledge property information. It uses the patent data obtained in Step 1 as input. Specifically, the server provides the AI ​​model with prompts such as "List three key technical elements of this patent," and extracts the main technical elements from the data. The output is data containing the summarized technical elements and features.

[0707] Step 3:

[0708] The server's AI agent analyzes the summarized patent information and explores its potential applications in other fields. It uses the technical information summarized in step 2 as input and leverages natural language processing techniques. The server compares the information against datasets and industry trend information to evaluate which industries the technology is applicable to. The output is the analysis results, including potential application areas.

[0709] Step 4:

[0710] The server generates new business proposals using an AI model based on the analysis results. The analysis data from step 3 and market trend data are used as input. The server activates the AI ​​model through the prompt, "Please suggest what new businesses can be conceived using this technology," and generates proposals. The output is a business proposal containing new business ideas.

[0711] Step 5:

[0712] The server quantitatively evaluates the generated business proposals and displays them in a visualized format on a dashboard. It uses new business proposals as input and calculates evaluation metrics using an AI model. Specifically, it scores novelty, market potential, and technical feasibility. The output is business proposal information with visualized evaluation scores.

[0713] Step 6:

[0714] The terminal provides an environment where users can view visualized business proposals and discuss them with other users and industry expert AI. The evaluated business proposals generated in step 5 are used as input. The terminal displays this data in a secure environment, enabling safe information sharing among users. The output is feedback on commercialization through collaborative discussion.

[0715] Step 7:

[0716] The user receives advice from a strategic consultant AI via their device and develops a concrete business plan. The feedback and suggestions obtained in step 6 are used as input. The user then performs specific actions such as resource allocation, risk assessment, and partner selection to build the business plan. The output is an actionable business plan.

[0717] (Application Example 1)

[0718] 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".

[0719] In today's business environment, there is a demand for the rapid and efficient utilization of existing knowledge assets. However, extracting useful information from vast amounts of knowledge asset data and applying it to new businesses is not easy. In particular, the process of applying technical information such as patent information to other industrial fields to create new business opportunities is complex and time-consuming. Against this backdrop, there is a need for methods to effectively analyze knowledge asset information and rapidly generate and share new business ideas.

[0720] 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.

[0721] In this invention, the server includes means for collecting publicly available knowledge asset information and summarizing the generated knowledge asset information; means for analyzing the summarized knowledge asset information and exploring the possibility of applying the technical information to other domains; and means for generating innovative business proposals based on the analysis results. This makes it possible to manage knowledge asset data and visualize new business ideas on the user's device.

[0722] "Publicly available knowledge asset information" refers to the collection of knowledge and information contained in patents, technical documents, etc., that have been made publicly available in a format that is accessible to the general public.

[0723] The "function for summarizing generated knowledge asset information" refers to the process or means of scrutinizing collected knowledge asset information and concisely summarizing important technical elements.

[0724] The "function to analyze and explore the possibility of applying that technical information to other fields" refers to a means of analyzing summarized technical information in detail and investigating how it can be applied to other industrial fields.

[0725] The "function for generating innovative business proposals" refers to the process of identifying new business opportunities based on analyzed information and developing them into concrete proposals.

[0726] "A means of managing knowledge asset data and visualizing new business ideas on users' devices" refers to a method of effectively organizing data related to knowledge assets and displaying analysis results and generated business proposals in an easy-to-understand manner on the user's device.

[0727] The server has a pipeline for collecting publicly available knowledge asset information, and it regularly accesses numerous patent databases to obtain new information. This information is stored on the server as knowledge asset data, including patent numbers, technical summaries, and classification information. Based on the collected information, a generative AI model is used to automatically summarize the data and extract important technical elements.

[0728] This system operates in a data center and is built using Python and the Flask framework on the backend. It also utilizes libraries such as spaCy and NLTK for natural language processing. PostgreSQL is used as the database for centralized management of patent information summaries.

[0729] The terminal (user) is provided with the ability to explore technological applications in other industrial fields based on the summary information provided by this server. The generated new business proposals are visualized on the user's device, allowing the user to efficiently evaluate business ideas and take the first step towards realization.

[0730] As a concrete example, if a user views patent information related to a new data storage technology in the app, the AI ​​will analyze this patent and generate a business proposal for an efficient storage solution for big data. This provides the user with an environment to plan projects. An example of a prompt message could be, "Based on this patent information, please generate a proposal for a new storage solution for data centers."

[0731] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0732] Step 1:

[0733] The server periodically accesses publicly available patent databases to collect knowledge asset information, including patent numbers, technical summaries, and patent classification information. The input is new patent data retrieved from the patent database, and the output is structured data stored within the server. This data is then organized for subsequent summarization processing.

[0734] Step 2:

[0735] The server summarizes the collected knowledge asset information using a generative AI model. The input is raw patent information obtained from a patent database, and the output is summarized information with key technological elements extracted. This summarization process utilizes natural language processing techniques to significantly reduce the amount of information while retaining the important points.

[0736] Step 3:

[0737] The server analyzes summarized technical information and explores its potential applications in other industrial fields. It takes summarized information as input and generates a list of potential technology candidates as output. This analysis uses an algorithm that finds correlations with known technology databases.

[0738] Step 4:

[0739] The server generates new business proposals based on the analysis results. Here, a list of potential technologies is used as input, and innovative business proposals are generated as output. This process also relies on a generation AI model, which designs realistic proposals by referencing market trend data.

[0740] Step 5:

[0741] The terminal (user) receives output from the server and visualizes the generated new business proposal on the device. The input is detailed plan data as a business proposal, and the output is an interface that the user can view and evaluate. The specific operation here is to provide the user with an easy-to-understand UI and to interactively evaluate the business feasibility.

[0742] Step 6:

[0743] The user carries out project planning based on a visualized business proposal. Here, the system receives output from the terminal and uses the provided prompt text as input to support strategic decision-making. This process enables the user to formulate a concrete business strategy.

[0744] 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.

[0745] This invention combines a system that supports the creation of new businesses by utilizing intellectual property information with an emotion engine that recognizes user emotions. This system collects intellectual property information from patent databases and can easily develop new businesses based on that information.

[0746] Collection and summarization of intellectual property information

[0747] Server: Accesses publicly available patent databases and regularly collects the latest intellectual property information. The collected information includes patent numbers, technical summaries, and patent classification information. Using a generative model, this information is concisely summarized and stored in the database.

[0748] Exploring the potential applications of technology

[0749] AI Agent (Server): Analyzes summarized information and uses natural language processing technology to evaluate its applicability in various industrial fields. Based on this information, it generates new business proposals.

[0750] Interface adjustment using an emotion engine

[0751] Terminal (User): The emotion engine analyzes the user's facial expressions and tone of voice in real time and dynamically adjusts the user interface. If the user shows interest, it highlights details of the suggestion and guidance on the next steps.

[0752] Evaluation and sharing of business proposals

[0753] Server: Evaluates generated business proposals using an AI model from the perspectives of novelty, marketability, and technical feasibility, and displays the results visually. Based on feedback from the emotion engine, it optimizes the method and order in which proposals are displayed.

[0754] Business development support through a collaboration platform

[0755] User (device): Share evaluated proposals with other users and experts on a shared platform and engage in discussions while utilizing emotion sensor data. This secure platform allows for rapid improvement of ideas and development of new proposals.

[0756] Specific example

[0757] Terminal (User): A user from a pharmaceutical company searches for patents related to new synthetic substances through the platform. This patent is analyzed, and its potential application as a new material in medical devices is proposed. If the user shows a positive reaction to this proposal, the emotion engine recognizes this and displays further information such as specific application examples and market data.

[0758] Users: Through group discussions, they will explore the potential for commercializing this application and formulate concrete actions for its realization together with a strategic consultant AI.

[0759] In this way, the present invention supports the efficient implementation of new businesses while increasing user interest through a system design that utilizes an emotion engine.

[0760] The following describes the processing flow.

[0761] Step 1:

[0762] The server accesses publicly available patent databases to collect the latest intellectual property information. The collected information consists of patent numbers, a summary of the technology, and patent classifications.

[0763] Step 2:

[0764] The server collects intellectual property information and summarizes it using a generative model. The summary is created in a way that concisely explains the key elements of the technology and its potential applications.

[0765] Step 3:

[0766] An AI agent (server) analyzes the summarized information and uses natural language processing technology to identify potential applications in other industrial fields. This lays the foundation for generating new business proposals.

[0767] Step 4:

[0768] The server evaluates the generated business proposals. An AI model quantifies the novelty, marketability, and technical feasibility of the proposals, and records the results in a database.

[0769] Step 5:

[0770] The server generates a dashboard on the user's terminal to visually display the evaluation results. The graphical interface allows users to easily understand the details of the recommendations.

[0771] Step 6:

[0772] An emotion engine built into the device (user) analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time. The user interface is then dynamically adjusted according to the recognized emotion.

[0773] Step 7:

[0774] When the sentiment engine detects a positive response while a user is viewing suggestions, detailed information and relevant data are highlighted on the interface, and the next action step is displayed at the top.

[0775] Step 8:

[0776] Users share evaluated business proposals with other team members and experts through the system. The collaboration platform is used to improve and refine ideas based on emotional feedback.

[0777] Step 9:

[0778] Users develop detailed plans for commercialization by considering feedback from an emotional engine and receiving advice from a strategic consultant AI. This increases the likelihood of new business ventures becoming feasible.

[0779] (Example 2)

[0780] 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".

[0781] In today's diverse economic activity landscape, there is a need for efficient methods to generate highly innovative proposals. However, the process of extracting useful knowledge from vast information resources and translating it into concrete proposals is complex and time-consuming. Furthermore, adjusting the interface to suit user emotions is necessary to enhance the acceptability of proposals, but effective means of achieving this are lacking. As a result, supporting the efficient and effective integration of these proposals into economic activity remains a challenging issue.

[0782] 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.

[0783] In this invention, the server includes means for collecting publicly available information resources and summarizing them using a generative model; means for analyzing the summarized information resources and exploring the possibility of applying their technological content to other areas of economic activity; and means for dynamically adjusting the user interface using an engine that analyzes user emotions. This seamlessly integrates information extraction, proposal generation, and emotion-based interface optimization, enabling the efficient and effective creation and realization of new economic activities.

[0784] "Information resources" refer to a collection of diverse information, such as publicly available patents, papers, and databases, which are used for analyzing technical content and discovering new knowledge.

[0785] A "generative model" is a technology that uses machine learning and natural language processing algorithms to summarize, generate, and analyze input data, enabling the acquisition of new insights from information resources.

[0786] The term "economic activity domain" encompasses diverse fields and cross-sectoral activities within industry and business, representing areas where the application of technologies and products can be considered.

[0787] A "user interface" is the interface through which information is exchanged between the user and the system, and its design must take into account ease of use and usability.

[0788] An "emotion engine" is a technology for analyzing a user's emotional state, particularly through facial recognition and voice analysis, to understand the user's reactions and dynamically optimize the interface.

[0789] This invention provides a system for extracting useful knowledge from publicly available information resources and creating new economic activities based on that knowledge. This system is realized through the interaction of a server, a terminal, and a user.

[0790] The server collects information resources such as patents and databases, and summarizes this information using a generative AI model. For example, it periodically searches for the latest patent information, retrieves patent numbers, technical summaries, and patent classification information, and then summarizes it. This summarized information is stored in the server's database and used for subsequent analysis.

[0791] The device interacts with the user through its user interface. Equipped with an emotion engine, it dynamically adjusts the interface by analyzing the user's facial expressions and voice tone using devices such as the camera and microphone. For example, it has a function that emphasizes the display of relevant information when the user shows interest.

[0792] Users can explore the possibilities of specific economic activities based on the information and suggestions provided. This system allows users to select information in areas of interest and evaluate its applicability. Furthermore, users can share suggestions with each other and engage in collaborative discussions toward commercialization. A shared platform is provided as the foundation for this, enabling efficient discussions utilizing emotion sensor data.

[0793] For example, if a user belongs to the pharmaceutical industry, they can search and analyze patent information on new synthetic substances and propose their application to medical devices. When the emotion engine determines that the user's response is positive, it displays more specific application examples and market data, providing guidance for the next action.

[0794] Examples of prompts include specific instructions such as, "Generate proposals to evaluate the potential of new businesses based on the latest patent information," or "Explain the interface adjustment function that responds to user emotions."

[0795] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0796] Step 1:

[0797] The server collects patent and database information from publicly available information resources. This collection is performed by inputting search prompt sentences using specific keywords and conditions into an AI model. The collected data includes patent numbers, technology summaries, and patent classification information. This data is temporarily stored on the server.

[0798] Step 2:

[0799] The server summarizes the collected information using a generative AI model. This summarization process uses natural language processing techniques to shorten long texts and extract key elements. The input is detailed patent information, and the output is summarized short text. This summarized information is stored in a database.

[0800] Step 3:

[0801] The server evaluates applicability based on the summarized information. Using natural language processing techniques, it analyzes the applicability of the technology across different industrial sectors. This analysis also considers market trends and past case studies. The input is summarized information, and the output is a list of potential industrial sectors and specific suggestions. These suggestions are stored in a database and can be accessed by users later.

[0802] Step 4:

[0803] The device uses an emotion engine to analyze facial expressions and tone of voice to understand the user's emotions. This analysis dynamically adjusts the information displayed on the interface. The input is real-time user behavior data, and the output is the adjusted interface display. Specifically, information that is of interest to the user is highlighted.

[0804] Step 5:

[0805] The server quantitatively evaluates the generated economic activity proposals and displays them visually on a screen. Artificial intelligence uses novelty, marketability, and technical feasibility as evaluation criteria. The input to this process is the proposal content, and the output is the evaluation results represented in graphs and charts. This information is transmitted to the user terminal.

[0806] Step 6:

[0807] Users utilize the platform to share information with other users based on their evaluated suggestions. This sharing platform allows for discussions while referencing emotion sensor data. Inputs are evaluated suggestions, and outputs are comments and feedback. One specific function is the ability to send notifications to other users.

[0808] (Application Example 2)

[0809] 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".

[0810] In today's complex industrial environment, creating new businesses requires the effective use of intellectual property information and the provision of dynamic interfaces based on user emotions. However, conventional systems have limitations in analyzing intellectual property information and generating business proposals, and are insufficient in adjusting interfaces to leverage user emotions. This also makes it difficult to quickly assess the marketability and feasibility of new businesses and to promote collaboration with other users.

[0811] 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.

[0812] This invention includes a server that collects publicly available intellectual property information and summarizes this intellectual property information using a generative model; a server that analyzes the summarized intellectual property information and explores the possibility of applying its technical content to other industrial fields; and a server that generates new business proposals based on the analysis results. This enables an efficient and dynamic business creation process based on intellectual property information, and by allowing interface adjustments that respond to user emotions, it becomes possible to quickly determine the marketability and feasibility of new businesses and promote collaboration with other users.

[0813] "Intellectual property information" refers to legally protected technical information and ideas, such as publicly available patents and trademarks.

[0814] A "generative model" is a computer program that automatically generates text and data using deep learning or machine learning algorithms.

[0815] "Methods of summarization" are techniques for extracting large amounts of information, summarizing the key points concisely, and presenting them in an easy-to-understand format.

[0816] "Natural language processing technology" is a technique for processing human language into a form that is easy for computers to handle and for analyzing its meaning.

[0817] "Means of recognizing emotions" refers to technologies that detect a user's facial expressions, voice, and other actions to determine their emotional state.

[0818] "Means of adjusting the interface" refers to technologies that adaptively change the displayed content and usability based on user responses.

[0819] "Means of visual display" refers to technologies that show analysis results and evaluation content to users in an easy-to-understand format, such as graphs and charts.

[0820] A "user" is an individual or organization that uses this system to obtain intellectual property information or business proposals.

[0821] This invention embodies a system that effectively supports the creation of new businesses by utilizing intellectual property information. The system's operation and necessary technical elements are described in detail below.

[0822] The server is responsible for periodically collecting publicly available patent information. This patent information mainly includes patent numbers, technical summaries, and patent classification information. The collected data is automatically summarized by a generative model using TensorFlow as a machine learning library and stored in a database.

[0823] Subsequently, the server uses natural language processing technology to analyze how patent information can be applied to various industrial fields. This makes it possible to generate new business proposals that meet the needs of the industry. The proposed businesses are then visualized using a visual evaluation tool, based on their marketability and feasibility.

[0824] The user device utilizes emotion recognition software (such as Microsoft Azure Emotion API) installed on smartphones or smart glasses. This allows for real-time analysis of the user's facial expressions and tone of voice, dynamically adjusting the user interface. Detailed information is highlighted when the user shows interest.

[0825] As a concrete example, imagine a user working at a startup company with new technology, and they search for new home automation technology patents through the platform. They can then receive suggestions on potential new applications of this patent as a smart home technology. If the user responds positively to a suggestion, the emotion engine recognizes this and provides more detailed market data and competitor information.

[0826] An example of a prompt for the generating AI model is: "Generate proposals for home automation utilizing new technologies in smart cities. In particular, output specific ideas based on recent patent information."

[0827] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0828] Step 1:

[0829] The server accesses the patent database to collect publicly available intellectual property information. This information includes patent numbers, technical summaries, and patent classification information. The collected data is stored directly in the database.

[0830] Step 2:

[0831] The server summarizes the collected intellectual property information using a generative AI model. The summarization process converts the information into a compact and easily understandable format. This output summary is then stored again in the database.

[0832] Step 3:

[0833] The server analyzes the summarized intellectual property information and uses natural language processing technology to process the data to identify which industrial sectors it can be applied to. Based on the analysis results, new business proposals are generated, and these generated proposals become the output.

[0834] Step 4:

[0835] The generated business proposals are quantitatively evaluated using AI-powered visualization tools, and the results are visually displayed to the user. Focusing on marketability and technical feasibility, the analysis results are presented in figures and charts.

[0836] Step 5:

[0837] On the user's device, emotion recognition software installed on the smartphone or smart glasses analyzes the user's facial expressions and tone of voice in real time. This allows the user interface to dynamically adjust based on emotional changes, highlighting relevant suggestions based on their interest.

[0838] Step 6:

[0839] Users can share evaluated suggestions with other users and engage in discussions within the system. Users can also input prompts as needed and use the AI ​​generation model to obtain further, more specific idea outputs.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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."

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] The following is further disclosed regarding the embodiments described above.

[0862] (Claim 1)

[0863] A means of collecting publicly available intellectual property information and summarizing this intellectual property information using a generative model,

[0864] A means of analyzing summarized intellectual property information and exploring the possibility of applying its technical content to other industrial fields,

[0865] A means of generating new business proposals based on the analysis results,

[0866] A means of quantitatively evaluating and visually displaying the generated business proposals,

[0867] A means to share evaluated business proposals with other users and provide a platform to support their commercialization,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, further comprising means for analyzing the technical content of publicly available intellectual property information using natural language processing technology.

[0871] (Claim 3)

[0872] The system according to claim 1, further comprising means for concretizing a business plan using artificial intelligence that acts as a virtual advisor based on the generated business proposal.

[0873] "Example 1"

[0874] (Claim 1)

[0875] A means of collecting knowledge property information from publicly available databases and summarizing this information using a generative model,

[0876] A means of analyzing summarized information using natural language processing technology and exploring its potential applications in other fields,

[0877] Based on the analysis results, a method for utilizing a generative AI model to generate new business proposals,

[0878] A means of quantitatively evaluating the generated business proposals and displaying them in a visualized format,

[0879] A means to provide an environment that supports commercialization while sharing evaluated business proposals with other users and securely exchanging information,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, further comprising means for analyzing the technical content of intellectual property information in detail using natural language processing technology and prompt sentences.

[0883] (Claim 3)

[0884] The system according to claim 1, further comprising means for concretizing a business plan using an intelligent mechanism that acts as a virtual advisor based on the generated business proposal.

[0885] "Application Example 1"

[0886] (Claim 1)

[0887] A function to collect publicly available knowledge asset information and summarize the generated knowledge asset information,

[0888] It has the function to analyze summarized knowledge asset information and explore the possibility of applying that technical information to other fields,

[0889] A function that generates innovative business proposals based on analysis results,

[0890] A function to numerically evaluate and visually display the generated business proposals,

[0891] Features that allow users to share evaluated business proposals and provide a platform to support their commercialization,

[0892] A means of managing knowledge asset data and visualizing new business ideas on users' devices,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising a function for analyzing technical information using natural language processing technology on publicly available knowledge asset information.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising means for realizing a business plan using artificial intelligence acting as a virtual advisor based on the generated business proposal.

[0898] "Example 2 of combining an emotion engine"

[0899] (Claim 1)

[0900] A means of collecting publicly available information resources and summarizing these resources using a generative model,

[0901] A means of analyzing summarized information resources and exploring the possibility of applying their technological content to other areas of economic activity,

[0902] A means of dynamically adjusting the user interface using an engine that analyzes user emotions,

[0903] A means for generating new economic activity proposals based on analysis results,

[0904] A means of quantitatively evaluating and visually displaying the generated economic activity proposals,

[0905] A means to share evaluated economic activity proposals with other users and provide a platform to support their commercialization,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, further comprising means for analyzing the technical content of publicly available information resources using natural language processing technology.

[0909] (Claim 3)

[0910] The system according to claim 1, further comprising means for concretizing an economic activity plan using artificial intelligence that acts as a virtual advisor based on the generated economic activity proposals.

[0911] "Application example 2 when combining with an emotional engine"

[0912] (Claim 1)

[0913] A means of collecting publicly available intellectual property information and summarizing this intellectual property information using a generative model,

[0914] A means of analyzing summarized intellectual property information and exploring the possibility of applying its technical content to other industrial fields,

[0915] A means of generating new business proposals based on the analysis results,

[0916] A means of quantitatively evaluating and visually displaying the generated business proposals,

[0917] A means to share evaluated business proposals with other users and provide a platform to support their commercialization,

[0918] A means of recognizing user emotions and adjusting the user interface in real time accordingly,

[0919] A system that includes this.

[0920] (Claim 2)

[0921] The system according to claim 1, further comprising means for analyzing the technical content of publicly available intellectual property information using natural language processing technology.

[0922] (Claim 3)

[0923] The system according to claim 1, further comprising means for concretizing a business plan using artificial intelligence that acts as a virtual advisor based on the generated business proposal. [Explanation of symbols]

[0924] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting publicly available intellectual property information and summarizing this intellectual property information using a generative model, A means of analyzing summarized intellectual property information and exploring the possibility of applying its technical content to other industrial fields, A means of generating new business proposals based on the analysis results, A means of quantitatively evaluating and visually displaying the generated business proposals, A means to share evaluated business proposals with other users and provide a platform to support their commercialization, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the technical content of publicly available intellectual property information using natural language processing technology.

3. The system according to claim 1, further comprising means for concretizing a business plan using artificial intelligence that acts as a virtual advisor based on the generated business proposal.

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